DHIS2 User guide

2.27

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License:  Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the source of this documentation, and is available here online: http://www.gnu.org/licenses/fdl.html.

Revision History
Revision HEAD@3bc77892017-10-18 02:54:07
Version 2.27

Table of Contents

About this guide
1. Getting started - help to navigate the user guide
2. What is DHIS2?
2.1. DHIS2 Background
2.2. Key features and purpose of DHIS2
2.3. Use of DHIS2 in HIS: data collection, processing, interpretation, and analysis.
2.4. Technical background
2.4.1. DHIS2 as a platform
2.4.2. Understanding platform independence
2.4.3. Deployment strategies - online vs offline
2.5. Difference between Aggregated and Patient data in a HIS
2.6. Free and Open Source Software (FOSS): benefits and challenges
3. Manage dashboards
3.1. About dashboards
3.2. Set up the dashboard
3.3. Change dashboards name
3.4. Add message widget to dashboards
3.5. Delete dashboards
3.6. Translate dashboard names
3.7. Dashboard sharing
3.8. Manage messages and feedback messages
3.8.1. About messages and feedback messages
3.8.2. Create a message
3.8.3. Read a message
3.8.4. Create a feedback message
3.8.5. Manage feedback messages
3.8.6. Configure feedback message function
4. Using the Data Entry app
4.1. About the Data Entry app
4.2. Enter data in a data entry form
4.3. Mark a data value for follow-up
4.4. Edit data values in a completed data entry form
4.5. Display a data value's history
4.6. Display a data value's audit trail
4.7. Create minimum maximum value range manually
4.8. Enter data offline
4.9. Enable multi-organisation unit data entry
4.10. See also
5. Using the Event Capture app
5.1. About the Event Capture app
5.2. Register an event
5.3. Edit an event
5.4. Edit events in grid
5.5. Share events in edit mode
5.6. View an event audit history
5.7. Delete an event
5.8. Modify an event list's layout
5.9. Print an event list
5.10. Download an event list
6. Using the Tracker Capture app
6.1. About the Tracker Capture app
6.2. About tracked entity instance (TEI) dashboards
6.3. Workflow
6.4. Create a TEI
6.5. Create a TEI and enroll it in a program
6.6. Open an existing TEI dashboard
6.6.1. Simple TEI search
6.6.2. Advanced TEI search
6.6.3. Find a TEI outside your organisation unit
6.6.4. Download TEI search results list
6.6.5. Modify TEI search results list's layout
6.7. Enroll an existing TEI in a program
6.8. Enter event data for a TEI
6.9. Manage a TEI's enrollments
6.9.1. Deactivate a TEI's enrollment
6.9.2. Activate a TEI's enrollment
6.9.3. Mark TEI's enrollment as complete
6.9.4. Reopen completed enrollment
6.9.5. Display TEI's enrollment history
6.9.6. Create a TEI enrollment note
6.10. Send a message to a TEI
6.11. Mark a TEI for follow-up
6.12. Edit a TEI's profile
6.13. Add a relationship to a TEI
6.14. Share a TEI dashboard
6.15. Deactivate a TEI
6.16. Activate a TEI
6.17. Delete a TEI
6.18. Configure the TEI dashboard
6.18.1. Show or hide widgets
6.18.2. Save the dashboard's layout as default
6.19. Create reports
7. Analyze data in pivot tables
7.1. About the Pivot Table app
7.2. Create a pivot table
7.2.1. Select dimension items
7.2.2. Modify pivot table layout
7.3. Change the display of your pivot table
7.4. Manage favorites
7.4.1. Open a favorite
7.4.2. Save a favorite
7.4.3. Rename a favorite
7.4.4. Write an interpretation for a favorite
7.4.5. Create a link to a favorite
7.4.6. Delete a favorite
7.4.7. View interpretations based on relative periods
7.5. Download data from a pivot table
7.5.1. Download table layout data format
7.5.2. Download plain data source format
7.5.3. Download a CSV format without rendering data in the web browser
7.6. Embed a pivot table in an external web page
7.7. Visualize pivot table data as a chart or a map
7.7.1. Open a pivot table as a chart
7.7.2. Open a pivot table selection as a chart
7.7.3. Open a pivot table as a map
7.7.4. Open a pivot table selection as a map
8. Using the Data Visualizer app
8.1. About the Data Visualizer app
8.2. Create a chart
8.3. Select a chart type
8.4. Select dimension items
8.4.1. Select indicators
8.4.2. Select data elements
8.4.3. Select reporting rates
8.4.4. Select fixed and relative periods
8.4.5. Select organisation units
8.4.6. Select additional dimension items
8.5. Select series, category and filter
8.6. Change the display of your chart
8.7. Manage favorites
8.7.1. Open a favorite
8.7.2. Save a favorite
8.7.3. Rename a favorite
8.7.4. Write an interpretation for a favorite
8.7.5. Create a link to a favorite
8.7.6. Delete a favorite
8.7.7. View interpretations based on relative periods
8.8. Download a chart as an image or a PDF
8.9. Download chart data source
8.10. Embed charts in any web page
8.11. Open a chart as a pivot table or as a map
9. Using the GIS app
9.1. About the GIS app
9.2. Create a new thematic map
9.3. Manage event layers
9.3.1. Create or modify event layer
9.3.2. Turn off cluster
9.3.3. Modify cluster style
9.3.4. Modify information in event pop-up windows
9.3.5. Clear event layer
9.4. Manage facility layers
9.4.1. Create or modify a facility layer
9.4.2. Search for an organisation unit
9.4.3. Clear facility layer
9.5. Manage facilities in a layer
9.5.1. Relocate a facility
9.5.2. Swap longitude and latitude of a facility
9.5.3. Display facility information
9.6. Manage thematic layers 1- 4
9.6.1. Create or modify a thematic layer
9.6.2. Filter values in a thematic layer
9.6.3. Search for an organisation unit
9.6.4. Navigate between organisation hierarchies
9.6.5. Clear thematic layer
9.7. Manage boundary layers
9.7.1. Create or modify boundary layers
9.7.2. Search for organisation units
9.7.3. Navigate between organisation hierarchies
9.7.4. Clear boundary layer
9.8. Manage Earth Engine layer
9.8.1. Create or modify an Earth Engine layer
9.9. Add external map layers
9.10. Manage map favorites
9.10.1. Save a map as a favorite
9.10.2. Open a favorite
9.10.3. Rename a favorite
9.10.4. Overwrite a favorite
9.10.5. Share a map interpretation
9.10.6. Modify sharing settings for a favorite
9.10.7. Delete a favorite
9.11. Save a map as an image
9.12. Embed a map in an external web page
9.13. Search for a location
9.14. Measure distances and areas in a map
9.15. Get the latitude and longitude at any location
9.16. View a map as a pivot table or chart
9.16.1. Open a map as a chart
9.16.2. Open a map as a pivot table
9.17. See also
10. Using the Event Reports app
10.1. About the Event Reports app
10.2. Create an event report
10.3. Select dimension items
10.4. Select series, category and filter
10.5. Change the display of your table
10.6. Download chart data source
10.7. Manage favorites
10.7.1. Open a favorite
10.7.2. Save a favorite
10.7.3. Rename a favorite
10.7.4. Write an interpretation for a favorite
10.7.5. Create a link to a favorite
10.7.6. Delete a favorite
10.7.7. View interpretations based on relative periods
10.8. Visualize an event report as a chart
11. Using the Event Visualizer app
11.1. About the Event Visualizer app
11.2. Create a chart
11.3. Select a chart type
11.4. Select dimension items
11.5. Select series, category and filter
11.6. Change the display of your chart
11.7. Download a chart as an image or a PDF
11.8. Download chart data source
11.9. Manage favorites
11.9.1. Open a favorite
11.9.2. Save a favorite
11.9.3. Rename a favorite
11.9.4. Write an interpretation for a favorite
11.9.5. Create a link to a favorite
11.9.6. Delete a favorite
11.9.7. View interpretations based on relative periods
11.10. Visualize a chart as a pivot table
12. Control data quality
12.1. About data quality checks
12.2. Validation rule analysis
12.2.1. About validation rule analysis
12.2.2. Workflow
12.2.3. Schedule a validation rule analysis to run automatically
12.2.4. Run a validation rule analysis manually
12.2.5. See also
12.3. Standard deviation outlier analysis
12.3.1. About standard deviation outlier analysis
12.3.2. Run a standard deviation outlier analysis
12.3.3. Modify a standard deviation outlier value
12.4. Minimum maximum outlier analysis
12.4.1. About minimum maximum value based outlier analysis
12.4.2. Workflow
12.4.3. Configure a minimum maximum outlier analysis
12.4.4. Run a minimum maximum outlier analysis
12.5. Follow-up analysis
12.5.1. About follow-up analysis
12.5.2. Create list of data values marked for follow-up
13. Data approval
13.1. Approving and accepting
13.2. Authorities for approving data
13.3. Configuring data approval
13.4. Data visibility
13.5. Approving data
13.6. Approving by category option group set
13.6.1. Approving by one category option group set
13.6.2. Approving by multiple category option group sets
14. Using reporting functionality
14.1. Reporting functionality in DHIS2
14.2. Using standard reports
14.3. Using dataset reports
14.4. Using resources
14.5. Using reporting rate summary
14.6. Using organisation unit distribution reports
14.7. Generate analytics tables
15. Set user account preferences
16. Manage users, user roles and user groups
16.1. About user management
16.1.1. About users
16.1.2. About user roles
16.1.3. About user groups
16.2. Workflow
16.3. Manage users
16.3.1. Create a user
16.3.2. Edit user objects
16.3.3. Disable users
16.3.4. Display a user's profile
16.3.5. View users by organisation unit
16.3.6. Assign search organisation units to users
16.3.7. Delete current user
16.3.8. Clone users
16.3.9. Change user password
16.3.10. Delete user objects
16.3.11. Display details of user objects
16.4. Manage user roles
16.4.1. Create a user role
16.4.2. Edit user objects
16.4.3. Delete user objects
16.4.4. Display details of user objects
16.4.5. Change sharing settings for user objects
16.5. Manage user groups
16.5.1. Create a user group
16.5.2. Join user groups
16.5.3. Leave user groups
16.5.4. Edit user objects
16.5.5. Delete user objects
16.5.6. Display details of user objects
16.5.7. Change sharing settings for user objects
16.6. Enable support for OpenID
16.7. Decentralize user management
16.8. Example: user management in a health system
17. Visualize usage statistics
17.1. About the Usage Analytics app
17.2. Create a usage analytics graph
18. Configure metadata
18.1. About the Maintenance app
18.2. Manage categories
18.2.1. About categories
18.2.2. Workflow
18.2.3. Create or edit a category option
18.2.4. Create or edit a category
18.2.5. Create or edit a category combination
18.2.6. Create or edit a category option group
18.2.7. Create or edit a category option group set
18.2.8. Use category combinations for data sets
18.2.9. Assign a code to a category option combination
18.2.10. Clone metadata objects
18.2.11. Change sharing settings for metadata objects
18.2.12. Delete metadata objects
18.2.13. Display details of metadata objects
18.2.14. Translate metadata objects
18.3. Manage data elements
18.3.1. About data elements
18.3.2. Workflow
18.3.3. Create or edit a data element
18.3.4. Create or edit a data element group
18.3.5. Create or edit a data element group set
18.3.6. Clone metadata objects
18.3.7. Change sharing settings for metadata objects
18.3.8. Delete metadata objects
18.3.9. Display details of metadata objects
18.3.10. Translate metadata objects
18.4. Manage data sets and data entry forms
18.4.1. About data sets and data entry forms
18.4.2. Workflow
18.4.3. Create or edit a data set
18.4.4. Override data elements' category combinations in a data set
18.4.5. Edit compulsory data elements in a data set
18.4.6. Download default data forms in PDF format
18.4.7. Manage section forms
18.4.8. Manage custom forms
18.4.9. Change sharing settings for metadata objects
18.4.10. Delete metadata objects
18.4.11. Display details of metadata objects
18.4.12. Translate metadata objects
18.5. Manage indicators
18.5.1. About indicators
18.5.2. Workflow
18.5.3. Create or edit an indicator type
18.5.4. Create or edit an indicator
18.5.5. Create or edit an indicator group
18.5.6. Create or edit an indicator group set
18.5.7. Clone metadata objects
18.5.8. Change sharing settings for metadata objects
18.5.9. Delete metadata objects
18.5.10. Display details of metadata objects
18.5.11. Translate metadata objects
18.6. Manage organisation units
18.6.1. About organisation units
18.6.2. Workflow
18.6.3. Create or edit an organisation unit
18.6.4. Create or edit an organisation unit group
18.6.5. Create or edit an organisation unit group set
18.6.6. Assign names to organisation unit levels
18.6.7. Move organisation units within a hierarchy
18.6.8. Close an organisation unit
18.6.9. Clone metadata objects
18.6.10. Change sharing settings for metadata objects
18.6.11. Delete metadata objects
18.6.12. Display details of metadata objects
18.6.13. Translate metadata objects
18.7. [Work in progress] Manage validation rules
18.7.1. About validation rules
18.7.2. Create or edit a validation rule
18.7.3. Create or edit a validation rule group
18.7.4. Create or edit a validation notification
18.7.5. Clone metadata objects
18.7.6. Change sharing settings for metadata objects
18.7.7. Delete metadata objects
18.7.8. Display details of metadata objects
18.7.9. Translate metadata objects
18.8. Manage attributes
18.8.1. About attributes
18.8.2. Create or edit an attribute
18.8.3. Clone metadata objects
18.8.4. Delete metadata objects
18.8.5. Display details of metadata objects
18.8.6. Translate metadata objects
18.9. Manage constants
18.9.1. About constants
18.9.2. Create or edit a constant
18.9.3. Clone metadata objects
18.9.4. Change sharing settings for metadata objects
18.9.5. Delete metadata objects
18.9.6. Display details of metadata objects
18.9.7. Translate metadata objects
18.10. Manage option sets
18.10.1. About option sets
18.10.2. Create or edit an option set
18.10.3. Clone metadata objects
18.10.4. Change sharing settings for metadata objects
18.10.5. Delete metadata objects
18.10.6. Display details of metadata objects
18.10.7. Translate metadata objects
18.11. Manage legends
18.11.1. About legends
18.11.2. Create or edit a legend
18.11.3. Clone metadata objects
18.11.4. Change sharing settings for metadata objects
18.11.5. Delete metadata objects
18.11.6. Display details of metadata objects
18.11.7. Translate metadata objects
18.11.8. Assign a legend to indicator or data element
18.11.9. See also
18.12. Manage predictors
18.12.1. About predictors
18.12.2. Create or edit a predictor
18.12.3. Clone metadata objects
18.12.4. Delete metadata objects
18.12.5. Display details of metadata objects
18.12.6. Translate metadata objects
18.13. Manage push reports
18.13.1. About push reports
18.13.2. Create or edit a push report
18.13.3. Preview push reports
18.13.4. Run push report jobs
18.13.5. Clone metadata objects
18.13.6. Delete metadata objects
18.13.7. Display details of metadata objects
18.13.8. Translate metadata objects
18.14. Manage external map layers
18.14.1. About external map layers
18.14.2. Create or edit an external map layer
18.14.3. Clone metadata objects
18.14.4. Delete metadata objects
18.14.5. Display details of metadata objects
18.14.6. Translate metadata objects
18.15. Edit multiple object groups at once
18.15.1. Edit multiple objects in an object group
18.15.2. Edit an object in multiple object groups
19. Configure programs in the Maintenance app
19.1. About programs
19.2. Configure event programs in the Maintenance app
19.2.1. About event programs
19.2.2. Workflow: Create an event program
19.2.3. Create or edit an event program
19.2.4. Reference information: Program notification parameters
19.3. Configure tracker programs in the Maintenance app
19.4. Configure program indicators
19.4.1. About program indicators
19.4.2. Create or edit a program indicator
19.4.3. Create or edit a program indicator group
19.4.4. Reference information: Expression and filter examples per value type
19.4.5. Reference information: Functions, variables and operators to use in program indicator expressions and filters
19.5. Configure program rules
19.5.1. About program rules
19.5.2. Workflow
19.5.3. Create or edit a program rule variable
19.5.4. Create or edit a program rule
19.5.5. Example: Program rules
19.5.6. Reference information: Operators and functions to use in program rule expression
19.6. Configure relationship types
19.6.1. About relationship types
19.6.2. Create or edit a relationship type
19.7. Configure tracked entities
19.7.1. About tracked entities
19.7.2. Create or edit a tracked entity attribute
19.7.3. Create or edit a tracked entity
19.8. Clone metadata objects
19.9. Delete metadata objects
19.10. Change sharing settings for metadata objects
19.11. Display details of metadata objects
19.12. Translate metadata objects
20. Configure programs in the Programs/Attributes app (legacy app)
20.1. About programs
20.2. Manage programs
20.2.1. Create a program
20.2.2. Assign a program to organisation units
20.2.3. Edit programs
20.2.4. Change sharing settings for programs
20.2.5. Delete programs
20.2.6. Display programs
20.2.7. Translate program names
20.3. Manage program stages
20.3.1. About program stages
20.3.2. Create a program stage
20.3.3. Create a program stage section
20.3.4. Change program stage sort order
20.3.5. Change program stage section sort order
20.3.6. Edit program stages
20.3.7. Display program stages
20.3.8. Translate program stages
20.4. Manage program notifications
20.4.1. About program notifications
20.4.2. Create a program notification
20.4.3. Create a program stage notification
20.5. Manage custom registration forms
20.5.1. About program custom registration forms
20.5.2. About program stage data entry forms
20.5.3. Create a custom program registration form
20.5.4. Create a program stage data entry form
21. About sharing of objects
21.1. Sharing of objects
21.2. Sharing and access control
21.3. Sharing applied
22. Data Administration
22.1. Data integrity
22.1.1. Data elements without data set
22.1.2. Data elements without groups
22.1.3. Data elements violating exclusive group sets
22.1.4. Data elements in data set but not in form or sections
22.1.5. Data elements assigned to data sets with different period types
22.1.6. Data sets not assigned to organisation units
22.1.7. Sections with invalid category combinations
22.1.8. Indicators with identical formulas
22.1.9. Indicators without groups
22.1.10. Invalid indicator numerators
22.1.11. Invalid indicator denominators
22.1.12. Indicators violating exclusive group sets
22.1.13. Duplicate periods
22.1.14. Organisation units with cyclic references
22.1.15. Orphaned organisation units
22.1.16. Organisation units without groups
22.1.17. Organisation units violating compulsory group sets
22.1.18. Organisation units violating exclusive group sets
22.1.19. Organisation unit groups without group sets
22.1.20. Validation rules without groups
22.1.21. Invalid validation rule left side expressions
22.1.22. Invalid validation rule right side expressions
22.2. Maintenance
22.3. Resource tables
22.4. Locale Management
22.5. SQL View
22.5.1. Creating a new SQL view
22.5.2. SQL View management
22.6. Duplicate data elimination
22.7. Data statistics
22.8. Lock exceptions
22.9. Min-Max Value Generation
22.10. Cache Statistics
22.11. Scheduling
22.12. Data synchronization
22.13. Metadata Synchronization Scheduling
23. Datastore Manager
23.1. Using the Datastore Manager
23.2. Add a new namespace and key to the Datastore Manager
23.3. Add a key to an existing namespace in the Datastore Manager
23.4. Delete a namespace or key from the Datastore Manager
23.5. Search for namespaces or keys
23.6. Search your JSON library
23.7. Edit namespaces or keys in the Datastore Manager
24. Configure the GIS app
24.1. Context
24.2. Importing coordinates
25. Configure report functionality
25.1. Data sources for reporting
25.1.1. Types of data and aggregation
25.1.2. Resource tables
25.1.3. Report tables
25.2. How to create report tables
25.2.1. General options
25.2.2. Selecting data
25.2.3. Selecting report parameters
25.2.4. Data element dimension tables
25.2.5. Report table - best practices
25.3. Report table outcome
25.4. Standard reports
25.4.1. What is a standard report?
25.4.2. Designing Standard reports in iReport
25.4.3. Designing SQL based standard reports
25.4.4. Designing HTML based standard reports
26. Import and export data and metadata
26.1. Meta-data import
26.1.1. Meta-data import
26.1.2. Import CSV meta-data
26.1.3. GML data import
26.2. Import data
26.2.1. XML data import
26.2.2. Import CSV data
26.2.3. Event data import
26.2.4. Import PDF data
26.2.5. Import data from DHIS2 1.4
26.3. Export data and meta-data
26.3.1. Metadata export
26.3.2. Metadata export with dependencies
26.3.3. Data export
26.3.4. Event data export
26.3.5. Export data to other systems
27. Configure metadata synchronizing
27.1. About data and metadata synchronization
27.2. Workflow
27.3. Configure metadata versioning on central instance
27.4. Connect local instance to central instance
27.5. Configure automatic metadata synchronization on local instance
27.6. Create a new metadata version manually on central or local instance
27.7. Reference information: metadata synchronization configuration parameters
28. Mobile
28.1. DHIS2 Mobile Introduction
28.2. Mobile browser based data entry
28.2.1. Getting started with mobile browser data entry
28.3. J2ME GPRS/3G Client
28.3.1. Data connection availability
28.3.2. J2ME GPRS 3G facility reporting client
28.3.3. Detailed configuration of data sets and reporting forms
28.3.4. Mobile application setup
28.4. SMS Command
28.4.1. Set up SMS command
28.4.2. SMS Command Type
28.5. SMS Service
28.5.1. Setting up SMS service
28.5.2. Gateway Configurations
29. DHIS2 Tutorials
29.1. Create Scorecards using the Pivot Table app
29.1.1. Create a legend for your scorecard
29.1.2. Create a scorecard in the Pivot Table app
29.1.3. Organise the layout and display of your scorecard
29.1.4. Save and share your scorecard
30. About demo server, live package and database design
30.1. Using the DHIS2 demo server
30.2. Using the DHIS2 live package
30.2.1. Starting the DHIS2 Live package
30.2.2. Downloading and installing the server version
30.3. Logging on to DHIS2
30.4. Logging out of DHIS2
30.5. Quick intro to designing a DHIS2 database
30.5.1. The organisational hierarchy
30.5.2. Data Elements
30.5.3. Datasets and data entry forms
30.5.4. Validation rules
30.5.5. Indicators
30.5.6. Report tables and reports
30.5.7. GIS
30.5.8. Charts and dashboard
31. About data dimensions in DHIS2
31.1. Data dimensions: Core building blocks in DHIS2
31.2. Data elements: The What dimension
31.2.1. Data element categories
31.2.2. Data element group sets
31.3. The organisation unit dimension
31.3.1. Organisation unit group sets and groups
31.3.2. Best practice on the use of group sets and groups
31.4. The period dimension in DHIS2
31.4.1. Period types
31.4.2. Relative periods
31.4.3. Aggregation of periods
31.5. Data collection vs. data analysis
31.5.1. Data collection and storage
31.5.2. Input does not equal Output
31.6. Extended examples of data elements and forms
31.7. How this works in pivot tables
31.8. Case study: From paper forms to multidimensional datasets - lessons learned
31.8.1. From tables to category combinations - designing multi-dimensional data sets
31.8.2. Step-by-step approach to designing datasets
32. DHIS2 Frequently Asked Questions
33. Release and upgrade notes
A. User authorities
B. System settings
B.1. General settings
B.2. Analytics settings
B.3. Server settings
B.4. Appearance settings
B.5. Email settings
B.6. Messaging settings
B.7. Access settings
B.8. Approval settings
B.9. Calendar settings
B.10. Data import settings
B.11. Synchronization settings
B.12. System monitoring
B.13. OAuth2 clients
DHIS2 Glossary
Bibliography
Index

List of Figures

2.1. The health information cycle
13.1. Approving at organisation units
13.2. Approving and accepting
13.3. Hiding of unapproved data
13.4. Example category option groups

List of Tables

3.1. Feedback handling tools
6.1. Data entry widgets in the Tracker Capture app
6.2. Report types in the Tracker Capture app
7.1. Data dimension types
7.2. Pivot table options
7.3. Available formats
8.1. Chart types
8.2. Selection modes
8.3. Chart options
8.4. Available formats
9.1. View organisation unit information
10.1. Selection modes
10.2. Event reports options
10.3. Available formats
11.1. Chart types
11.2. Selection modes
11.3. Chart options
11.4. Available formats
13.1. Example Category Option Groups
13.2. Example Category Option Group Set approval levels
13.3. Example Multiple Category Option Group Sets
13.4. Example Multiple Category Option Group Set approval levels
16.1. User management terms and definitions
16.2. Objects in the Users app
18.1. Category objects in the Maintenance app
18.2. Data element objects in the Maintenance app
18.3. Value types
18.4. Aggregation operators
18.5. Data entry form types
18.6. Data set objects in the Maintenance app
18.7. Data entry events
18.8. Indicator formula
18.9. Indicator objects in the Maintenance app
18.10. Organisation unit objects in the Maintenance app
18.11.
18.12. Different behavior of validation rules when you use or do not use sliding windows
18.13. Attribute objects in the Maintenance app
18.14. Constant objects in the Maintenance app
18.15. Option set objects in the Maintenance app
18.16.
18.17. Predictor objects in the Maintenance app
18.18. Push reports objects in the Maintenance app
18.19. External map layer objects in the Maintenance app
18.20. Object types in the Metadata group editor
19.1. Program types
19.2. Program metadata objects in the Maintenance app
19.3. Program metadata objects in the Program / Attributes app
19.4. Types of data entry forms for event programs
19.5. Program notification parameters to use in program notifications
19.6. Program indicator components
19.7. Expression and filter examples per value type
19.8. Functions to use in a program indicator expression or filter
19.9. Variables to use in a program indicator expression or filter
19.10. Operators to use in a program indicator filter
19.11. Program rule components
19.12. Possible operators to use in a program rule expression
19.13. Custom functions to use in a program rule expression
19.14. Value types
19.15. Aggregation operators
20.1. Program metadata objects in the Program / Attributes app
20.2. Program metadata objects in the Maintenance app
20.3.
20.4.
20.5.
20.6.
20.7.
20.8.
20.9.
22.1. Data maintenance functions in the Data Administration app
24.1. Organisation unit identifiers supported for GML import
26.1. Object types and their dependencies
28.1.
28.2. Common Parameters
28.3. Gateway Configuration Parameters
31.1.
31.2. Example of detailed storage of data values when using data element categories "Place of Service" and "Age" (simplified for readability compared to the actual database table)
31.3.
31.4.
31.5.
33.1. DHIS2 releases
A.1.
B.1. General settings
B.2. Analytics settings
B.3. Server settings
B.4. Appearance settings
B.5. Email settings
B.6. Messaging settings
B.7. Access settings
B.8. Approval settings
B.9. Calendar settings
B.10. Data import settings
B.11. Synchronization settings
B.12. System monitoring settings

List of Examples

3.1.
6.1.
6.2.
6.3. Mother-Child relationship
6.4. Program summary report
7.1. Example pivot table with data elements as columns and periods as rows.
8.1. Chart illustrating the concepts of series, categories and filter
12.1.
16.1.
16.2.
16.3.
18.1. Three age categories
18.2. Category combination
18.3. Category options groups and group sets
18.4. Use category combination for a data set
18.5. Categories for data sets
18.6. Open future periods for data entry
18.7.
18.8. Section form example
18.9.
18.10. Classify facilities based on ownership
18.11. Create parallel dynamic administrative organisation unit structure
18.12.
18.13.
18.14. Vaccination coverage legends
18.15.
18.16.
18.17.
18.18.
18.19. Push report
19.1.
19.2.
19.3.
19.4.
19.5.
19.6.
19.7.
19.8.
19.9.
19.10.
19.11.
19.12.
19.13.
19.14.
19.15.
19.16. Display key/value pair
19.17. Show display text in Feedback widget
19.18. Show information from first program stage in Feedback widget
19.19. Calculate gestational age in weeks at visit
20.1.
20.2.
20.3.
20.4.
20.5.
20.6.
20.7.
27.1.
27.2. Versioning table for a central instance
27.3. Versioning table for a local instance
27.4. Metadata synchronization configuration parameters
B.1.
B.2.
B.3.
B.4.
B.5.
B.6.

About this guide

The DHIS2 documentation is a collective effort and has been developed by the development team and users. While the guide strives to be complete, there may be certain functionalities which have been omitted or which have yet to be documented. This section explains some of the conventions which are used throughout the document.

DHIS2 is a browser-based application. In many cases, screenshots have been included for enhanced clarity. Shortcuts to various functionalities are displayed such as Data element > Data element group. The ">" symbol indicates that you should click Data element and then click Data element group in the user interface.

Different styles of text have been used to highlight important parts of the text or particular types of text, such as source code. Each of the conventions used in the document are explained below.

[Note]Note

A note contains additional information which should be considered or a reference to more information which may be helpful.

[Tip]Tip

A tip can be a useful piece of advice, such as how to perform a particular task more efficiently.

[Important]Important

Important information should not be ignored, and usually indicates something which is required by the application.

[Caution]Caution

Information contained in these sections should be carefully considered, and if not heeded, could result in unexpected results in analysis, performance, or functionality.

[Warning]Warning

Information contained in these sections, if not heeded, could result in permanent data loss or affect the overall usability of the system.

Program listings usually contain some type of computer code.
They will be displayed with a shaded background and a different font. 

Commands will be displayed in bold text, and represent a command which would need to be executed on the operating system or database.

Links to external web sites or cross references will be displayed in blue text, and underlined like this..

Bibliographic references will displayed in square brackets like this [Store2007]. A full reference can be found in the bibliography contained at the end of this document.

Chapter 1. Getting started - help to navigate the user guide

What do you want to do?

Link to documentation

Related app(s)

Enter data

Enter aggregate data

Using the Data Entry app

Data Entry

Enter data for a program without registration (event program)

Using the Event Capture app

Event Capture

Enter data for a program with registration (tracker program)

Using the Tracker Capture app

Tracker Capture

Analyze and visualize data

Analyze data in a table

Analyze data in pivot tables

Pivot Table

Visualize data in a chart

Using the Data Visualizer app

Data Visualizer

Visualize data in a map

Using the GIS app

GIS

Analyze data in two types of reports.

Using the Event Reports app

Event Report

Visualize program data in a chart

Using the Event Visualizer app

Event Visualizer

Create a dashboard

Manage dashboards

Dashboard

Control data quality

Control data quality

Data Quality

Manage users and authorities

Create or edit users, user roles or user groups

Manage users, user roles and user groups

Users

Look up all user authorities

Appendix A. User authorities

Users

Visualize statistics about how users work with the Dashboard, Pivot Table, GIS, Event Visualizer, Data Visualizer and Event Reports apps

Visualize usage statistics

Usage Analytics

Customize the user interface

Change your account preferences

Set user account preferences

-

Configure metadata

Create metadata, for example organisation units and data elements

Configure metadata

Maintenance

Create metadata to use in an event or a tracker program

Configure programs in the Maintenance app

Maintenance

Configure the system

Look up all system settings

Appendix B. System settings

System Settings

Perform database maintenance

Data administration

Data Administration

Set up metadata synchronization between a central instance and multiple local instances

Configure metadata synchronization

System Settings

Data Administration

Configure data approval

Data approval

System Settings

Configure data and metadata import or export

Import and export data and metadata

Import-Export

Learn more about sharing of objects

About sharing of objects

-

Import coordinates and configure the GIS app

Configure the GIS app

Manage legends

Manage external map layers

Maintenance

Set up report functionality

Configure report functionality

-

Learn about event and tracker programs

Create a program

Configure programs in the Maintenance app

Configure programs in the Programs/Attributes app (legacy app)

Maintenance

Program

Enter data for a program with registration (tracker program)

Using the Tracker Capture app

Tracker Capture

Enter data for a program without registration (event program)

Using the Event Capture app

Event Capture

Visualize data from a program in a chart

Using the Event Visualizer app

Event Visualizer

Analyze data from a program in two types of reports

Using the Event Reports app

Event Report

Learn more about DHIS2

What is DHIS2?

What is DHIS2?

-

Learn about the DHIS2 data dimensions

Data dimensions in DHIS2

-

Chapter 2. What is DHIS2?

After reading this chapter you will be able to understand:

  • What is DHIS2 and what purpose it serves with respect to health information systems (HIS)?

  • What are the major technological considerations when it comes to deploying DHIS2, and what are the options are for extending DHIS2 with new modules?

  • What is the difference between patient based and aggregate data?

  • What are some of the benefits and challenges with using Free and Open Source Software (FOSS) for HIS?

2.1. DHIS2 Background

DHIS2 is a tool for collection, validation, analysis, and presentation of aggregate and patient-based statistical data, tailored (but not limited) to integrated health information management activities. It is a generic tool rather than a pre-configured database application, with an open meta-data model and a flexible user interface that allows the user to design the contents of a specific information system without the need for programming. DHIS2 is a modular web-based software package built with free and open source Java frameworks.

DHIS2 is open source software released under the BSD license and can be obtained at no cost. It runs on any platform with a Java Runtime Environment (JRE 7 or higher) installed.

DHIS2 is developed by the Health Information Systems Programme (HISP) as an open and globally distributed process with developers currently in India, Vietnam, Tanzania, Ireland, and Norway. The development is coordinated by the University of Oslo with support from NORAD and other donors.

The DHIS2 software is used in more than 40 countries in Africa, Asia, and Latin America, and countries that have adopted DHIS2 as their nation-wide HIS software include Kenya, Tanzania, Uganda, Rwanda, Ghana, Liberia, and Bangladesh. A rapidly increasing number of countries and organisations are starting up new deployments.

The documentation provided herewith, will attempt to provide a comprehensive overview of the application. Given the abstract nature of the application, this manual will not serve as a complete step-by-step guide of how to use the application in each and every circumstance, but rather will seek to provide illustrations and examples of how DHIS2 can be implemented in a variety of situations through generalized examples.

Before implementing DHIS2 in a new setting, we highly recommend reading the DHIS2 Implementation Guide (a separate manual from this one), also available at the main DHIS2 website.

2.2. Key features and purpose of DHIS2

The key features and purpose of DHIS2 can be summarised as follows:

  • Provide a comprehensive data management solution based on data warehousing principles and a modular structure which can easily be customised to the different requirements of a management information system, supporting analysis at different levels of the organisational hierarchy.

  • Customisation and local adaptation through the user interface. No programming required to start using DHIS2 in a new setting (country, region, district etc.).

  • Provide data entry tools which can either be in the form of standard lists or tables, or can be customised to replicate paper forms.

  • Provide different kinds of tools for data validation and improvement of data quality.

  • Provide easy to use - one-click reports with charts and tables for selected indicators or summary reports using the design of the data collection tools. Allow for integration with popular external report design tools (e.g. JasperReports) to add more custom or advanced reports.

  • Flexible and dynamic (on-the-fly) data analysis in the analytics modules (i.e. GIS, PivotTables,Data Visualizer, Event reports, etc).

  • A user-specific dashboard for quick access to the relevant monitoring and evaluation tools including indicator charts and links to favourite reports, maps and other key resources in the system.

  • Easy to use user-interfaces for metadata management e.g. for adding/editing datasets or health facilities. No programming needed to set up the system in a new setting.

  • Functionality to design and modify calculated indicator formulas.

  • User management module for passwords, security, and fine-grained access control (user roles).

  • Messages can be sent to system users for feedback and notifications. Messages can also be delivered to email and SMS.

  • Users can share and discuss their data in charts and reports using Interpretations, enabling an active information-driven user community.

  • Functionalities of export-import of data and metadata, supporting synchronisation of offline installations as well as interoperability with other applications.

  • Using the DHIS2 Web-API , allow for integration with external software and extension of the core platform through the use of custom apps.

  • Further modules can be developed and integrated as per user needs, either as part of the DHIS2 portal user interface or a more loosely-coupled external application interacting through the DHIS2 Web-API.

In summary, DHIS2 provides a comprehensive HIS solution for the reporting and analysis needs of health information users at any level.

2.3. Use of DHIS2 in HIS: data collection, processing, interpretation, and analysis.

The wider context of HIS can be comprehensively described through the information cycle presented in Figure 1.1 below. The information cycle pictorially depicts the different components, stages and processes through which the data is collected, checked for quality, processed, analysed and used.

Figure 2.1. The health information cycle

The health information cycle

DHIS2 supports the different facets of the information cycle including:

  • Collecting data.

  • Running quality checks.

  • Data access at multiple levels.

  • Reporting.

  • Making graphs and maps and other forms of analysis.

  • Enabling comparison across time (for example, previous months) and space (for example, across facilities and districts).

  • See trends (displaying data in time series to see their min and max levels).

As a first step, DHIS2 serves as a data collection, recording and compilation tool, and all data (be it in numbers or text form) can be entered into it. Data entry can be done in lists of data elements or in customised user defined forms which can be developed to mimic paper based forms in order to ease the process of data entry.

As a next step, DHIS2 can be used to increase data quality. First, at the point of data entry, a check can be made to see if data falls within acceptable range levels of minimum and maximum values for any particular data element. Such checking, for example, can help to identify typing errors at the time of data entry. Further, user can define various validation rules, and DHIS2 can run the data through the validation rules to identify violations. These types of checks help to ensure that data entered into the system is of good quality from the start, and can be improved by the people who are most familiar with it.

When data has been entered and verified, DHIS2 can help to make different kinds of reports. The first kind are the routine reports that can be predefined, so that all those reports that need to be routine generated can be done on a click of a button. Further, DHIS2 can help in the generation of analytical reports through comparisons of for example indicators across facilities or over time. Graphs, maps, reports and health profiles are among the outputs that DHIS2 can produce, and these should routinely be produced, analysed, and acted upon by health managers.

2.4. Technical background

2.4.1. DHIS2 as a platform

DHIS2 can be perceived as a platform on several levels. First, the application database is designed ground-up with flexibility in mind. Data structures such as data elements, organisation units, forms and user roles can be defined completely freely through the application user interface. This makes it possible for the system to be adapted to a multitude of locale contexts and use-cases. We have seen that DHIS2 supports most major requirements for routine data capture and analysis emerging in country implementations. It also makes it possible for DHIS2 to serve as management system for domains such as logistics, labs and finance.

Second, due to the modular design of DHIS2 it can be extended with additional software modules or through custom apps. These software modules/apps can live side by side with the core modules of DHIS2 and can be integrated into the DHIS2 portal and menu system. This is a powerful feature as it makes it possible to extend the system with extra functionality when needed, typically for country specific requirements as earlier pointed out.

The downside of the software module extensibility is that it puts several constraints on the development process. The developers creating the extra functionality are limited to the DHIS2 technology in terms of programming language and software frameworks, in addition to the constraints put on the design of modules by the DHIS2 portal solution. Also, these modules must be included in the DHIS2 software when the software is built and deployed on the web server, not dynamically during run-time.

In order to overcome these limitations and achieve a looser coupling between the DHIS2 service layer and additional software artifacts, a REST-based API has been developed as part of DHIS2. This Web API complies with the rules of the REST architectural style. This implies that:

  • The Web API provides a navigable and machine-readable interface to the complete DHIS2 data model. For instance, one can access the full list of data elements, then navigate using the provided URL to a particular data element of interest, then navigate using the provided URL to the list of data sets which the data element is a member of.

  • (Meta) Data is accessed through a uniform interface (URLs) using plain HTTP requests. There are no fancy transport formats or protocols involved - just the well-tested, well-understood HTTP protocol which is the main building block of the Web today. This implies that third-party developers can develop software using the DHIS2 data model and data without knowing the DHIS2 2specific technology or complying with the DHIS2 design constraints.

  • All data including meta-data, reports, maps and charts, known as resources in REST terminology, can be retrieved in most of the popular representation formats of the Web of today, such as XML, JSON, PDF and PNG. These formats are widely supported in applications and programming languages and gives third-party developers a wide range of implementation options.

2.4.2. Understanding platform independence

All computers have an Operating System (OS) to manage it and the programs running it. The operating system serves as the middle layer between the software application, such as DHIS2, and the hardware, such as the CPU and RAM. DHIS2 runs on the Java Virtual Machine, and can therefore run on any operating system which supports Java. Platform independence implies that the software application can run on ANY OS - Windows, Linux, Macintosh etc. DHIS2 is platform independent and thus can be used in many different contexts depending on the exact requirements of the operating system to be used.

Additionally, DHIS2 supports three major database management systems systems (DBMS). DHIS2 uses the Hibernate database abstraction framework and is compatible with the following database systems: PostgreSQL, MySQL and H2. PostgreSQL and MySQL are high-quality production ready databases, while H2 is a useful in-memory database for small-scale applications or development activities.

Lastly, and perhaps most importantly, since DHIS2 is a browser-based application, the only real requirement to interact with the system is with a web browser. DHIS2 supports most web browsers, although currently either Google Chrome, Mozilla Firefox or Opera are recommended.

2.4.3. Deployment strategies - online vs offline

DHIS2 is a network enabled application and can be accessed over the Internet, a local intranet as well as a locally installed system. The deployment alternatives for DHIS2 are in this chapter defined as i) offline deployment ii) online deployment and iii) hybrid deployment. The meaning and differences will be discussed in the following sections.

2.4.3.1. Offline Deployment

An off-line deployment implies that multiple standalone off-line instances are installed for end users, typically at the district level. The system is maintained primarily by the end users/district health officers who enters data and generate reports from the system running on their local server. The system will also typically be maintained by a national super-user team who pay regular visits to the district deployments. Data is moved upwards in the hierarchy by the end users producing data exchange files which are sent electronically by email or physically by mail or personal travel. (Note that the brief Internet connectivity required for sending emails does not qualify for being defined as on-line). This style of deployment has the obvious benefit that it works when appropriate Internet connectivity is not available. On the other side there are significant challenges with this style which are described in the following section.

  • Hardware: Running stand-alone systems requires advanced hardware in terms of servers and reliable power supply to be installed, usually at district level, all over the country. This requires appropriate funding for procurement and plan for long-term maintenance.

  • Software platform: Local installs implies a significant need for maintenance. From experience, the biggest challenge is viruses and other malware which tend to infect local installations in the long-run. The main reason is that end users utilize memory sticks for transporting data exchange files and documents between private computers, other workstations and the system running the application. Keeping anti-virus software and operating system patches up to date in an off-line environment are challenging and bad practices in terms of security are often adopted by end users. The preferred way to overcome this issue is to run a dedicated server for the application where no memory sticks are allowed and use an Linux based operating system which is not as prone for virus infections as MS Windows.

  • Software application: Being able to distribute new functionality and bug-fixes to the health information software to users are essential for maintenance and improvement of the system. Relying on the end users to perform software upgrades requires extensive training and a high level of competence on their side as upgrading software applications might a technically challenging task. Relying on a national super-user team to maintain the software implies a lot of traveling.

  • Database maintenance: A prerequisite for an efficient system is that all users enter data with a standardized meta-data set (data elements, forms etc). As with the previous point about software upgrades, distribution of changes to the meta-data set to numerous off-line installations requires end user competence if the updates are sent electronically or a well-organized super-user team. Failure to keep the meta-data set synchronized will lead to loss of ability to move data from the districts and/or an inconsistent national database since the data entered for instance at the district level will not be compatible with the data at the national level.

2.4.3.2. Online deployment

An on-line deployment implies that a single instance of the application is set up on a server connected to the Internet. All users (clients) connect to the on-line central server over the Internet using a web browser. This style of deployment is increasingly possible due to increased availability in (mobile) Internet coverage globally, as well as readily available and cheap cloud-computing resources. These developments make it possible to access on-line servers in even the most rural areas using mobile Internet modems (also referred to as dongles).

This on-line deployment style has huge positive implications for the implementation process and application maintenance compared to the traditional off-line standalone style:

  • Hardware: Hardware requirements on the end-user side are limited to a reasonably modern computer/laptop and Internet connectivity through a fixed line or a mobile modem. There is no need for a specialized server for each user, any Internet enabled computer will be sufficient. A server will be required for on-line deployments, but since there is only one (or several) servers which need to be procured and maintained, this is significantly simpler (and cheaper) than maintaining many separate servers is disparate locations. Given that cloud-computing resources continue to steadily decrease in price while increasing in computational power, setting up a powerful server in the cloud is far cheaper than procuring hardware.

  • Software platform: The end users only need a web browser to connect to the on-line server. All popular operating systems today are shipped with a web browser and there is no special requirement on what type or version. This means that if severe problems such as virus infections or software corruption occur one can always resort to re-formatting and installing the computer operating system or obtain a new computer/laptop. The user can continue with data entry where it was left and no data will be lost.

  • Software application: The central server deployment style means that the application can be upgraded and maintained in a centralized fashion. When new versions of the applications are released with new features and bug-fixes it can be deployed to the single on-line server. All changes will then be reflected on the client side the next time end users connect over the Internet. This obviously has a huge positive impact for the process of improving the system as new features can be distributed to users immediately, all users will be accessing the same application version, and bugs and issues can be sorted out and deployed on-the-fly.

  • Database maintenance: Similar to the previous point, changes to the meta-data can be done on the on-line server in a centralized fashion and will automatically propagate to all clients next time they connect to the server. This effectively removes the vast issues related to maintaining an upgraded and standardized meta-data set related to the traditional off-line deployment style. It is extremely convenient for instance during the initial database development phase and during the annual database revision processes as end users will be accessing a consistent and standardized database even when changes occur frequently.

This approach might be problematic in cases where Internet connectivity is volatile or missing in long periods of time. DHIS2 however has certain features which requires Internet connectivity to be available only part of the time for the system to work properly, such as offline data entry. In general however, DHIS2 does require Internet connectivity of some sort, but this is increasingly an easy problem to solve even in remote locations.

2.4.3.3. Hybrid deployment

From the discussion so far one realizes that the on-line deployment style is favourable over the off-line style but requires decent Internet connectivity where it will be used. It is important to notice that the mentioned styles can co-exist in a common deployment. It is perfectly feasible to have on-line as well as off-line deployments within a single country. The general rule would be that districts and facilities should access the system on-line over the Internet where sufficient Internet connectivity exist, and off-line systems should be deployed to districts where this is not the case.

Defining decent Internet connectivity precisely is hard but as a rule of thumb the download speed should be minimum 10 Kbyte/second for the client and at least 1 MBit/sec (dedicated) bandwidth for the server.

In this regard mobile Internet modems which can be connected to a computer or laptop and access the mobile network is an extremely capable and feasible solution. Mobile Internet coverage is increasing rapidly all over the world, often provide excellent connectivity at low prices and is a great alternative to local networks and poorly maintained fixed Internet lines. Getting in contact with national mobile network companies regarding post-paid subscriptions and potential large-order benefits can be a wort-while effort. The network coverage for each network operator in the relevant country should be investigated when deciding which deployment approach to opt for as it might differ and cover different parts of the country.

2.4.3.4. Server hosting

The on-line deployment approach raises the question of where and how to host the server which will run the DHIS2 application. Typically there are several options:

  1. Internal hosting within the Ministry of Health

  2. Hosting within a government data centre

  3. Hosting through an external hosting company

The main reason for choosing the first option is often political motivation for having “physical ownership” of the database. This is perceived as important by many in order to “own” and control the data. There is also a wish to build local capacity for server administration related to sustainability of the project. This is often a donor-driven initiatives as it is perceived as a concrete and helpful mission.

Regarding the second option, some places a government data centre is constructed with a view to promoting and improving the use and accessibility of public data. Another reason is that a proliferation of internal server environments is very resource demanding and it is more effective to establish centralized infrastructure and capacity.

Regarding external hosting there is lately a move towards outsourcing the operation and administration of computer resources to an external provider, where those resources are accessed over the network, popularly referred to as “cloud computing” or “software as a service”. Those resources are typically accessed over the Internet using a web browser.

The primary goal for an on-line server deployment is provide long-term stable and high-performance accessibility to the intended services. When deciding which option to choose for server environment there are many aspects to consider:

  1. Human capacity for server administration and operation. There must be human resources with general skills in server administration and in the specific technologies used for the application providing the services. Examples of such technologies are web servers and database management platforms.

  2. Reliable solutions for automated backups, including local off-server and remote backup.

  3. Stable connectivity and high network bandwidth for traffic to and from the server.

  4. Stable power supply including a backup solution.

  5. Secure environment for the physical server regarding issues such as access, theft and fire.

  6. Presence of a disaster recovery plan. This plan must contain a realistic strategy for making sure that the service will be only suffering short down-times in the events of hardware failures, network downtime and more.

  7. Feasible, powerful and robust hardware.

All of these aspects must be covered in order to create an appropriate hosting environment. The hardware requirement is deliberately put last since there is a clear tendency to give it too much attention.

Looking back at the three main hosting options, experience from implementation missions in developing countries suggests that all of the hosting aspects are rarely present in option one and two at a feasible level. Reaching an acceptable level in all these aspects is challenging in terms of both human resources and money, especially when compared to the cost of option three. It has the benefit that is accommodates the mentioned political aspects and building local capacity for server administration, on the other hand can this be provided for in alternative ways.

Option three - external hosting - has the benefit that it supports all of the mentioned hosting aspects at a very affordable price. Several hosting providers - of virtual servers or software as a service - offer reliable services for running most kinds of applications. Example of such providers are Linode and Amazon Web Services. Administration of such servers happens over a network connection, which most often anyway is the case with local server administration. The physical location of the server in this case becomes irrelevant as that such providers offer services in most parts of the world. This solution is increasingly becoming the standard solution for hosting of application services. The aspect of building local capacity for server administration is compatible with this option since a local ICT team can be tasked with maintaining the externally hosted server, but with not being burdened with worrying about power supply and bandwidth constraints which usually exist outside of major data centres.

An approach for combining the benefits of external hosting with the need for local hosting and physical ownership is to use an external hosting provider for the primary transactional system, while mirroring this server to a locally hosted non-critical server which is used for read-only purposes such as data analysis and accessed over the intranet.

2.5. Difference between Aggregated and Patient data in a HIS

Patient data is data relating to a single patient, such as his/her diagnosis, name, age, earlier medical history etc. This data is typically based on a single patient-health care worker interaction. For instance, when a patient visits a health care clinic, a variety of details may be recorded, such as the patient's temperature, their weight, and various blood tests. Should this patient be diagnosed as having "Vitamin B 12 deficiency anaemia, unspecified" corresponding to ICD-10 code D51.9, this particular interaction might eventually get recorded as an instance of "Anaemia" in an aggregate based system. Patient based data is important when you want to track longitudinally the progress of a patient over time. For example, if we want to track how a patient is adhering to and responding to the process of TB treatment (typically taking place over 6-9 months), we would need patient based data.

Aggregated data is the consolidation of data relating to multiple patients, and therefore cannot be traced back to a specific patient. They are merely counts, such as incidences of Malaria, TB, or other diseases. Typically, the routine data that a health facility deals with is this kind of aggregated statistics, and is used for the generation of routine reports and indicators, and most importantly, strategic planning within the health system. Aggregate data cannot provide the type of detailed information which patient level data can, but is crucial for planning and guidance of the performance of health systems.

In between the two you have case-based data, or anonymous "patient" data. A lot of details can be collected about a specific health event without necessarily having to identify the patient it involved. Inpatient or outpatient visits, a new case of cholera, a maternal death etc. are common use-cases where one would like to collect a lot more detail that just adding to the total count of cases, or visits. This data is often collected in line-listing type of forms, or in more detailed audit forms. It is different from aggregate data in the sense that it contains many details about a specific event, whereas the aggregate data would count how many events of a certain type, e.g. how many outpatient visits with principal diagnosis "Malaria", or how many maternal deaths where the deceased did not attend ANC, or how many cholera outbreaks for children under 5 years. In DHIS2 this data is collected through programs of the type single event without registration.

Patient data is highly confidential and therefore must be protected so that no one other than doctors can get it. When in paper, it must be properly stored in a secure place. For computers, patient data needs secure systems with passwords, restrained access and audit logs.

Security concerns for aggregated data are not as crucial as for patient data, as it is usually impossible to identify a particular person to a aggregate statistic . However, data can still be misused and misinterpreted by others, and should not be distributed without adequate data dissemination policies in place.

2.6. Free and Open Source Software (FOSS): benefits and challenges

Software carries the instructions that tell a computer how to operate. The human authored and human readable form of those instructions is called source code. Before the computer can actually execute the instructions, the source code must be translated into a machine readable (binary) format, called the object code. All distributed software includes the object code, but FOSS makes the source code available as well.

Proprietary software owners license their copyrighted object code to a user, which allows the user to run the program. FOSS programs, on the other hand, license both the object and the source code, permitting the user to run, modify and possibly redistribute the programs. With access to the source code, the users have the freedom to run the program for any purpose, redistribute, probe, adapt, learn from, customise the software to suit their needs, and release improvements to the public for the good of the community. Hence, some FOSS is also known as free software, where “free” refers, first and foremost, to the above freedoms rather than in the monetary sense of the word.

Within the public health sector, FOSS can potentially have a range of benefits, including:

  • Lower costs as it does not involve paying for prohibitive license costs.

  • Given the information needs for the health sector are constantly changing and evolving, there is a need for the user to have the freedom to make the changes as per the user requirements. This is often limited in proprietary systems.

  • Access to source code to enable integration and interoperability. In the health sector interoperability between different software applications is becoming increasingly important, meaning enabling two or more systems to communicate metadata and data. This work is a lot easier, and sometimes dependent on the source code being available to the developers that create the integration. This availability is often not possible in the case of proprietary software. And when it is, it comes at a high cost and contractual obligations.

  • FOSS applications like DHIS2 typically are supported by a global network of developers, and thus have access to cutting edge research and development knowledge.

Chapter 3. Manage dashboards

3.1. About dashboards

Dashboards are intended to provide quick access to different analytical objects (maps, charts, reports, tables, etc) to an individual user. Dashboards can also be shared with user groups.

Example 3.1. 

A user or administrator could create a dashboard called "Malaria" which might contain all relevant information on malaria. This dashboard could then be shared with the user group called "Malaria control", which might consist of all users of the malaria control program. All users within this group would then be able to view the same dashboard.


3.2. Set up the dashboard

The dashboard can contain any number of objects (charts, maps, reports, tables, resources, etc). These can be freely arranged on the dashboard as you wish. Dashboard items can be located and added by searching for favourites, resources, users or messages in the available search box and clicking on the "Add" button.

In this screen shot, the dashboard has already been populated with a number of objects, such as charts, map views, tables and messages. There are several hyperlink options available on each item:

  • Remove

    Allows you to remove the item from the dashboard when you have the appropriate user rights.

  • Get as Image

    Opens up a pop-up window and allows you to download the image to your computer.

  • Share interpretation

    Allows you to share an interpretation of the dashboard item. Your interpretation will be shared publicly with other users of the DHIS2 system, in the "Interpretation" section of the dashboard.

  • Explore

    Loads the favorite in its corresponding app (ie. a map will open full-sized in the GIS app).

  • Resize

    Resizes the dashboard item. There are 3 sizes in which to choose from.

Maps, charts and tables can be viewed as full size as images (in the case of charts and map views) or as HTML resources (in the case of reports, tables and messages).

To reorder how the dashboard appears, simply drag-and-drop any of the objects to a new position. In order to change between the various dashboards which are available, simply select the listed items that are available to review. The list can be scrolled though by using the <, > symbols to the left of the dashboard names.

3.3. Change dashboards name

  1. Open a DHIS2 dashboard.

  2. Click Manage.

  3. In the Name field, type the new name of the dashboard.

  4. Click Rename.

3.4. Add message widget to dashboards

  1. Open a DHIS2 dashboard.

  2. Click Manage and click Messages.

3.5. Delete dashboards

  1. Open a DHIS2 dashboard.

  2. Click Manage and click Delete.

3.6. Translate dashboard names

  1. Open a DHIS2 dashboard.

  2. Click Manage and click Translate.

  3. Select a locale and enter the dashboard name's translation.

  4. Click Save.

3.7. Dashboard sharing

In order to share a dashboard with user groups, first select "Share" from the dashboard page. This will bring up the dashboard sharing settings options. To share the dashboard with specific user groups, type in their name in the sharing settings dialogue box and click on the "+" sign to add them to the dashboard sharing settings

All dashboards have two sharing groups set by default.

  • External access (without login)

    This option, when selected, provides access to the dashboard as an external resource. This is useful for when you are creating an external web portal but would like to call information from a dashboard you have made internally within DHIS2. By default, this option is not selected.

  • Public access (with login)

    This option allows the selected dashboard to be pushed to all users within your DHIS2 instance. This can also be hidden from public view by selecting the "None" option, which is the default option for new dashboards.

User groups which have been added manually can be assigned two types of permissions within the dashboard

  • Can view

    Provides the user group with view only rights to the dashboard.

  • Can edit and view

    Allows the user groups to edit the dashboard in addition to viewing it. Editing allows for altering the layout, resizing and removing items, renaming/deleting the dashboard etc.

3.8. Manage messages and feedback messages

3.8.1. About messages and feedback messages

Within DHIS2 you can send messages and feedback messages to users, user groups and organisation units. When you send a feedback message, it is routed to a particular user group. If you're a member of this user group, you've access to feedback handling tools. You can for example set the status of an incoming feedback to "Pending" while you're waiting for information.

[Note]Note

Messages and feedback messages are not sent to users' e-mail addresses, the messages only appear within DHIS2.

3.8.2. Create a message

  1. From the Dashboard, click Messages.

  2. Click Write message.

  3. Define who you want to receive the message. You can send a message to organisation units, users and user groups.

    • In the To org unit field, select the organisation units or group of organisation units you want to send the message to.

    • In the To user field, select the users or user groups you want to send the message to.

  4. Type a subject and a message.

  5. Click Send.

3.8.3. Read a message

  1. From the Dashboard, click Messages.

  2. Click a message.

    If the message is part of a conversation, you'll see all messages in this conversation.

3.8.4. Create a feedback message

  1. From the Dashboard, click Write feedback.

  2. Type a subject and a feedback message.

  3. Click Send.

    The feedback message will appear in all of the specified users' inboxes.

3.8.5. Manage feedback messages

[Note]Note

You'll only see feedback messages and have access to the feedback handling tools if you are a member of the user group that is set up to handle feedback messages.

You'll receive feedback messages to your Messages inbox. For feedback messages you've the following options in addition to the messages options:

Table 3.1. Feedback handling tools

FunctionDescription

Priority

You can mark a feedback message with different priorities: None, Low, Medium or High.

Setting the priority makes it easier to keep track of which feedback message you need resolved first, and which feedback messages that can wait.

Status

All feedback messages get the status Open when created.

To keep track of existing feedback messages, you can change the status to Pending, Invalid or Solved.

You can filter feedback messages in your inbox based on their status. This makes it easier to switch between feedback messages and normal messages.

Assigned to

You can assign a feedback message to any member of the user group that is set up to handle feedback messages.

None means that you haven't assigned a user to the feedback message.

Internal reply

When you work in a feedback handling team you might want to discuss the feedback before sending an answer to the sender. You can keep this discussion in the same message conversation as the feedback itself.

To send a reply that within the feedback handling user group, click Internal reply.


3.8.6. Configure feedback message function

To configure the feedback message function, you must:

  1. Create a user group (for example "Feedback message recipients") that contains all the users who should receive feedback messages.

  2. Open the System Settings app and click General > Feedback recipients and select the user group you created in the previous step.

Chapter 4. Using the Data Entry app

4.1. About the Data Entry app

The Data Entry app is where you manually enter aggregated data in DHIS2. You register data for an organisation unit, a period, and a set of data elements (data set) at a time. A data set often corresponds to a paper-based data collection tool. You configure the data sets in the Maintenance app.

[Note]A data set can have both section and custom forms

If a data set has both a section form and a custom form, the system displays the custom form during data entry. Users who enter data can't select which form they want to use. In web-based data entry the order of display preference is:

  1. Custom form (if it exists)

  2. Section form (if it exists)

  3. Default form

Mobile devices do not support custom forms. In mobile-based data entry the order of display preference is:

  1. Section form (if it exists)

  2. Default form

When you close an organisation unit, you can't register or edit data to this organisation unit in the Data Entry app.

4.2. Enter data in a data entry form

  1. Open the Data Entry app.

  2. In the organisation unit tree to the left, select an organisation unit.

  3. Select a Data set.

  4. Select a Period.

    The available periods are controlled by the period type of the data set (reporting frequency). You can jump a year back or forward by clicking Prev year or Next year.

    [Note]Note

    Depending on how you've configured the data entry form, you might have to enter additional information before you can open the date entry form. This can for example be a project derived from a category combination.

  5. Enter data in the data entry form.

    • A green field means that the system has saved the value.

    • A grey field means that the field is disabled and you can't enter a value. The cursor will automatically jump to the next open field.

    • To move to the next field, press the Tab key or the Down Arrow key.

    • To move back to the previous field, press Shift+Tab or the Up Arrow key.

    • If you type in an invalid value, for example a character in a field that only accepts numeric values, you'll get a pop-up that explains the problem and the field will be coloured yellow (not saved) until you have corrected the value.

    • If you have defined a minimum maximum value range for the field and you enter a value that is outside this range, you'll get a pop-up message that says the value is out of range. The value remains unsaved until you've changed the value or updated the value range and then re-entered the value.

  6. When you've filled in the form, click Run validation in the top right corner or below the data entry form.

    All validation rules which involves data elements in the current data entry form (data set) are then run against the new data. If there are no violations of the validation rules, you'll see a message saying The data entry screen successfully passed validation. If there are validation violations, they will be presented in a list.

  7. (Optional) Correct validation violations.

    [Note]Note

    Zero (0) will delete the value if the data element has been configured to not store zeros.

  8. When you've corrected errors and you're done with data entry, click Complete.

    The system uses this information when generating completeness reports for district, county, province or the national level.

4.3. Mark a data value for follow-up

If you for example have a suspicious value that you need to investigate further, you can keep it the system, but mark it for follow-up. In the Data Quality app you can then run a follow-up analysis to view and correct all marked values.

  1. Open the Data Entry app.

  2. Open an existing data entry form.

  3. Double-click the field with the value you want to mark for follow-up.

  4. Click the star icon.

4.4. Edit data values in a completed data entry form

  1. Open the Data Entry app.

  2. Open an existing data entry form.

  3. Click Incomplete.

  4. Change the relevant data values.

    [Note]Note

    Zero (0) will delete the value if the data element has been configured to not store zeros,

  5. Click Complete.

4.5. Display a data value's history

You can display the last 12 values registered for a field.

  1. Open the Data Entry app.

  2. Open an existing data entry form.

  3. Double-click the field with the value you want to view the history for.

  4. Click Data element history.

4.6. Display a data value's audit trail

The audit trail allows you to view other data values which have been entered prior to the current value. The audit trail also shows when the data value was altered and which user who made the changes.

  1. Open the Data Entry app.

  2. Open an existing data entry form.

  3. Double-click the field with the value you want to view the audit trail for.

  4. Click Audit trail.

4.7. Create minimum maximum value range manually

  1. In the Data Entry app, open a data entry form.

  2. Double-click the field for which you want to set the minimum maximum value range.

  3. Enter Min limit and Max limit.

  4. Click Save.

    If values don't fall within the new value range the next time you enter data, the data entry cell will appear with an orange background.

  5. (Optional) Type a comment to explain the reason for the discrepancy, for example an event at a facility which may have generated a large number of clients.

  6. (Optional) Click Save comment.

[Tip]Tip

Click the star icon to mark the value for further follow-up.

4.8. Enter data offline

The Data Entry app works even if you don't have a stable Internet connection during data entry. When you don't have an internet connection, the data you enter is saved to your local computer. When the Internet connection is back, the app will push the data to the server. The total bandwidth usage is reduced since data entry forms no longer are retrieved from the server for each rendering.

[Note]Note

To use this functionality, you must login to the server while you've an Internet connection.

  • When you're connected to the Internet, the app displays this message at the top of the data entry form:

  • If your Internet connection breaks during data entry, the app detects it and displays this message:

    Now your data will be stored locally. You can continue to enter data as normal.

  • Once you have entered all necessary data and the app detects that the Internet connection is back, you'll see this message:

    Click Upload to synchronize data with the server.

  • When the data has successfully synchronized with the server, you'll see this confirmation message:

4.9. Enable multi-organisation unit data entry

It can be useful to enter data for multiple organisation units in the same data entry form, for instance if there are few data elements in the form and a huge number of organisation units in the hierarchy. In that case, you can enable multi-organisation unit data entry.

[Note]Note

Multi-organisation unit data entry only works for section forms.

  1. Open the System Settings app.

  2. Select Enable multi-organisation unit forms.

  3. In the Data Entry app, select the organisation unit immediately above the organisation unit you want to enter data for in the organisation unit hierarchy.

    Data elements will appear as columns and organisation units as rows in the form.

    [Note]Note

    The data entry forms should still be assigned to the facilities that you actually enter data for, that is the organisation units now appearing in the form.

Chapter 5. Using the Event Capture app

5.1. About the Event Capture app

In the Event Capture app you register events that occurred at a particular time and place. An event can happen at any given point in time. This stands in contrast to routine data, which can be captured for predefined, regular intervals. Events are sometimes called cases or records. In DHIS2, events are linked to a program. The Event Capture app lets you select the organisation unit and program and specify a date when a event happened, before entering information for the event.

The Event Capture app works online and offline. If the Internet connectivity drops, you can continue to capture events. The events will be stored locally in your web browser (client). When connectivity has returned, the system will ask you to upload the locally stored data. The system then sends the data to the server where the data is stored.

[Note]Note

If you close the web browser while in offline mode, it is not possible to reopen a new web browser window and continue the working session. However the data will still be saved locally and can be uploaded to the server the next time the machine is online and the you have logged into the server.

  • You only see programs associated with the organisation unit you've selected and programs you've access to view through your user role.

  • Both skip-logic and validation error/warning messages are supported during registration.

  • When you close an organisation unit, you can't register or edit events to this organisation unit in the Event Capture app. You can still view and filter the event list and view the details of an event.

  • On-the-fly indicator expression evaluation is supported. If a program has indicators defined for it and the moment all values related to the indicator expression are filled, the system will calculate indicator and display the result.

  • Sorting: this can be done by clicking the sorting icon of each column header. A red sorting icon implies the current sorting column. However, the sorting functionality works only within the page displayed. Currently, it is not possible to do sorting from serverside.

  • Filtering: this is done by clicking the small search icon shown to the right of each column header. Clicking them provides an input field to type a filtering criteria. The system starts applying the filter the moment a user starts to type. During filtering it is possible to define start and end dates for date type data elements and lower and upper limits for number types. Server side filtering is not-support at the moment.

5.2. Register an event

  1. Open the Event Capture app.

  2. Select an organisation unit.

  3. Select a program.

    You'll only see programs associated with the selected organisation unit and programs you've access to through your user role.

  4. Click Register event.

  5. Select a date.

  6. Fill in the required information.

    If the program's program stage is configured to capture GPS coordinate, you can enter the coordinates in two ways:

    • Enter values directly in corresponding fields.

    • Choose a location in a map. The map option also displays polygons and points that are defined for organisation units.

  7. Click Save and add new or Save and go back.

5.3. Edit an event

  1. Open the Event Capture app.

  2. Select an organisation unit.

  3. Select a program.

    All events registered to the selected program show up in a list.

  4. Click the event you want to modify and select Edit.

  5. Modify the event details and click Update.

5.4. Edit events in grid

The Edit in grid function allows you to edit a selected event within the table but only those columns (data elements) visible in the grid. If you need more columns, use Show/hide columns to specify which columns should be displayed in the list.

  1. Open the Event Capture app.

  2. Select an organisation unit.

  3. Select a program.

    All events registered to the selected program show up in a list.

  4. Click the event you want to modify and select Edit in grid.

  5. Modify the event details.

  6. Click on another event to close the edit mode.

5.5. Share events in edit mode

You can share an event in edit mode via its web address.

  1. Open the Event Capture app.

  2. Open the event you want to share in edit mode.

  3. Copy the URL.

    Make sure that the URL contains "event" and "ou" (organisation unit) parameters.

  4. Paste the URL in the sharing method of your choice, for example an e-mail or a message within DHIS2.

    If you're not logged in to DHIS2 when you click the link, you'll be asked to do so and then taken to the dashboard.

5.6. View an event audit history

  1. Open the Event Capture app.

  2. Select an organisation unit.

  3. Select a program.

    All events registered to the selected program show up in a list.

  4. Click an event and select Audit history.

5.7. Delete an event

  1. Open the Event Capture app.

  2. Select an organisation unit.

  3. Select a program.

    All events registered to the selected program show up in a list.

  4. Click an event and select Remove.

  5. Click Remove to cocnfirm the deletion.

5.8. Modify an event list's layout

You can select which columns to show or hide in an event list. This can be useful for example when you have a long list of data elements assigned to a program stage. Once you've modified the layout, it's saved on your user profile. You can have different layouts for different programs.

  1. Open the Event Capture app.

  2. Select an organisation unit.

  3. Select a program.

    All events registered to the selected program show up in a list.

  4. Click the Show/hide columns icon.

  5. Select the columns you want to display and click Close.

5.9. Print an event list

  1. Open the Event Capture app.

  2. Select an organisation unit.

  3. Select a program.

    All events registered to the selected program show up in a list.

  4. Click Print list.

5.10. Download an event list

  1. Open the Event Capture app.

  2. Select an organisation unit.

  3. Select a program.

    All events registered to the selected program show up in a list.

  4. Click the Downlad icon and select a format.

    You can download an event list in XML, JSON or CSV formats.

Chapter 6. Using the Tracker Capture app

6.1. About the Tracker Capture app

The Tracker Capture app is an advanced version of the Event Capture app.

  • Event Capture: handles single events without registration

  • Tracker Capture: handles multiple events (including single event) with registration.

  • You capture event data for a registered tracked entity instance (TEI).

  • You only see programs associated with the organisation unit you've selected and programs you've access to view through your user role.

  • The options you see in the search and register functions depend on the program you've selected. The program attributes control these options. The attributes also decide the columns names in the TEI list.

    If you don't select a program, the system picks default attributes.

  • Both skip-logic and validation error/warning messages are supported during registration.

  • When you close an organisation unit, you can't register or edit events to this organisation unit in the Tracker Capture app. You can still search for TEIs and filter the search results. You can also view the dashboard of a particular TEI.

6.2. About tracked entity instance (TEI) dashboards

You manage a TEI from the TEI's dashboard in the Tracker Capture app.

  • The dashboard consist of widgets. Drag and drop the widgets to place them in the order and in the position you want.

  • Click the pin icon to stick the right column of widgets to a fix position. This is useful especially during data entry.

    Example 6.1. 

    If you have many data elements or big form to fill in, stick the right widget column. Then all the widgets you've placed in the right column remain visible while you scroll in the data entry part.


  • Any indicator defined for the program you've selected will have its value calculated and displayed in the Indicators widget.

  • Navigation:

    • Back: takes you back to the search and registration page

    • Previous and next buttons: takes you to the previous or next TEI dashboard in the TEI search results list

    • Other programs field: if the TEI is enrolled in other programs, they're listed here. Click a program to change the program for which you enter data for the selected TEI. When you change programs, the content in the widgets change too.

6.3. Workflow

Example 6.2. 

Working process of Mother and child health program

  1. Create new or find existing TEI.

    You can search on defined attributes, for example name or address.

  2. Enroll TEI in a program.

  3. Based on the services of the program by the time, the app creates an activity plan for the TEI.

  4. The TEI is provided with various services depending on the program. All services are recorded.

  5. Use information about the individual cases to create reports.


6.4. Create a TEI

  1. Open the Tracker Capture app.

  2. In the organisation unit tree in the left hand pane, select an organisation unit.

  3. Verify that the Program field is empty.

  4. Click Register.

  5. Select an entity type.

  6. Fill in the required information.

  7. Click Save and continue or Save and add new.

    • Save and continue: completes the registration and opens the registered TEI's dashboard

    • Save and add new: completes the registration but stays on the same page. Use this option when you want to register one TEI after another without enrollment to a program.

[Note]Note

For unique tracked entity attributes the system can automatically generate and assign numeric IDs. When registering tracked entity instances on web, the registration form will then automatically be populated with a number in the given pattern. On Android, the ID generation is used to reserve a series of IDs for each Android device. This allows offline registration of tracked entity instances without risking duplicate IDs when syncing with the server.

You configure automated IDs in the Maintenance app: Tracker > Tracked entity attribute.

6.5. Create a TEI and enroll it in a program

You can create a TEI and enroll that TEI to a program in one operation:

  1. Open the Tracker Capture app.

  2. In the organisation unit tree in the left hand pane, select an organisation unit.

  3. Select a program.

  4. Click Register.

  5. Fill in the required information.

  6. Click Save and continue or Save and add new.

    • Save and continue: completes the registration and opens the registered TEI's dashboard

    • Save and add new: completes the registration but stays on the same page. Use this option when you want to register and enroll one TEI after another without enter data.

6.6. Open an existing TEI dashboard

There are two ways to find a TEI: simple and advanced search. You can also modify the search results list's layout and download the search results list in several formats.

Example: searching/registration

6.6.1. Simple TEI search

  1. Open the Tracker Capture app.

  2. (Optional) In the organisation unit tree in the left hand pane, select an organisation unit, then a program.

  3. In the right hand search field, type your search criteria.

    The search criteria could for example be a last name. You can search on all TEI attributes.

  4. Click the Search icon.

    A list of TEIs that match your search criteria displays.

  5. If you have selected a program, you can filter the search results based on enrollment status:

    • Only those with active enrollment

    • Only those with completed enrollment

    • Only those with cancelled enrollment

  6. Click a TEI.

    The TEI dashboard opens.

6.6.2. Advanced TEI search

Advanced search is conducted for the organisation units you select in the organisation tree inside the Advanced search window. The left-hand side organisation tree is generated based on your assigned organisation units. So in the Advanced search window you can select organisation units outside your own organisation unit.

  1. Open the Tracker Capture app.

  2. (Optional) In the organisation unit tree in the left hand pane, select an organisation unit, then a program.

    If a program is selected, advanced search allows you to search on the incident date if the program has one.

  3. In the right hand search field, click the Advanced search arrow.

    An expanded search form opens.

  4. Enter your search criteria(s).

    • Organisation unit: The tree displayed here depends on your user role. If the you have role "Search Tracked Entity Instance in All Org Units" or "ALL", a tree with all available organisation units is provided. Otherwise the tree displayed in advanced search is the same as the one on the left-hand side.

    • You can select the scope of the organisation unit search. In the Organisation unit scope section select Selected, Immediate children or All children.

    • Date or enrollment: appears if you have selected a program

  5. Click Search.

    A list of TEIs that match your search criteria(s) displays.

  6. If you have selected a program, you can filter the search results based on enrollment status:

    • Only those with active enrollment

    • Only those with completed enrollment

    • Only those with cancelled enrollment

  7. Click a TEI.

    The TEI dashboard opens.

6.6.3. Find a TEI outside your organisation unit

You can search for a TEI from another organisation unit, outside your assigned organisation units. To do this:

  • Your user role must have "Search Tracked Entity Instance in All Org Units" or "ALL" assigned to it.

  • You must select another organisation unit than your own in the organisation unit tree in the Advanced search window.

6.6.4. Download TEI search results list

  1. Create a TEI search results list.

  2. Click Download as and select a format:

    • XML

    • JSON

    • CSV

6.6.5. Modify TEI search results list's layout

You can select which columns to show or hide in a TEI search result list. Once you've modified the layout, it's saved on your user profile. You can have different layouts for different programs.

  1. Create a TEI search results list.

  2. Click Show/hide columns.

  3. Select the columns you want to display and click Close.

6.7. Enroll an existing TEI in a program

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. Select a program.

  4. In the Enrollment widget, click Add new.

  5. Fill in the required information and click Enroll.

6.8. Enter event data for a TEI

In a TEI dashboard, you enter event data in the Timeline Data entry or Tabular data entry widgets.

Table 6.1. Data entry widgets in the Tracker Capture app

Widget name

Description

Timeline Data entry

For data entry using either default or custom forms.

Depending on program definition, in particular program stages, events will be displayed in a timely fashion. Clicking on any of them displays the corresponding data entry. If a stage needs new event, a plus icon is displayed for new event creation. To proceed with data entry, it is mandatory to have event date. Once an event date is specified it is not possible to change due date. The assumption is that by specifying event date, the event has already taken place. If the event hasn't occurred yet, it is possible to change due date - this is effectively doing nothing but rescheduling. The buttons at the bottom help to change the status of a selected event.

Another key feature from this widget is addition of multiple notes for an event. Normally data recording is through data elements, however there are cases where it is necessary to record additional information or comments. This is where the notes section comes handy. However it is not possible to delete a note. The idea is notes are more like log books. Both skip-logic and validation error/warning messages are supported during data entry.

Tabular data entry

For tabular-style data entry.

The widget displays the list of program stages as left-hand side labels. Events will be listed in table for repeatable program stage, and allows for in-line edits of event data values.


6.9. Manage a TEI's enrollments

6.9.1. Deactivate a TEI's enrollment

If you deactivate a TEI dashboard, the TEI becomes 'read-only'. You can't enter data, enroll the TEI or edit the TEI's profile.

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Enrollment widget, click Deactivate.

  4. Click Yes to confirm.

6.9.2. Activate a TEI's enrollment

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Enrollment widget, click Activate.

  4. Click Yes to confirm.

6.9.3. Mark TEI's enrollment as complete

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Enrollment widget, click Complete.

  4. Click Yes to confirm.

6.9.4. Reopen completed enrollment

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Enrollment widget, click Reopen.

  4. Click Yes to confirm.

6.9.5. Display TEI's enrollment history

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Profile widget, click the Audit history icon.

6.9.6. Create a TEI enrollment note

An enrollment note is useful to record information about for example why an enrollment was cancelled.

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Notes widget, type your note and click Add.

6.10. Send a message to a TEI

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Messaging widget and select SMS or E-mail.

  4. Enter the required contact information.

    If the TEI's profile contains an e-mail address or a phone number, these fields are filled in automatically.

  5. Type a message.

  6. Click Send.

6.11. Mark a TEI for follow-up

You can use mark a TEI's enrollment for follow-up and then use this status as a filter when you create Upcoming events and Overdue events reports. This can be useful for example to monitor high-risk cases during a pregnancy program.

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Enrollment widget, click the Mark for follow-up icon.

6.12. Edit a TEI's profile

You edit a TEI's profile or tracked entity attributes in the Profile widget.

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Profile widget, click Edit.

  4. Modify the profile and click Save.

6.13. Add a relationship to a TEI

You can create a relationship from one TEI to another, for example linking a mother and a child together or a husband and a wife. Depending on how the relationship type is configured, the relative can inherit attributes.

Example 6.3. Mother-Child relationship

Assume there are two programs: Antenatal care for the mother and Immunization for the child. If first name, last name and address attributes are required for both programs, it is possible to configure last name and address attributes as inheritable. Then during child registration, there is no need to enter these inheritable attributes. You can add them automatically based on the mother's value. If you want to have a different value for the child, you can override the automatically generated value.


  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the Relationships widget, and click Add.

  4. Select a relationship type.

  5. Search for the relative and select it.

  6. Click Save.

6.14. Share a TEI dashboard

You can share a TEI dashboard via its web address.

  1. Open the Tracker Capture app.

  2. Open the dashboard you want to share.

  3. Copy the URL.

    Make sure that the URL contains "tei", "program" and "ou" (organisation unit) parameters.

  4. Paste the URL in the sharing method of your choice, for example an e-mail or a message within DHIS2.

    If you're not logged in to DHIS2 when you click the link, you'll be asked to do so and then taken to the dashboard.

6.15. Deactivate a TEI

If you deactivate a TEI, the TEI becomes 'read-only'. Data associated with the TEI is not deleted.

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the top right corner, click the button > Deactivate.

  4. Click Yes to confirm.

6.16. Activate a TEI

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the upper top corner, click the button > Activate.

  4. Click Yes to confirm.

6.17. Delete a TEI

[Warning]Warning

When you delete a TEI, you delete all data associated with the TEI.

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. In the top right corner, click the button > Delete.

  4. Click Yes to confirm.

6.18. Configure the TEI dashboard

6.18.1. Show or hide widgets

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. Click the Settings icon, and select Show/hide widgets.

  4. Select the widgets you want to show or hide.

  5. Click Close.

6.18.2. Save the dashboard's layout as default

You can save the dashboard's layout as default for a program.

  1. Open the Tracker Capture app.

  2. Open an existing TEI dashboard.

  3. Click the Settings icon, and select Save dashboard layout as default.

6.19. Create reports

  1. Open the Tracker Capture app.

  2. Click Reports.

  3. Select a report type.

    Table 6.2. Report types in the Tracker Capture app

    Report typeDescription

    Program summary

    A summary report for a particular program, organisation unit and time frame. The report consist of a list of TEIs and their records organised based on program stages.

    Program statistics

    A statistics report for a particular program. The report provides for example an overview of drop-outs or completion rates in a given time frame at a particular organisation unit.

    Upcoming events

    A tabular report showing tracked entity instances and their upcoming events for a selected program and time. You can sort the columns and search the values. Show/hide operations are possible on the columns. You can also export the table to Microsoft Excel.

    Overdue events

    A list of events for a selected program. The report displays a list of TEIs and their events that are not completed on time. You can sort the columns and search the values You can also export the table to Microsoft Excel.


Example 6.4. Program summary report

The summary report displays a list of TEIs and their records for "MNCH/PNC (Adult Woman)" program. The records are organized in the form of tabs where each tab is a program stage. The columns in the table are data elements which are configured to be displayed in reports under program stage definition.


Chapter 7. Analyze data in pivot tables

7.1. About the Pivot Table app

With the Pivot Table app, you can create pivot tables based on all available data dimensions in DHIS2. A pivot table is a dynamic tool for data analysis which lets you summarize and arrange data according to its dimensions. Examples of data dimensions in DHIS2 are:

  • data dimension itself (for example data elements, indicators and events)

  • periods (representing the time period for the data)

  • organisation hierarchy (representing the geographical location of the data)

From these dimensions you can freely select dimension items to include in the pivot table. You can create additional dimensions in DHIS2 with the group set functionality. This allows for different aggregation pathways, such as aggregation by "Partner" or facility type.

A pivot table can arrange data dimensions on columns, rows, and as filters. When you place a data dimension on columns, the pivot table will display one column per dimension item. If you place multiple data dimensions on columns, the pivot table displays one column for all combinations of the items in the selected dimensions. When you place a data dimension on rows, the pivot table displays one row per dimension item in a similar fashion. The dimensions you select as filters will not be included in the pivot table, but will aggregate and filter the table data based on the selected filter items.

[Tip]Constraints and tips
  • You must select at least one dimension on columns or rows.

  • You must include at least one period.

  • Data element group sets and reporting rates can't appear in the same pivot table.

  • A pivot table can't contain more than the maximum number of analytic records which have been specified in the system settings. The maximum number of records could also be constrained by the maximum RAM which is available to your browser. Consider making smaller tables instead of one table which displays all of your data elements and indicators together.

  • The Pivot Table app supports drill-down and up for periods and organisation unit. This means that you can for example drill down from yearly periods to quarters, months and weeks inside a pivot table. You can also drill down from the global organisation unit to countries, provinces and facilities.

7.2. Create a pivot table

  1. Open the Pivot Table app.

  2. In the menu to the left, select the dimension items you want to analyse, for example data elements or indicators.

  3. Click Layout and arrange the data dimensions as columns, rows and filters.

    You can keep the default selection if you want.

  4. Click Update.

Example 7.1. Example pivot table with data elements as columns and periods as rows.

In this example, indicators are listed as columns and periods as rows.


7.2.1. Select dimension items

The left menu lists sections for all available data dimensions. From each section you can select any number of dimension items. As an example, you can open the section for data elements and select any number of data elements from the available list. You can select an item by marking it and clicking on the arrow in the section header or simply double-clicking on the item. Before you can use a data dimension in your pivot table you must at least select one dimension item. If you arrange a dimension as columns or rows but do not select any dimension items, the dimension is ignored.

You must choose at least one data dimension type to create a pivot table. The available types are described in this table:

Table 7.1. Data dimension types

Data dimension typeDefinitionExamples
IndicatorsAn indicator is a calculated formula based on data elements.Coverage of immunization across a specific district.
Data elementsRepresents the phenomenon for which data has been captured.Number of malaria cases; number of BCG doses given.
Data setsA collection of data elements grouped for data collection. You can select :
  • Reporting rates: the percentage of actual reports compared to the expected number of reports

  • Reporting rates on time: the reporting rates based on timely form submissions. A timely submission must happen within a number of days after the reporting period.

  • Actual reports: the actual number of reports

  • Actual reports on time: the actual number of reports based on timely form submissions. A timely submission must happen within a number of days after the reporting period.

  • Expected reports: the number of expected reports based on organisation units where the data set and the reporting frequency has been assigned.

Reporting rates for immunization and morbidity forms.
Event data itemsA data element that is part of a program representing events that have been captured.Average weight and height for children in a nutrition program.
Program indicatorsA calculated formula based on data elements in a program representing events. Average BMI score for children in a nutrition program.


You can combine these dimensions to display for example aggregate data with reporting rates, or event data items together with program indicators, all in the same pivot tables. For the "data element" data dimension, you are also able to select "Totals" and "Details", which will allow you to view different category combination options together on the same pivot table.

For the period dimension you can choose between using fixed periods or relative periods. An example of a fixed period is "January 2012". To select fixed periods start by selecting a period type from the period type list. You can then select periods from the list of available periods.

Relative periods are periods relative to the current date. Examples of relative periods are "Last month", "Last 12 months", "Last 5 years". Relative periods can be selected by ticking the check-boxes next to each period. The main advantage of using relative periods is that when you save a pivot table favorite, it will stay updated with the latest data as time goes by without the need for constantly updating it.

For the organisation unit dimension you can select any number of organisation units from the hierarchy. To select all organisation units below a specific parent organisation unit, right click and click "Select all children". To manually select multiple organisation units, click and hold the Ctrl key while clicking on organisation units. You can tick "User org unit", "User sub-units" or "User sub-x2-units" in order to dynamically insert the organisation unit or units associated with your user account. This is useful when you save a pivot table favorite and want to share it with other users, as the organisation units linked with the other user's account will be used when viewing the favorite.

Selection of fixed and relative periods.

Dynamic dimensions can consist of organisation unit group sets, data element group sets, or category option group sets which have been configured with the type of "Disaggregation". Once the group sets have been configured, they will be come available in the pivot tables, and can be used as additional analysis dimensions, for instance to analyse aggregate data by Type of organisation unit or Implementing partner. Dynamic dimensions work the same as fixed dimensions.

[Tip]Tip

Some dynamic dimensions may contain many items. This can cause issues with certain browsers due to the length of the URL when many dimension members are selected. A special "All" check box is available for dynamic dimensions, which allows you to include all available dimensions implicitly in your pivot table, without specifying each and every dimension member.

7.2.2. Modify pivot table layout

After selecting data dimensions it is time to arrange your pivot table. Click "Layout" in the top menu to open the layout screen. In this screen you can position your data dimensions as table columns, rows or filters by clicking and dragging the dimensions from the dimensions list to the respective column, row and filter lists. You can set any number of dimensions in any of the lists. For instance, you can click on "Organisation units" and drag it to the row list in order to position the organisation unit dimension as table rows. Note that indicators, data elements and data set reporting rates are part of the common "Data" dimension and will be displayed together in the pivot table. For instance, after selecting indicators and data elements in the left menu, you can drag "Organisation Unit" from the available dimensions list to the row dimension list in order to arrange them as rows in the pivot table.

The table layout screen.

After you have set up your pivot table you can click "Update" to render your pivot table, or click "Hide" to hide the layout screen without any changes taking effect. Since we in our example have selected both the period and organisation unit dimension as rows, the pivot table will generate all combinations of the items in these dimensions and produce a table like this:

Pivot table where organisation units and periods are repeated on rows.

7.3. Change the display of your pivot table

  1. Open the Pivot Table app.

  2. Create a new pivot table or open a favorite.

  3. Click Options.

  4. Set the options as required.

    Table 7.2. Pivot table options

    Option

    Description

    Data

    Show column totals

    Show row totals

    Displays total values in the table for each row and column, as well as a total for all values in the table.

     

    Show column sub-totals

    Show row sub-totals

    Displays subtotals in the table for each dimension.

    If you only select one dimension, subtotals will be hidden for those columns or rows. This is because the values will be equal to the subtotals.

     

    Show dimension labels

    Shows the dimension names as part of the pivot tables.

     

    Hide empty rows

    Hides empty rows from the table. This is useful when you look at large tables where a big part of the dimension items don't have data in order to keep the table more readable.

     

    Hide empty columns

    Hides empty columns from the table. This is useful when you look at large tables where a big part of the dimension items don't have data in order to keep the table more readable.

     

    Skip rounding

    Skips the rounding of data values, offering the full precision of data values. Can be useful for finance data where the full dollar amount is required.

     

    Aggregation type

    The default aggregation operator can be over-ridden here, by selecting a different aggregation operator. Some of the aggregation types are Count, Min and Max.

     

    Number type

    Sets the type of value you want to display in the pivot table: Value, Percentage of row or Percentage of column.

    The options Percentage of row andPercentage of column mean that you'll display values as percentages of row total or percentage of column total instead of the aggregated value. This is useful when you want to see the contribution of data elements, categories or organisation units to the total value.

    Events

    Include only completed events

    Includes only completed events in the aggregation process. This is useful for example to exclude partial events in indicator calculations.

    Organisation units

    Show hierarchy

    Shows the name of all ancestors for organisation units, for example "Sierra Leone / Bombali / Tamabaka / Sanya CHP" for Sanya CHP.

    The organisation units are then sorted alphabetically which will order the organisation units according to the hierarchy.

    When you download a pivot table with organisation units as rows and you've selected Show hierarchy, each organisation unit level is rendered as a separate column. This is useful for example when you create Excel pivot tables on a local computer.

    Legend

    Apply legend

    Applies a legend to the values. This mean that you can apply a colour to the values.

    Select By data item to color the table cells individually according to each data element or indicator.

    You configure legends in the Maintenance app.

     

    Style

    Colors the text or background of cells in pivot tables based on the selected legend.

    You can use this option for scorecards to identify high and low values at a glance.

    Style

    Display density

    Controls the size of the cells in the table. You can set it to Comfortable, Normal or Compact.

    Compact is useful when you want to fit large tables into the browser screen.

     

    Font size

    Controls the size of the table text font. You can set it to Large, Normal or Small.

     

    Digit group separator

    Controls which character to separate groups of digits or "thousands". You can set it to Comma, Space or None.

    General

    Table title

    Type a title here to display it above the table.

    Parameters (for standard reports only)

    [Note]Note

    You create standard reports in the Reports app.

    In the Pivot Table app you set which parameters the system should prompt the user for.

    Reporting period

    Controls whether to ask user to enter a report period.

    Organisation unit

    Controls whether to ask user to enter an organisation unit.

    Parent organisation unit

    Controls whether to ask user to enter a parent organisation unit.

    Include regression

    Includes a column with regression values to the pivot table.

    Include cumulative

    Includes a column with cumulative values to the pivot table.

    Sort order

    Controls the sort order of the values.

    Top limit

    Controls the maximum number of rows to include in the pivot table.


  5. Click Update.

7.4. Manage favorites

Saving your charts or pivot tables as favorites makes it easy to find them later. You can also choose to share them with other users as an interpretation or display them on the dashboard.

You view the details and interpretations of your favorites in the Pivot Table, Data Visualizer, Event Visualizer, Event Reports apps. Use the Favorites menu to manage your favorites.

7.4.1. Open a favorite

  1. Click Favorites > Open.

  2. Enter the name of a favorite in the search field, or click Prev and Next to display favorites.

  3. Click the name of the favorite you want to open.

7.4.2. Save a favorite

  1. Click Favorites > Save as.

  2. Enter a Name and a Description for your favorite.

  3. Click Save.

7.4.3. Rename a favorite

  1. Click Favorites > Rename.

  2. Enter the new name for your favorite.

  3. Click Update.

7.4.4. Write an interpretation for a favorite

An interpretation is a link to a resource with a description of the data at a given period. This information is visible in the Dashboard app. To create an interpretation, you first need to create a favorite. If you've shared your favorite with other people, the interpretation you write is visible to those people.

  1. Click Favorites > Write interpretation.

  2. In the text field, type a comment, question or interpretation. You can see this information in the Dashboard app.

  3. Search for a user group that you want to share your favorite with, then click the + icon.

  4. Change sharing settings for the user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • None: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Share.

7.4.5. Create a link to a favorite

  1. Click Favorites > Get link.

  2. Select one of the following:

    • Open in this app: You get a URL for the favorite which you can share with other users by email or chat.

    • Open in web api: You get a URL of the API resource. By default this is an HTML resource, but you can change the file extension to ".json" or ".csv".

7.4.6. Delete a favorite

  1. Click Favorites > Delete.

  2. Click OK.

7.4.7. View interpretations based on relative periods

To view interpretations for relative periods, such as a year ago:

  1. Open a favorite with interpretations.

  2. Click >>> in the top right of the workspace.

  3. Click an interpretation. Your chart displays the data and the date based on when the interpretation was created.To view other interpretations, click them.

7.5. Download data from a pivot table

7.5.1. Download table layout data format

To download the data in the current pivot table:

  1. Click Download.

  2. Under Table layout, click the format you want to download: Microsoft Excel, CSV or HTML.

    The data table will have one column per dimension and contain names of the dimension items.

    [Tip]Tip

    When you download a pivot table with organisation units as rows and you've selected Show hierarchy in Table options, each organisation unit level is rendered as a separate column. This is useful for example when you create Excel pivot tables on a local computer.

[Tip]Tip

You can create a pivot table in Microsoft Excel from the downloaded Excel file.

7.5.2. Download plain data source format

You can download data in the current pivot table in JSON, XML, Excel, and CSV as plain data formats with different identification schemes (ID, Code, and Name). The data document uses identifiers of the dimension items and opens in a new browser window to display the URL of the request to the Web API in the address bar. This is useful for developers of apps and other client modules based on the DHIS2 Web API or for those who require a plan data source, for instance for import into statistical packages.

To download plain data source formats:

  1. Click Download.

  2. Under Plain data source, click the format you want to download.

    Table 7.3. Available formats

    Format

    Action

    Description

    JSON

    Click JSON

    Downloads JSON format based on ID property.

    You can also download JSON format based on Code or Name property.

    XML

    Click XML

    Downloads XML format based on ID property.

    You can also download XML format based on Code or Name property.

    Microsoft Excel

    Click Microsoft Excel

    Downloads XML format based on ID property.

    You can also download Microsoft Excel format based on Code or Name property.

    CSV

    Click CSV

    Downloads CSV format based on ID property.

    You can also download CSV format based on Code or Name property.

    JRXML

    Put the cursor on Advanced and click JRXML

    Produces a template of a Jasper Report which can be further customized based on your exact needs and used as the basis for a standard report in DHIS2.

    Raw data SQL

    Put the cursor on Advanced and click Raw data SQL

    Provides the actual SQL statement used to generate the pivot table. You can use it as a data source in a Jasper report, or as the basis for an SQL view.


7.5.3. Download a CSV format without rendering data in the web browser

You can download data in CSV format directly without rendering the data in the web browser. This helps to reduce any constraints in the system settings that has been set with regards to the maximum number of analytic records. This lets you download much larger batches of data that you can use for later offline analysis.

To download data in CSV format without first rendering data in the web browser:

  1. Click the arrow beside Update.

  2. Click CSV to download the format based on ID property.

    The file downloads to your computer.

    [Tip]Tip

    You can also download CSV format based on Code or Name property.

7.6. Embed a pivot table in an external web page

Certain analysis-related resources in DHIS2, like pivot tables, charts and maps, can be embedded in any web page by using a plug-in. You will find more information about the plug-ins in the Web API chapter in the DHIS2 Developer Manual.

To generate a HTML fragment that you can use to display the pivot table in an external web page:

  1. Click Embed.

  2. Click Select to highlight the HTML fragment.

7.7. Visualize pivot table data as a chart or a map

When you have made a pivot table you can switch between pivot table, chart and map visualization of your data.

7.7.1. Open a pivot table as a chart

  1. Click Chart > Open this table as chart.

    Your current pivot table opens as a chart.

7.7.2. Open a pivot table selection as a chart

If you want to visualize a small part of your pivot table as a chart you can click directly on a value in the table instead opening the whole table.

  1. In the pivot table, click a value.

  2. To verify the selection, hold the cursor over Open selection as chart. The highlighted dimension headers in the table indicate what data will be visualized as a chart.

  3. Click Open selection as chart.

7.7.3. Open a pivot table as a map

  1. Click Chart > Open this table as map

    Your current pivot table opens as a map.

7.7.4. Open a pivot table selection as a map

  1. In the pivot table, click a value.

    A menu displays.

  2. Click Open selection as map.

    Your selection opens as a map.

Chapter 8. Using the Data Visualizer app

8.1. About the Data Visualizer app

With the Data Visualizer app, you can select content, for example indicators, data elements, periods and organisation units, for an analysis. The app works well over poor Internet connections and generates charts in the web browser.

[Tip]Constraints and tips
  • Hide and show individual data series in the chart by clicking directly on the series label in the chart. They appear either at the top or to the right of the chart.

  • Click the triple left-arrow button on the top centre menu. This collapses the left side menu and gives more space for the chart. You can get the menu back by clicking on the same button again.

8.2. Create a chart

  1. Open the Data Visualizer app and select a chart type.

  2. In the menu to the left, select the metadata you want to analyse. You must select one or more elements from all of the three dimensions - data (indicators, data elements, reporting rates), periods (relative, fixed) and organisation units (units or groups).

    [Note]Note

    If you've access to the system settings, you can change the default period type under General settings > Default relative period for analysis.

    Last 12 Months from the period dimension and the root organisation unit are selected by default.

  3. Click Layout and arrange the dimensions.

    You can keep the default selection if you want.

  4. Click Update.

8.3. Select a chart type

The Data Visualizer app has nine different chart types, each with different characteristics. To select a chart type:

  1. In Chart type, click the chart type you need.

    Table 8.1. Chart types

    Chart type

    Description

    Column chart

    Displays information as vertical rectangular columns with lengths proportional to the values they represent.

    Useful when you want to, for example, compare performance of different districts.

    Stacked column chart

    Displays information as vertical rectangular columns, where bars representing multiple categories are stacked on top of each other.

    Useful when you want to, for example, display trends or sums of related data elements.

    Bar chart

    Same as column chart, only with horizontal bars.

    Stacked bar chart

    Same as stacked column chart, only with horizontal bars.

    Line chart

    Displays information as a series of points connected by straight lines. Also referred to as time series.

    Useful when you want to, for example, visualize trends in indicator data over multiple time periods.

    Area chart

    Is based on line chart, with the space between the axis and the line filled with colors and the lines stacked on top of each other.

    Useful when you want to compare the trends of related indicators.

    Pie chart

    Circular chart divided into sectors (or slices).

    Useful when you want to, for example, visualize the proportion of data for individual data elements compared to the total sum of all data elements in the chart.

    Radar chart

    Displays data on axes starting from the same point. Also known as spider chart.

    Speedometer chart

    Semi-circle chart which displays values out of 100 %. Also referred to as a gauge chart.


  2. Click Update.

8.4. Select dimension items

A dimension refers to the elements which describe the data values in the system. There are three main dimensions in the system:

  • Data: Includes data elements, indicators and datasets (reporting rates), describing the phenomena or event of the data.

  • Periods: Describes when the event took place.

  • Organisation units: Describes where the event took place.

The Data Visualizer app lets you use these dimensions completely flexible in terms of appearing as series, categories and filter.

[Note]Note

You can select dimension items in different ways:

  • Double-click a dimension item name.

  • Highlight one or several dimension items and click the single-arrow.

  • To select all dimension items in a list, click the double-arrow.

  • To clear dimension items, use the arrows or double-click the names in the Selected list.

8.4.1. Select indicators

The Data Visualizer app can display any number of indicators and data elements in a chart. You can select both indicators and data elements to appear together in the same chart, with their order of appearance the same as the order in which they are selected.

  1. Click Data and select Indicators.

  2. Select an indicator group.

    The indicators in the selected group appear in the Available list.

  3. Select one or several indicators by double-clicking the name.

    The indicator moves to the Selected list.

8.4.2. Select data elements

The Data Visualizer app can display any number of indicators and data elements in a chart. You can select both indicators and data elements to appear together in the same chart, with their order of appearance the same as the order in which they are selected.

  1. Click Data and select Data elements.

  2. Select a data element group.

    The data elements in the selected group appear in the Available list.

  3. Select one or several data elements by double-clicking the name.

    The data element moves to the Selected list.

8.4.3. Select reporting rates

The Data Visualizer app can display reporting rates in a chart, by itself or together with indicators and data elements. Reporting rates are defined by data sets.

  1. Click Data and select Reporting rates.

    The reporting rates appear in the Available list.

  2. Select one or several reporting rates by double-clicking the name.

    The reporting rate moves to the Selected list.

8.4.4. Select fixed and relative periods

  1. Click Periods.

  2. Select one or several periods.

    You can combine fixed periods and relative periods in the same chart. Overlapping periods are filtered so that they only appear once.

    • Fixed periods: In the Select period type box, select a period type. You can select any number of fixed periods from any period type.

    • Relative periods: In the lower part of the Periods section, select as many relative periods as you like. The names are relative to the current date. This means that if the current month is March and you select Last month, the month of February is included in the chart.

8.4.5. Select organisation units

  1. Click Organisation units.

  2. Click the gearbox icon.

  3. Select a Selection mode and an organisation unit.

    There are three different selection modes:

    Table 8.2. Selection modes

    Selection mode

    Description

    Select organisation units

    Lets you select the organisation units you want to appear in the chart from the organization tree.

    Select User org unit to disable the organisation unit tree and only select the organisation unit that is related to your profile.

    Select User sub-units to disable the organisation unit tree and only select the sub-units of the organisation unit that is related to your profile.

    Select User sub-x2-units to disable the organisation unit tree and only select organisation units two levels down from the organisation unit that is related to your profile.

    This functionality is useful for administrators to create a meaningful "system" favorite. With this option checked all users find their respective organisation unit when they open the favorite.

    Select levels

    Lets you select all organisation units at one or more levels, for example national or district level.

    You can also select the parent organisation unit in the tree, which makes it easy to select for example, all facilities inside one or more districts.

    Select groups

    Lets you select all organisation units inside one or several groups and parent organisation units at the same time, for example hospitals or chiefdoms.


  4. Click Update.

8.4.6. Select additional dimension items

Depending on the settings for your organisation unit group sets and data element group sets, you can select additional dimension items from the left menu.

Here you can add dimension items such as age, sex, etc. without having to add them as detailed data element selections. This is useful when you want to separate these categories in your analysis.

The additional dimension items you select are available in Chart layout as dimensions.

8.5. Select series, category and filter

You can define which dimension of the data you want to appear as series, category and filter.

  1. Click Layout.

  2. Drag and drop the dimensions to the appropriate space. Only one dimension can be in each section.

  3. Click Update.

Example 8.1. Chart illustrating the concepts of series, categories and filter

  • Series: A series is a set of continuous, related elements (for example periods or data elements) which you want to visualize in order to emphasize trends or relations in its data.

  • Categories: A category is a set of elements (for example indicators or organisation units) for which you want to compare its data.

  • Filter: The filter selection will filter the data displayed in the chart. Note that if you use the data dimension as filter, you can only specify a single indicator or data set as filter item, whereas with other dimension types you can select any number of items.


8.6. Change the display of your chart

  1. Click Options.

  2. Set the options as required.

    Table 8.3. Chart options

    Option

    Description

    Data

    Show values

    Shows the values above the series in the chart.

    Use 100% stacked values

    Displays 100 % stacked values in column charts.

    Use cumulative values

    Displays cumulative values in line charts.

    Hide empty categories

    Hides the category items with no data from the chart.

    None: doesn't hide any of the empty categories

    Before first: hides missing values only before the first value

    After last: hides missing values only after the last value

    Before first and after last: hides missing values only before the first value and after the last value

    All: hides all missing values

    This is useful for example when you create column and bar charts.

    Trend line

    Displays the trend line which visualizes how your data evolves over time. For example if performance is improving or deteriorating. Useful when periods are selected as category.

    Target line value/title

    Displays a horizontal line at the given domain value. Useful for example when you want to compare your performance to the current target.

    Base line value/title

    Displays a horizontal line at the given domain value. Useful for example when you want to visualize how your performance has evolved since the beginning of a process.

    Sort order

    Allows you to sort the values on your chart from either low to high or high to low.

    Aggregation type

    Defines how the data elements or indicators will be aggregated within the chart. Some of the aggregation types are By data element, Count, Min and Max.

    Events

    Include only completed events

    Includes only completed events in the aggregation process. This is useful when you want for example to exclude partial events in indicator calculations.

    Axes

    Range axis min/max

    Defines the maximum and minimum value which will be visible on the range axis.

    Range axis tick steps

    Defines the number of ticks which will be visible on the range axis.

    Range axis decimals

    Defines the number of decimals which will be used for range axis values.

    Range axis title

    Type a title here to display a label next to the range axis (also referred to as the Y axis). Useful when you want to give context information to the chart, for example about the unit of measure.

    Domain axis title

    Type a title here to display a label below the domain axis (also referred to as the X axis). Useful when you want to give context information to the chart, for example about the period type.

    General

    Hide chart legend

    Hides the legend and leaves more room for the chart itself.

    Hide chart title

    Hides the title (default or custom) of your chart.

    Chart title

    Type a title here to display a custom title above the chart. If you don't enter a title, the default title is displayed.

    Hide chart subtitle

    Hides the subtitle of your chart.

    Chart subtitle

    Type a subtitle here to display a custom subtitle above the chart but below the title. If you don't enter a subtitle, no subtitle is displayed in the chart.


  3. Click Update.

8.7. Manage favorites

Saving your charts or pivot tables as favorites makes it easy to find them later. You can also choose to share them with other users as an interpretation or display them on the dashboard.

You view the details and interpretations of your favorites in the Pivot Table, Data Visualizer, Event Visualizer, Event Reports apps. Use the Favorites menu to manage your favorites.

8.7.1. Open a favorite

  1. Click Favorites > Open.

  2. Enter the name of a favorite in the search field, or click Prev and Next to display favorites.

  3. Click the name of the favorite you want to open.

8.7.2. Save a favorite

  1. Click Favorites > Save as.

  2. Enter a Name and a Description for your favorite.

  3. Click Save.

8.7.3. Rename a favorite

  1. Click Favorites > Rename.

  2. Enter the new name for your favorite.

  3. Click Update.

8.7.4. Write an interpretation for a favorite

An interpretation is a link to a resource with a description of the data at a given period. This information is visible in the Dashboard app. To create an interpretation, you first need to create a favorite. If you've shared your favorite with other people, the interpretation you write is visible to those people.

  1. Click Favorites > Write interpretation.

  2. In the text field, type a comment, question or interpretation. You can see this information in the Dashboard app.

  3. Search for a user group that you want to share your favorite with, then click the + icon.

  4. Change sharing settings for the user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • None: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Share.

8.7.5. Create a link to a favorite

  1. Click Favorites > Get link.

  2. Select one of the following:

    • Open in this app: You get a URL for the favorite which you can share with other users by email or chat.

    • Open in web api: You get a URL of the API resource. By default this is an HTML resource, but you can change the file extension to ".json" or ".csv".

8.7.6. Delete a favorite

  1. Click Favorites > Delete.

  2. Click OK.

8.7.7. View interpretations based on relative periods

To view interpretations for relative periods, such as a year ago:

  1. Open a favorite with interpretations.

  2. Click >>> in the top right of the workspace.

  3. Click an interpretation. Your chart displays the data and the date based on when the interpretation was created.To view other interpretations, click them.

8.8. Download a chart as an image or a PDF

After you have created a chart you can download it to your local computer as an image or PDF file.

  1. Click Download.

  2. Under Graphics, click Image (.png) or PDF (.pdf).

    The file is automatically downloaded to your computer. Now you can for example embed the image file into a text document as part of a report.

8.9. Download chart data source

You can download the data source behind a chart in JSON, XML, Excel, CSV, JXRML or Raw data SQL formats with different identification schemes (ID, Code, and Name). The data document uses identifiers of the dimension items and opens in a new browser window to display the URL of the request to the Web API in the address bar. This is useful for developers of apps and other client modules based on the DHIS2 Web API or for those who require a plan data source, for instance for import into statistical packages.

To download plain data source formats:

  1. Click Download.

  2. Under Plain data source, click the format you want to download.

    Table 8.4. Available formats

    Format

    Action

    Description

    JSON

    Click JSON

    Downloads JSON format based on ID property.

    You can also download JSON format based on Code or Name property.

    XML

    Click XML

    Downloads XML format based on ID property.

    You can also download XML format based on Code or Name property.

    Microsoft Excel

    Click Microsoft Excel

    Downloads Microsoft Excel format based on ID property.

    You can also download Microsoft Excel format based on Code or Name property.

    CSV

    Click CSV

    Downloads CSV format based on ID property.

    You can also download CSV format based on Code or Name property.

    JRXML

    Put the cursor on Advanced and click JRXML

    Produces a template of a Jasper Report which can be further customized based on your exact needs and used as the basis for a standard report in DHIS 2.

    Raw data SQL

    Put the cursor on Advanced and click Raw data SQL

    Provides the actual SQL statement used to generate the data visualization. You can use it as a data source in a Jasper report, or as the basis for a SQL view.


8.10. Embed charts in any web page

Certain analysis-related resources in DHIS2, like pivot tables, charts and maps, can be embedded in any web page by using a plug-in. You will find more information about the plug-ins in the Web API chapter in the DHIS2 Developer Manual.

To generate a HTML fragment that you can use to display the chart in an external web page:

  1. Click Share > Embed in web page.

    The Embed in web page window opens.

  2. Click Select to highlight the HTML fragment.

8.11. Open a chart as a pivot table or as a map

  • Open a Chart and click Chart or click Map.

Chapter 9. Using the GIS app

Table of Contents

9.1. About the GIS app
9.2. Create a new thematic map
9.3. Manage event layers
9.3.1. Create or modify event layer
9.3.2. Turn off cluster
9.3.3. Modify cluster style
9.3.4. Modify information in event pop-up windows
9.3.5. Clear event layer
9.4. Manage facility layers
9.4.1. Create or modify a facility layer
9.4.2. Search for an organisation unit
9.4.3. Clear facility layer
9.5. Manage facilities in a layer
9.5.1. Relocate a facility
9.5.2. Swap longitude and latitude of a facility
9.5.3. Display facility information
9.6. Manage thematic layers 1- 4
9.6.1. Create or modify a thematic layer
9.6.2. Filter values in a thematic layer
9.6.3. Search for an organisation unit
9.6.4. Navigate between organisation hierarchies
9.6.5. Clear thematic layer
9.7. Manage boundary layers
9.7.1. Create or modify boundary layers
9.7.2. Search for organisation units
9.7.3. Navigate between organisation hierarchies
9.7.4. Clear boundary layer
9.8. Manage Earth Engine layer
9.8.1. Create or modify an Earth Engine layer
9.9. Add external map layers
9.10. Manage map favorites
9.10.1. Save a map as a favorite
9.10.2. Open a favorite
9.10.3. Rename a favorite
9.10.4. Overwrite a favorite
9.10.5. Share a map interpretation
9.10.6. Modify sharing settings for a favorite
9.10.7. Delete a favorite
9.11. Save a map as an image
9.12. Embed a map in an external web page
9.13. Search for a location
9.14. Measure distances and areas in a map
9.15. Get the latitude and longitude at any location
9.16. View a map as a pivot table or chart
9.16.1. Open a map as a chart
9.16.2. Open a map as a pivot table
9.17. See also

9.1. About the GIS app

With the GIS app you can overlay multiple layers and choose among different base maps. You can create thematic maps of areas and points, view facilities based on classifications, and visualize catchment areas for each facility. You can add labels to areas and points, and search and filter using various criteria. You can move points and set locations on the fly. Maps can be saved as favorites and shared with other people.

[Note]Note

To use predefined legends in the GIS app, you need to create them first in the Maintenance app.

Here's an overview of the GIS app workspace

  • The icons in the top left of the workspace represent the map layers. They are the starting point of the GIS app.

  • The panel on the right side of the workspace shows an overview of the layers:

    • The default base map is OSM Light. It's selected by default. If you're online you'll also see OpenStreetMap, Google Streets and Google Hybrid. You can use these maps as background maps and layers. Switch between them by selecting or clearing the checkbox.

    • If you want to increase or reduce the opacity of a layer, use the up and down arrows for the selected layer.

    • Use the map legends when you create a thematic map. A legend explains the link between values and colors on your map.

  • Zoom to content automatically adjusts the zoom level and map center position to put the data on your map in focus.

  • To view information for an event, simply click the event.

  • Right-click to display the longitude and latitude of the map.

9.2. Create a new thematic map

You use four vector layers to create a thematic map. The workflow for creating a new thematic map is:

  1. In the Apps menu, click GIS.

    The DHIS2 GIS window opens.

  2. In the top menu, click a layer you want to add to the map.

    • Event layer

    • Facility layer

    • Boundary layer

    • Thematic layer 1 - 4

  3. Click Edit layer and select the parameters you need..

  4. Click Update.

9.3. Manage event layers

The event layer displays the geographical location of events registered in the DHIS2 tracker. Provided that events have associated GPS coordinates, you can use this layer to drill down from the aggregated data displayed in the thematic layers to the underlying individual events or cases.

You can also display aggregated events at the facility or at the boundary level. You do this through a thematic layer using event data items. This is useful when you only have the coordinates for the Org Unit under which the events are recorded.

Event layer

9.3.1. Create or modify event layer

  1. In the top menu, click the event layer icon.

  2. Click Edit layer.

  3. Select a program and then select a program stage.

    If there is only one stage available for the selected program, the stage is automatically selected. A list of data elements and attributes will appear in the Available data items panel.

  4. Select any data element or attribute from this list as part of your query.

    • To select you can either double-click a data element or (multi) select and use the single-arrow downward button. The double-arrow button will select all data elements in the list. All selected data elements will get their own row in the Selected data items.

    • For data elements of type text you will get two choices: Contains implies that the query will match all values which contains your search value, and Is exact implies that only values which is completely identical to your search query will be returned.

    • For data elements of type option set, you can select any of the options from the drop down box by using the down-wards arrow or by start typing directly in the box to filter for options.

  5. In the Periods section, select the time span for when the events took place. You can select either a fixed period or a relative period.

    • Fixed period: In the Period field, select Start/end dates and fill in a start date and an end date.

    • Relative period: In the Period field, select one of the relative periods, for example This month or Last year.

  6. In the Organisation units section, select the organisation units you want to include in the query.

  7. In the Options section, you can:

    • Select a value from the Coordinate field for the positions shown on the map. By default, "Event location" is selected. Depending on the data elements or attributes that belong to a program, other coordinates such as "Household position" are available.

    • Select or clear Clustering to group nearby events.

    • Go to Style to select a color for the cluster points or change the radius of clusters (between 1 and 20).

    Clustering if you want to group nearby events and change the style of the cluster points.

  8. Click Update.

9.3.2. Turn off cluster

By default events are clustered in a map. You can turn off this function to display all events separately.

  1. In the top menu, click the event layer icon.

  2. Click Edit layer.

  3. Click Options.

  4. Clear Group nearby events check box.

  5. Click Update.

9.3.3. Modify cluster style

  1. In the top menu, click the event layer icon.

  2. Click Edit layer.

  3. In the Options section, change the Point color and Point radius.

  4. Click Update.

9.3.4. Modify information in event pop-up windows

For events in a cluster map, you can modify the information displayed in the event pop-up window.

Pop-up window with event information

  1. Open the Programs / Attributes app.

  2. Click Program.

  3. Click the program you want to modify and select View program stages.

  4. Click the program stage name and select Edit.

  5. Scroll down to the Selected data elements section.

  6. For every data element you want to display in the pop-up window, select corresponding Display in reports.

  7. Click Update.

9.3.5. Clear event layer

To clear all data in a map:

  1. In the top menu, click the event layer icon.

  2. Click Clear.

9.4. Manage facility layers

The facility layer displays icons that represent types of facilities. Polygons do not show up on the map, so make sure that you select an organisation unit level that has facilities.

A polygon is an enclosed area on a map representing a country, a district or a park. In GIS, a polygon is a shape defined by one or more rings, where a ring is a path that starts and ends at the same point.

Facility layer

9.4.1. Create or modify a facility layer

  1. In the top menu, click the facility layer icon.

  2. Click Edit layer.

  3. In the Organisation unit group icons section, select a Group set.

  4. In the Organisation units section, select one or several organisation units.

  5. In the Options section, select if you want to show labels and if so, how they look.

  6. In the Options section, select if you want to display a circle with a certain radius around each facility.

  7. Click Update.

9.4.2. Search for an organisation unit

To locate an organisation unit in the map:

  1. In the top menu, click the facility layer icon.

  2. Click Search.

    The Organisation unit search dialog box opens.

  3. In the text field, type the name of the organisation unit you are looking for or click a name in the list.

    The organisation unit is highlighted in the map.

9.4.3. Clear facility layer

To clear all data in a facility layer:

  1. In the top menu, click the facility layer icon.

  2. Click Clear.

9.5. Manage facilities in a layer

You can have facilities in Facility, Boundary and Thematic layers.

9.5.1. Relocate a facility

  1. Right-click a facility and click Relocate.

  2. Put the cursor in the new location.

    The new coordinate is stored permanently. This cannot be undone.

9.5.2. Swap longitude and latitude of a facility

  1. Right-click a facility and click Swap long/lat.

    This is useful if a user inverted latitude and longitude coordinates when creating the organisation unit.

9.5.3. Display facility information

You can view organisation unit information set by the administrator as follows:

Table 9.1. View organisation unit information

FunctionAction

View information for the current period

  1. Click a facility.

View information for a selected period

  1. Right-click a facility and click Show information.

  2. In the Infrastructural data section, select a period.

[Note]Note

You configure the displayed infrastructural data in the System Settings app.


9.6. Manage thematic layers 1- 4

There are four thematic layers in the GIS app. With these layers panels you can use your data for thematic mapping. Select your desired combination of indicator/data element, and period. then the organisation unit level. If your database has coordinates and aggregated data values for these organisation units, they will appear on the map.

[Note]Note

You must refresh the DHIS2 analytics tables to have aggregated data values available.

Example of a thematic map

9.6.1. Create or modify a thematic layer

  1. In the top menu, click the icon of the thematic layer you want to create or modify.

  2. Click Edit layer.

  3. In the Data and periods section, select the data and periods you want to display.

  4. In the Organisation units section, select one or several organisation units.

  5. In the Options section, go to Legend type and select Automatic or Predefined.

    • Automatic legend types means that the application will create a legend set for you based on your what method, number of classes, low color and high color you select. Method alludes to the size of the legend classes.

      Set to Equal intervals they will be “highest map value – lowest map value / number of classes”.

      Set to Equal counts the legend creator will try to distribute the organisation units evenly.

      The legend appears as an even gradation from the start color to the end color.

    • If you have facilities in your thematic layer, you can set the radius for maximum and minimum values by changing the values in the Low color / size and High color size boxes.

  6. In the Options section, select if you want to show labels and if so, how they look.

  7. In the Options panel, select an aggregation type. See also Aggregation operators.

  8. Click Update.

9.6.2. Filter values in a thematic layer

Thematic layer 1-4 menu have a Filter option in addition to the boundary layer menu options. It lets you apply value filters to the organisation units on the map. The filter is removed when you close the filter window.

To filter values in a thematic layer:

  1. In the top menu, click the icon of thematic layer you want to create or modify.

  2. Click Filter....

  3. Modify the Greater than and And/or lower than values.

  4. Click Update.

9.6.3. Search for an organisation unit

To locate an organisation unit in a thematic layer:

  1. In the top menu, click the relevant thematic layer icon.

  2. Click Search.

    The Organisation unit search dialog box opens.

  3. In the text field, type the name of the organisation unit you are looking for or click a name in the list.

    The organisation unit is highlighted in the map.

9.6.4. Navigate between organisation hierarchies

When there are visible organisation units on the map, you can easily navigate up and down in the hierarchy without using the level/parent user interface.

  1. Right-click one of the organisation units.

  2. Select Drill up or Drill down.

    The drill down option is disabled if you are on the lowest level or if there are no coordinates available on the level below. Vice versa goes for drilling up.

9.6.5. Clear thematic layer

To clear all data in a thematic layer:

  1. In the top menu, click the relevant thematic layer icon.

  2. Click Clear.

9.7. Manage boundary layers

The boundary layer displays the borders and locations of your organisation units. This layer is useful if you are offline and don't have access to background maps.

Boundary layer

9.7.1. Create or modify boundary layers

  1. In the top left menu, click the boundary layer icon.

  2. Click Edit layer.

  3. In the Organisation units section, select one or several organisation units.

    You can select the organisation units you want to show on the map by selecting a level and a parent. That means "show all organisations units at this level that are children of this parent".

  4. In the Options section, select if you want to show labels and if so, how they look.

  5. Click Update.

9.7.2. Search for organisation units

To locate an organisation unit on the map:

  1. In the top menu, click the boundary layer icon.

  2. Click Search.

    The Organisation unit search dialog box opens.

  3. In the text field, type the name of the organisation unit you are looking for or click a name in the list.

    The organisation unit is highlighted in the map.

9.7.3. Navigate between organisation hierarchies

When there are visible organisation units on the map, you can easily navigate up and down in the hierarchy without using the level/parent user interface.

  1. Right-click one of the organisation units.

  2. Select Drill up or Drill down.

    The drill down option is disabled if you are on the lowest level or if there are no coordinates available on the level below. The same applies when you are drilling up.

9.7.4. Clear boundary layer

To clear data in a boundary layer:

  1. In the top menu, click the boundary layer icon.

  2. Click Clear.

9.8. Manage Earth Engine layer

The Google Earth Engine layer lets you display satellite imagery and geospatial datasets from Google's vast catalog. This layer is useful in combination with thematic and event layers to enhance analysis. The following layers are supported:

  • Elevation: Metres above sea level

  • Nighttime lights: Lights from cities, towns, and other sites with persistent lighting, including gas flares (from 2013)

  • Population density: Population in 100 x 100 m grid cells (from 2010)

  • Temperature, population and land cover at any location.

    Right-click on the layers to view more information, for example temperature and elevation.

9.8.1. Create or modify an Earth Engine layer

  1. In the top menu, click the Google Earth Engine layer icon.

  2. Select a data set, for example "Elevation".

  3. Select Min / max value.

    The meaning of these values depend on which data set you've selected.

  4. Select a Color scale.

  5. Select the number of Steps.

    The number of steps means the number of distinct colors in the color scale.

  6. Click Update.

9.9. Add external map layers

  1. In the top menu, click the External layer icon.

  2. Click Edit to add a new layer.

  3. Select a layer from the list.

  4. Click Update.

    To remove a layer, click Clear.

    To hide a layer, go to the Layer stack/opacity menu pane and clear the External layer checkbox.

Here are some examples of external layers:

Example 1: First-order administrative boundaries

Example 2: Aerial imagery of Dar-es-Salaam

Example 3: Dark basemap with nighttime lights from Google Earth Engine

Example 4: World time zones

[Note]Note

To define external map layers, see the Maintenance app documentation.

9.10. Manage map favorites

Favorite maps

Saving your maps as favorites makes it easy to restore them later. It also gives you the opportunity to share them with other users as an interpretation or put it on the dashboard. You can save all types of layers as a favorite. A favorite always opens with the default background map.

9.10.1. Save a map as a favorite

When you have created a map it is convenient to save it as a favorite:

  1. Click Favorites.

    The Manage favorites dialog box opens.

  2. Click Add new.

    The Create new favorite dialog box opens.

  3. In the text field, type the name you want to give your pivot table.

  4. Click Create.

    Your favorite is added to the list.

9.10.2. Open a favorite

  1. Click Favorites.

    The Manage favorites dialog box opens.

  2. Find the favorite you want to open. You can either use Prev and Next or the search field to find a saved favorite. The list is filtered on every character that you enter.

  3. Click the name.

9.10.3. Rename a favorite

  1. Click Favorites.

    The Manage favorites dialog box opens.

  2. Find the favorite you want to rename.

    You can either use Prev and Next or the search field to find a saved favorite.

  3. Click the grey rename icon next to the favorite's name.

    The Rename favorite dialog box favorite opens.

  4. Type the new name and click Update.

9.10.4. Overwrite a favorite

To save the current map to an existing favorite (overwrite):

  1. Click Favorites.

    The Manage favorites dialog box opens.

  2. Find the favorite you want to overwrite.

    You can either use Prev and Next or the search field to find a saved favorite.

  3. Click the green overwrite icon next to the favorite's name.

  4. Click OK to confirm that you want to overwrite the favorite.

9.10.5. Share a map interpretation

For certain analysis-related resources in DHIS2, you can share a data interpretation. An interpretation is a link to the relevant resource together with a text expressing some insight about the data.

To create an interpretation of a map and share it with all users of the system:

  1. Open or create a favorite map.

  2. Click Share > Write interpretation.

    The Write interpretation dialog box opens.

  3. In the text field, type a comment, question or interpretation.

  4. Click Share.

    The dialog box closes automatically. You can see the interpretation on the Dashboard.

9.10.6. Modify sharing settings for a favorite

After you have created a map and saved it as a favorite, you can share the favorite with everyone or a user group. To modify the sharing settings:

  1. Click Favorites.

  2. Find the favorite you want to share.

    You can either use Prev and Next or the search field to find a saved favorite.

  3. Click the blue share icon next to the favorite's name.

  4. In the text box, enter the name of the user group you want to share your favorite with and click the + icon.

    The chosen user group is added to the list of recipients.

    Repeat the step to add more user groups.

  5. If you want to allow external access, select the corresponding box.

  6. For each user group, choose an access setting. The options are:

    • None

    • Can view

    • Can edit and view

  7. Click Save.

9.10.7. Delete a favorite

  1. Click Favorites.

    The Manage favorites dialog box opens.

  2. Find the favorite you want to delete.

    You can either use Prev and Next or the search field to find a saved favorite.

  3. Click the red delete icon next to the favorite's name.

  4. Click OK to confirm that you want to delete the favorite.

9.11. Save a map as an image

  1. Take a screenshot of the map with the tool of your choice.

  2. Save the screenshot in desired format.

9.12. Embed a map in an external web page

Certain analysis-related resources in DHIS2, like pivot tables, charts and maps, can be embedded in any web page by using a plug-in. You will find more information about the plug-ins in the Web API chapter in the DHIS2 Developer Manual.

To generate a HTML fragment that you can use to display the map in an external web page:

  1. Click Share > Embed in web page.

    The Embed in web page window opens.

  2. Click Select to highlight the HTML fragment.

9.13. Search for a location

The place search function allows you to search for almost any location or address. The place search is powered by the Mapzen mapping platform. This function is useful in order to locate for example sites, facilities, villages or towns on the map.

  1. On the left side of the GIS window, click the magnifier icon.

  2. Type the location you're looking.

    A list of matching locations appear as you type.

  3. From the list, select a location. A pin indicates the location on the map.

9.14. Measure distances and areas in a map

  1. In the upper left part of the map, put the cursor on the Measure distances and areas icon and click Create new measurement.

  2. Add points to the map.

  3. Click Finish measurement.

9.15. Get the latitude and longitude at any location

Right-click a map and select Show longitude/latitude. The values display in a pop-up window.

9.16. View a map as a pivot table or chart

When you have made a map you can switch between pivot table, chart and map visualization of your data. The function is inactive if the data the map is based on cannot render as a chart or table.

9.16.1. Open a map as a chart

  1. Click Chart > Open this map as chart.

    Your current map opens as a chart.

9.16.2. Open a map as a pivot table

  1. Click Chart > Open this map as table.

    Your current map opens as a pivot table.

9.17. See also

Chapter 10. Using the Event Reports app

10.1. About the Event Reports app

With the Event Reports app you can analyse events in two types of reports:

  • Aggregated event reports: Pivot table-style analysis with aggregated numbers of events

    By selecting Aggregated values from the top-left menu you can use the Event Reports app to create pivot tables with aggregated numbers of events. An event report is always based on a program. You can do analysis based on a range of dimensions. Each dimension can have a corresponding filter. Dimensions can be selected from the left-side menu.

  • Individual event reports: Lists of events

    By selecting Events from the top-left menu you can use the Event Reports app to make searches or queries for events based on a flexible set of criteria. The report will be displayed as a table with one row per event. Each dimension can be used as a column in the table or as a filter. Each dimension can have a criteria (filter). Data elements of type option set allows for "in" criteria, where multiple options can be selected. Numeric values can be compared to filter values using greater than, equal or less than operators.

10.2. Create an event report

  1. Open the Event Reports app.

  2. Select Aggregated values or Events.

  3. In the menu to the left, select the meta data you want to analyse.

  4. Click Layout and arrange the dimensions.

    You can keep the default selection if you want.

  5. Click Update.

10.3. Select dimension items

An event report is always based on a program and you can do analysis based on a range of dimensions. For programs with category combinations, you can use program categories and category option group sets as dimensions for tables and charts. Each dimension item can have a corresponding filter.

  1. Select data elements:

    1. Click Data.

    2. Select a program and a program stage.

      The data elements associated with the selected program are listed under Available. Each data element acts as a dimension.

    3. Select the data elements you need by double-clicking their names.

      After selecting a data element, it is visible under Selected data items.

    4. (Optional) For each data element, specify a filter with operators such as "greater than", "in" or "equal" together with a filter value.

  2. Select periods.

    1. Click Periods.

    2. Select one or several periods.

      You have three period options: relative periods, fixed periods and start/end dates. You can combine fixed periods and relative periods in the same chart. You cannot combine fixed periods and relative periods with start/end dates in the same chart. Overlapping periods are filtered so that they only appear once.

      • Fixed periods: In the Select period type box, select a period type. You can select any number of fixed periods from any period type. Fixed periods can for example be "January 2014".

      • Relative periods: In the lower part of the Periods section, select as many relative periods as you like. The names are relative to the current date. This means that if the current month is March and you select Last month, the month of February is included in the chart. Relative periods has the advantage that it keeps the data in the report up to date as time goes.

      • Start/end dates: In the list under the Periods tab, select Start/end dates. This period type lets you specify flexible dates for the time span in the report.

  3. Select organisation units.

    1. Click Organisation units.

    2. Click the gearbox icon.

    3. Select a Selection mode and an organisation unit.

      There are three different selection modes:

      Table 10.1. Selection modes

      Selection mode

      Description

      Select organisation units

      Lets you select the organisation units you want to appear in the chart from the organization tree.

      Select User org unit to disable the organisation unit tree and only select the organisation unit that is related to your profile.

      Select User sub-units to disable the organisation unit tree and only select the sub-units of the organisation unit that is related to your profile.

      Select User sub-x2-units to disable the organisation unit tree and only select organisation units two levels down from the organisation unit that is related to your profile.

      This functionality is useful for administrators to create a meaningful "system" favorite. With this option checked all users find their respective organisation unit when they open the favorite.

      Select levels

      Lets you select all organisation units at one or more levels, for example national or district level.

      You can also select the parent organisation unit in the tree, which makes it easy to select for example, all facilities inside one or more districts.

      Select groups

      Lets you select all organisation units inside one or several groups and parent organisation units at the same time, for example hospitals or chiefdoms.


  4. Click Update.

10.4. Select series, category and filter

You can define which data dimension you want to appear as columns, rows and filters in the pivot table. Each data element appears as individual dimensions and can be placed on any of the axes.

[Note]Note

Data elements of continuous value types (real numbers/decimal numbers) can only be used as filters, and will automatically be positioned as filters in the layout dialog. The reason for this is that continuous number cannot be grouped into sensible ranges and used on columns and rows.

  1. Click Layout.

  2. Drag and drop the dimensions to the appropriate space.

  3. Click Update.

10.5. Change the display of your table

You can customize the display of an event report.

  1. Click Options.

  2. Set the options as required. Available options are different between aggregated event reports and individual event reports.

    Table 10.2. Event reports options

    Option

    Description

    Available for report type

    Data

    Show column totals

    Displays totals at the end of each column in the pivot table.

    Aggregated event report

     

    Show column sub-totals

    Displays sub-totals for each column in the pivot table.

    Aggregated event report

     

    Show row totals

    Displays totals at the end of each row in the pivot table.

    Aggregated event report

     

    Show row sub-totals

    Displays sub-totals for each row in the pivot table.

    Aggregated event report

     

    Show dimension labels

    Displays labels for dimensions.

    Aggregated event report

     

    Hide empty rows

    Hides empty rows in the pivot table.

    Aggregated event report

     

    Hide n/a data

    Hides data tagged as N/A from the chart.

    Aggregated event report

     

    Include only completed events

    Includes only completed events in the aggregation process. This is useful when you want for example to exclude partial events in indicator calculations.

    Aggregated event report

    Individual event report

     

    Limit

    Sets a limit of the maximum number of rows that you can display in the table, combined with a setting for showing top or bottom values.

    Aggregated event report

     

    Output type

    Defines the output type. The output types are Event, Enrollment andTracked entity instance.

    Aggregated event report

    Program status

    Filters data based on the program status: All, Active, Completed or Cancelled.

    Aggregated event report

    Event status

    Filters data based on the event status: All, Active, Completed, Scheduled, Overdue or Skipped.

    Aggregated event report

    Organisation units

    Show hierarchy

    Includes the names of all parents of each organisation unit in labels.

    Aggregated event report

    Style

    Display density

    Controls the size of the cells in the table. You can set it to Comfortable, Normal or Compact.

    Compact is useful when you want to fit large tables into the browser screen.

    Aggregated event report

    Individual event report

     

    Font size

    Controls the size of the table text font. You can set it to Large, Normal or Small.

    Aggregated event report

    Individual event report

     

    Digit group separator

    Controls which character to separate groups of digits or "thousands". You can set it to Comma, Space or None.

    Aggregated event report

    Individual event report


  3. Click Update.

10.6. Download chart data source

You can download the data source behind an event report in HTML, JSON, XML, Microsoft Excel or CSV formats.

  1. Click Download.

  2. Under Plain data source, click the format you want to download.

    Table 10.3. Available formats

    Format

    Description

    HTML

    Creates HTML table based on selected meta data

    JSON

    Downloads data values in JSON format based on selected meta data

    XML

    Downloads data values in XML format based on selected meta data

    Microsoft Excel

    Downloads data values in Microsoft Excel format based on selected meta data

    CSV

    Downloads data values in CSV format based on selected meta data


10.7. Manage favorites

Saving your charts or pivot tables as favorites makes it easy to find them later. You can also choose to share them with other users as an interpretation or display them on the dashboard.

You view the details and interpretations of your favorites in the Pivot Table, Data Visualizer, Event Visualizer, Event Reports apps. Use the Favorites menu to manage your favorites.

10.7.1. Open a favorite

  1. Click Favorites > Open.

  2. Enter the name of a favorite in the search field, or click Prev and Next to display favorites.

  3. Click the name of the favorite you want to open.

10.7.2. Save a favorite

  1. Click Favorites > Save as.

  2. Enter a Name and a Description for your favorite.

  3. Click Save.

10.7.3. Rename a favorite

  1. Click Favorites > Rename.

  2. Enter the new name for your favorite.

  3. Click Update.

10.7.4. Write an interpretation for a favorite

An interpretation is a link to a resource with a description of the data at a given period. This information is visible in the Dashboard app. To create an interpretation, you first need to create a favorite. If you've shared your favorite with other people, the interpretation you write is visible to those people.

  1. Click Favorites > Write interpretation.

  2. In the text field, type a comment, question or interpretation. You can see this information in the Dashboard app.

  3. Search for a user group that you want to share your favorite with, then click the + icon.

  4. Change sharing settings for the user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • None: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Share.

10.7.5. Create a link to a favorite

  1. Click Favorites > Get link.

  2. Select one of the following:

    • Open in this app: You get a URL for the favorite which you can share with other users by email or chat.

    • Open in web api: You get a URL of the API resource. By default this is an HTML resource, but you can change the file extension to ".json" or ".csv".

10.7.6. Delete a favorite

  1. Click Favorites > Delete.

  2. Click OK.

10.7.7. View interpretations based on relative periods

To view interpretations for relative periods, such as a year ago:

  1. Open a favorite with interpretations.

  2. Click >>> in the top right of the workspace.

  3. Click an interpretation. Your chart displays the data and the date based on when the interpretation was created.To view other interpretations, click them.

10.8. Visualize an event report as a chart

When you have made an event report you can open it as a chart:

Click Chart > Open this chart as table.

Chapter 11. Using the Event Visualizer app

11.1. About the Event Visualizer app

With the Event Visualizer app, you can create charts based on event data.

11.2. Create a chart

  1. <Open the Event Visualizer app and select a chart type.

  2. In the menu to the left, select the meta data you want to analyse.

  3. Click Layout and arrange the dimensions.

    You can keep the default selection if you want.

  4. Click Update.

11.3. Select a chart type

The Event Visualizer app has eight different chart types, each with different characteristics. To select a chart type:

  1. In Chart type, click the chart type you need.

    Table 11.1. Chart types

    Chart type

    Description

    Column chart

    Displays information as vertical rectangular columns with lengths proportional to the values they represent.

    Useful when you want to, for example, compare performance of different districts.

    Stacked column chart

    Displays information as vertical rectangular columns, where bars representing multiple categories are stacked on top of each other.

    Useful when you want to, for example, display trends or sums of related data elements.

    Bar chart

    Same as column chart, only with horizontal bars.

    Stacked bar chart

    Same as stacked column chart, only with horizontal bars.

    Line chart

    Displays information as a series of points connected by straight lines. Also referred to as time series.

    Useful when you want to, for example, visualize trends in indicator data over multiple time periods.

    Area chart

    Is based on line chart, with the space between the axis and the line filled with colors and the lines stacked on top of each other.

    Useful when you want to compare the trends of related indicators.

    Pie chart

    Circular chart divided into sectors (or slices).

    Useful when you want to, for example, visualize the proportion of data for individual data elements compared to the total sum of all data elements in the chart.

    Radar chart

    Displays data on axes starting from the same point. Also known as spider chart.


  2. Click Update.

11.4. Select dimension items

An event chart is always based on a program and you can do analysis based on a range of dimensions. For programs with category combinations, you can use program categories and category option group sets as dimensions for tables and charts. Each dimension item can have a corresponding filter. You select dimension items from the left-side menu.

  1. Select data elements:

    1. Click Data.

    2. Select a program and a program stage.

      The data elements associated with the selected program are listed under Available. Each data element acts as a dimension.

    3. Select the data elements you need by double-clicking their names.

      After selecting a data element, it is visible under Selected data items.

    4. (Optional) For each data element, specify a filter with operators such as "greater than", "in" or "equal" together with a filter value.

  2. Select periods.

    1. Click Periods.

    2. Select one or several periods.

      You have three period options: relative periods, fixed periods and start/end dates. You can combine fixed periods and relative periods in the same chart. You cannot combine fixed periods and relative periods with start/end dates in the same chart. Overlapping periods are filtered so that they only appear once.

      • Fixed periods: In the Select period type box, select a period type. You can select any number of fixed periods from any period type. Fixed periods can for example be "January 2014".

      • Relative periods: In the lower part of the Periods section, select as many relative periods as you like. The names are relative to the current date. This means that if the current month is March and you select Last month, the month of February is included in the chart. Relative periods has the advantage that it keeps the data in the report up to date as time goes.

      • Start/end dates: In the list under the Periods tab, select Start/end dates. This period type lets you specify flexible dates for the time span in the report.

  3. Select organisation units.

    1. Click Organisation units.

    2. Click the gearbox icon.

    3. Select a Selection mode and an organisation unit.

      There are three different selection modes:

      Table 11.2. Selection modes

      Selection mode

      Description

      Select organisation units

      Lets you select the organisation units you want to appear in the chart from the organization tree.

      Select User org unit to disable the organisation unit tree and only select the organisation unit that is related to your profile.

      Select User sub-units to disable the organisation unit tree and only select the sub-units of the organisation unit that is related to your profile.

      Select User sub-x2-units to disable the organisation unit tree and only select organisation units two levels down from the organisation unit that is related to your profile.

      This functionality is useful for administrators to create a meaningful "system" favorite. With this option checked all users find their respective organisation unit when they open the favorite.

      Select levels

      Lets you select all organisation units at one or more levels, for example national or district level.

      You can also select the parent organisation unit in the tree, which makes it easy to select for example, all facilities inside one or more districts.

      Select groups

      Lets you select all organisation units inside one or several groups and parent organisation units at the same time, for example hospitals or chiefdoms.


  4. Click Update.

11.5. Select series, category and filter

You can define which data dimension you want to appear as series, category and filter. Each data element appears as individual dimensions and can be placed on any of the axes. Series and category panels can only have one dimension at the time.

[Note]Note

Data elements of continuous value types (real numbers/decimal numbers) can only be used as filters, and will automatically be positioned as filters in the layout dialog. The reason for this is that continuous number cannot be grouped into sensible ranges and used on columns and rows.

  1. Click Layout.

  2. Drag and drop the dimensions to the appropriate space. Only one dimension can be in each section.

  3. Click Update.

11.6. Change the display of your chart

You can customize the display of an event report.

  1. Click Options.

  2. Set the options as required.

    Table 11.3. Chart options

    Option

    Description

    Data

    Show values

    Displays values as numbers on top of each series.

    Use 100% stacked values

    Displays 100 % stacked values in column charts.

    Use cumulative values

    Displays cumulative values in line charts.

    Hide n/a data

    Hides data tagged as N/A from the chart.

    Include only completed events

    Includes only completed events in the aggregation process. This is useful when you want for example to exclude partial events in indicator calculations.

    Hide empty categories

    Hides the category items with no data from the chart.

    None: doesn't hide any of the empty categories

    Before first: hides missing values only before the first value

    After last: hides missing values only after the last value

    Before first and after last: hides missing values only before the first value and after the last value

    All: hides all missing values

    This is useful for example when you create column and bar charts.

    Trend line

    Displays the trend line which visualizes how your data evolves over time. For example if performance is improving or deteriorating. Useful when periods are selected as category.

    Target line value/title

    Displays a horizontal line and title (optional) at the given domain value. Useful for example when you want to compare your performance to the current target.

    Base line value/title

    Displays a horizontal line and title (optional) at the given domain value. Useful for example when you want to visualize how your performance has evolved since the beginning of a process.

    Sort order

    Allows you to sort the values on your chart from either low to high or high to low.

    Output type

    Defines the output type. The output types are Event, Enrollment andTracked entity instance.

    Program status

    Filters data based on the program status: All, Active, Completed or Cancelled.

    Event status

    Filters data based on the event status: All, Active, Completed, Scheduled, Overdue or Skipped.

    Axes

    Range axis min/max

    Defines the maximum and minimum value which will be visible on the range axis.

    Range axis tick steps

    Defines the number of ticks which will be visible on the range axis.

    Range axis decimals

    Defines the number of decimals which will be used for range axis values.

    Range axis title

    Type a title here to display a label next to the range axis (also referred to as the Y axis). Useful when you want to give context information to the chart, for example about the unit of measure.

    Domain axis title

    Type a title here to display a label below the domain axis (also referred to as the X axis). Useful when you want to give context information to the chart, for example about the period type.

    General

    Hide chart legend

    Hides the legend and leaves more room for the chart itself.

    Hide chart title

    Hides the title (default or custom) of your chart.

    Chart title

    Type a title here to display a custom title above the chart. If you don't enter a title, the default title is displayed.

    Hide chart subtitle

    Hides the subtitle of your chart.

    Chart subtitle

    Type a subtitle here to display a custom subtitle above the chart but below the title. If you don't enter a subtitle, no subtitle is displayed in the chart.


  3. Click Update.

11.7. Download a chart as an image or a PDF

After you have created a chart you can download it to your local computer as an image or PDF file.

  1. Click Download.

  2. Under Graphics, click PNG (.png) or PDF (.pdf).

    The file is automatically downloaded to your computer. Now you can for example embed the image file into a text document as part of a report.

11.8. Download chart data source

You can download the data source behind a chart in HTML, JSON, XML, Microsoft Excel or CSV formats. The data document uses identifiers of the dimension items and opens in a new browser window to display the URL of the request to the Web API in the address bar. This is useful for developers of apps and other client modules based on the DHIS2 Web API or for those who require a plan data source, for instance for import into statistical packages.

To download plain data source formats:

  1. Click Download.

  2. Under Plain data source, click the format you want to download.

    Table 11.4. Available formats

    Format

    Description

    HTML

    Creates HTML table based on selected meta data

    JSON

    Downloads data values in JSON format based on selected meta data

    XML

    Downloads data values in XML format based on selected meta data

    Microsoft Excel

    Downloads data values in Microsoft Excel format based on selected meta data

    CSV

    Downloads data values in CSV format based on selected meta data


11.9. Manage favorites

Saving your charts or pivot tables as favorites makes it easy to find them later. You can also choose to share them with other users as an interpretation or display them on the dashboard.

You view the details and interpretations of your favorites in the Pivot Table, Data Visualizer, Event Visualizer, Event Reports apps. Use the Favorites menu to manage your favorites.

11.9.1. Open a favorite

  1. Click Favorites > Open.

  2. Enter the name of a favorite in the search field, or click Prev and Next to display favorites.

  3. Click the name of the favorite you want to open.

11.9.2. Save a favorite

  1. Click Favorites > Save as.

  2. Enter a Name and a Description for your favorite.

  3. Click Save.

11.9.3. Rename a favorite

  1. Click Favorites > Rename.

  2. Enter the new name for your favorite.

  3. Click Update.

11.9.4. Write an interpretation for a favorite

An interpretation is a link to a resource with a description of the data at a given period. This information is visible in the Dashboard app. To create an interpretation, you first need to create a favorite. If you've shared your favorite with other people, the interpretation you write is visible to those people.

  1. Click Favorites > Write interpretation.

  2. In the text field, type a comment, question or interpretation. You can see this information in the Dashboard app.

  3. Search for a user group that you want to share your favorite with, then click the + icon.

  4. Change sharing settings for the user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • None: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Share.

11.9.5. Create a link to a favorite

  1. Click Favorites > Get link.

  2. Select one of the following:

    • Open in this app: You get a URL for the favorite which you can share with other users by email or chat.

    • Open in web api: You get a URL of the API resource. By default this is an HTML resource, but you can change the file extension to ".json" or ".csv".

11.9.6. Delete a favorite

  1. Click Favorites > Delete.

  2. Click OK.

11.9.7. View interpretations based on relative periods

To view interpretations for relative periods, such as a year ago:

  1. Open a favorite with interpretations.

  2. Click >>> in the top right of the workspace.

  3. Click an interpretation. Your chart displays the data and the date based on when the interpretation was created.To view other interpretations, click them.

11.10. Visualize a chart as a pivot table

When you have made a chart you can open it as a pivot table:

Click Chart > Open this chart as table.

Chapter 12. Control data quality

12.1. About data quality checks

The Data Quality app contains tools to validate the accuracy and reliability of the data in the system. You can verify the data quality with the help of validation rules and various statistical checks. Data quality has different dimensions including:

Dimension

Description

Correctness

Data should be within the normal range for data collected at that facility. There should be no gross discrepancies when compared with data from related data elements.

Completeness

Data for all data elements for all reporting organisation units should have been submitted.

Consistency

Data should be consistent with data entered during earlier months and years while allowing for changes with reorganization, increased work load, etc. and consistent with other similar facilities.

Timeliness

All data from all reporting organisation units should be submitted at the appointed time.

You can verify data quality in different ways, for example:

  • At point of data entry, DHIS2 can check the data entered to see if it falls within the minimum maximum value ranges of that data element (based on all previous data registered).

  • By defining validation rules, which can be run once the user has finished data entry. The user can also check the entered data for a particular period and organization unit(s) against the validation rules, and display the violations for these validation rules.

  • By analysing data sets, that is, examine gaps in the data.

  • By data triangulation, that is, comparing the same data or indicator from different sources.

12.2. Validation rule analysis

12.2.1. About validation rule analysis

A validation rule is based on an expression which defines a relationship between data element values. The expression forms a condition which should assert that certain logical criteria are met.

The expression consist of:

  • a left side

  • a right side

  • an operator

Example 12.1. 

A validation rule could assert that "Suspected malaria cases tested" >= "Confirmed malaria cases".


The validation rule analysis tests validation rules against the data registered in the system. Validation violations are reported when the condition defined in the validation rule expression is not met, which means when the condition is false.

You can configure a validation rule analysis to automatically send out information about validation violations to selected user groups. These messages are called validation notifications and you create them in the Maintenance app. Validation notifications are sent via the internal DHIS2 messaging system.

12.2.2. Workflow

  1. In the Maintenance app, create validation rules and validation rule groups.

  2. (Optional) In the Maintenance app, create validation notifications.

  3. Run the validation rule analysis, either automatically or manually.

    • In the Data Administration app, you schedule the validation rule analysis to run automatically for all validation rules included in one or several validation notifications. After the system has run the analysis, you'll see the validation violations (if any) in the validation notifications sent via the internal DHIS2 messaging system.

    • In the Data Quality app, you run the validation rule analysis manually for selected validation rules. After the analysis process has finished, you'll see a list of validation violations (if any).

12.2.3. Schedule a validation rule analysis to run automatically

[Note]Note

Only validation rules that are included in one or several validation notifications will be a part of the validation rule analysis. If there's no corresponding validation notification for a validation rule, the system has nowhere to send the validation violations.

  1. Verify that you have created all the validation rules, validation rule groups and validation notifications you need.

  2. Open the Data Administration app and click Scheduling.

  3. If scheduling is active, click Stop.

  4. In the Data monitoring section, select All daily.

  5. Click Start.

12.2.4. Run a validation rule analysis manually

  1. Verify that you have created all the validation rules, validation rule groups and validation notifications you need.

  2. Open the Data Quality app and click Validation rule analysis.

  3. Select Start date and End date.

  4. Select which Validation rule group you want to include in the analysis.

    You can select all validation rules or all validation rules from a single validation rule group.

  5. (Optional) Select Send notifications to trigger validation notifications.

    [Note]Note

    If you want to send out validation notifications, you must first create them in the Maintenance app.

  6. Select a Parent organisation unit.

  7. Click Validate.

    The analysis process duration depends on the amount of data that is being analysed. If there are no violations of the validation rules, you'll see a message saying Validation passed successfully. If there are validation violations, they will be presented in a list.

  8. (Optional) Click the show details icon to get more information about a validation violation. In the pop-up window you'll find information about the data elements included in the validation rules and their corresponding data values. You can use this information to identify the source of the validation rule violation.

  9. (Optional) Click Download as PDF, Download as Excel or Download as CSV to download the validation violations list in PDF, Excel or CSV formats.

12.3. Standard deviation outlier analysis

12.3.1. About standard deviation outlier analysis

The standard deviation outlier analysis identifies values that are numerically distant from the rest of the data. The analysis is based on the standard normal distribution. The system calculates the average, based on values since the beginning of time, for one particular combination of organisation unit, data element, category option combination and attribute option combination. Outliers can occur by chance but often indicate a measurement error or a heavy-tailed distribution which leads to very high numbers. You should investigate measurement errors and try to correct them before you discard them from the analysis.

[Warning]Warning

It's not recommended to use tools or interpretations that assume a normal distribution for heavy-tailed distributions.

For example: the standard deviation outlier analysis is not an appropriate tool when you expect huge seasonal variations in the data.

12.3.2. Run a standard deviation outlier analysis

  1. Open the Data Quality app and click Std dev outlier analysis.

  2. Select From date and To date.

  3. Select data set(s).

  4. Select Parent organisation unit.

    All children of the organisation unit will be included. The analysis is made on raw data "under" the parent organisation unit, not on aggregated data.

  5. Select a number of standard deviations.

    This refers to the number of standard deviations the data is allowed to deviate from the mean before it is classified as an outlier.

  6. Click Start.

    The analysis process duration depends on the amount of data that is being analysed. If there are standard deviations outliers, they will be presented in a list.

    For each outlier, you'll see the data element, organisation unit, period, minimum value, actual value and maximum value. The minimum and maximum values refer to the border values derived from the number of standard deviations selected for the analysis.

[Tip]Tip

Click the star icon to mark an outlier value for further follow-up.

12.3.3. Modify a standard deviation outlier value

You can modify an outlier value directly in the analysis result list:

  1. In the value column, click inside the field that contains the value you want to change.

  2. Enter a value and then navigate away from that field either by clicking tab or anywhere outside the field.

    The system provides an alert if the value is still outside the defined minimum and maximum values, but the value will be saved in any case. The field will have a red background color if the value is outside the range, and a green if inside.

12.4. Minimum maximum outlier analysis

12.4.1. About minimum maximum value based outlier analysis

You can verify the data quality at the point of data entry by setting a minimum maximum value range for each data element. You create the value ranges manually or generate them automatically.

The auto-generated minimum maximum value range is suitable only for normally distributed data. DHIS2 will determine the arithmetic mean and standard deviation of all values for a given data element, category option, organisation unit and attribute combination. Then the system will calculate the minimum maximum value range based on the Data analysis std dev factor specified in the System Settings app.

For data which is highly-skewed or zero inflated (as is often the case with aggregate data), the values which DHIS2 auto-generates may not provide an accurate minimum maximum value range. This can lead to excessive false violations, for example if you analyse values related to seasonal diseases.

[Note]Note

Minimum maximum value ranges are calculated across all attribute combination options for a given data element, category option and organisation unit combination.

12.4.2. Workflow

  1. Create a minimum maximum value range, either automatically or manually.

    • In the Data Administration app, you generate value ranges automatically.

    • In the Data Entry app, you set value ranges manually for each field.

  2. In the Data Quality app, run the Min-max outlier analysis.

12.4.3. Configure a minimum maximum outlier analysis

12.4.3.1. Create minimum maximum value range automatically

[Note]Note

Auto-generated minimum maximum value ranges can be useful for many situations, but it's recommended to verify that the data is actually normally distributed prior to using this function.

You generate minimum maximum value ranges calculated by data set in the Data Administration app. The new value ranges override any value ranges that the system has calculated previously.

  1. Set the Data analysis std dev factor:

    1. Open the System Settings app, and click General.

    2. In the Data analysis std dev factor field, enter a value.

      This sets the number of standard deviations to use in the outlier analysis. The default value is 2. A high value will catch less outlier values than a low value.

  2. Open the Data Administration app and click Min-max value generation.

  3. Select data set(s).

  4. Select an Organisation unit.

  5. Click Generate.

    New minimum maximum value ranges for all data elements in the selected data sets for all organisation units (including descendants) of the selected organisation units are generated.

12.4.3.2. Create minimum maximum value range manually

  1. In the Data Entry app, open a data entry form.

  2. Double-click the field for which you want to set the minimum maximum value range.

  3. Enter Min limit and Max limit.

  4. Click Save.

    If values don't fall within the new value range the next time you enter data, the data entry cell will appear with an orange background.

  5. (Optional) Type a comment to explain the reason for the discrepancy, for example an event at a facility which may have generated a large number of clients.

  6. (Optional) Click Save comment.

[Tip]Tip

Click the star icon to mark the value for further follow-up.

12.4.3.3. Delete minimum maximum value range

You can permanently delete all minimum maximum value ranges for selected data sets and organisation units in the Data Administration app.

  1. Open the Data Administration app and click Min-max value generation.

  2. Select data set(s).

  3. Select an Organisation unit.

  4. Click Remove.

12.4.4. Run a minimum maximum outlier analysis

  1. Verify that you've created minimum maximum value ranges.

  2. Open the Data Quality app and click Min-max outlier analysis.

  3. Select From date and To date.

  4. Select which data set(s) you want to include in the analysis.

  5. Select Parent organisation unit.

    All children of the organisation unit will be included. The analysis is made on raw data "under" the parent organisation unit, not on aggregated data.

  6. Click Start.

    The analysis process duration depends on the amount of data that is being analysed. If there are validation violations, they will be presented in a list.

  7. (Optional) Click Download as PDF, Download as Excel or Download as CSV to download the list in PDF, Excel or CSV formats.

[Tip]Tip

Click the star icon to mark the value for further follow-up.

12.5. Follow-up analysis

12.5.1. About follow-up analysis

The follow-up analysis creates a list of all data values marked for follow-up. You can mark a data value for follow-up in the Data Entry app and in the result list you get from a standard deviation outlier or minimum maximum outlier analysis.

12.5.2. Create list of data values marked for follow-up

  1. Open the Data Quality app and click Follow-up analysis.

  2. Select an Organisation unit.

    The analysis process duration depends on the amount of data that is being analysed. If there are data values marked for follow-up, they will be presented in a list.

  3. (Optional) Click Download as PDF, Download as Excel or Download as CSV to download the validation violations list in PDF, Excel or CSV formats.

[Tip]Tip

Click the star icon to remove the follow-up tag from the data value.

Chapter 13. Data approval

DHIS2 has an optional feature that allows authorized users to approve data that has been entered. It allows data to be reviewed and approved at selected levels in the organisation unit hierarchy, so the approval follows the structure of the hierarchy from lower levels to higher levels.

Data is approved for a combination of (a) period, (b) organisation unit and (c) workflow. Data may be approved for the organisation unit for which it is entered, as well as for higher-level organisation units to which the data is aggregated. As part of system settings, you can choose the organisation unit level(s) at which data is approved. It can be approved at higher levels only after it has been approved for all that organisation unit's descendants at lower levels for the same workflow and period. When you approve a workflow, it approves data for any data sets that have been assigned to that workflow.

After a period, organisation unit and workflow combination has been approved, data sets associated with that workflow will be locked for that period and organisation unit, and any further data entry or modification will be prohibited unless it is first un-approved.

For example, the following diagram illustrates that data has already been approved for organisation units C and D, for a given period and workflow. It may now be approved for organisation unit B for the same period and workflow. But it is not ready to be approved for organization unit A. Before it can be approved for organisation unit A, it must be approved for B, and for any other children of organisation unit A, for that period and workflow.

Figure 13.1. Approving at organisation units

Approving at organisation units

13.1. Approving and accepting

DHIS2 supports two different types of approval processes: either a one-step process where the data is approved at each level, or a two-step process where data is first approved and then accepted at each level. This is illustrated in the following diagram:

Figure 13.2. Approving and accepting

Approving and accepting

In the one-step process, data is approved at one level, and then approved at the next higher level. Until it is approved at the next higher level, it may be unapproved at the first level. (For example, if the data was approved my mistake, this allows the approver to undo their mistake.) Once the data is approved at the next higher level, it may not be unapproved at the lower level unless it is first unapproved at the higher level.

In the two-step process, data is approved at one level, and then the approval is accepted at the same level. This acceptance is done by a user who is authorized to approve data at the next higher level. Once the data is accepted, it may not be changed or unapproved unless it is first unaccepted.

The two-step process is not required by DHIS2. It is an optional step for a user reviewing data at the next higher level. It has the benefit of locking the acceptance from the level below, so reviewer does not have to worry that the data could be changing from below while it is being reviewed. It can also be used by the higher-level user to keep track of which lower-level data has already been reviewed.

13.2. Authorities for approving data

To approve data, you must be assigned a role containing one of these authorities:

  • Approve data - You may approve data for the organisation unit(s) to which you are assigned. Note that this authority does not allow you to approve data for lower-levels below the organisation unit(s) to which you are assigned. This is useful to separate the users authorized to approve at one level from the users authorized to approve at levels below.

  • Approve data at lower levels - Allows you to approve data for all lower levels below the organisation units assigned to you. This is useful if, for example, you are a district-level user whose role includes approving the data for all the facilities within that district, but not for the district itself. If you are assigned this as well as the Approve data authority, you may approve data at the level of the organisation unit(s) to which you have been assigned, and for any level below.

  • Accept data at lower levels - Allows you to accept data for the level just below the organisation unit(s) assigned to you. This authority can be given to the same users as approve data. Or it may be given to different users, if you want to have some users who accept data from the level below, and a different set of users who approve data to go up to the next level above.

13.3. Configuring data approval

In the Settings section under System Approval Settings you can specify the levels at which you want to approve data in the system. Click the Add new button on this page and select the organisation unit level at which you want approvals. It will be added to the list of approval settings. You may configure the system for approving data at every organisation unit level, or only at selected organisation unit levels.

Note that when you add a new approval level, you may optionally choose a Category option group set. This feature is discussed later in this chapter.

Also under System Approval Settings, you can define the workflows that will be used for approving data. Each workflow can be associated with one or more approval levels. Any two workflows may operate at all the same approval levels as each other, some of the same and some different levels, or completely different levels.

If you want data for a data set to be approved according to a workflow, then assign the workflow to the data set when you add or edit the data set. If you do not want data for a data set to be subject to approval, then do not assign any workflow to that data set. For data sets that you want to approve at the same time as each other, assign them to the same workflow. For data sets that you want to approve independently, assign each data set to its own workflow.

On the System Approval Settings page, you may select the option Hide unapproved data in analytics to hide unapproved data in reports, pivot table, data visualizer and GIS. If this option is checked, unapproved data will be hidden from users assigned to higher-level organisation units compared to where approval is required. Users who are assigned to organisation units where data is ready for approval can still view the data, as can users assigned to higher-level organisation units if they have the Approve data at lower levels authority. If this option is not checked, then all data is shown whether approved or not.

13.4. Data visibility

If the option Hide unapproved data in analytics is enabled, data will be hidden from viewing by users associated with higher levels. When determining whether a data record should be hidden for a specific user, the system associates a user with a specific approval level and compares it to the level to which the data record has been approved up to. A user is associated with the approval level which matches the level of the organisation unit(s) she is linked to, or if no approvel level exists at that level, the next approval level linked to an organisation unit level below herself. A user will be allowed to see data which has been approved up to the level immediately below her associated approval level. The rationale behind this is that a user must be ablet to view the data that has been approved below so that she can eventually view and approve it herself.

Note that if the user has been granted the View unapproved data or the ALL authority she will be able to view data irrespective of the approval status.

Lets consider the following example: There are four organisation unit levels, with approval levels associated with level 2 and 4. User A at country level (1) gets associated with approval level 1 since the approval level exists at the same level as the organisation unit level. User B gets associated with approval level 2 since there is no approval level directly linked to her organisation unit level and approval level 2 is the immediate level below. User C gets associated with approval level 2. User D is below all approval levels which implies that she can see all data entered at or below her organisation unit level.

Figure 13.3. Hiding of unapproved data

Hiding of unapproved data

Using this example, lets consider some scenarios:

  • Data is entered at facility level: Only User D can see the data, as the data has not yet been approved at all.

  • Data is approved by User D at facility level: Data becomes visible to User C and User B, as the data is now approved at their level.

  • Data is approved by User C at district level: Data becomes visible to User A, as data is now approved at the level immediately below herself.

13.5. Approving data

To approve data, go to Reports and choose Data Approval. When this report shows data that is configured for approval, it shows the approval status of the data in the report. The approval status will be one of the following:

  • Waiting for lower level org units to approve - This data is not yet ready to be approved, because it first needs to be approved for all the child organisation units to this organisation unit, for the same workflow and period.

  • Ready for approval - This data may now be approved by an authorized user.

  • Approved - This data has already been approved.

  • Approved and accepted - This data has already been approved, and also accepted.

If the data you are viewing is in an approval state that can be acted upon, and if you have sufficient authority, one or more of the following actions will be available to you on the Data Approval form:

  • Approve - Approve data that has not yet been approved, or that was formerly approved and has been unapproved.

  • Unapprove - Return to an unapproved state data that has been approved or accepted.

  • Accept - Accept data that has been approved.

  • Unaccept - Return to an unaccepted (but still approved) state data that has been accepted.

In order to unapprove data for a given organisation unit, you must have the authority to approve data for that organisation unit or to approve data for a higher-level organisation unit to which that data is aggregated. The reason for this is as follows: If you are reviewing data for approval at a higher organisation unit level, you should consider whether the data at lower organisation units are reasonable. If all lower-level data looks good, you can approve the data at the higher level. If some lower-level data looks suspect, you can unapprove the data at the lower level. This allows the data to be reviewed again at the lower level, corrected if necessary, and re-approved up through the organisation unit levels according to the hierarchy.

13.6. Approving by category option group set

When defining an approval level, you specify the organisation unit level at which data will be approved. You may also optionally specify a category option group set. This is useful if you are using category option groups to define additional dimensions of your data, and you want approvals to be based on these dimensions. The following examples illustrate how this can be done within a single category option group set, and by using multiple category option group sets.

13.6.1. Approving by one category option group set

For example, suppose you define a category option group set to represent NGOs who serve as healthcare partners at one or more organisation units. Each category option group within this set represents a different partner. The category option group for Partner 1 may group together category options (such as funding account codes) that are used by that partner as a dimension of the data. So data entered by Partner 1 is attributed to a category option in Partner 1's category option group. Whereas data entered by partner 2 is attributed to a category option in Partner 2's category option group:

Table 13.1. Example Category Option Groups

Category option group setCategory option groupCategory options
PartnerPartner 1Account 1A, Account 1B
PartnerPartner 2Account 2A, Account 2B

Each partner could enter data for their accounts independently of the other, for the same or different workflows, at the same or different facilities. So for example, data can be entered and/or aggregated at the following levels for each partner, independently of each other:

Figure 13.4. Example category option groups

Example category option groups

[Tip]Tip

You can use the sharing feature on category options and category option groups to insure that a user can enter data (and/or see data) only for certain category options and groups. If you don't want users to see data that is aggregated beyond of their assigned category options and/or category option groups, you can assign Selected dimension restrictions for data analysis, when adding or updating a user.

You can optionally define approval levels for partner data within any or all of these organisation unit levels. For example, you could define any or all of the following approval levels:

Table 13.2. Example Category Option Group Set approval levels

Approval levelOrganisation unit levelCategory option group set
1CountryPartner
2DistrictPartner
3FacilityPartner

13.6.2. Approving by multiple category option group sets

You can also define approval levels for different category option group sets. To continue the example, suppose that you have various agencies that manage the funding to the different partners. For example, Agency A funds accounts 1A and 2A, while Agency B funds accounts 1B and 2B. You could set up category option groups for Agency A, and Agency B, and make them both part of a category option group set called Agency. So you would have:

Table 13.3. Example Multiple Category Option Group Sets

Category option group setCategory option groupCategory options
PartnerPartner 1Account 1A, Account 1B
PartnerPartner 2Account 2A, Account 2B
AgencyAgency AAccount 1A, Account 2A
AgencyAgency BAccount 1B, Account 2B

Now suppose that at the country level, you want each partner to approve the data entered by that partner. Once this approval is done, you want each agency to then approve the data from accounts that are managed by that agency. Finally, you want to approve data at the country level across all agencies. You could do this by defining the following approval levels:

Table 13.4. Example Multiple Category Option Group Set approval levels

Approval levelOrganisation unit levelCategory option group set
1Country 
2CountryAgency
3CountryPartner

Note that multiple approval levels can be defined for the same organisation unit level. In our example, Partner 1 would approve country-wide data at approval level 3 from category options Account 1A and Account 1B. Next, Agency A would approve country-wide data at approval level 2 from category options Account 1A (after approval by Partner 1) and Account 2A (after approval by Partner 2.) Finally, after approval from all agencies, country-wide data can be approved at approval level 1 across all category options. Note that approval level 1 does not specify a category option group set, meaning that it is for approving data across all category options.

This example is meant to be illustrative only. You may define as many category option groups as you need, and as many approval levels as you need at the same organisation unit level for different category option group sets.

If you have multiple approval levels for different category option group sets at the same organisation unit level, you may change the approval ordering in the Settings section, under System Approval Settings. Just click on the approval level you wish to move, and select Move up or Move down. If you have an approval level with no category option groups set, it must be the highest approval level for that organisation unit level.

Chapter 14. Using reporting functionality

14.1. Reporting functionality in DHIS2

The reporting module in DHIS2 provides a range of reporting alternatives, and this section will explain how to use them to view and analyse data. Another section explains how to configure and set up the various reporting tools.

Standard reports: Standard reports are built on pivot tables, but are more advanced in its design allowing for more cosmetics and styles. These reports can also combine multiple tables and charts in the same report and be made available as one-click reports that are very easy to use. These reports can be downloaded as PDF files which makes them ideal for printing as well as sharing offline.

Dataset reports: Dataset reports are simply a printer friendly way to look at the data entry forms with either raw or aggregated data (over time or place). The design used in data entry will be used also in the data set reports. This will work only for data sets that has a custom data entry form set up.

Dashboard: The fastest way to view your data. The dashboard can display up to four updated charts as well as shortcuts to your favourite reports, report tables, and map views. Each user can configure a personal dashboard.

Data Visualizer: Do flexible visualizations of your data as charts and data tables. Any number of indicators and data elements can be included. Several chart types are available, such as column, stacked column, line, area and pie charts. The charts can be saved in order to be easily retrieved later and can also be put on your personal dashboard. Charts can be downloaded as image and PDF files to your local computer.

Orgunit distribution reports: These reports are generated off the orgunit group set information and can show what types (and how many of each type) of health facilities that are located in a given area (any level in the hierarchy). These reports are automatically generated and display the information in both tables and charts, and downloads in PDF, excel, and CSV are available.

Reporting rate summary: These reports provide a nice overview of how many facilities that have submitted their data for a given dataset and period. Here you can get both the counts and the percentages showing the reporting rate for all or single data sets.

Web-based pivot tables: The built in pivot table tool is a web-based tool to display indicator data by orgunit and period in a typical pivot table view and allows for pivoting manipulations of the tables. It allows for large amounts of data to be downloaded offline for analysis as well.

GIS: Present and analyse your data using thematic maps. You can view both data elements and indicators and given that you have coordinates for all your orgunits you can drill down the hierarchy and view maps for all levels from country polygons to facility points. See the separate chapter on GIS for more details. All the map information is built into DHIS2 and all you need to do is to register coordinates for your organisation units and the maps will be available.

14.2. Using standard reports

You access the available reports by navigating to Apps->Reports. In the report menu in the left bar, click Standard Report. A list of all pre-defined reports will appear in the main window.

Standard reports

You run/view a report by clicking on the name of the report and then selecting "Create" from the contextual menu. If there are any pre-defined paramaters, you will see a report parameter window where you must fill in the values needed for orgunit and/or reporting month, depending on what has been defined in the underlying report table(s). Click on "Get Report" when you are ready. The report will either appear directly in your browser or be available as a PDF file for download, depending on your browser settings for handling PDF files. You can save the file and keep it locally on your computer for later use.

14.3. Using dataset reports

Dataset reports are printer friendly views of the data entry screen filled with either raw or aggregated data. These are only available for data sets that have custom data entry forms and not for default or section forms.

You can access data set reports from Apps->Reports.

A Criteria window will appear where you fill in the details for your report:

Dataset: The data set you want to display.

Reporting period: The actual period you want data for. This can be aggregated as well as raw periods. This means that you can ask for a quarterly or annual report even though the data set is collected monthly. A data set's period type (collection frequency) is defined in data set maintenance. First select the period type (Monthly, Quarterly, Yearly etc.) in the drop down next to Prev and Next buttons, and then select one of the available periods from the dropdown list below. Use Prev and Next to jump one year back or forward.

Use data for selected unit only: Use this option if you want a report for an orgunit that has children, but only want the data collected directly for this unit and not the data collected by its children. If you want a typical aggregated report for an orgunit you do not want to tick this option.

Reporting Organisation unit: Here you select the orgunit you want the report for. This can be at any level in the hierarchy as the data will be aggregated up to this level automatically (if you do not tick the option above).

When you are done filling in the report criteria you click on "Generate". The report will appear as HTML in a printer-friendly format. Use the print and save as functions in the browser to print or save (as HTML) the report.You can also export the data set report in Excel and PDF formats.

14.4. Using resources

The resource tool allows you to upload both files from your local computer to the DHIS server and to add links to other resources on the Internet through URLs. If cloud storage is configured for your system, resources will be saved there.

To create a new resource:

  1. Open the Reports app and click Resource.

  2. Click Add new.

  3. Enter a Name.

  4. Select a Type: Upload file or External URL.

  5. Click Save.

14.5. Using reporting rate summary

Access the reporting rate summary from the Apps->Reports menu. Reporting rate summaries will show how many datasets (forms) that have been submitted by organisation unit and period. There are two methods available to calculate reporting rates (completeness):

  • Based on complete data set registrations. A complete data set registration refers to a user marking a data entry form as complete, typically by clicking the complete button in the data entry screen, hereby indicating to the system that she considers the form to be complete. This is i.e. a subjective approach to calculating completeness.

  • Based on compulsory data element: You can define any number of data elements in a data set to be compulsory. This implies that data values must be captured for all data elements which have been marked as compulsory in order for the data set to be considered complete. This is i.e. an objective approach to calculating completeness.

The reporting rate summary will for each row show a range of measures:

  • Actual reports: Indicates the number of data entry complete registrations for the relevant data set.

  • Expected reports: Indicates how many data entry complete registrations are expected. This number is based on the number of organisation units the relevant data set has been assigned to (enabled for data entry).

  • Percent: The percentage of reports registered as complete based on the number expected.

  • Reports on time: Same as actual reports, only reports registered as complete within the maximum number of days after the end of the reporting period. This number of days after reporting period can be defined per data set in the data set management.

  • Percent on time: Same as percentage, only reports registered as complete on time used as numerator.

To run the report you can follow these steps:

  • Select an orgunit from the tree.

  • Select one of the completeness methods to use to calculate the reporting rates.

    Select all or one data set. All will give you a report with all data sets for the selected organisation unit. A single data set will give you a report with completeness for all children of the selected organisation unit.

  • Select a period type and a period from the list of available periods for that period type. Move back/forward one year by using the prev/next buttons.

  • The report will then be rendered. Change any of the parameters above and the report will be updated automatically.

Reporting rate summary

14.6. Using organisation unit distribution reports

You can access the Orgunit Distribution reports from the left side menu in the Apps->Reports.

Orgunit distribution reports are reports that show how the orgunits are distributed on various properties like type and ownership, and by geographical areas.

The result can be presented in a table-based report or in a chart.

Running a report:

To run a report first select an orgunit in the upper left side orgunit tree. The report will be based on orgunits located under the selected orgunit. The select the orgunit group set that you want to use, typically these are Type, Ownership, Rural/Urban, but can be any user-defined orgunit group set. The you can click on either Get Report to get the table-based presentation or Get chart to get the same result in a chart. You can also download other format such as PDF, Excel and CSV.

Orgunit distribution report

14.7. Generate analytics tables

DHIS2 generates database tables which the system then uses as basis for various analytics functions. These tables are also valuable if you write advanced SQL reports. In the Reports app, you can execute the tables immediately or schedule them to be executed at regular intervals. This means that you can refresh recent analytics on demand and see updated pivot tables without waiting for all of the past years data to re-process.

[Note]Note

You can also generate the tables through the web API. This task is typically performed by a system administrator.

  1. Open the Reports app and click Analytics.

  2. Select the parts of the analytics process you want to skip:

    • Skip generation of resource tables

    • Skip generation of aggregate data and completeness data

    • Skip generation of event data

    • Skip generation of enrollment data

  3. Select Number of last years of data to include.

  4. Click Start export.

Chapter 15. Set user account preferences

In User settings, you can change the display language of DHIS2 and the language of the database. The database language is the translated content of the metadata, such as data elements and indicators. You can also choose a display style, and enable or disable SMS and email notifications. If you wish to, you can choose to display a short name, such as "Joe" in the analysis modules, rather than your full name.

In User profile, you can add personal information to your profile such as your email address, mobile phone number, date of birth and more. When you send messages, the person receiving the message can see these profile details.

In Account settings, you can reset your password.

Chapter 16. Manage users, user roles and user groups

16.1. About user management

Multiple users can access DHIS2 simultaneously and each user can have different authorities. You can fine-tune these authorities so that certain users can only enter data, while others can only generate reports.

  • You can create as many users, user roles and user groups as you need.

  • You can assign specific authorities to each user.

  • You can create multiple user roles each with their own authorities.

  • You can assign user roles to users to grant the users the corresponding authorities.

  • You can assign each user to organisation units. Then the user can enter data for the assigned organisation units.

Table 16.1. User management terms and definitions

Term

Definition

Example

Authority

A permission to perform one or several specific tasks

Create a new data element

Update an organisation unit

View a report

User

A person's DHIS2 user account

admin

traore

guest

User role

A group of authorities

Data entry clerk

System administrator

Antenatal care program access

User group

A group of users

Kenya staff

Feedback message recipients

HIV program coordinators


You manager users, user roles and user groups in the Users app.

Table 16.2. Objects in the Users app

Object type

Available functions

User

Create, edit, clone, disable, assign search organisation units, display by organisation unit, delete and show details

User role

Create, edit, share, delete and show details

User group

Create, edit, join, leave, share, delete and show details


16.1.1. About users

Each user in DHIS2 must have a user account which is identified by a user name. You should register a first and last name for each user as well as contact information, for example an email address and a phone number.

It is important that you register the correct contact information. DHIS2 uses this information to contact users directly, for example sending emails to notify users about important events. You can also use the contact information to share for example dashboards and pivot tables.

A user in DHIS2 is associated with an organisation unit. You should assign the organisation unit where the user works.

Example 16.1. 

When you create a user account for a district record officer, you should assign the district where he/she works as the organisation unit.


The assigned organisation unit affects how the user can use DHIS2:

  • In the Data Entry app, a user can only enter data for the organisation unit she is associated with and the organisation units below that in the hierarchy. For instance, a district records officer will be able to register data for her district and the facilities below that district only.

  • In the Users app, a user can only create new users for the organisation unit she is associated with in addition to the organisation units below that in the hierarchy.

  • In the Reports app, a user can only view reports for her organisation unit and those below. (This is something we consider to open up to allow for comparison reports.)

An important part of user management is to control which users are allowed to create new users with which authorities. In DHIS2, you can control which users are allowed to perform this task. The key principle is that a user can only grant authorities and access to data sets that the user itself has access to. The number of users at national, province and district level are often relatively few and can be created and managed by the system administrators. If a large proportion of the facilities are entering data directly into the system, the number of users might become unwieldy. It is recommended to delegate and decentralize this task to the district officers, it will make the process more efficient and support the facility users better.

16.1.2. About user roles

A user role in DHIS2 is a group of authorities. An authority means the permission to perform one or more specific tasks.

Example 16.2. 

A user role can contain authorities to create a new data element, update an organisation unit or view a report.


A user can have multiple user roles. If so, the user's authorities will be the sum of all authorities and data sets in the user roles. This means that you can mix and match user roles for special purposes instead of only creating new ones.

A user role is associated with a collection of data sets. This affects the Data Entry app: a user can only enter data for the data sets registered for his/her user role. This can be useful when, for example, you want to allow officers from health programs to enter data only for their relevant data entry forms.

Recommendations:

  • Create one user role for each position within the organisation.

  • Create the user roles in parallel with defining which user is doing which tasks in the system.

  • Only give the user roles the exact authorities they need to perform their job, not more. Only those who are supposed to perform a task should have the authorities to perform it.

16.1.3. About user groups

A user group is a group of users. You use user groups when you set up sharing of objects or notifications, for example push reports or program notifications.

See also:

Sharing

Manage program notifications

Mange push reports

16.2. Workflow

  1. Define the positions you need for your project and identify which tasks the different positions will perform.

  2. Create roughly one user role for each position.

  3. Create users.

  4. Assign user roles to the users.

  5. Assign the users to organisation units.

  6. Assign data sets to the user role.

  7. (Optional) Group users in user groups.

[Tip]Tip

For users to be able to enter data, you must add them to both a data set and an organisational unit level.

16.3. Manage users

16.3.1. Create a user

  1. Open the Users app and click User.

  2. Click Add new.

  3. Select whether you want to fill in all the personal user information, or invite the user by email to complete the rest of the user information:

    • Create account with user details

      Choose this option if you would like to enter all the details of the new user such as name, password, etc.

      Enter the following information: user name, password, surname, first name, email, OpenID account (if any) and mobile phone number (if any).

      After you've created the user, the account is ready for the user to use with the user name and password that you provide.

    • Email invitation to create account

      Choose this option if you want to send an invitation by email to the user. Then she/he must return to DHIS2 and finish setting up their user account. The account that the user finishes setting up will be limited according to how you configure the account.

      [Note]Note

      You may not select this option to create an account with "critical" system authorities such as All, Scheduling Administration, Perform maintenance tasks, Merge organisation units, Eliminate duplicate data elements, SQL View Management, Change system settings, and List, Add or Delete user roles.

      In order to use this feature "Enable email message notifications" in SystemSettings -> Messaging should be checked.

      Enter the email address to which the invitation should be sent. If you want to, you may also enter the user name that the account will have. If you leave the user name empty, then the user may choose their own user name when they respond to the invitation (as long as it is not taken already for another user.)

      After you've created the user, the system sends two emails to the address you provided. One contains a unique web link by which the user can return to the system and activate their account by entering the rest of their user information. The other email contains a unique code that they must enter into the system in order to complete the registration, after following the link in the first email. The user must finish setting up the account within three months, after that the invitation becomes invalid.

  4. Select an Interface language.

    You can select a language into which fixed elements of the DHIS2 user interface have been translated.

  5. Select a Database language.

    You can select a language into which implementation-supplied items have been translated in the database, for example data element names or organisation unit level names.

  6. In the Available roles section, double-click the user roles you want to assign to the user.

  7. Select Data capture and maintenance organisation units.

    The data capture and maintenance organisation units control for which organisation units the user can do data entry. You must assign at least one data capture and maintenance organisation unit to each user.

    Users will have access to all sub-organisation units of the assigned organisation units. For example, if you've assigned a user to a district which has several facilities contained in the district, the user would have access to the district's data, as well as all of the facilities contained within the district.

  8. (Optional) Select Data output and analysis organisation units.

    The data output and analysis organisation units controls for which organisation units the user can view aggregated data in the analytics apps, for example the Pivot Table and GIS apps. You can assign any number of data output and analysis organisation units to a user.

    Users will have access to all sub-organisation units of the assigned organisation units. You shouldn't select the descendants of an organisation unit which you have already selected. For example, if you've assigned the user to a district, you shouldn't select the facilities within that district.

    [Note]Note

    Assigning data output and analysis organisation units organisation units is optional. If you don't specify any organisation unit, the user will have access to the full organisation unit hierarchy for viewing aggregated data. As with the data capture organisation units, you should not select descendant organisation units of a unit which you have already selected.

    In several places in the analytics apps, you can select "user organisation unit" for the organisation unit dimension. This mechanism will first attempt to use the data view organisation units linked to the current user. If not found, it will use the data capture and maintenance organisation units. If the user has been assigned to multiple organisation units, the use of "user organisation unit" may result in unpredictable behavior.

  9. Click Show more options.

  10. (Optional) In the Available user groups section, double-click the user groups you want to assign to the user.

  11. (Optional) In the Available dimension restrictions for data analytics section, double-click the dimensions you want to assign to the user.

    You can restrict the values the user sees in data analytics apps by selecting dimensions that will restrict the user's view.

    Example 16.3. 

    Let's say you have defined Implementing Partner as a category option group set, and you have shared with this user only one or more specific implementing partners (category option groups). If you want to make sure that the user does not see totals in analytics that include values from other groups, assign Implementing Partner to the user. This insures that any data visible to the user through the analytics apps will be filtered to select only the Implementing Partner category option group(s) which are visible to the user.


  12. Click Add.

16.3.2. Edit user objects

  1. Open the Users app and find the type of user object you want to edit.

  2. In the object list, click the relevant object and select Edit.

  3. Modify the options you want.

  4. Click Save.

16.3.3. Disable users

You can disable a user. This means that the user's account is not deleted, but the user can't log in or use DHIS2.

  1. Open the Users app and click User.

  2. In the list, click the relevant user and select Disable.

  3. Click OK to confirm.

16.3.4. Display a user's profile

  1. Open the Users app and click User.

  2. In the list, click the relevant user and select Profile.

16.3.5. View users by organisation unit

You can view all users that have been assigned to a particular organisation unit.

  1. Open the Users app and click User by organisation unit.

  2. In the left-hand organisation unit tree, click an organisation unit.

    A list of users which have been assigned to this organisation unit is displayed.

16.3.6. Assign search organisation units to users

  1. Open the Users app and click User.

  2. In the object list, click the relevant user and select Assign search org units.

  3. Click the organisation units you want the user to be able to search in.

  4. Click Save.

16.3.7. Delete current user

You can delete the user that is currently logged into the system.

  1. Open the Users app and click Delete current user.

  2. Enter your password and click Delete.

16.3.8. Clone users

  1. Open the Users app and click User.

  2. In the object list, click the relevant user and select Replicate.

  3. Enter a new user name and password for the cloned user account.

  4. Click Replicate.

  5. In the object list, click the user you just created and click Edit.

  6. Modify the options you want.

  7. Click Save.

16.3.9. Change user password

The following rules apply when you create a new password:

  • Password must contain at least one special character, that is any character other then alphabets and digit numbers.

  • Password must contain at least one upper case character.

  • Password must contain at least one digit number.

  • Password can not contain user's user name or email address.

  • Password can not contain generic words for example system, admin, user, login, manager etc.

  • Password can not be one of the previous 24 passwords the user has used.

    This doesn't apply in case a super user resets the password for another user.

  • Password must contain more than minimum number of characters.

    [Note]Note

    You can configure the minimum number of characters: Open the System Settings app and click Access > Minimum characters in password.

  • Password can not contain more than 40 characters

To change a user's password:

  1. Open the Users app and click User.

  2. In the object list, click the relevant user and select Edit.

  3. Enter a new password and retype it.

  4. Click Save.

16.3.10. Delete user objects

  1. Open the Users app and find the type of user object you want to delete.

  2. In the object list, click the relevant object and select Remove.

  3. Click OK to confirm.

16.3.11. Display details of user objects

  1. Open the Users app and find the type of user object you want to view.

  2. In the object list, click the relevant object and select Show details.

16.4. Manage user roles

16.4.1. Create a user role

  1. Open the Users app and click User role.

  2. Click Add new.

  3. Enter a Name, for example "Super user" or "Admin user".

  4. Enter a Description.

  5. In the Data sets section, double-click the data sets you want the user role to have access to.

  6. In the Programs section, double-click the programs you want the user role to have access to.

  7. Authorities section, double-click the authorities you want to give to the user role.

  8. Click Add.

[Tip]Tip

You can select multiple data sets, programs or authorities:

  • One by one: press the Ctrl key and click the items one by one, then click the right arrow.

  • In a series: press the Shift key and select the first and last item in the series, then click the right arrow.

16.4.2. Edit user objects

  1. Open the Users app and find the type of user object you want to edit.

  2. In the object list, click the relevant object and select Edit.

  3. Modify the options you want.

  4. Click Save.

16.4.3. Delete user objects

  1. Open the Users app and find the type of user object you want to delete.

  2. In the object list, click the relevant object and select Remove.

  3. Click OK to confirm.

16.4.4. Display details of user objects

  1. Open the Users app and find the type of user object you want to view.

  2. In the object list, click the relevant object and select Show details.

16.4.5. Change sharing settings for user objects

  1. Open the Users app and find the type of user object you want to modify.

  2. In the object list, click the relevant object and select Sharing settings.

  3. (Optional) Search for a user group and select it, then click the plus icon. The user group is added to the list.

  4. (Optional) Select External access (without login).

  5. Change the settings for the user groups you want to modify.

    • None

    • Can view: Everyone in the user group can view the object

    • Can edit and view: Everyone in the user group can view and edit the object

  6. Click Save.

16.5. Manage user groups

16.5.1. Create a user group

  1. Open the Users app and click User group.

  2. Click Add new.

  3. In the Name field, type the name of the user group.

  4. In the Available users section, double-click the users you want to add to the user group.

  5. In the Available user groups section, double-click the user groups you want to add to the user group.

  6. Click Add.

16.5.2. Join user groups

  1. Open the Users app and click User group.

  2. In the list, click the relevant user group and select Join group.

16.5.3. Leave user groups

  1. Open the Users app and click User group.

  2. In the list, click the relevant user group and select Leave group.

16.5.4. Edit user objects

  1. Open the Users app and find the type of user object you want to edit.

  2. In the object list, click the relevant object and select Edit.

  3. Modify the options you want.

  4. Click Save.

16.5.5. Delete user objects

  1. Open the Users app and find the type of user object you want to delete.

  2. In the object list, click the relevant object and select Remove.

  3. Click OK to confirm.

16.5.6. Display details of user objects

  1. Open the Users app and find the type of user object you want to view.

  2. In the object list, click the relevant object and select Show details.

16.5.7. Change sharing settings for user objects

  1. Open the Users app and find the type of user object you want to modify.

  2. In the object list, click the relevant object and select Sharing settings.

  3. (Optional) Search for a user group and select it, then click the plus icon. The user group is added to the list.

  4. (Optional) Select External access (without login).

  5. Change the settings for the user groups you want to modify.

    • None

    • Can view: Everyone in the user group can view the object

    • Can edit and view: Everyone in the user group can view and edit the object

  6. Click Save.

16.6. Enable support for OpenID

DHIS2 supports the OpenID standard, which allows third party login using a OpenID provider, for more information see http://openid.net. To create a custom OpenID URL for a user name you can visit this URL and log in with your OpenID provider: http://openid-provider.appspot.com.

To enable support for OpenID in DHIS2, you must:

  1. Set your OpenID provider: This can be done inside system settings, under "Access". Here you can set both the OpenID provider, and also the label to display on the login page to login with this provider (defaults to Login with OpenID).

  2. Set the OpenID identifier on the user: For every user that should be able to login with his OpenID identifier, you will need to set this on the user itself. This can be done in user management, under the email field, there is not a field called OpenID which can be used to fill in the OpenID identifier.

16.7. Decentralize user management

DHIS2 supports a concept for user management referred to as managed users which allows to explicitly define which users should be allowed to manage or modify which users. To "manage a user" implies that you can see and modify that user. The basic concept for user management is that you can see and modify users which you have been granted all of the authorities; in other words you can modify users which have a subset of your own authorities. The managed users concept gives you greater control over this.

The managed users concept allows you to define which users should be able to manage which users. This is configured through user groups and memberships within such groups. A user group can be configured to be allowed to manage other user groups from the standard add and update user interface. The effect is that a specific user can manage all users which are members of user groups which can be managed by a user group that the user is member of. In other words, users can be managed by all members of user groups which are managing user groups they are member of.

To enable this concept you should grant users the authority to "Add/update users within managed groups", and not grant access to the standard "Add/update users" authority. An implication of the managed users concept is that when creating a user with the "Add/update users within managed groups" only, the user must be made a member of at least one user group that the current user can manage. If not, the current user would lose access to the user being created immediately. This is validated by the system.

When granted the "Add/update users within managed groups" authority, the system lets a user add members to user groups for which she has read-only access to. The purpose of this is to allow for decentralized user management. You may define a range of user groups where other users may add or remove members, but not remove or change the name of the group.

16.8. Example: user management in a health system

In a health system, users are logically grouped with respect to the task they perform and the position they occupy.

  1. Define which users should have the role as system administrators. They are often part of the national HIS division and should have full authority in the system.

  2. Create roughly one user role for each position.

Examples of common positions are:

Position

Typical tasks

Recommended authorities

Comment

System administrators

Set up the basic structure (metadata) of the system.

Add, update and delete the core elements of the system, for example data elements, indicators and data sets.

Only system administrators should modify metadata.

If you allow users outside the system administrators team to modify the metadata, it might lead to problems with coordination.

Updates to the system should only be performed by the administrators of the system.

National health managers

Province health managers

Monitor and analyse data

Access to the reports module, the GIS, Data Quality apps and the dashboard.

Don't need access to enter data, modify data elements or data sets.

National health information system division officers (HISO)

District health records and information officers (DHRIO)

Facility health records and information officers (HRIO)

Enter data that comes from facilities which are not able to do so directly

Monitor, evaluate and analyse data

Access to all the analysis and validation apps

Access to the Data Entry app.

-

Data entry clerks

-

-

-

Chapter 17. Visualize usage statistics

17.1. About the Usage Analytics app

The Usage Analytics app lets you visualize statistics on how users are working with the Dashboard, Pivot Table, GIS, Event Visualizer, Data Visualizer and Event Reports apps within DHIS2. With this statistics you can answers questions such as:

  • How many times people have loaded charts, pivots tables and dashboards?

  • How many favorites have users created?

  • How many users that are logging in versus total number of users?

  • What are the most viewed favorites?

17.2. Create a usage analytics graph

  1. Open the Usage Analytics app.

  2. Select a Start date and End date.

  3. Select an Interval: day, week month or year.

  4. Select a Category.

    There are five analytics categories:

    • Favorite views: Provides the number of times various types of favorites have been viewed, such as charts, pivot tables and dashboards, over time. This analysis lets you switch between all types of favorites, the total across all types and the average number of views.

    • Favorites: Provides the number of favorites which have been created and stored in the system over time.

    • Users: Provides the number of active as well as total number of users over time.

    • Top favorites: Shows the most viewed favorites in the system by type.

    • Data values: Provides the number of data values stored in the system over time.

  5. Click Update.

Chapter 18. Configure metadata

Table of Contents

18.1. About the Maintenance app
18.2. Manage categories
18.2.1. About categories
18.2.2. Workflow
18.2.3. Create or edit a category option
18.2.4. Create or edit a category
18.2.5. Create or edit a category combination
18.2.6. Create or edit a category option group
18.2.7. Create or edit a category option group set
18.2.8. Use category combinations for data sets
18.2.9. Assign a code to a category option combination
18.2.10. Clone metadata objects
18.2.11. Change sharing settings for metadata objects
18.2.12. Delete metadata objects
18.2.13. Display details of metadata objects
18.2.14. Translate metadata objects
18.3. Manage data elements
18.3.1. About data elements
18.3.2. Workflow
18.3.3. Create or edit a data element
18.3.4. Create or edit a data element group
18.3.5. Create or edit a data element group set
18.3.6. Clone metadata objects
18.3.7. Change sharing settings for metadata objects
18.3.8. Delete metadata objects
18.3.9. Display details of metadata objects
18.3.10. Translate metadata objects
18.4. Manage data sets and data entry forms
18.4.1. About data sets and data entry forms
18.4.2. Workflow
18.4.3. Create or edit a data set
18.4.4. Override data elements' category combinations in a data set
18.4.5. Edit compulsory data elements in a data set
18.4.6. Download default data forms in PDF format
18.4.7. Manage section forms
18.4.8. Manage custom forms
18.4.9. Change sharing settings for metadata objects
18.4.10. Delete metadata objects
18.4.11. Display details of metadata objects
18.4.12. Translate metadata objects
18.5. Manage indicators
18.5.1. About indicators
18.5.2. Workflow
18.5.3. Create or edit an indicator type
18.5.4. Create or edit an indicator
18.5.5. Create or edit an indicator group
18.5.6. Create or edit an indicator group set
18.5.7. Clone metadata objects
18.5.8. Change sharing settings for metadata objects
18.5.9. Delete metadata objects
18.5.10. Display details of metadata objects
18.5.11. Translate metadata objects
18.6. Manage organisation units
18.6.1. About organisation units
18.6.2. Workflow
18.6.3. Create or edit an organisation unit
18.6.4. Create or edit an organisation unit group
18.6.5. Create or edit an organisation unit group set
18.6.6. Assign names to organisation unit levels
18.6.7. Move organisation units within a hierarchy
18.6.8. Close an organisation unit
18.6.9. Clone metadata objects
18.6.10. Change sharing settings for metadata objects
18.6.11. Delete metadata objects
18.6.12. Display details of metadata objects
18.6.13. Translate metadata objects
18.7. [Work in progress] Manage validation rules
18.7.1. About validation rules
18.7.2. Create or edit a validation rule
18.7.3. Create or edit a validation rule group
18.7.4. Create or edit a validation notification
18.7.5. Clone metadata objects
18.7.6. Change sharing settings for metadata objects
18.7.7. Delete metadata objects
18.7.8. Display details of metadata objects
18.7.9. Translate metadata objects
18.8. Manage attributes
18.8.1. About attributes
18.8.2. Create or edit an attribute
18.8.3. Clone metadata objects
18.8.4. Delete metadata objects
18.8.5. Display details of metadata objects
18.8.6. Translate metadata objects
18.9. Manage constants
18.9.1. About constants
18.9.2. Create or edit a constant
18.9.3. Clone metadata objects
18.9.4. Change sharing settings for metadata objects
18.9.5. Delete metadata objects
18.9.6. Display details of metadata objects
18.9.7. Translate metadata objects
18.10. Manage option sets
18.10.1. About option sets
18.10.2. Create or edit an option set
18.10.3. Clone metadata objects
18.10.4. Change sharing settings for metadata objects
18.10.5. Delete metadata objects
18.10.6. Display details of metadata objects
18.10.7. Translate metadata objects
18.11. Manage legends
18.11.1. About legends
18.11.2. Create or edit a legend
18.11.3. Clone metadata objects
18.11.4. Change sharing settings for metadata objects
18.11.5. Delete metadata objects
18.11.6. Display details of metadata objects
18.11.7. Translate metadata objects
18.11.8. Assign a legend to indicator or data element
18.11.9. See also
18.12. Manage predictors
18.12.1. About predictors
18.12.2. Create or edit a predictor
18.12.3. Clone metadata objects
18.12.4. Delete metadata objects
18.12.5. Display details of metadata objects
18.12.6. Translate metadata objects
18.13. Manage push reports
18.13.1. About push reports
18.13.2. Create or edit a push report
18.13.3. Preview push reports
18.13.4. Run push report jobs
18.13.5. Clone metadata objects
18.13.6. Delete metadata objects
18.13.7. Display details of metadata objects
18.13.8. Translate metadata objects
18.14. Manage external map layers
18.14.1. About external map layers
18.14.2. Create or edit an external map layer
18.14.3. Clone metadata objects
18.14.4. Delete metadata objects
18.14.5. Display details of metadata objects
18.14.6. Translate metadata objects
18.15. Edit multiple object groups at once
18.15.1. Edit multiple objects in an object group
18.15.2. Edit an object in multiple object groups

18.1. About the Maintenance app

In the Maintenance app you configure all the metadata objects you need to collect and analyze data:

  • Categories

  • Data elements

  • Data sets and data entry forms

  • Indicators

  • Organisation units

  • Program metadata: tracked entity, tracked entity attribute and relationship type

  • Validation rules

  • Attributes

  • Constants

  • Options sets

  • Legends

  • Predictors

  • Push reports

  • External map layers

[Note]Note

The functions you have access to depend on your user role's access permissions.

18.2. Manage categories

18.2.1. About categories

Categories are typically a concept, for example "Gender", "Age" or "Disease Status". Data elements such as "Number of cases of confirmed malaria" are often broken into smaller component parts to determine, for example, the number of confirmed malaria cases of particular age groups.

Use categories to disaggregate data elements into individual components. You can also use categories to assign metadata attributes to all data recorded in a specific dataset, such as "Implementing partner" or "Funding agency."

Example 18.1. Three age categories

Create three categories: "Under 1", "1-5" and "Over 5". Assign them as categories to the data element. This creates three separate fields for this data in the data entry forms:

  • Number of confirmed malaria cases (Under 1)

  • Number of confirmed malaria cases (1-5)

  • Number of confirmed malaria cases (Over 5)

Without categories, you would have had to create each of the data elements listed above separately.


In the Maintenance app, you manage the following and category objects:

Table 18.1. Category objects in the Maintenance app

Object type

Available functions

Category option

Create, edit, clone, share, delete, show details and translate

Category

Create, edit, clone, share, delete, show details and translate

Category combination

Create, edit, clone, share, delete, show details and translate

Category option combination

Edit and show details

Category option group

Create, edit, clone, share, delete, show details and translate

Category option group set

Create, edit, clone, share, delete, show details and translate


18.2.2. Workflow

  1. Create all category options.

  2. Create categories composed by the multiple category options you've created.

  3. Create category combinations composed by either one or multiple categories.

  4. Create data elements and assign them to a category combination.

18.2.3. Create or edit a category option

When possible, recycle category options. For instance, there might be two categories which might share a particular category option (for example <1 year of age). When creating the categories, this category option could be reused. This is important if particular category options (or category option combinations) that need to be analyzed together.

  1. Open the Maintenance app and click Category > Category option.

  2. Click the add button.

  3. Fill in the form:

    1. Name

    2. Short name

    3. Start date

    4. End date

  4. Select organisation units and assign them.

    [Tip]Tip

    You can automatically select all organisation units that belong to an organisation unit level or organisation unit group, for example "Chiefdom" or "Urban. To do this:

    Select an Organisation unit level or Organisation unit group and click Select.

  5. Click Save.

18.2.4. Create or edit a category

When you have created all category options for a particular category, you can create that category.

  1. Open the Maintenance app and click Category > Category.

  2. Click the add button.

  3. Fill in the form:

    1. Name

    2. Code

    3. Data dimension type

      A category either be of type "Disaggregation" or "Attribute". For disaggregation of data elements, you select Disaggregation. The data dimension type "Attribute" allows the category to be used to assign a combination of categories to data recorded through a data set.

    4. Data dimension

      If you select Data dimension, the category will be available to the analytics as another dimension, in addition to the standard dimensions of "Period" and "Organisation unit".

  4. Select category options and assign them.

  5. Click Save.

18.2.5. Create or edit a category combination

Category combinations lets you combine multiple categories into a related set.

Example 18.2. Category combination

You can disaggregate the data element "Number of new HIV infections" into the following categories:

  • HIV Service: "Other", "PMTCT", "TB"

  • Gender: "Male", "Female"

In this example, there are two levels of disaggregation that consist of two separate data element categories. Each data element category consist of several data element category options.


In DHIS2, different data elements are disaggregated according to a common set of categories. By combining these different categories into a category combination and assigning these combinations to data elements, you can apply the appropriate disaggregation levels quickly to a large number of data elements.

  1. Open the Maintenance app and click Category > Category combination.

  2. Click the add button.

  3. Fill in the form:

    1. Name

    2. Code

    3. Data dimension type

    4. Skip category total in reports

  4. Select categories and assign them.

  5. Click Save.

18.2.6. Create or edit a category option group

You can group and classify category options by using category option groups. The main purpose of the category option group set is to add more dimensionality to your captured data for analysis in for example the Pivot table or Data Visualizer apps.

Example 18.3. Category options groups and group sets

In a system, data is collected by "projects", where projects is modeled as category options. The system must be able to analyse data based on which donor that supports the project. In this case, create a category option group set called "Donor". Each donor can be created as a category option group, where each category option / project is put in the appropriate group. In the data analysis applications, the "Donor" group set will appear as a data dimension, while each donor appear as dimension items, ready to be included in reports.


To create a category option group:

  1. Open the Maintenance app and click Category > Category option group.

  2. Click the add button.

  3. Fill in the form:

    1. Name

    2. Short name: Define a short name for the data element.

    3. Code

    4. Data dimension type

  4. Select Category options and assign them.

  5. Click Save.

18.2.7. Create or edit a category option group set

You can group category option groups in category option group sets. The main purpose of the category option group set is to add more dimensionality to your captured data for analysis in for example the Pivot table or Data Visualizer apps.

  1. Open the Maintenance app and click Category > Category option group set.

  2. Click the add button.

  3. Fill in the form:

    1. Name

    2. Description

    3. Data dimension

    4. Data dimension type

  4. Select Category option groups and assign them.

  5. Click Save.

18.2.8. Use category combinations for data sets

When categories and category combinations have the data dimension type "Attribute", they can apply a common set of attributes to a related set of data values contained in a data set. When category combinations are used as a attribute, they serve as another dimension (similar to "Period" and "Organisation unit") which you can use in your analysis.

Example 18.4. Use category combination for a data set

Suppose that a NGO is providing ART services in a given facility. They would need to report each month on the "ART monthly summary", which would contain a number of data elements. The NGO and project could potentially change over time. In order to attribute data to a given NGO and project at any point in time, you need to record this information with each data value at the time of data entry.

  1. Create two categories with the data dimension type "Attribute": "Implementing partner" and "Projects".

  2. Create a category combination with the data dimension type "Attribute": "Implementing partners and projects".

  3. Assign the categories you've created to the category combination.

  4. Create a data set called "ART monthly summary" and select the "Implementing partners and projects" category combination.

When you enter data in the Data entry app, you can select an "Implementing partner" and a "Project". Each recorded data value, is assigned a specific combination of these categories as an attribute. These attributes (when specified as a dimension) can be used in the analysis applications similar to other dimensions, for example the period and organisation unit.


18.2.9. Assign a code to a category option combination

You can assign a code to category option combinations. This makes data exchange between DHIS2 and external systems easier. The system creates the category option combinations automatically.

  1. Open the Maintenance app and click Category > Category option combination.

  2. In the list, find the object you want to modify.

  3. Click the options menu and select Edit.

  4. Enter a code.

  5. Click Save.

18.2.10. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.2.11. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.2.12. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.2.13. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.2.14. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.3. Manage data elements

18.3.1. About data elements

Data elements are the base of DHIS2. Data elements define what is actually recorded in the system, for example number of immunisations or number of cases of malaria.

Data elements such as "Number of cases of confirmed malaria" are often broken into smaller component parts to determine, for example, the number of confirmed malaria cases of particular age groups.

In the Maintenance app, you manage the following data elements objects:

Table 18.2. Data element objects in the Maintenance app

Object type

Available functions

Data element

Create, edit, clone, share, delete, show details and translate

Data element group

Create, edit, clone, share, delete, show details and translate

Data element group set

Create, edit, clone, share, delete, show details and translate


18.3.2. Workflow

  1. Create all category options.

  2. Create categories composed by the multiple category options you've created.

  3. Create category combinations composed by either one or multiple categories.

  4. Create data elements and assign them to a category combination.

18.3.3. Create or edit a data element

  1. Open the Maintenance app and click Data elements > Data element.

  2. Click the add button.

  3. In the Name field, define the precise name of the data element.

    Each data element must have a unique name.

  4. In the Short name field, define a short name for the data element.

    Typically, the short name is an abbreviation of the full data element name. This attribute is often used in reports to display the name of the data element, where space is limited.

  5. (Optional) In the Code field, assign a code.

    In many countries data elements are assigned a code.

  6. In the Description field, type a description of the data element. Be as precise as possible and include complete information about how the data element is measured and what its purpose is.

  7. In the Form name field, type an alternative name of the data element. This name can be used in either section or automatic data entry forms. The form name is applied automatically.

  8. In the Domain type field, select whether the data element is an aggregate or tracker type of data element.

  9. In the Value type field, select the type of data that the data element will record.

    Table 18.3. Value types

    Value type

    Description

    Age

    -

    Coordinate

    A point coordinate specified as longitude and latitude in decimal degrees. All coordinate should be specified in the format "-19.23 , 56.42" with a comma separating the longitude and latitude.

    Date

    Dates rendered as calendar widget in data entry.

    Date & time

    -

    Email

    Email.

    File

    A file resource where you can store external files, for example documents and photos.

    Integer

    Any whole number (positive and negative), including zero.

    Letter

    A single letter.

    Long text

    Textual value. Renders as text area with no length constraint in forms.

    Negative integer

    Any whole number less than (but not including) zero.

    Number

    Any real numeric value with a single decimal point. Thousands separators and scientific notation is not supported.

    Percentage

    Whole numbers inclusive between 0 and 100.

    Phone number

    Phone number.

    Positive integer

    Any whole number greater than (but not including) zero.

    Positive of zero integer

    Any positive whole number, including zero.

    Organisation unit

    Organisation units rendered as a hierarchy tree widget.

    Unit interval

    Any real number greater than or equal to 0 and less than or equal to 1.

    Text

    Textual value. The maximum number of allowed characters per value is 50,000.

    Time

    Time is stored in HH:mm format.

    HH is a number between 0 and 23

    mm is a number between 00 and 59

    Tracker associate

    Tracked entity instance. Rendered as dialog with a list of tracked entity instances and a search field.

    Username

    DHIS 2 user. Rendered as a dialog with a list of users and a search field.

    Yes/No

    Boolean values, renders as drop-down lists in data entry.

    Yes only

    True values, renders as check-boxes in data entry.


  10. In the Aggregation type field, select the default aggregation operation that will be used on the data element.

    Most data elements should have the Sum operator. This includes all data elements which should be added together. Other data elements, such as staffing levels, should be set to use the Average operator, when values along the time dimension should not be added together, but rather averaged.

    Table 18.4. Aggregation operators

    Aggregation operator

    Description

    Average

    Average the values in both the period as and the organisation unit dimensions.

    Average (sum in organisation unit hierarchy)

    Average of data values in the period dimension, sum in the organisation unit dimensions.

    Count

    Count of data values.

    Min

    Minimum of data values.

    Max

    Maximum of data values.

    None

    No aggregation is performed in any dimension.

    Sum

    Sum of data values in the period and organisation unit dimension.

    Standard deviation

    Standard deviation (population-based) of data values.

    Variance

    Variance (population-based) of data values.


  11. If you want to save zeros for a particular reason, select Store zero data values. By default, DHIS2 does not store zeros entered in the data entry module.

  12. In the URL field, enter a link to an in-depth description of the data element.

    For example a link to a metadata repository or registry that contains detailed technical information about the definition and measurement of the data element.

  13. In the Category combination field, define which category combination the data element should have. This is also known as the "disaggregation".

  14. Select an Option set.

    Option sets are predefined lists of options which can be used in data entry.

  15. Select an Option set for comments.

    Option sets for comments are predefined lists of options which can be used to specify standardized comments for data values in data entry.

  16. Assign one or multiple Legends.

    Legends are used in for example the GIS app to display certain data elements with certain icons.

  17. Set the Aggregation levels to allow the data element to be aggregated at one or more levels:

    1. In the left pane, select the levels you want to assign to the data element.

    2. Click the right arrow to assign the aggregation levels.

    By default, the aggregation will start at the lowest assigned organisation unit. If you for example select "Chiefdom", it means that "Chiefdom", "District", and "National" aggregates use "Chiefdom" (the highest aggregation level available) as the data source, and PHU data will not be included. PHU data will still be available for the PHU level, but not included in aggregations to the levels above.

    If you select both "District" and "Chiefdom", it means that the "District" and "National" level aggregates use District data as their source, "Chiefdom" will use Chiefdom, and "PHU" will use PHU.

  18. If applicable, enter custom attributes values, for example Classification or Collection method.

    [Note]Note

    You create custom attributes in the Maintenance app: Other > Attributes.

  19. If applicable, select compulsory data element group sets, for example Main data element group or Tracker-based data.

    [Note]Note

    You'll only see data element group sets in this form if you've created them and set them to Compulsory.

    You create data element group sets in the Maintenance app: Data element > Date element group set.

  20. Click Save.

18.3.4. Create or edit a data element group

Data element groups lets you classify related data elements into a common theme. For example, two data elements "Measles immunisation" and "BCG Immunisation" might be grouped together into a data element group "Childhood immunisation".

To create a data element group:

  1. Open the Maintenance app and click Data elements > Data element group.

  2. Click the add button.

  3. Fill in the form:

    1. Name

    2. Short name

    3. Code

  4. Select data elements and assign them.

  5. Click Save.

18.3.5. Create or edit a data element group set

Data element group sets allows you to categorise multiple data element groups into a set. The system uses data element group sets during analysis and reporting to combine similar data element groups into a common theme. A data element group can be part of multiple data element group sets.

  1. Open the Maintenance app and click Data elements > Data element group set.

  2. Click the add button.

  3. Fill in the form:

    1. Name

    2. Code

    3. Description

    4. Compulsory

    5. Data dimension

  4. Select data element groups and assign them.

    Available data element groups are displayed in the left panel. Data element groups that are currently members of the data element group set are displayed in the right hand panel.

  5. Click Save.

18.3.6. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.3.7. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.3.8. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.3.9. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.3.10. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.4. Manage data sets and data entry forms

18.4.1. About data sets and data entry forms

All data entry in DHIS2 is organised in data sets. A data set is a collection of data elements grouped together for data entry and data export between instances of DHIS2. To use a data set to collect data for a specific organisation unit, you must assign the organisation unit to the data set. Once you have assigned the data set to an organisation unit, that data set is available in the Data entry app. Only the organisation units that you have assigned the data set to can use the data set for data entry.

A category combination can link to both data elements and data sets. If you use a category combination for a data set, the category combinations is applicable for the whole form. This means that you can use categories to capture information which is common to an entire form, for example the name of the a project or grant. When a data set is linked to a category combination, those categories will be displayed as drop-down boxes in the Data entry app. Data captured in the form will then be linked to the selected category options from those drop-down boxes. For information about how to create categories and category combinations, see section "Manage data elements and categories". Make sure that you set the type of categories and category combinations to "Attribute".

Example 18.5. Categories for data sets

An scenario for when categories are useful is when you need to capture a data entry form for a implementing partner organisation and a project. In that case:

  1. Create category options and categories for all partner organisations and projects and link them in a new category combination.

  2. Assign the category combination to the data set (form) for which you need to capture this information.

    When opening this data set in data entry module, the partner organisation and project categories will automatically be rendered as drop-down boxes, allowing you to select a specific implementing partner organisation and project before continuing to do data entry.


You create and edit data sets in the Maintenance app. Here you define, for example, which data elements you want to include in the data set and the data collection frequency.

You enter data in the Data entry app. The Data entry app uses data entry forms to display the data sets. There are three types of data entry forms:

Table 18.5. Data entry form types

Data entry form typeDescription

Default form

Once you have assigned a data set to an organisation unit, a default form is created automatically. The default form is then available in the Data entry app for the organisation units you have assigned it to.

A default form consist of a list of the data elements belonging to the data set together with a column for inputting the values. If your data set contains data elements with a non-default category combination, for example age groups or gender, additional columns are automatically created in the default form based on the different categories.

If you use more than one category combination you get multiple columns in the default form with different column headings for the options.

Section form

If the default form doesn't meet your needs, you can modify it to create a section form. Section forms give you more flexibility when it comes to using tabular forms.

In a section form you can, for example, create multiple tables with subheadings and disable (grey out) cells in a table.

When you have added a section form to a data set, the section form is available in the Data entry app.

Custom form

If the form you want to design is too complicated for default or section forms, you can create a custom form. A custom form takes more time to create than a section form, but you have full control over the design.

You can, for example, mimic an existing paper aggregation form with a custom form. This makes data entry easier, and should reduce the number incorrectly entered data elements.

When you have added a custom form to a data set, the custom form is available in the Data entry app.


[Note]A data set can have both section and custom forms

If a data set has both a section form and a custom form, the system displays the custom form during data entry. Users who enter data can't select which form they want to use. In web-based data entry the order of display preference is:

  1. Custom form (if it exists)

  2. Section form (if it exists)

  3. Default form

Mobile devices do not support custom forms. In mobile-based data entry the order of display preference is:

  1. Section form (if it exists)

  2. Default form

In the Maintenance app, you manage the following data set objects:

Table 18.6. Data set objects in the Maintenance app

Object type

Available functions

Data set

Create, assign to organisation units, edit, share, delete, show details and translate

Edit compulsory data elements

Add and remove multiple data sets to organisation units at once

Section form

Create, edit and manage grey fields

Section

Change display order, delete and translate

Custom form

Create, edit and script


18.4.2. Workflow

You need to have data elements and categories to create data sets and data entry forms.

  1. Create a data set.

  2. Assign the data set to organisation units.

    A default form is created automatically.

  3. Create a section form or a custom form.

    Now you can register data in the Data entry app.

18.4.3. Create or edit a data set

  1. Open the Maintenance app and click Data set > Data set.

  2. Click the add button.

  3. In the Name field, type the precise name of the data set.

  4. In the Short name field, define a short name for the data set.

    Typically, the short name is an abbreviation of the full data set name. This attribute is often used to display the name of the data set where space is limited.

  5. (Optional) In the Code field, assign a code.

  6. In the Description field, type a description of the data set.

  7. Enter the number of Expiry days.

    The number of expiry days controls for how long it should be possible to enter data in the Data entry app for this data set. Expiry days refer to the number of days after the end date of the selected data entry period where the data entry form should be open for entry. After the number of days has expired, the data set will be locked for further entry.

    You can set manual exceptions to this using the lock exception functionality in the Data Administration app.

    [Note]Note

    To allow data entry into all possible historical time periods, set the number of expiry days to zero.

  8. If you want it to be possible to enter data for future periods, type the number of periods in the Open future periods for data entry field.

    The value is the number of future periods which are available for data entry.

    Example 18.6. Open future periods for data entry

    For a monthly data set a value of 2 allows you to enter data for 2 months in advance. This is useful for, by example, population, target and planning data.


  9. In the Days after period to qualify for timely submission field, type the number of days in which data can be entered to be considered reported on time.

    To verify the number of timely reports submitted, go to Reports > Reporting rate summary.

  10. Select a Period type.

    The period type defines the frequency of reporting for the particular data set. The frequency can for example be daily, quarterly or yearly.

  11. Select a Category combination to assign it to the data set.

    [Tip]Tip

    Click Add new to create category combinations that you're missing. In the form that opens, create the category combinations you need. When you're done, click Refresh values.

  12. In the Complete notification recipients list, select a user group that should receive a message when the data set is marked as complete in the Data Entry app.

    The message is delivered through the DHIS2 messaging system.

  13. If you want the user who entered the data to receive a message when the data set is marked as complete in the Data entry app, select Send notification to completing user.

    The message is delivered through the DHIS2 messaging system.

  14. If applicable, select, a Data approval workflow.

  15. If you want it to be possible to use the data set within the Java mobile DHIS 2 application, select Enable for Java mobile client.

  16. If you want it to be mandatory to fill all values for a data element in data entry if one or more values have been filled, select All fields for data elements required.

    This means that if you enter one data value for a data element in an entry field (that is for a category option combination), then you must enter data for all fields belonging to that data element (that is all category option combinations).

  17. If you want it to be possible to mark a data entry form as complete only if the validation of that form is successful, select Complete allowed only if validation passes.

    If you select this option, you can't mark the form as complete if validation fails.

  18. If you want it to be mandatory that any missing values require a comment to justify their absence, select Missing values requires comment on complete.

  19. (Optional) Assign one or multiple Legends.

  20. If applicable, select Skip offline.

    This option controls whether this data entry form should be downloaded and saved in the user's web browser. Normally you shouldn't select Skip offline. This is the default setting. If you have big forms which are rarely used you can consider selecting this option to speed up initial loading in the data entry module.

  21. If applicable, select Data element decoration

    If you select this option, descriptions of data elements render in call-outs in downloaded data sets in offline mode in the Data entry app.

  22. If applicable, select Render sections as tabs.

    This option is only applicable for section forms. The option allows you to render each section as a tab horizontally above the data set. This is useful for long data sets as it allows appropriate sections to be selected quickly without going through the entire form.

  23. If applicable, select Render vertically.

    This option is only applicable for section forms.

  24. Select data elements and assign them.

    You can override the category combination for each selected data set by clicking on the gear icon above the list of selected data elements. This allows you to utilize a specific category combination (disaggregation) within the current data set instead of the category combination associated directly with the data element itself.

  25. Select indicators and assign them.

  26. In the organisation unit tree, select the organisation units you want to assign the data set to.

    [Tip]Tip
    • Click Organisation unit level to select all organisation units that belong to a certain organisation level.

    • Click Organisation unit group to select all organisation units that belong to a certain organisation unit group.

  27. Click Save.

You can now use the data set in the Data Entry app for the organisation units that you have assigned to and for periods according to the selected frequency (period type).

18.4.4. Override data elements' category combinations in a data set

You can override which category combination to use for a data element within the context of a data set. This means that a data element can use different category combinations within different data sets. This is useful when you want to reuse a data element since you don't have to replicate the data element to allow multiple category combinations.

Example 18.7. 

If different regions within your organisation unit hierarchy use different disaggregations, or if the disaggregations change over time, you can represent this by creating different data sets with the appropriate category combinations.


  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the data set you want to modify.

  3. Click the options menu and select Edit.

  4. Go to the data elements section and click the spanner icon.

  5. Select new category combinations and click Close.

  6. Click Save.

18.4.5. Edit compulsory data elements in a data set

You can add or remove data elements which will be marked as compulsory during data entry.

  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the data set you want to edit.

  3. Click the options menu and select Edit compulsory data elements.

  4. Assign the compulsory data elements.

  5. Click Save.

18.4.6. Download default data forms in PDF format

You can download a default data from in PDF format for offline data entry.

  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the object you want to download.

  3. Click the options menu and select Get PDF for data entry.

18.4.7. Manage section forms

18.4.7.1. Create a section form

Section forms are separated automatically by data element category combinations, which produce a spreadsheet like data entry form for each section.

  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the data set you want to create a section form for.

  3. Click the options menu and select Manage sections.

  4. Click the add button.

  5. (Optional) In the Name field, type the name of the section.

  6. (Optional) In the Description field, type a description of the section.

  7. (Optional) To display totals for rows in the section form during data entry, select Show row totals.

  8. (Optional) To display totals for columns in the section form during data entry, select Show column totals.

  9. Assign data elements to the section:

    1. (Optional) Select a Category combination filter.

      [Note]Note

      You can only use one category combination per section.

      Option

      Description

      None

      Displays all data elements that don't have a category combination.

      <No filter>

      Displays all data elements.

    2. Select data elements and assign them.

  10. (Optional) Sort the data elements within the section by using the up and down arrows to the left of the assigned data elements field.

  11. Click Save.

  12. Repeat add section steps for each section you want to have in your section form.

    In the Data Entry app you can now use the section form. The section form appears automatically when sections are available for the selected data set. Data sets which have section forms will automatically display the section form.

Example 18.8. Section form example

Note how each data element category has been separated into a separate section, and a data entry table has been automatically generated by the system. Use of section forms in combination with data element categories can drastically reduce the amount of time which is required to create data entry forms for data sets.


18.4.7.2. Edit a section form

  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the data set you want to edit the section form for.

  3. Click the options menu and select Manage sections.

  4. In the list, find the section you want to edit.

  5. Click the options menu and select Edit.

  6. Edit the section and click Save.

  7. Repeat edit section steps for each section you want to edit.

18.4.7.3. Manage grey fields in a section form

You can disable data elements and category options for data entry. That means it won’t be possible to enter data into these fields during data entry.

  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the data set you want to edit the section form for.

  3. Click the options menu and select Manage sections.

  4. In the list, find the section you want to edit.

  5. Click the options menu and select Manage grey fields.

  6. Select which fields you want to disable.

    [Note]Note

    If you've sections that contain data elements assigned to multiple category combinations, switch between the category combinations to view all fields.

  7. Click Save.

18.4.7.4. Change section display order in a section form

You can control in which order sections are displayed in a section form.

  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the data set you want to edit the section form for.

  3. Click the options menu and select Manage sections.

  4. In the list, find the section you want to move.

  5. Click the options menu and select Move up or Move down.

    If the section you want to move is the first or last section in the list, you'll only see one of the move options.

18.4.7.5. Delete a section in a section form

  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the data set you want to edit the section form for.

  3. Click the options menu and select Manage sections.

  4. In the list, find the section you want to delete.

  5. Click the options menu and select Delete.

18.4.7.6. Translate a section in a section form

  1. Open the Maintenance app and click Data set > Data set.

  2. In the list, find the data set you want to edit the section form for.

  3. Click the options menu and select Translate.

  4. Select a locale.

  5. Enter the required information.

  6. Click Close.

18.4.8. Manage custom forms

18.4.8.1. Create a custom form

You design custom forms in a built-in WYSIWYG HTML editor. If you select Source, you can paste HTML code directly in the editing area. For a complete guide on how to use the editor, refer to http://docs.ckeditor.com/.

To create a custom form:

  1. Open the Maintenance app and click Data set.

  2. In the list, find the data set you want to add a custom form to.

  3. Click the options menu and select Design data entry form.

  4. In the editing area, create the custom form.

    • Double-clik on a object in the left-hand list to insert it in the form.

    • If you already have the HTML code for your form, click Source and paste the code.

  5. Select a Form display style.

  6. Click Save.

18.4.8.2. Scripting in custom forms

In custom data entry form you can use JavaScript to create dynamic behavior and customizations. As an example, you can hide form sections based on specific user input for data elements, or show specific information when a form loads.

18.4.8.2.1. Events

The DHIS2 data entry module provides a range of events which you can register for and use to perform actions at certain times. The events are registered on the document element. The jQuery event object and the data set identifier are always the first two arguments provided to the callback functions. The table below provides an overview of the events and when they are triggered.

Table 18.7. Data entry events

KeyDescriptionArguments

dhis2.de.event.formLoaded

Triggered after the data entry form is rendered, but before data values are set in entry fields.

Event | Data set ID

dhis2.de.event.dataValuesLoaded

Triggered after data values are set in entry fields.

Event | Data set ID

dhis2.de.event.formReady

Triggered when the data entry form is completely rendered and loaded with all elements.

Event | Data set ID

dhis2.de.event.dataValueSaved

Triggered when a data value is saved successfully.

Event | Data set ID | Data value object

dhis2.de.event.completed

Triggered when a data set is successfully marked as complete.

Event | Data set ID | Complete registration object

dhis2.de.event.uncompleted

Triggered when a data set is successfully marked as incomplete.

Event | Data set ID

dhis2.de.event.validationSuccess

Triggered when validation is done and there were no violations.

Event | Data set ID

dhis2.de.event.validationError

Triggered when validation is done and there were one or more violations.

Event | Data set ID

dhis2.ou.event.orgUnitSelected

Triggered when one or more organisation units are selected in the org unit web tree.

Event | Org unit IDs | Org unit names | Sub org unit IDs


To register for an event:

<script type="text/javascript">

dhis2.util.on( 'dhis2.de.event.formReady', function( event, ds ) {
  console.log( 'The form with id: ' + ds + ' is loaded!' );
} );

dhis2.util.on( 'dhis2.de.event.dataValueSaved', function( event, ds, dv ) {
  console.log( 'Data value: ' + dv.value + ' was saved with data element: ' + dv.de );
} );

dhis2.util.on( 'dhis2.de.event.completed', function( event, ds, cr ) {
  console.log( 'Form was completed for org unit: ' + cr.ou );
} );

</script>
[Note]Note

Be careful to only use "namespaced" events like the ones in the example above and not general ones like "click" as the dhis2.util.on method will unregister the event first.

If your function only applies to certain data sets you can use the supplied data set identifier and shortcut your function for unwanted data sets like this:

dhis2.de.on( 'dhis2.de.event.validationSuccess', function( event, ds ) {
  if ( $.inArray( ds, ['utXOiGbEj14', 'Re7qzHEThSC'] ) == -1 ) {
    return false;
  }
  console.log( 'Form with id: ' + ds + ' validated successfully!' );
} );

The identifiers of the input fields in the data entry form is on the format described below. This format can be used to select the input fields in your script and perform actions on them:

<dataelementid>-<optioncomboid>-val

Since the data set identifier is provided for all events a feasible alternative is to utilize the "files" Web API resource and keep your callback functions in a single file, where you let the JavaScript code take action based on which data set is currently loaded.

18.4.8.2.2. Functions

The DHIS2 data entry module contains JavaScript API functions which can be accessed from custom data entry forms.

dhis2.de.api.getSelections: This function returns a JavaScript object which contains properties for all dimensions with corresponding values for the identifiers of the selected options. It contains properties for "ds" (data set), "pe" (period), "ou" (organisation unit) and identifiers for all data set categories.

An example response looks like this:

{
 +  ds: "lyLU2wR22tC",
 +  pe: "201605",
 +  ou: "g8upMTyEZGZ",
 +  LFsZ8v5v7rq: "CW81uF03hvV",
 +  yY2bQYqNt0o: "yMj2MnmNI8L"
 +}

Example JavaScript usage of this function:

var sel = dhis2.de.api.getSelections();
 +var orgUnit = sel["ou"];
 +var partner = sel["LFsZ8v5v7rq"];

18.4.9. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.4.10. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.4.11. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.4.12. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.5. Manage indicators

18.5.1. About indicators

An indicator is a formula that can consist of multiple data elements, constants, organisation unit group counts and mathematical operators. The indicator consist typically of a numerator and denominator. You use indicators to calculate coverage rates, incidence and other values that are a result of data element values that have been entered into the system. Calculated totals do not have a denominator.

[Note]Note

You never enter indicators directly in DHIS2, you calculate them.

An indicator formula can consist of mathematical operators, for example plus and minus, and of the following elements:

Table 18.8. Indicator formula

Formula elementTypeDescription

Constant

Component

Constants are numerical values which remain the same for all indicator calculations. This is useful in order to have a single place to change values that might change over time.

Constants are applied AFTER data element values have been aggregated.

Data elements

Component

Data elements are substituted by the data value captured for the data element.

Days

Operator

"Days" is special operator that always provides the number of days for a given indicator calculation.

For example: if you want to calculate the "Percentage of time vaccine refrigerator was non-functional", you could define the numerator as:

("Days-"Number of days vaccine refrigerator was available"")/"Days"

If the fridge was available 25 days in June, the indicator would be calculated as:

(30-25/25)*100 = 17 %

If you want to calculate the total for Quarter 1, the number of days ("Days") would be:

31+28+31 = 90

The "Days" parameter will always be the number of days in the period of interest.

Organisation unit counts

Component

You can use organisation unit groups in formulas. They will be replaced by the number of organisation units in the group. During aggregation, the organisation units in the group will be intersected with the part of the organisation unit hierarchy being requested.

This lets you use the number of public facilities in a specific district in indicators. This is useful for example when you create facility infrastructure surveys and reports.

Programs

Component

Click Programs and select a program to view all data elements, attributes and indicators related to a specific program.

The program components you include in your formula will have a program tag assigned to them.


In the Maintenance app, you manage the following indicator objects:

Table 18.9. Indicator objects in the Maintenance app

Object type

Available functions

Indicator

Create, edit, clone, share, delete, show details and translate

Indicator type

Create, edit, clone, delete, show details and translate

Indicator group

Create, edit, clone, share, delete, show details and translate

Indicator group set

Create, edit, clone, share, delete, show details and translate


18.5.2. Workflow

  1. Create indicator types.

  2. Create indicators.

  3. Create indicator groups.

  4. Create indicator group sets.

18.5.3. Create or edit an indicator type

Indicator types define a factor that is applied during aggregation. Indicator values that are calculated during a data mart export or report table generation process will appear properly formatted, and will therefore not require an additional multiplier (for example 100 in the case of percents) for the values to appear correctly formatted.

[Note]Note

As of version 2.4 of DHIS2, the "Calculated data element" object has been deprecated. Instead, you can create a calculated data element by creating an indicator type with a factor of "1" and by setting the "Number" option to "Yes". The effect of setting the "Number" option to "Yes" will be that the indicator will effectively not have a denominator. You will therefore only be able to define a numerator, which will serve as the formula of the calculated data element.

  1. Open the Maintenance app and click Indicator > Indicator type.

  2. Click the add button.

  3. In the Name field, type the name of the indicator type, for example "Per cent", "Per thousand", "Per ten thousand".

  4. Type a Factor.

    The factor is the numeric factor that will be multiplied by the indicator formula during the calculation of the indicator.

  5. Click Save.

18.5.4. Create or edit an indicator

  1. Open the Maintenance app and click Indicator > Indicator.

  2. Click the add button.

  3. In the Name field, type the full name of the indicator, for example "Incidence of confirmed malaria cases per 1000 population".

  4. In the Short name field, type an abbreviated name of the indicator, for example "Inc conf. malaria per 1000 pop".

    The short name must be less than or equal to 25 characters, including spaces.

  5. (Optional) In the Code field, assign a code.

    In many countries indicators are assigned a code.

  6. In the Description field, type a brief, informative description of the indicator and how it is calculated.

  7. If you want to apply an annualization factor during the calculation of the indicator, select Annualized.

    Typically, an annualized indicator's numerator is multiplied by a factor of 12, and the denominator is for instance a yearly population figure. This allows for monthly coverage values to be calculated with yearly population figures.

  8. Select the number of Decimals in data output.

  9. Select an Indicator type.

    This field determines a factor that will automatically be applied during the calculation of the indicator. Possible choices are determined by the indicator types. For example, a "Percent" indicator will automatically be multiplied by a factor of 100 when exported to the data mart, so that it will display as a percentage.

  10. (Optional) Assign one or multiple Legends.

  11. In the URL field, enter a link, for example a link to an indicator registry, where a full metadata description of the indicator can be made available.

  12. (Optional) Enter a Category option combination for aggregate data export..

    You use this setting to map aggregated data exported as raw data to another server. Typically you do this type of data exchange mapping when you want to create anonymous aggregated data from patient data recorded in programs (event data).

  13. (Optional) Enter an Attribute option combination for aggregate data export..

    You use this setting to map aggregated data exported as raw data to another server. Typically you do this type of data exchange mapping when you want to create anonymous aggregated data from patient data recorded in programs (event data).

  14. If applicable, enter custom attributes values, for example Classification or Collection method.

    [Note]Note

    You create custom attributes in the Maintenance app: Other > Attributes.

  15. Click Edit numerator.

    1. Type a clear description of the numerator.

    2. Define the numerator by double-clicking components in the right-hand field. The components then appears as part of the formula in the left-hand field. Add mathematical operators by double-clicking the icons below the left-hand field.

      You formula must be mathematically valid. This includes correct use of parentheses when necessary.

    3. Click Done to save all changes to the numerator.

  16. Click Edit denominator.

    1. Type a clear description of the denominator.

    2. Define the denominator by double-clicking components in the right-hand field. The components then appears as part of the formula in the left-hand field. Add mathematical operators by double-clicking the icons below the left-hand field.

      You formula must be mathematically valid. This includes correct use of parentheses when necessary.

    3. Click Done to save all changes to the denominator.

  17. If applicable, select compulsory indicator group sets, for example Human resources.

    [Note]Note

    You'll only see indicator group sets in this form if you've created them and set them to Compulsory.

    You create indicator group sets in the Maintenance app: Indicator > Indicator group set.

  18. Click Save.

18.5.5. Create or edit an indicator group

  1. Open the Maintenance app and click Indicator > Indicator group.

  2. Click the add button.

  3. Type a name.

  4. Select indicators and assign them.

  5. Click Save.

18.5.6. Create or edit an indicator group set

Indicator group sets create combined groups of similar indicators. For example, you might have a group of indicators called "Malaria" and "Leishmaniasis". Both of these groups could be combined into a group set called "Vector-borne diseases". Indicator groups sets are used during analysis of data to combine similar themes of indicators.

  1. Open the Maintenance app and click Indicators > Indicator group.

  2. Click the add button.

  3. Fill in the form:

    1. Name

    2. Description

    3. Compulsory

  4. Select indicator groups and assign them.

    Available indicator groups are displayed in the left panel. Indicator groups that are currently members of the indicator group set are displayed in the right hand panel.

  5. Click Save.

18.5.7. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.5.8. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.5.9. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.5.10. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.5.11. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.6. Manage organisation units

In this section you will learn how to:

  • Create a new organisation unit and build up the organisation unit hierarchy

  • Create organisation unit groups, group sets, and assign organisation units to them

  • Modify the organisation unit hierarchy

18.6.1. About organisation units

The organisation unit hierarchy defines the organisation structure of DHIS2, for example how health facilities, administrative areas and other geographical areas are arranged with respect to each other. It is the "where" dimension of DHIS2, similar to how periods represent the "when" dimension.

The organisation unit hierarchy is built up by parent-child relations. In DHIS2, each of these nodes is an organisation unit. A country might for example have eight provinces, and each province might have a number of districts as children. Normally, the lowest levels consist of facilities where data is collected. Data collecting facilities can also be located at higher levels, for example national or provincial hospitals. Therefore, you can create skewed organisation trees in DHIS2.

  • You can only have one organisation hierarchy at the same time.

  • You can have any number of levels in a hierarchy.

    Typically national organisation hierarchies in public health have four to six levels.

  • You can create additional classifications by using organisation groups and organisation group sets.

    For example to create parallel administrative boundaries to the health care sector.

  • It is recommended to use organisation unit groups to create a non-geographical hierarchy.

  • An organisation unit can only be a member of a single organisation unit group within an organisation unit group set.

  • An organisation unit group can be part of multiple organisation unit group sets.

  • The organisation unit hierarchy is the main vehicle for data aggregation on the geographical dimension.

  • When you close an organisation unit, you can't register or edit events to this organisation unit in the Event Capture and Tracker Capture apps.

[Important]Changing the organisation unit hierarchy

You can change the organisation unit hierarchy after you've created it, even organisation units that collect data. However, DHIS2 always uses the latest hierarchy for data aggregation. So if you change the hierarchy, you loose the temporal representation of the hierarchy across time.

Example 18.9. 

District A is sub-divided into District B and District C. Facilities which belonged to District A are reassigned to District B and C. Any historical data, which you entered before the split occurred, is still registered as belonging to District B and C, not to the obsolete District A.


In the Maintenance app, you manage the following organisation unit objects:

Table 18.10. Organisation unit objects in the Maintenance app

Object type

Available functions

Organisation unit

Create, edit, clone, delete, show details and translate

Organisation unit group

Create, edit, clone, share, delete, show details and translate

Organisation unit group set

Create, edit, clone, share, delete, show details and translate

Organisation unit level

Edit and translate

Hierarchy operations

Move organisation units


18.6.2. Workflow

The recommended workflow is:

  1. Create organisation units.

  2. Create organisation unit groups.

  3. Create organisation unit group sets.

18.6.3. Create or edit an organisation unit

You add organisation units to the hierarchy one by one, either as a root unit or as a child of a selected organisation unit. You can only have one root unit.

  1. Open the Maintenance app and click Organisation unit > Organisation unit.

  2. Click the add button.

  3. Select which organisation unit your new organisation unit will belong to:

    1. Click Parent organisation unit.

    2. In the organisation unit tree, locate the parent organisation unit and select it. Your selection is marked in yellow.

      [Tip]Tip

      Click the arrows to expand the organisation unit tree.

    3. Click Select.

  4. Enter a Name of the organisation unit.

    Each organisation unit must have an unique name.

  5. Enter a Short name for the organisation unit.

    Typically, the short name is an abbreviation of the full organisation unit name. This attribute is often used in reports to display the name of the organisation unit, where space is limited.

  6. (Optional) Assign a Code.

    In many countries organisation units are assigned a code.

  7. (Optional) Type a Description of the organisation unit.

  8. Select an Opening date.

    The opening dates control which organisation units that existed at a point in time, for example when analysing historical data.

  9. If applicable, select a Closed date.

  10. In the Comment field, enter any additional information that you would like to add.

  11. (Optional) In the URL field, enter a link to an external web site that has additional information about the organisation unit.

  12. Enter contact information:

    • Contact person

    • Address

    • E-mail

    • Phone number

  13. (Optional) Enter Latitude and Longitude.

    You must have latitude and longitude values to create maps in the GIS app. Then your organisation units can be represented as points on a map, for example a health facility. Without this information, the GIS app will not work.

    It might be more efficient to import coordinates later as a batch job for all organisation units using the Import-Export app. You also use the Import-Export app to create polygons. A polygon is an organisation unit that represent an administrative boundary.

  14. If applicable, select Data sets and assign them.

    [Note]Note

    You control whether a user should be able to assign data sets to an organisation unit in the System Settings app:

    Open the System Settings app, click Access and select Allow assigning object to related objects during add or update.

  15. If applicable, enter custom attributes values, for example HR identifier.

    [Note]Note

    You configure the custom attributes in the Maintenance app:

    Open the Maintenance app and click Other > Attribute.

  16. Click Save.

18.6.4. Create or edit an organisation unit group

Organisation unit groups allow you to classify related organisation units into a common theme. You can for example group all organisation units that are hospitals in an Hospital group.

  1. Open the Maintenance app and click Organisation unit > Organisation unit group.

  2. Click the add button.

  3. Fill in the form:

    1. Name: Provide a precise, unique and descriptive name for the organisation unit group.

    2. Short name: The short name should be less than 25 characters. Typically, the short name is an abbreviation of the full organisation unit name. This attribute is used in certain places in DHIS2 where space is limited.

    3. Code

    4. Symbol: Select a symbol which will be used to display the organisation unit (points only) when the layer is displayed in the GIS app.

  4. In the organisation tree, click the organisation units you want to add to the organisation unit group.

    You can locate an organisation unit in the tree by expanding the branches (click on the arrow symbol), or by searching for it by name.

    The selected organisation units display in orange.

  5. Click Save.

18.6.5. Create or edit an organisation unit group set

Organisation unit group sets allows you to create additional classifications of organisation units. The group sets create new dimensions so that you can make a more detailed data analysis. You an easily filter, organise or aggregate data by groups within a group set.

  • You can have any number of organisation unit group sets.

  • The default organisation unit group sets are Type and Ownership.

  • An organisation unit can only be a member of a single organisation unit group within an organisation unit group set.

  • An organisation unit group can be part of multiple organisation unit group sets.

  • You can define whether an organisation unit group set is compulsory or not, which will affect the completeness of the data. Compulsory means that all organisation units must be member of a group in that group set.

[Note]Data completeness

In the Data integrity part of the Data administration app you can verify if you've accidentally assigned the same organisation unit to multiple groups within the same group set. In this app you also find information about organisation units that are not members of a compulsory organisation unit group set.

  1. Open the Maintenance app and click Organisation unit > Organisation unit group set.

  2. Click the add button.

  3. Fill in:

    1. Name: Provide a precise name for the organisation unit group set.

    2. Code

    3. Description: Describe what the organisation unit group set measures or captures.

  4. If you want all organisation units to be members of a group within the group set, select Compulsory.

  5. (Optional) Select Data dimension.

  6. (Optional) Select Include subhierarchy in analytics.

    If you select this, a sub-organisation unit will inherit the organisation unit group property from its closest "parent" organisation unit. Any property on the sub-organisation unit will override the inherit value.

    If an organisation unit have no associated organisation unit group, the organisation unit can inherit its closest parent's organisation unit group. If none of the parent organisation unit groups have an organisation unit group for a given org unit group set, the result will still be "blank", but if at least one parent has an organisation unit group, sub-organisation unit will inherit it.

    include subhierarchy in analytics" is enabled, which means the org units inherit their closest parents org unit group IF the org unit is white (no org unit group associated with it).

  7. Select organisation unit groups and assign them.

    In the left-hand list, you find the available organisation unit groups. Use the arrows to move selected groups between the two lists.

    If there are no organisation unit groups in the left-hand list, click Add new. In the form that opens, create the organisation units group you need. When you're done, click Refresh values.

    [Note]Note

    An organisation unit can only be a member of a single organisation unit group within an organisation unit group set.

  8. Click Save.

Example 18.10. Classify facilities based on ownership

You want to analyse data based on the ownership of the facilities. All facilities have an owner so you need to make sure that all organisation units get this classification. To do that you can use the Compulsory option:

  1. Create a group for each ownership type, for example "MoH", "Private" and "Faith-based".

  2. Assign all facilities in the database to one of these groups.

  3. Create an organisation unit group set called "Ownership" and select Compulsory.

  4. Assign the organisation unit groups "MoH", "Private" and "Faith-based" to the "Ownership" organisation group set.


Example 18.11. Create parallel dynamic administrative organisation unit structure

Group you organisation unit in two ways and aggregate data on these two parallel hierarchies

Use to aggregate data (only in analytics apps)

An additional setting to the organisation unit group set, creates a dynamic "membership" to a organisation unit group set.


You don't change the organisation unit hierarchy

Scalable and dynamic

Dynamic inclusion of hierarchy

Dynamic additional classification

18.6.6. Assign names to organisation unit levels

When you add children to an organisation unit, DHIS2 automatically creates a new organisation unit level if necessary. The system also assigns a generic name to this level, for example "Level 5". You can replace the generic name with a contextual name, for example "Country", "Province", "District" or "Health Facility". DHIS2 uses the contextual names anywhere levels are referred to, for example in the GIS app.

  1. Open the Maintenance app and click Organisation unit > Organisation unit level.

    The loading time of the list depends on the depth of the organisation unit hierarchy tree.

  2. For the organisation unit levels you want to modify, type a name.

  3. Select the number of offline levels.

    [Note]Note

    You configure the default value in the System Settings app:

    Open the System Settings app, click General and select a level in the Max offline organisation unit levels list.

  4. Click Save.

18.6.7. Move organisation units within a hierarchy

You can move organisation units within in the hierarchy by changing the parent of a selected organisation unit.

  1. Open the Maintenance app and click Organisation unit > Hierarchy operations.

  2. In the left-hand hierarchy tree, select the organisation unit(s) you want to move.

    [Note]Note

    If the selected organisation unit is has sub-organisation units, all of them move to the new parent organisation unit.

  3. In the right-hand hierarchy tree, select which organisation unit you want to move the selected organisation unit(s) to.

  4. Click Move x organisation units, where x stands for the number of organisation units you have selected.

    Your changes are immediately reflected in the left-hand side hierarchy tree.

18.6.8. Close an organisation unit

When you close an organisation unit, you can't register or edit events to this organisation unit in the Event Capture and Tracker Capture apps.

  1. Open the Maintenance app and click Organisation unit > Organisation unit.

  2. In the object list, click the options menu and select Edit.

  3. Select a Closed date.

  4. Click Save.

18.6.9. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.6.10. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.6.11. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.6.12. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.6.13. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.7. [Work in progress] Manage validation rules

18.7.1. About validation rules

A validation rule is based on an expression. The expression defines a relationship between data element values. The expression forms a condition with certain logical criteria.

The expression consists of:

  • A left side

  • A right side

  • An operator

Example 18.12. 

A validation rule asserting that the total number of vaccines given to infants is less than or equal to the total number of infants.


In the Maintenance app, you manage the following validation rule objects:

Table 18.11. 

Object type

What you can do

Validation rule

Create, edit, clone, delete, show details, and translate

Validation rule group

Create, edit, clone, delete, share, show details, and translate

Validation notification

Create, edit, clone, delete, show details, and translate


18.7.1.1. About sliding windows

You can use sliding windows to group data across multiple periods as opposed to selecting data for a single period. Sliding windows have a size, that is to say, the number of days to cover, a starting point and an end point. The example below shows a sliding window that is customized to display weekly periods, a predicator, and an expression that compares the number of cases against the threshold of the period. Whenever the threshold is exceeded, a warning message displays.

Table 18.12. Different behavior of validation rules when you use or do not use sliding windows

With sliding windows

Without sliding windows

Used only for event data.

Used for event data and aggregate data.

Data selection is based on a fixed number of days (periodType).

Data selection is always based on a period.

The position of the sliding window is always relative to the period being compared.

Data is always selected for the same period as the period being compared.


See also: How to use sliding windows when you're Creating or editing a validation rule.

18.7.1.2. About validation rule groups

A validation rule group allows you to group related validation rules. When you run a validation rule analysis, you can choose to run all of the validation rules in your system, or just the validation rules in one group.

18.7.1.3. About validation notifications

You can configure a validation rule analysis to automatically send notifications about validation errors to selected user groups. These messages are called validation notifications. They are sent via the internal DHIS2 messaging system.

You can send validation rule notifications as individual messages or as message summaries. This is useful, for example, if you want to send individual messages for high-priority disease outbreaks, and summaries for low-priority routine data validation errors.

18.7.2. Create or edit a validation rule

  1. Open the Maintenance app and click Validation > Validation rule.

  2. Click the add button.

  3. Type a Name.

    The name must be unique among the validation rules.

  4. (Optional) In the Code field, assign a code.

  5. (Optional) Type a Description.

  6. Select an Importance: High, Medium or Low.

  7. Select a Period type.

  8. Select an Operator: Compulsory pair, Equal to, Exclusive pair, Greater than, Greater than or equal to or Not equal to.

    The Compulsory pair operator allows to require that data values must be entered for a form for both left and right sides of the expression, or for neither side. This means that you can require that if one field in a form is filled, then one or more other fields must also be filled.

    The Exclusive pair allows to assert that if any value exist on the left side then there should be no values on the right side (or vice versa). This means that data elements which compose the rule on either side should be mutually exclusive from each other, for a given time period / organisation unit /attribute option combo.

  9. Create the left side of the expression:

    1. Click Left side.

    2. Select Sliding window if you want to view data relative to the period you are comparing. See also About validation rules.

    3. Select a Missing value strategy. This selection sets how the system evaluates a validation rule if data is missing.

      Option

      Description

      Skip if any value is missing

      The validation rule will be skipped if any of the values which compose the expression are missing. This is the default option.

      Always select this option you use the Exclusive pair or Compulsory pair operator.

      Skip if all values are missing

      The validation rule will be skipped only if all of the operands which compose it are missing.

      Never skip

      The validation rule will never be skipped in case of missing data, and all missing operands will be treated effectively as a zero.

    4. Type a Description.

    5. Build an expression based on the available data elements, program objects, organisation units, counts and constants.

      In the right pane, double-click the data objects you want to include in the expression. Combine with the mathematical operators located below the left pane.

    6. Click Save.

  10. Create the right side of the expression:

    1. Click Right side.

    2. Select a Missing value strategy. This selection sets how the system evaluates a validation rule if data is missing.

      Option

      Description

      Skip if any value is missing

      The validation rule will be skipped if any of the values which compose the expression are missing. This is the default option.

      Always select this option you use the Exclusive pair or Compulsory pair operator.

      Skip if all values are missing

      The validation rule will be skipped only if all of the operands which compose it are missing.

      Never skip

      The validation rule will never be skipped in case of missing data, and all missing operands will be treated effectively as a zero.

    3. Select Sliding window if you want to view data relative to the period you are comparing. See also About validation rules.

    4. Type a Description.

    5. Build an expression based on the available data elements, program objects, organisation units, counts and constants.

      In the right pane, double-click the data objects you want to include in the expression. Combine with the mathematical operators located below the left pane.

    6. Click Save.

  11. Click Save.

18.7.3.  Create or edit a validation rule group

  1. Open the Maintenance app and click Validation > Validation rule group.

  2. Click the add button.

  3. Type a Name.

  4. (Optional) In the Code field, assign a code.

  5. (Optional) Type a Description.

  6. Double-click the Validation rules you want to assign to the group.

  7. Click Save.

18.7.4. Create or edit a validation notification

  1. Open the Maintenance app and click Validation > Validation notification.

  2. Click the add button.

  3. Type a Name.

  4. (Optional) In the Code field, assign a code.

  5. Select Validation rules.

  6. Select Recipient user groups.

  7. (Optional) Select Notify users in hierarchy only.

    If you select this option, the system will filter the recipient users. (The system derives the recipient users from the recipient user groups.) The filter is based on which organisation unit the recipient user belongs to. The users linked to organisation units which are ancestors of the organisation unit where the violation took place will receive validation notifications. The system will ignore other users and these users won't receive validation notifications.

  8. Create the message template:

    1. Create the Subject template.

      Double-click the parameters in the Template variables field to add them to your subject.

    2. Create the Message template.

      Double-click the parameter names in the Template variables field to add them to your message.

  9. Click Save.

18.7.5. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.7.6. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.7.7. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.7.8. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.7.9. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.8. Manage attributes

18.8.1. About attributes

You can use metadata attributes to add additional information to metadata objects. In addition to the standard attributes for each of these objects it may be useful to store information for additional attributes, for example the collection method for a data element.

In the Maintenance app, you manage the following attribute objects:

Table 18.13. Attribute objects in the Maintenance app

Object type

Available functions

Attribute

Create, edit, clone, delete, show details and translate


18.8.2. Create or edit an attribute

  1. Open the Maintenance app and click Attribute.

  2. Click the add button.

  3. In the Name field, type the name of the attribute.

    Each attribute must have a unique name

  4. (Optional) In the Code field, assign a code.

  5. Select a Value type.

    If the value supplied for the attribute does not match the value type you will get a warning.

  6. Select an Option set .

  7. Select the options you want, for example:

    • Select Mandatory if you want an object to always have the dynamic attribute.

    • Select Unique if you want the system to enforce that values are unique for a specific object type.

  8. Click Save.

    The dynamic attribute is now available for the objects you assigned it to.

18.8.3. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.8.4. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.8.5. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.8.6. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.9. Manage constants

18.9.1. About constants

Constants are static values which can be made available to users for use in data elements and indicators. Some indicators, such as "Couple year protection rate" depend on constants which usually do not change over time.

In the Maintenance app, you manage the following constant objects:

Table 18.14. Constant objects in the Maintenance app

Object type

Available functions

Constant

Create, edit, clone, share, delete, show details and translate


18.9.2. Create or edit a constant

  1. Open the Maintenance app and click Other > Constant.

  2. Click the add button.

  3. In the Name field, type the name of the constant.

  4. (Optional) In the Short name field, type an abbreviated name of the constant.

  5. (Optional) In the Code field, assign a code.

  6. In the Description field, type a brief, informative description of the constant.

  7. In the Value field, define the constant's value.

  8. Click Save.

    The constant is now available for use.

18.9.3. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.9.4. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.9.5. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.9.6. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.9.7. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.10. Manage option sets

18.10.1. About option sets

Option sets provide a pre-defined drop-down (enumerated) list for use in DHIS2. You can define any kind of options.

Example 18.13. 

An option set called "Delivery type" would have the options: "Normal", "Breach", "Caesarian" and "Assisted".


Table 18.15. Option set objects in the Maintenance app

Object type

Available functions

Option set

Create, edit, clone, share, delete, show details and translate


18.10.2. Create or edit an option set

[Important]Important

Option sets must have a code as well as a name. You can change the names but you can't change the codes. Both names and codes of all options must be unique, even across different option sets.

  1. Open the Maintenance app and click Other > Option set.

  2. Click the add button.

  3. In the Primary details tab, define the option set:

    1. In the Name field, type the name of the constant.

    2. In the Code field, assign a code.

    3. Select a Value type.

    4. Click Save.

  4. For each option you need, perform the following tasks:

    1. Click the Options tab.

    2. Click the add button.

    3. Type a Name and a Code.

    4. Sort the options by name, code/value or manually.

    5. Click Save.

18.10.3. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.10.4. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.10.5. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.10.6. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.10.7. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.11. Manage legends

18.11.1. About legends

You can create, edit, clone, delete, show details and translate legends to make the maps you're setting up for your users meaningful. You create maps in the GIS app.

[Note]Note

Continuous legends must consist of legend items that end and start with the same value, for example: 0-50 and 50-80. Do not set legend items like this: 0-50 and 51-80. This will create gaps in your legend.

18.11.2.  Create or edit a legend

[Note]Note

It is not allowed to have gaps in a legend.

It is not allowed to have overlapping legend items.

  1. Open the Maintenance app and click Other > Legend.

  2. Click the add button.

  3. In the Name field, type the legend name.

  4. (Optional) In the Code field, assign a code.

  5. Create the legend items you want to have in your legend:

    1. Select Start value and End value.

    2. Select Number of legend items.

    3. Select a color scheme.

    4. Click Create legend items.

    [Tip]Tip

    Click the options menu to edit or delete a legend item.

  6. (Optional) Add more legend items:

    1. Click the add button.

    2. Enter a name and select a start value, an end value and a color.

    3. Click OK.

  7. (Optional) Change the color scales.

    1. Click the colour scale to view a list of color scale options, and select a color scale.

    2. To customize a color scale, click the add button. In the Edit legend item dialog, click the color scale button and handpick colors, or enter your color values.

  8. Click Save.

Example 18.14. Vaccination coverage legends

Table 18.16. 

Legend itemStart valueEnd value
Low bad050
Medium5080
High good80100
Too high1001000


18.11.3. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.11.4. Change sharing settings for metadata objects

You can assign different sharing settings to metadata objects, for example organisation units and tracked entity attributes. These sharing settings control which users and users groups that can view or edit a metadata object.

[Note]Note

The default setting is that everyone (Public access) can find, view and edit metadata objects.

  1. Open the Maintenance app and find the type of metadata object you want to modify.

  2. In the object list, click the options menu and select Sharing settings.

  3. (Optional) Add users or user groups: search for a user or a user group and select it. The user group is added to the list.

  4. Change sharing settings for the users and user groups you want to modify.

    • Can edit and view: Everyone can view and edit the object.

    • Can view only: Everyone can view the object.

    • No access: The public won't have access to the object. This setting is only applicable to Public access.

  5. Click Close.

18.11.5. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.11.6. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.11.7. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.11.8. Assign a legend to indicator or data element

You can assign a legend to an indicator or a data element in the Maintenance app, either when you create the object or edit it. When you then select the indicator or data element in the GIS app, the system automatically selects the assigned legend.

18.11.9. See also

18.12. Manage predictors

18.12.1. About predictors

Predictors are data elements that are automatically generated from samples of current and past data. You use predictors to analyse previous data in order to predict future values, for example for disease surveillance.

A predictor specifies an expression and a set of sample constraints, identical to the implementation of validation rules. This includes a period type, organisation unit levels, and parameters specifying past or periodic sample windows. The expression should evaluate to true or false.

In the Maintenance app, you manage the following predictor objects:

Table 18.17. Predictor objects in the Maintenance app

Object type

Available functions

Predictor

Create, edit, clone, delete, show details and translate


18.12.2. Create or edit a predictor

  1. Open the Maintenance app and click Other > Predictor.

  2. Click the add button.

  3. In the Name field, type the predictor name.

  4. (Optional) In the Code field, assign a code.

  5. Select an Output data element.

  6. (Optional) Type a Description.

  7. Select a Period type.

  8. (Optional) Assign organisation unit levels.

  9. Create a Generator.

    The generator is the expression that is used to calculate the predicted value.

  10. (Optional) Click Sample skip test and create an expression which is used to exclude data from the generation process. The expression should evaluate to true or false.

    Example 18.15. 

    Use the sample skip test when you want to calculate the average number of malaria cases and you want to exclude the "spikes" you get from outbreaks.


  11. Enter a Sequential sample count value.

    This value decides for how many sequential periods the calculation should go back in time to collect data for the calculations. The sequential sample count depends on the value type.

    Example 18.16. 

    If the period type is "Monthly" and the sequential sample count is "3", the predictor calculations will include data three months back in time.


  12. Enter an Annual sample count value.

    This value decides for how many years the calculation should go back in time to collect data for the calculations. The annual sample count depends on the value type and sequential sample count.

    Example 18.17. 

    If the period type is "Monthly", the sequential sample count is "3" and the annual sample count is "4", the predictor calculations will include data three months back in time for this year and for two (3-1) years back in time:

    June, July, August 2016; June, July, August, 2015; and June, July, August 2014.


  13. (Optional) Enter a Sequential skip count value.

    This value decides how many periods the calculation should go back in time before the sequential sample count starts. The sequential skip count depends on the value type and sequential sample count.

    Example 18.18. 

    If the period type is "Monthly", the sequential sample count is "3" and the sequential sample count is " 2", the predictor calculations will go back two months in time, then include the following three months in the calculations:

    April, May and June (July and August are skipped because the sequential skip count is "2")


  14. Click Save.

18.12.3. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.12.4. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.12.5. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.12.6. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.13. Manage push reports

18.13.1. About push reports

Push reports allows you to increase awareness and usage of data analysis by sending reports with charts, tables and maps directly to users e-mail addresses.

  • A push report gets its content from existing dashboards.

  • A push report lists the dashboard items in the same order as on the dashboard.

  • A push report can only contain dashboard items with charts, maps or tables.

  • You create the push report and its schedule in the Maintenance app.

  • The Title and Message parameters you set up in the Maintenance app, are included in each report. The Name you give the report is not included in the report. Instead, the name is used to identify the push analysis object in the system. This way a report can be named one thing, and the title of the report can be another.

  • When you run a push report job, the system compiles a list of recipients from the user groups you've selected. The system then generates a report for each member of the selected user groups. Each of the dashboard items are generated specifically for each user. This means that the data included in the report reflects the data the user has access to. All users could therefore get the same report (if all the data is "static") or custom reports (if all the data is "dynamic"), or a combination of the two.

  • Push reports are sent by e-mail to the recipients, not through the internal DHIS2 messaging system. If a user doesn't have a valid e-mail, or if the job fails, no e-mails are sent. In this case, the problem is logged on the server.

[Note]Note

The data generated in the push reports is public so verify that you don't include any sensitive data.

Example 18.19. Push report


In the Maintenance app, you manage the following push reports objects:

Table 18.18. Push reports objects in the Maintenance app

Object type

Available functions

Push analysis

Create, edit, clone, delete, show details, translate, preview and run


18.13.2. Create or edit a push report

  1. Open the Maintenance app and click Other > Push analysis.

  2. Click the add button.

  3. In the Name field, type the name of the scheduled report.

    This name is not included in the report e-mail. Instead, the name is used to identify the push analysis object in the system.

  4. (Optional) In the Code field, assign a code.

  5. Add a report Title.

    This title is included in the report e-mail.

  6. (Optional) Add a Message.

    This message is included in the report e-mail.

  7. Select a Dashboard to base the report on.

  8. Select and assign the user groups you want to send the report to.

  9. Select a Scheduling frequency: Daily, Weekly or Monthly.

    [Note]Note

    If you schedule a push report to "Monthly" and "31", the scheduled report job will not run if the month has less than 31 days.

  10. (Optional) Select Enable to activate the push report job.

    The job won't run until you activate it.

  11. Click Save.

18.13.3. Preview push reports

  1. Open the Maintenance app and click Other > Push analysis.

  2. In the push report list, locate the push report you want to preview.

  3. Click the options menu and select Preview.

    A preview of the push report opens in a new window.

18.13.4. Run push report jobs

  1. Open the Maintenance app and click Other > Push analysis.

  2. In the push report list, locate the push report you want to run.

  3. Click the options menu and select Run now.

    The push report job runs immediately.

18.13.5. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.13.6. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.13.7. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.13.8. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.14. Manage external map layers

18.14.1. About external map layers

You can customize GIS by including map layers from various sources and combine them with your own data in DHIS2. DHIS2 supports common map service formats such as Web Map Service (WMS), Tile Map Service (TMS) and XYZ tiles.

18.14.2. Create or edit an external map layer

[Note]Note

DHIS 2 only supports the Web Mercator projection (EPSG:3857) so make sure that the external service supports this projection.

Table 18.19. External map layer objects in the Maintenance app

Object type

Available functions

External map layer

Create, edit, clone, delete, show details and translate


  1. Open the Maintenance app and click Other > External map layer.

  2. Click the add button.

  3. In the Name field, type a name that describes the content of the external map layer.

    This is the name you'll see in the GIS app.

  4. (Optional) In the Code field, assign a code.

  5. Select a Map service format.

    DHIS2 supports three common map service formats:

    • Web Map Service (WMS)

      Image format: PNG format allows layers to be transparent, JPG format offers better compression and is often faster to load.

      Layers: A WMS can contain several individual layers, and you can specify which you want to include (comma separated). Refer to the WMS GetCapabilities document to see the available layers.

    • Tile Map Service (TMS)

    • XYZ tiles (can also be used for WMTS)

  6. Enter the URL to the map service.

    [Note]Note

    XYZ and TMS URLs must contain placeholders {}, for example: http://{s}.tile.osm.org/{z}/{x}/{y}.png.

  7. (Optional) Enter Source of the map layers. The field can contain HTML tags if you want to link to the source.

    When you use an external map service it is important to highlight where the data comes from.

  8. Select a Placement:

    • Bottom - basemap: places the external map layer above other DHIS2 base maps but below the thematic map layers.

    • Top - overlay: places the external map layer above the thematic map layers but below facility and event data layers.

  9. (Optional) Add a legend.

    You can add a legend in two ways:

    • Select a predefined Legend to describe the colors of the map layer.

      [Tip]Tip

      Click Add new to create legends that you're missing. In the form that opens, create the legends you need. When you're done, click Refresh values.

    • Enter a link to an external image legend in Legend image URL.

      These are often provided for WMS. See under LegendURL in the WMS GetCapabilites document.

  10. Click Save.

18.14.3. Clone metadata objects

Cloning a data element or other objects can save time when you create many similar objects.

  1. Open the Maintenance app and find the type of metadata object you want to clone.

  2. In the object list, click the options menu and select Clone.

  3. Modify the options you want.

  4. Click Save.

18.14.4. Delete metadata objects

[Note]Note

You can only delete a data element and other data element objects if no data is associated to the data element itself.

[Warning]Warning

Any data set that you delete from the system is irrevocably lost. All data entry forms, and section forms which may have been developed will also be removed. Make sure that you have made a backup of your database before deleting any data set in case you need to restore it at some point in time.

  1. Open the Maintenance app and find the type of metadata object you want to delete.

  2. In the object list, click the options menu and select Delete.

  3. Click Confirm.

18.14.5. Display details of metadata objects

  1. Open the Maintenance app and find the type of metadata object you want to view.

  2. In the object list, click the options menu and select Show details.

18.14.6. Translate metadata objects

DHIS2 provides functionality for translations of database content, for example data elements, data element groups, indicators, indicator groups or organisation units. You can translate these elements to any number of locales. A locale represents a specific geographical, political, or cultural region.

[Tip]Tip

To activate a translation, open the System Settings app, click > Appearance and select a language.

  1. Open the Maintenance app and find the type of metadata object you want to translate.

  2. In the object list, click the options menu and select Translate.

    [Tip]Tip

    If you want to translate an organisation unit level, click directly on the Translate icon next to each list item.

  3. Select a locale.

  4. Type a Name, Short name and Description.

  5. Click Save.

18.15. Edit multiple object groups at once

The Metadata group editor in the Maintenance app allows you to edit multiple object groups at the same time. You can edit the following objects types:

Table 18.20. Object types in the Metadata group editor

Object type

Available functions

Category option

Category option group

Data element

Add one data element to multiple data element groups

Remove one data element from multiple data element groups

Data element group

Add multiple data elements to one data element group

Remove multiple data elements from one data element group

Indicator

Add one indicator to multiple indicator groups

Remove one indicator from multiple indicator groups

Indicator group

Add multiple indicators to one indicator group

Remove multiple indicators from one indicator group


18.15.1. Edit multiple objects in an object group

  1. Open the Maintenance app and click Metadata group editor.

  2. Click Manage items in group.

  3. Select an object group type, for example Indicator groups.

  4. Select an object group, for example HIV.

  5. In the left-hand list, select the object(s) you want to add to the object group and click the right arrow.

  6. In the right-hand list, select the object(s) you want to remove from the object group and click the left arrow.

18.15.2. Edit an object in multiple object groups

  1. Open the Maintenance app and click Metadata group editor.

  2. Click Manage groups for item.

  3. Select an object type, for example Indicators.

  4. Select an object, for example ANC LLITN coverage.

  5. In the left-hand list, select the objects group(s) you want to add the object to and click the right arrow.

  6. In the right-hand list, select the object group(s) you want to remove the object from and click the left arrow,

Chapter 19. Configure programs in the Maintenance app

19.1. About programs

Traditionally, public health information systems have been reporting aggregated data of service provision across its health programs. This does not allow you to trace the people provided with these services. In DHIS2, you can define your own programs with stages. These programs are a essential part of the "tracker" functionality which lets you track individual records. You can also track other ‘entities’ such as wells or insurances. You can create two types of programs:

Table 19.1. Program types

Program type

Description

Examples of use

Event program

Single event without registration program (anonymous program or SEWoR)

Anonymous, individual events are tracked through the health system. No person or entity is attached to these individual transactions.

Has only one program stage.

To record health cases without registering any information into the system.

To record survey data or surveillance line-listing.

Tracker program

Single event with registration program (SEWR)

An entity (person, commodity, etc.) is tracked through each individual transaction with the health system

Has only one program stage.

A tracked entity instance (TEI) can only enroll in the program once.

To record birth certificate and death certificate.

Multi events with registration program (MEWR)

An entity (person, commodity, etc.) is tracked through each individual transaction with the health system

Has multiple program stages.

Mother Health Program with stages as ANC Visit (2-4+), Delivery, PNC Visit.


To create a program, you must first configure several types of metadata objects. You create these metadata objects in the Maintenance app or the Program / Attributes (legacy) app.

Table 19.2. Program metadata objects in the Maintenance app

Object type

Description

Available functions

Event program

A program to record single event without registration

Create, edit, share, delete, show details and translate

Program indicator

An expression based on data elements and attributes of tracked entities which you use to calculate values based on a formula.

Create, edit, share, delete, show details and translate

Program rule

Allows you to create and control dynamic behavior of the user interface in the Tracker Capture and Event Capture apps.

Create, edit, delete, show details and translate

Program rule variable

Variables you use to create program rule expressions.

Create, edit, delete, show details and translate

Relationship type

Defines the relationship between tracked entity A and tracked entity B, for example mother and child.

Create, edit, clone, delete, show details and translate

Tracked entity

Types of entities which can be tracked through the system. Can be anything from persons to commodities, for example a medicine or a person.

A program must have one tracked entity. To enrol a tracked entity instance into a program, the tracked entity of an entity and tracked entity of a program must be the same.

[Note]Note

A program must be specified with only one tracked entity. Only tracked entity as same as the tracked entity of program can enroll into that program.

Create, edit, clone, delete, show details and translate

Tracked entity attribute

Used to register extra information for a tracked entity.

Can be shared between programs.

Create, edit, clone, share, delete, show details and translate


Table 19.3. Program metadata objects in the Program / Attributes app

Object type

Description

Available functions

Program

A program consist of program stages.

Create, edit, share, delete, assign to organisation units, show details and translate

Program stage

A program stage defines which actions should be taken at each stage.

Create, edit, change sort order, delete, show details and translate

Program stage section

N/A

Create, edit, change sort order, delete, show details and translate

Program indicator group

A group of program indicators

Create, edit, delete, show details and translate

Validation rule

A validation rule is based on an expression which defines a relationship between data element values.

Create, edit and delete

Program notification

Automated message reminder

Set reminders to be automatically sent to enrolled tracked entity instances before scheduled appointments and after missed visits.

Create, edit and delete

Program stage notification

-

Create, edit and delete

Design custom registration form

-

-


19.2. Configure event programs in the Maintenance app

19.2.1. About event programs

Single event without registration programs are called event programs. You configure them in the Maintenance app. Event programs can have three types of data entry forms:

Table 19.4. Types of data entry forms for event programs

Form type

Description

Basic

Lists all data elements which belong to the program. You can change the order of the data elements.

Section

A section groups data elements. You can then arrange the order of the sections to create the desired layout of the data entry form.

Custom

Defines the data entry form as HTML page.


[Note]Note
  • Custom forms takes precedence over section forms if both are present.

  • If no custom or section form are defined, the basic form will be used.

  • The Android apps only supports section forms.

You can create program notifications for event programs. The notifications are sent either via the internal DHIS2 messaging system, via e-mail or via text messages (SMS). You can use program notifications to, for example, send an automatic reminder to a tracked entity 10 days before a scheduled appointment. You use the program’s tracked entity attributes (for example first name) and program parameters (for example enrollment date) to create a notification template. In the Parameters field, you'll find a list of available tracked entity attributes and program parameters.

19.2.2. Workflow: Create an event program

  1. Enter the event program details.

  2. Assign data elements.

  3. Create data entry form(s): Basic, Section or Custom.

  4. Assign the program to organisation unit(s).

  5. Create program notification(s).

19.2.3. Create or edit an event program

19.2.3.1. Enter event program details

  1. Open the Maintenance app and click Program > Program.

  2. Click the add button.

  3. Enter program details, then click next.

    Field

    Description

    Name

    The name of the program.

    Short name

    A short name of the program. The short name is used as the default chart or table title in the analytics apps.

    Description

    A detailed description of the program.

    Version

    The version of the program. This is used for example when people collect data offline in an Android implementation. When they go online and synchronize their metadata, they should get the latest version of the program.

    Category combination

    The category combination you want to use. The default setting is None.

    Data approval workflow

    The data approval workflow you want to use. The default setting is No value.

    Completed events expiry date

    Defines the number of days for which you can edit a completed event. This means that when an event is completed and the specified number of expiry days has passed, the event is locked.

    Example 19.1. 

    If you set "Completed events expiry days" to 10", an event is locked ten days after the completion date. After this date you can no longer edit the event.


    Expiry period type

    Expiry days

    The expiry days defines for how many days after the end of the previous period, an event can be edited. The period type is defined by the expiry period type. This means that when the specified number of expiry days has passed since the end date of the previous period, the events from that period are locked.

    Example 19.2. 

    If you set the expiry type to "Monthly" and the expiry days to "10" and the month is October, then you can't add or edit an event to October after the 10th of November.


  4. Click next.

19.2.3.2. Assign data elements

  1. Click Assign data elements.

  2. In the list of available items, double-click the data elements you want to assign to the event program.

  3. (Optional) For each data element, add additional settings:

    Setting

    Description

    Compulsory

    The value of this data element must be filled into data entry form before you can comple the event.

    Allow provided elsewhere

    Specify if the value of this data element comes from other facility, not in the facility where this data is entered.

    Display in reports

    Displays the value of this data element into the single event without registration data entry function.

    Date in future

    Will allow user to select a date in future for date data elements.

    Render option as radio

    Displays a radio button in the data entry form. It's only possible to use for option sets.

  4. Click next.

19.2.3.3. Create data entry forms

The data entry forms decide how the data elements will be displayed to the user in the Event Capture app.

  1. Click Create data entry form.

  2. Click Basic, Section or Custom.

  3. To create a Basic data entry form: Drag and drop the data elements in the order you want.

  4. To create a Section data entry form:

    1. Click the add button and enter a section name.

    2. Click the section so it's highlighted by a black line.

    3. Add data elements by clicking the plus sign next to the data elements' names.

    4. Repeat above steps until you've all the sections you need.

    5. Change the section order: click the options menu, then drag the section to the place you want.

  5. To create a Custom data entry from: Use the WYSIWYG editor to create a completely customized form. If you select Source, you can paste HTML code directly in the editing area. You can also insert images for example flags or logos.

  6. Click next.

19.2.3.4. Assign organisation units

  1. Click Assign organisation units.

  2. In the organisation tree, double-click the organisation units you want to add to the program to.

    You can locate an organisation unit in the tree by expanding the branches (click on the arrow symbol), or by searching for it by name. The selected organisation units display in orange.

  3. Click next.

19.2.3.5. Create program notifications

  1. Create the message you want to send:

    1. Click What to send?.

    2. Enter a Name.

    3. Create the Subject template: Double-click the parameters in the Template variables field to add them to your subject.

      [Note]Note

      The subject is not included in text messages.

    4. Create the Message template: Double-click the parameter names in the Template variables list to add them to your message.

      Example 19.3. 

      Dear A{w75KJ2mc4zz}, You're now enrolled in V{program_name}.


  2. Define when you want to send the message:

    1. Click When to send it?.

    2. Select a Notification trigger.

      Notification trigger

      Description

      Program stage completion

      The program stage notification is sent when the program stage is completed

      Days scheduled (due date)

      The program stage notification is sent XX number of days before or after the due date

      You need to enter the number of days before or after the scheduled date that the notification will be send.

  3. Define who you want to send the message to:

    1. Click Who to send it to?.

    2. Select a Notification recipient.

      Notification recipient

      Description

      Tracked entity instance

      Receives program notifications via e-mail or text message.

      To receive a program notification, the recipient must have an e-mail address or a phone number attribute.

      Organisation unit contact

      Receives program notifications via e-mail or text message.

      To receive a program notification, the receiving organisation unit must have a registered contact person with e-mail address and phone number.

      Users at organisation unit

      All users registered to the selected organisation unit receive program notifications via the internal DHIS2 messaging system.

      User group

      All members of the selected user group receive the program notifications via the internal DHIS2 messaging system

      Program

      TBA

    3. Click Save.

  4. Repeat above steps to create all the program notifications you need.

  5. Click Save.

[Note]Note

You configure when the program notifications are sent in the Data Administration app > Scheduling > Program notifications scheduler.

  • Click Run now to send the program notifications immediately.

  • Select a time and click Start to schedule the program notifications to be send at a specific time.

19.2.4. Reference information: Program notification parameters

Table 19.5. Program notification parameters to use in program notifications

Notification type

Variable name

Variable code

Program

Current date

V{current_date}

Days since enrollment date

V{days_since_enrollment_date}

Enrollment date

V{enrollment_date}

Incident date

V{incident_date}

Organisation unit name

V{org_unit_name}

Program name

V{program_name}

Program stage

Current date

V{current_date}

Days since due date

V{days_since_due_date}

Days until due date

V{days_until_due_date}

Due date

V{due_date}

Organisation unit name

V{org_unit_name}

Program name

V{program_name}

Program stage name

V{program_stage_name}


19.3. Configure tracker programs in the Maintenance app

[Note]Note

From release 2.27, you create event programs (programs without registration) in the Maintenance app. You still create tracker programs (programs with registration) in the Program / Attributes app.

19.4. Configure program indicators

19.4.1. About program indicators

Program indicators are expressions based on data elements and attributes of tracked entities which can be used to calculate values based on a formula. Program indicators consist of an aggregation type, an analytics type, an expression and a filter.

Program indicators are evaluated based on the assigned aggregation type, expression and filter. The order of evaluation is:

  1. The filter will filter the events which become part of the evaluation/aggregation routine.

  2. The expression will be evaluated per event.

  3. All evaluated expression values will be aggregated according to the aggregation type of the program indicator.

Table 19.6. Program indicator components

Program rule component

Description

Aggregation type

The aggregation type determines how the program indicator will be aggregated. The following aggregation types are available:

  • Average

  • Average (number)

  • Average (number, disaggregation)

  • Average (sum in organisation unit hierarchy)

  • Average (sum of numbers)

  • Average (sum of numbers, disaggregation)

  • Average (Yes/No)

  • Count

  • Custom

    The "custom" aggregation type allows you to specify the aggregation type in-line in the expression. All other aggregation types are applied to the entire expression.

    Using the "custom" aggregation type might lead to an exception of the order of evaluation described above where individual parts of the expression can be evaluated and aggregated, as opposed to the entire expression being evaluated prior to aggregation.

  • Default

  • Max

  • Min

  • None

  • Standard deviation

  • Sum

  • Variance

Analytics type

The available analytics types are event and enrollment.

The analytics type defines whether the program indicator is calculated based on events or program enrollments. This has an impact on what type of calculations can be made.

  • Events implies a data source where each event exists as an independent row. This is suitable for performing aggregations such as counts and sums.

  • Enrollments implies a data source where all events for a single enrollment is combined on the same row. This allows for calculations which can compare event data from various program stages within a program enrollment.

Expression

The expression defines how the indicator is being calculated. The expression can contain references to various entities which will be substituted with a related values when the indicator is calculated:

  • Data elements: Will be substituted with the value of the data element for the time period and organisation unit for which the calculation is done. Refers to both program stage and data element.

  • Attributes: Will be substituted with the value of the attribute for the person / tracked entity for which the calculation is done.

  • Variables: Will be substituted with special values linked to the program, including incident date and date of enrollment for the person, current date and count of values in the expression for the time period and organisation unit for which the calculation is done.

  • Constants: Will be substituted with the value of the constant.

The expression is a mathematical expression and can also contain operators.

For single event programs and tracker programs with analytics type event, the expression will be evaluated per event , then aggregated according to its aggregation type.

For tracker programs with analytics type enrollment, the expression will be evaluated per enrollment, then aggregated according to its aggregation type.

Filter

The filter is applied to events and filters the data source used for the calculation of the indicator. I.e. the filter is applied to the set of events before the indicator expression is being evaluated. The filter must evaluate to either true or false. It filter is applied to each individual event. If the filter evaluates to true then the event is included later in the expression evaluation, if not it is ignored. The filter can, in a similar way as expressions, contain references to data elements, attributes and constants.

The program indicator filter can in addition use logical operators. These operators can be used to form logical expressions which ultimately evaluate to either true or false. For example you can assert that multiple data elements must be a specific value, or that specific attributes must have numerical values less or greater than a constant.


In the Maintenance app, you manage the following program indicator objects:

Object type

Available functions

Program indicator

Create, edit, clone, share, delete, show details and translate

Program indicator group

Create, edit, clone, share, delete, show details and translate

19.4.2. Create or edit a program indicator

[Note]Note

A program indicator belongs to exactly one program.

  1. Open the Maintenance app and click Indicator > Program indicator.

  2. Click the add button.

  3. Select a Program and enter:

    • Name

    • Short name

    • Code

    • Description

  4. Select number of Decimals in data output.

  5. Select an Aggregation type.

  6. Select a if you want to Display in form.

  7. Assign one or multiple Legends.

  8. (Optional) Enter a Category option combination for aggregate data export.

  9. (Optional) Enter an Attribute option combination for aggregate data export.

  10. Create the expression.

    1. Click Edit expression.

    2. Create the expression based on mathematical operators and the attributes, variables and constants listed to the right.

  11. Create the filter.

    1. Click Edit filter.

    2. Create the expression based on mathematical operators and the attributes, variables and constants listed to the right.

  12. Click Save.

19.4.3. Create or edit a program indicator group

  1. Open the Maintenance app and click Indicator > Program indicator group.

  2. Click the add button.

  3. Enter Name and Code.

  4. In the list of available program indicators, double-click the program indicators you want to assign to your group.

  5. Click Save.

19.4.4. Reference information: Expression and filter examples per value type

The table below shows examples of how to write expressions and filters for different data element and attribute value types:

Table 19.7. Expression and filter examples per value type

Value typesExample syntax

Integer

Negative integer

Positive or zero integer

Positive integer

Number

Percentage

Numeric fields, can be used for aggregation as an expression, or in filters:

#{mCXR7u4kNBW.K0A4BauXJDl} >= 3

Yes/No

Yes only

Boolean fields. Yes is translated to numeric 1, No to numeric 0. Can be used for aggregation as an expression, or in filters:

#{mCXR7u4kNBW.Popa3BauXJss} == 1

Text

Long text

Phone number

Email

Text fields. Can be checked for equality in filters:

#{mCXR7u4kNBW.L8K4BauIKsl} == 'LiteralValue'

Date

Age

Date fields. Most useful when combined with a d2:daysBetween function, which produces a number that can be aggregated as an expression or used in filters:

d2:daysBetween(#{mCXR7u4kNBW.JKJKBausssl},V{enrollment_date}) > 100

Can also directly be checked for equality in filters:

#{mCXR7u4kNBW.JKJKBausssl} == '2011-10-28'

Date

Age

Date fields. Most useful when combined with a d2:daysBetween function, which produces a number that can be aggregated as an expression or used in filters:

d2:daysBetween(#{mCXR7u4kNBW.JKJKBausssl},V{enrollment_date}) > 100

Can also directly be checked for equality in filters:

#{mCXR7u4kNBW.JKJKBausssl} == '2011-10-28'


19.4.5. Reference information: Functions, variables and operators to use in program indicator expressions and filters

Example 19.4. 

An expression that includes both attributes, data elements and constants looks like this:

(A{GPkGfbmArby} + #{mCXR7u4kNBW.NFkjsNiQ9PH}) * C{bCqvfPR02Im}


Example 19.5. 

An expression which uses the custom aggregation type and hence can use inline aggregation types looks like this:

(sum(#{mCXR7u4kNBW.K0A4BauXJDl} * #{mCXR7u4kNBW.NFkjsNiQ9PH}) / sum(#{mCXR7u4kNBW.NFkjsNiQ9PH})) * 100

Note how the "sum" aggregation operator is used inside the expression itself.


19.4.5.1. Functions to use in a program indicator expression or filter

The program indicator expression and filter support a range of functions. The functions can be applied to data elements and attributes:

Table 19.8. Functions to use in a program indicator expression or filter

Function

Arguments

Description

d2:hasValue

(object)

Returns true if the data element/attribute has a value. Can be used in filters to distinguish between the number 0 and no value, and to distinguish between exlicit "No" and no selection for a Yes/No field.

d2:daysBetween

(date, date)

Produces the number of days between two data elements/attributes of type date. The static date format is 'yyyy-MM-dd'.

d2:weeksBetween

(date, date)

Produces the number of full weeks between two data elements/attributes of type date. The static date format is 'yyyy-MM-dd'.

d2:monthsBetween

(date, date)

Produces the number of full months between two data elements/attributes of type date. The static date format is 'yyyy-MM-dd'.

d2:yearsBetween

(date, date)

Produces the number of full years between two data elements/attributes of type date. The static date format is 'yyyy-MM-dd'.

d2:condition

(boolean-expr, true-val, false-val)

Evaluates the conditional expression and if true returns the true value, if false returns the false value. The conditional expression must be quoted.

d2:zing

(number)

Evaluates the data element/attribute of type number to zero if the value is negative, otherwise to the value itself.

d2:oizp

(number)

Evaluates the data element/attribute of type number to one if the value is zero or positive, otherwise to zero.

d2:zpvc

(object, [,object, object,...])

Returns the number of numeric zero and positive values among the given object arguments. Can be provided any number of arguments.


Example 19.6. 

A filter that uses the "hasValue" function looks like this: this:

d2:hasValue(#{mCXR7u4kNBW.NFkjsNiQ9PH})


Example 19.7. 

An expression that uses the "zing" and "oizp" functions looks like this:

d2:zing(A{GPkGfbmArby}) + d2:oizp(#{mCXR7u4kNBW.NFkjsNiQ9PH}))


Example 19.8. 

An expression that uses the "daysBetween" function looks like this:

d2:daysBetween(#{mCXR7u4kNBW.k8ja2Aif1Ae},'2015-06-01')


Example 19.9. 

An expression that uses the "condition" function looks like this:

d2:condition('#{mCXR7u4kNBW.NFkjsNiQ9PH} > 100',150,50)


Example 19.10. 

An expression that uses the "zpvc" function looks like this:

d2:zpvc(A{GPkGfbmArby}),#{mCXR7u4kNBW.NFkjsNiQ9PH}),4,-1)


19.4.5.2. Variables to use in a program indicator expression or filter

The program indicator expression and filter support a range of variables:

Table 19.9. Variables to use in a program indicator expression or filter

Variable

Description

event_date

The date of when the event took place.

due_date

The date of when an event is due.

incident_date

The date of the incidence of the event.

enrollment_date

The date of when the tracked entity instance was enrolled in the program.

enrollment_status

Can be used to include or exclude enrollments in certain statuses.

Example 19.11. 

When calculating the hemoglobin improvement/deterioration throughout a pregnancy, it might make sense to only consider completed enrollments. If non-completed enrollments is not filtered out, these will represent half-finished ANC followups, where the final improvement/deterioration is not yet established.


current_date

The current date.

value_count

The number of non-null values in the expression part of the event.

zero_pos_value_count

The number of numeric positive values in the expression part of the event.

event_count

The count of events (useful in combination with filters).

enrollment_count

The count of enrollments (useful in combination with filters).

tei_count

The count of tracked entity instances (useful in combination with filters).

program_stage_name

Can be used in filters for including only certain program stages in a filter for tracker programs. Uses the name of the program stage:

V{program_stage_name} == 'ANC first visit'

program_stage_id

Can be used in filters for including only certain program stages in a filter for tracker programs. Uses the unique identifier of the program stage:

V{program_stage_id} == 'YPSSfbmAtt1'


Example 19.12. 

An expression that uses the "value count" variable looks like this:

(#{A03MvHHogjR.a3kGcGDCuk6} + #{A03MvHHogjR.wQLfBvPrXqq}) / V{value_count}


Example 19.13. 

An expression that uses the "event_date" and "incident_date" variables looks like this:

d2:daysBetween(V{incident_date},V{event_date})


19.4.5.3. Operators to use in a program indicator filter

Table 19.10. Operators to use in a program indicator filter

Operator

Description

and

Logical AND

or

Logical OR

==

Equal to

!=

Not equal to

<

Less than

<=

Less than or equal to

>

Greater than

>=

Greater than or equal to


These operators can be used to form logical expressions which ultimately evaluate to either true or false. For example you can assert that multiple data elements must be a specific value, or that specific attributes must have numerical values less or greater than a constant.

Example 19.14. 

A filter that uses both attributes and data elements looks like this:

A{cejWyOfXge6} == 'Female' and #{A03MvHHogjR.a3kGcGDCuk6} <= 2


[Tip]Tip

DHIS2 is using the JEXL library for evaluating expressions which supports additional syntax beyond what is covered in this documentation. See the reference at the project home page to learn how you can create more sophisticated expressions

19.5. Configure program rules

19.5.1. About program rules

Program rules allows you to create and control dynamic behavior of the user interface in the Tracker Capture and Event Capture apps. During data entry, the program rules expressions are evaluated each time the user interface is displayed, and each time a data element is changed. Most types of actions will take effect immediately when the user enters values in the Tracker Capture and Event Capture apps.

Table 19.11. Program rule components

Program rule component

Description

Program rule action

Each program rule contains one or multiple actions. These are the behaviors that are triggered in the user interface when the expression is true. Actions will be applied at once if the expression is true, and will be reverted if the expression is no longer true. There are several types of actions and you can have several actions in one program rule.

Program rule expression

Each program rule has a single expression that determines whether the program rule actions should be triggered, if the expression evaluates to true. If the expression is true the program rule is in effect and the actions will be executed. If the expression is false, the program rule is no longer in effect and the actions will no longer be applied.

You create the expression with standard mathematical operators, custom functions, user-defined static values and program rule variables. The program rule variables represent attribute and data element values which will be evaluated as part of the expression.

Program rule variable

Program rule variables lets you include data values and attribute values in program rule expressions. Typically, you'll have to create one or several program rule variables before creating a program rule. This is because program rules expressions usually contain at least one data element or attribute value to be meaningful.

The program rule variables are shared between all rules in your program. When you create multiple program rules for the same program, these rules will share the same library of program rule variables.


In the Maintenance app, you manage the following program rule objects:

Object type

Available functions

Program rule

Create, edit, clone, delete, show details and translate

Program rule variable

Create, edit, clone, share, delete, show details and translate

19.5.2. Workflow

  1. In the Maintenance app, create program rule variable(s) if needed.

  2. In the Maintenance app, create the program rule:

    1. Enter the program rule details.

    2. Create the program rule expression.

    3. Define the program rule actions.

  3. In the Tracker Capture or Event Capture apps, verify that the program rule behaves as expected.

19.5.3. Create or edit a program rule variable

  1. Open the Maintenance app and click Program > Program rule variable.

  2. Click the add button.

  3. Select a Program and enter a Name.

  4. Select if you want to Use code for option set.

    This option is only effective when the data element or tracked entity attribute is connected to an option set. If you don't select this option, the program rule variable will be populated with the option set's name. If you select the option, the program rule variable will be populated with the option set's code instead.

  5. Select a Source type and enter the required information.

    Depending on the source type, you'll have to select, for example, a Program stage, Data element or Tracked entity attribute.

    The source types determine how the program rule variable is populated with a value.

    Source type

    Description

    Data element from the newest event for a program stage

    This source type works the same way as Data element from the newest event in the current program, except that it only evaluates values from one program stage.

    This source type can be useful in program rules where the same data element is used in several program stages, and a rule needs to evaluate the newest data value from within one specific stage.

    Data element from the newest event in the current program

    This source type is used when a program rule variable needs to reflect the newest known value of a data element, regardless of what event the user currently has open.

    This source type is populated slightly differently in Tracker Capture and Event Capture apps:

    Tracker Capture: the program rule variable will be populated with the newest data value collected for the given data element within the enrollment.

    Event Capture: the program rule variable will be populated with the newest data value found within the 10 newest events in the same organisation unit.

    The newest data value is determined with event date.

    Data element in current event

    Program rule variables with this source type will contain the data value from the same event that the user currently has open.

    This is the most commonly used source type, especially for skip logic (hide actions) and warning/error rules.

    Data element from previous event

    Program rule variables with this source type will contain the value from a specified data element from a previous event. Only older events is evaluated, not including the event that the user currently has open.

    This source type is commonly used when a data element only should be collected once during an enrollment, and should be hidden in subsequent events.

    Another use case is making rules for validating input where there is an expected progression from one event to the next - a rule can evaluate whether the previous value is higher/lower and give a warning if an unexpected value is entered.

    This source type is populated slightly differently in Tracker Capture and Event Capture apps:

    Tracker Capture: the program rule variable will be populated with the newest data value collected for the given data element within the enrollment - but only evaluating the events that comes before the current event date.

    Event Capture: the program rule variable will be populated with the newest data value collected within the 10 events preceding the current event date - not including the current event.

    The newest data value is determined with event date.

    Calculated value

    TBA

    Tracked entity attribute

    Populates the program rule variable with a specified tracked entity attribute for the current enrollment.

    Use this is the source type to create program rules that evaluate data values entered during registration.

    This source type is also useful when you create program rules that compare data in events to data entered during registration.

    This source type is only used for tracker programs (programs with registration).

  6. Click Save.

19.5.4. Create or edit a program rule

[Note]Note

A program rule belongs to exactly one program.

  1. Open the Maintenance app and click Program > Program rule.

  2. Click the add button.

  3. Enter the program rule details. These fields are not shown to the end user, they are only meant for the program administrator.

    • Program

    • Name

    • Description

    • Priority

      Example 19.15. 

      Let's say you have 16 program rules in your program. You configure the program rules with the following priority settings:

      • Priority 1 for program rule A

      • Priority 2 for program rules B - K

      • No priority for program rules L - P

      Result: the system runs the program rules in the following order:

      1. Program rule A

      2. Program rules B - K (you can't find out or configure in which order the system runs these program rules)

      3. Program rules L - P.


  4. Click Enter program rule expression and create the program rule expression with the help of variables, functions and operators.

  5. Click Define program rule actions and create the actions executed when the expression is true.

    1. Click the add button, select an Action and enter the required information.

      Depending on the action type, you'll have to perform different types of settings. For some action types, you must also enter free text or create expressions.

      Action type

      Required settings

      Description

         

      Assign value

      Data element to assign value to

      Program rule variable to assign value to

      Expression to evaluate and assign

      Used to help the user calculate and fill out fields in the data entry form. The idea is that the user shouldn’t have to fill in values that the system can calculate, for example BMI.

      When a field is assigned a value, the user sees the value but the user can't edit it.

      Example from Immunization stock card i Zambia: The data element for vaccine stock outgoing balance is calculated based on the data element for incoming stock balance minus the data elements for consumption and wastage.

      Advanced use: configure an 'assign value' to do a part of a calculation and then assign the result of the calculation to a program rule variable. This is the purpose with the "Calculated value" program rule variable.

      Display text

      Display widget

      Static text

      Expression to evaluate and display after static text

      Used to display information that is not an error or a warning, for example feedback to the user. You can also use this action to display important information, for example the patient's allergies, to the user.

      Display key/value pair

      Display widget

      Key label

      Expression to evaluate and display as value

      Used to display information that is not an error or a warning.

      Example: calculate number of weeks and days in a pregnancy and display it in the format the clinician is used to see it in. The calculation is based on previous recorded data.

      Error on complete

      Data element to display error next to

      Tracked entity attribute to display error next to

      Static text

      Expression to evaluate and display after static text

      Used whenever you've cross-consistencies in the form that must be strictly adhered to. This action prevents the user from continuing until the error is resolved.

      This action differs from the regular Show error since the error is not shown until the user tries to actually complete the form.

      If you don't select a data element or a tracked entity attribute to display the error next to, make sure you write a comprehensive error message that helps the user to fix the error.

      Hide field

      Data element to hide

      Tracked entity attribute to hide

      Custom message for blanked field

      Used when you want to hide a field from the user.

      Custom message for blanked field allows you to define a custom message displayed to the user in case the program rule hides and blanks out the field after the user typed in or selected a value.

      If a hide field action hides a field that contains a value, the field will always removed. If no message is defined, a standard message will be displayed to alert the user.