1. Data quality in data demand and use
Comprehensive Training to support the National Integrated TB/HIV Information System Implementation
Data quality in data demand and use

2. DHMIS policy data quality principles
The TB Patient's Journey through the Revised Data Collection tools
January 2008
DHMIS policy data quality principles
Data Quality
Relevance
Integrity
Timeliness
Accessibility
Reliability
Completeness
Accuracy
Coherence and comparability
8 dimensions of data quality
Relevance
To ensure relevance of all indicators and data elements, NDoH engages a broad range of stakeholders at all levels of health system,
National Health Information Systems Committee of South Africa (NHISSA) is used as a framework for the structured consultation process to select indicators and data elements
Integrity
values and related practices that maintain the confidence users have in the information itself
The information unit at each level is responsible for validating the integrity of data for each level
Timeliness
Significant delays in data collection, conversion into information or data submission compromise the value of the data for decision-making purposes
See data flow timelines
Accessibility
ease with which users can obtain the information
Reliability
data should be analyzed at all levels with purpose of identifying establishments with unstable data, and thus unstable service delivery
Completeness
All levels of health system should implement mechanisms for verifying the completeness and consistency of data
District Health managers and Provincial HOD should ensure that all health establishments submit complete data
Accuracy
All facility managers shall be responsible for ensuring that data accuracy assessments are conducted in each facility, comparing tally sheets, registers and/or patient folders with the summary data and applying data validation rules before data is submitted for capturing.
The NDoH shall incorporate relevant data validation rules for the NIDS into the NIDS and into the National data Dictionary
Coherence and comparability
Coherence of information is the degree to which it can be successfully brought together with other similar information from different sources within a broad analytical framework overtime
Comparability of information is the ability to compare data on the same characteristics between different points in time and geographical areas
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

3. The TB Patient's Journey through the Revised Data Collection tools
January 2008
Data quality tools
WHO Data Quality Tool
Integrated audit tool
Site visit task list
Maintenance tools
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

4. WHO Data Quality Tool (1)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (1)
Tool supports automated identification of data quality and completeness issues
The tool looks at data quality by focusing on
Consistency over time
Outliers
Missing data
The tool does not only displays potential errors, but also contributes to improved understanding of the data quality
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

5. WHO Data Quality Tool (2)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (2)
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

6. WHO Data Quality Tool (3)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (3)
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

7. WHO Data Quality Tool (4)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (4)
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

8. WHO Data Quality Tool (5)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (5)
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

9. WHO Data Quality Tool (6)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (6)
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

10. WHO Data Quality Tool (7)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (7)
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

11. WHO Data Quality Tool (8)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (8)
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

12. WHO Data Quality Tool (9)
The TB Patient's Journey through the Revised Data Collection tools
January 2008
WHO Data Quality Tool (9)
CM – Change Management
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

13. The TB Patient's Journey through the Revised Data Collection tools
January 2008
Exercise #4
WHO Data Quality Tool
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

14. The TB Patient's Journey through the Revised Data Collection tools
January 2008
Exercise – 30 min (1)
DHIS WHO DQ Tool
Training participants to split into their respective districts
At least one member of the district should have webDHIS login details
Districts to go through their own district data
Log into webDHIS
Go to “Apps”
Click on the “WHO DQ Tool” App
Participants can sit in their groups and only need one computer with webDHIS log in details and follow the necessary steps
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

15. The TB Patient's Journey through the Revised Data Collection tools
January 2008
Exercise – 30 min (2)
Pull the “Outlier and Missing data” table for the district, disaggregated by facility
Under “Indicator” select ‘Total remain on ART’
For period 1 January 2018 to 31 August 2018
Under “Boundary” select your District
Under “Disaggregation” select “Facility”
Click on “Analyze”
Repeat the same process, but for an indicator of your choice
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

16. The TB Patient's Journey through the Revised Data Collection tools
January 2008
Exercise – 30 min (3)
What are your top 3 findings from reviewing the outliers and missing data?
How can you address identified issues?
How can you institutionalise this tool in your routine data review activities?
Training package for Revised TB data Collection Tools developed by the National TB Control Programme

17. Thank you