1. DATA QUALITY AND VERIFICATION
Nirvasha Moodley
KwaZulu-Natal
South Africa

2. CONTRIBUTING FACTORS Non standardized collection tools
Patient held record
Large volumes of data
No dedicated data clerk at clinic level
Poor registry
Lack of supervision and unaccountability
Low morale/ Lack of information culture/poor attitude
1. 15% increase in population, but
2. 80% increase in PHC headcount (total attendance)
3. 10% more public health facilities – but shift to sub-facility (level 6) reporting means going from 750 to over 35,000 reporting units.
4. The number of routine data records have gone up from under 300,000 to over 20 million per year
5. Facility data coverage is close to 100% and average data capture time has come down from around 30 to less than 10 days.
6. Data clean-up and verification take considerable time, but deadline for submission to national is steadily decreasing.
PEPFAR’S DEMAND FOR DATA WITHIN 15 DAYS DO NOT PROVIDE SUFFICIENT TIME FOR DATA QUALITY ASSURANCE!

3. What have we done so far? Rationalisation of Registers clinics ( 56 7)
Implementation of Facility held Patient records in 3 NHI districts (156 facilities)
Implementation of WEB DHIS at connected hospitals and CHCs
Data Quality Audits – one on one support (150 visits a year)
Implementation of Data Management policy/ SOP’s
Implementation of sign off tools
Revival of information committees at all levels
Inclusion of data quality in all CEO’s and programme Managers performance agreements
Consider:
What is the district doing to address audit reports?
Systems manager – filing system?
Districts to ensure PA
Information committees need to sit and discuss information on a monthly basis

4. Data Flow in KZN
..\SOPS\Primary Health Care Data Flow.docx

5. Current data quality tools utilised
..\SOPS\Data Reconciliation Tool Hospital for FIO and M&E Manager.xls
..\SOPS\DHIS DQ Functions Checklist.xlsx
..\SOPS\Sign off of District Data Revised.doc
..\SOPS\DHMIS policy checklist updated.xlsx

6. Facility Visits - effective
..\2017 facility reports\Phoenix CHC.doc

7. What do we need More dedicated information staff at grass root level
Proper planning prior to implementation
Investment into health systems/IT
Improved local use of data

8. Thank you