1. THE IMPORTANCE OF DATA QUALITY ANOVA Data Symposium Crowne Plaza, Rosebank 21 May 2012 Rentia Voormolen

2. Background of ESI Project Implemented by JSI – John Snow Incorporate Funded by USAID ESI Project – Enhancing Strategic Information To contribute towards reducing the burden of HIV and AIDS in Southern Africa by enhancing the use of information for evidence based decision making

3. Content of Presentation 1.Basic principles of Data Quality 2. Using the DHIS to optimise Data Quality 3. DQ pivot tables on Timeliness and Completeness of data in DHIS

4. WHAT IS DATA QUALITY? The REAL world In the real world, project /program activities are implemented in the field. These activities are designed to produce results that are quantifiable. Data Management System An information system e.g. DHIS, represents these activities by collecting the results that were produced and mapping them to a recording system. Data Quality: How well the DMS represents the real world Data Management System Real World ? 4

5. “Accurate, timely and accessible health care data play a vital role in the planning, development and maintenance of health care services. Quality improvement and the timely dissemination of quality data are essential if health authorities wish to maintain health care at an optimal level” (WHO, 2003).

6. WHY IS DATA QUALITY IMPORTANT? Good Quality RAW data = Good Quality INDICATORS Evidence that can be trusted enables managers to optimize health care coverage, quality and ultimately health status by :  forming accurate pictures of health needs, programs & services in specific areas  informing appropriate planning and decision making  allocating and using resources effectively and efficiently  supporting ongoing monitoring to identify best practices to learn from and areas where support and corrective measures are needed  improve quality of care

7. Daily -Collection during each patient/client contact - Validation & sub-totals Weekly Interim aggregation & validation 1st Validated clinician/service point summarised to facility manager 7th Validated facility summary submitted for capturing 10th Export of facility captured data sent to next level 15th Capturing, import, validation & export completed 20th District import, validation & export completed 30th Provincial import, validation & export completed 10th of following month National import, validation & saving on server Feedback in 5 days Do the right things right the first time! Monthly Data flow timelines: DHMIS Policy DQ –WHERE, WHEN & WHO ?

8. CRITERIA FOR DATA QUALITY Reliable Appropriate Valid Easy Sensitive Specific Validity Reliability Integrity Precision Timeliness Correct Complete Consistent Comprehensive Comparable

9. ACCURACY CHECKS – raw data Eyeballing – visual scanning  missing data values / gaps  inconsistencies / unlikely values  calculation errors  unusual month to month variation / fluctuations  duplication  preferential end-digits  data entered in the wrong box

10. USING THE DHIS TO OPTIMISE DATA QUALITY DHIS is the Routine Health Information Reporting System of NDoH (DHMIS Policy:7)

11. Min / Max out of range Graph

12. Colour Coding – Values out of range

13. Validate in Data Entry

14. Data Completeness Report

15. Data marked for Checking Report

16. Absolute Validation Rules

17. Statistical Validation Rules

19. Gap and Outlier Analysis

21. Data Integrity Check

22. What does the DHIS data tell us about Data Quality? Data quality pivot tables Monitor Timeliness and Completeness of Monthly DHIS health facility data submitted to NDoH Developed by ESI Accepted by HIS task team Currently for internal use To be incorporated in DHIS Pivot tables for external use

23. Definitions of timeliness and completeness Timeliness is the % of expected health care facilities that reported into the DHIS database for the last reporting month (DHMIS policy 60 days) Completeness is the average % of expected health facility reports that were captured into the DHIS for the last 12 reporting months

24. PROXY INDICATOR TO MEASURE TIMELINESS AND COMPLETENESS Indicator: Reporting rate (%) – Target 95% Numerator: Number facilities which reported/captured data on a specific element Denominator: Number facilities for which this data element is activated for capturing into the DHIS

25. Proxy data elements used to identify facilities PHC total Headcount – Clinic, CHC, Mobile & Satelite clinics Delivery in facility – CHC, MOU, District, Regional, Tertiary & Central Hospitals Usable beds – District, Regional, Tertiary & Central Hospitals

26. Ranges used for colour coded pivot tables < 70 (69.5) % - Critical 70 (69.5) to 94 (94.4) % - improvement needed 95 (94.5) to 100% - target met

27. GP: Hospital Reporting Rates – T 95% Month-Year Ekurhuleni MM Johannesburg MM Sedibeng DM Tshwane MM West Rand DMAverage Feb-11 100 Mar-11 100 Apr-11 100 May-11 100 Jun-11 100 Jul-11 100 Aug-11 100 Sep-11 100 Oct-11 100 Nov-11 100 Dec-11 100 Jan-12 100 Average 100 Timeliness – reporting rate for the last reporting month Completeness – average reporting rate for the last 12 reporting months

28. GP: PHC Reporting Rates – T 95% Month-Year Ekurhuleni MM Johannesburg MMSedibeng DMTshwane MM West Rand DMAverage Feb-11 97 98 100 96 98 97 Mar-11 95 98 100 96 98 97 Apr-11 95 98 100 96 98 97 May-11 95 98 100 96 98 97 Jun-11 95 98 100 97 98 97 Jul-11 94 98 100 97 98 97 Aug-11 98 100 97 98 Sep-11 97 96 97 96 Oct-11 98 100 96 98 Nov-11 98 100 95 98 97 Dec-11 99 96 100 95 98 97 Jan-12 99 96 97 95 98 97 Average 97 100 96 98 97

29. GP: PHC Reporting Rates - PMTCT

30. GP: PHC / District - PMTCT DataElementName Ekurhuleni MM Johanne sburg MM Sediben g DM Tshwan e MM West Rand DM Averag e Antenatal 1st visit 95 96 95 93 97 95 Antenatal 1st visit before 20 weeks 94 92 93 Antenatal client CD4 1st test 94 91 92 85 90 Antenatal client eligible for HAART 82 41 68 49 66 59 Antenatal client HIV 1st test 95 96 91 97 94 Antenatal client HIV 1st test positive 94 91 86 89 90 Antenatal client initiated on AZT 93 90 93 86 88 90 Antenatal client initiated on HAART 78 47 67 58 62 Cervical smear in woman 30 years and older 92 93 94 96 93 Medroxyprogesterone injection 96 98 100 97 100 98 Norethisterone enanthate injection 97 99 100 97 99 98 Oral pill cycle 97 99 100 97 99 98 Postnatal care mother within 6 days after delivery 14 80 90 85 74 65 Average 86 87 91 86 88 87

31. GP: Hospital Reporting Rates - PMTCT

32. GP: PHC Reporting Rates - ART

33. GP: PHC / District - ART DataElementName Ekurhul eni MM Johanne sburg MM Sediben g DM Tshwan e MM West Rand DMAverage Adult patient started on ART during this month - new 89 66 83 74 81 78 Adult patients remaining on ART at end of the month - total 0 0 0 0 Children under 15 years remaining on ART at end of the month - total 0 0 0 0 Female condoms distributed 70 60 64 68 77 67 HIV positive adult patient eligible for ART 87 63 83 71 81 76 HIV positive child under 15 years eligible for ART 30 15 49 27 36 28 HIV positive new patient started on Co-trimoxazole prophylaxis 85 88 96 84 93 88 HIV positive new patient started on INH prevention therapy 73 77 90 78 90 79 Male condoms distributed 95 97 96 98 97 New child under 15 years started on ART during this month 29 14 46 25 33 27 Sputum results received within 48 hours 92 96 98 92 96 94 STI partner treated - new 92 84 85 86 87 STI treated - new episode 93 97 99 97 98 96 Suspected TB case smear positive 90 88 89 85 80 87 Suspected TB case smear positive - treatment start 86 83 85 82 77 83 Suspected TB case with sputum sent 96 97 99 96 98 97 Average 79 76 83 76 81 78

34. GP: Hospital Reporting Rates - ART

35. The best way to improve Data Quality is to USE the data!

36. THANK YOU SIYABONGA REALEBOGA BAIE DANKIE.