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Assessment & adjustment for data quality used in the South African DISTRICT HEALTH BAROMETER

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    Assessment & adjustment for data quality used in the South African DISTRICT HEALTH BAROMETER Assessment & adjustment for data quality used in the South African DISTRICT HEALTH BAROMETER Presentation Transcript

    • Assessment & adjustment for data quality used in the South African DISTRICT HEALTH BAROMETER Candy Day 21 September 2009
    • Assessment of data sources Data Source Contents Capacity & Practices Dissemination Integration and use Total Census Highly adequate 100% Highly adequate 75% Adequate 71% Adequate 56% Highly adequate 75% Vital statistics Highly adequate 89% Adequate 67% Highly adequate 100% Highly Adequate 83% Highly adequate 85% Population-based surveys Adequate 57% Highly Adequate 88% Highly adequate 100% Present but not adequate 33% Adequate 70% Health and disease records (incl. surveillance) Adequate 56% Adequate 59% Present but not adequate 44% Present but not adequate 28% Present but not adequate 47% Health service records Not adequate at all 12% Present but not adequate 41% Highly adequate 78% Adequate 50% Present but not adequate 45% Resource records Adequate 63% Present but not adequate 40% Present but not adequate 33% Present but not adequate 31% Present but not adequate 42% Total Adequate 63% Adequate 62% Adequate 71% Present but not Adequate 47% Adequate 61%
    • Problems of health records
      • Range from burdensome paper-records to high-tech paperless EMRs
      • In general these systems do not function well
      • Incomplete, poor quality, time delays
      • Inadequate staffing and resourcing
      • Poor feedback, dissemination and use
      • Poor integration
    • Record review
      • Challenges for routine health system data management in a large public programme to prevent mother-to-child HIV transmission in South Africa. Kedar S Mate, Brandon Bennett, Wendy Mphatswe, Pierre Barker, Nigel Rollins (2009) PloS one 4 (5) p. e5483
      • An evaluation of the District Health Information System in rural South Africa. A Garrib, N Stoops, A McKenzie, L Dlamini, T Govender, J Rohde, K Herbst (2008) South African medical journal 98 (7) p. 549-52
    • All indicators
    • Single indicator
    • Monthly data
      • Trend smoothing
      • Data variability
      • Noteworthy events
    • Data quality issues
    • HIV prevalence data sources
    • DHIS Survey
    • Vital statistics
    • Linking expenditure to utilisation
    • THANK YOU!
        • Candy Day
        • [email_address]
        • http://www.hst.org.za