Improving Data Quality

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Improving Data Quality

  1. 1. 4 th International RHINO Workshop Guanajuato, Mexico March 8-12, 2010 Measuring and Improving Routine Health Information System Performance Session 3.4.2: Concurrent Session : Improving Data Quality
  2. 2. General Session Objectives <ul><li>Understand why data quality is critical in RHIS performance and in planning and management of health service delivery </li></ul><ul><li>Identify potential factors that compromise data quality </li></ul><ul><li>Discuss and recommend various strategies for achieving optimal data quality as part of RHIS performance </li></ul>
  3. 3. Specific Objectives <ul><li>Update of latest developments in the data quality assurance for RHIS </li></ul><ul><li>Review of current practices, opportunities and challenges </li></ul><ul><li>Identification of agenda specific to key RHIS stakeholder groups (e.g. RHINO, donors, MoH, academia, etc.) </li></ul>
  4. 4. Why Data Quality is Important to RHIS <ul><li>Planning </li></ul><ul><ul><li>efficient use of scarce resources </li></ul></ul><ul><li>Evaluation </li></ul><ul><ul><li>do the programs work? </li></ul></ul><ul><li>Progress towards targets </li></ul><ul><ul><li>M.D.G., local benchmarks </li></ul></ul>
  5. 5. Factors that compromise data quality <ul><li>Lack of standards </li></ul><ul><ul><li>tools for data collection, compilation and analysis </li></ul></ul><ul><ul><li>Indicators and their definitions </li></ul></ul><ul><li>Lack of resources </li></ul><ul><ul><li>Human </li></ul></ul><ul><ul><li>Financial </li></ul></ul><ul><ul><li>Material (e.g. forms, computers, transport) </li></ul></ul><ul><li>Others? </li></ul>
  6. 6. Developments in the data quality assurance for RHIS <ul><li>Review of current practices, opportunities and challenges </li></ul><ul><ul><li>PRISM Tools and Methods </li></ul></ul><ul><ul><li>DQA/RDQA </li></ul></ul><ul><ul><li>WHO/HMN/CHeSS </li></ul></ul><ul><ul><li>Others? </li></ul></ul>
  7. 7. PRISM Tools <ul><li>Accuracy check on up to four indicators </li></ul><ul><ul><li>Facility: Recount value from register, compare to monthly report </li></ul></ul><ul><ul><li>District: Recount monthly reports from facilities, compare to database, district monthly report </li></ul></ul><ul><li>Timeliness, completeness </li></ul><ul><li>LQAS </li></ul>
  8. 8. DQA/RDQA <ul><li>Accuracy check: </li></ul><ul><ul><li>Recount value of indicator using source document (e.g. medical record), compare to monthly report </li></ul></ul><ul><li>Cross-checks </li></ul><ul><li>Spot-checks </li></ul><ul><li>Cluster sampling </li></ul>
  9. 9. WHO/HMN/CHeSS <ul><li>Data Quality Assessments from facility record reviews </li></ul><ul><li>Data profiling at National level </li></ul><ul><li>Identification of data quality problems </li></ul><ul><li>Adjustments to make data useable </li></ul><ul><li>Comparisons with other data sources, e.g. survey data, pharmacy, supply chain management etc. </li></ul>
  10. 10. Strategies for ensuring data quality in RHIS <ul><li>Routine DQ assessment </li></ul><ul><li>Performance monitoring </li></ul><ul><li>Oversight / supervision </li></ul><ul><li>Comparisons / Adjustment </li></ul><ul><li>Others? </li></ul>
  11. 11. RHIS Data Quality Agenda <ul><li>Identification of agenda specific to key RHIS stakeholder groups (e.g. RHINO, donors, MoH, academia, etc.) </li></ul>

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