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Alan Bauck

Systematic and Scalable Clinical Data Quality Assessment Kaiser Permanente Center for Effectiveness and Safety Research. Alan Bauck. Background. Kaiser is composed of eight regions, each with a research center

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Alan Bauck

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  1. Systematic and Scalable Clinical Data Quality AssessmentKaiser Permanente Center for Effectiveness and Safety Research Alan Bauck

  2. Background • Kaiser is composed of eight regions, each with a research center • Kaiser Permanente (KP) Center for Effectiveness and Safety Research (CESR) is a KP research collaborative • Common Data Model is the CESR Virtual Data Warehouse • KP CESR Data Coordinating Center responsible for data quality assessments

  3. Guiding Principles for DQA

  4. DQA Process

  5. Process

  6. DQA Program Templates & Macros • Audience: DCC programmers and site programmers • Provides efficient, tested code to simplify DQA programs and ensures consistent, reliable output

  7. Single Site Report • Audience: Site data managers and programmers • Generated by the DQA program and available to sites as soon as they run the DQA. This encourages site review and self-improvement of data.

  8. Multi-Site Comparisons Report • Audience: Site data managers and programmers • Combines site data and compares patterns across sites and over time

  9. Summary Report • Audience: Researchers • Synthesizes key points across data domains to inform research and avoid large data quality surprises

  10. Take Aways • Provide feedback loops to improve the data quality • Encourages site review and self-improvement • Allows comparisons between sites • Develop tools for repeatable processes • Check for a wide range of the data quality categories (conformance, completeness, plausibility)

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