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Analysis of Anesthesia Screens for Rule-Based Data Quality Assessment Opportunities
Zhan Wang1, Melody Penning2, Meredith Zozus2
1University of Arkansas at Little Rock.
Abstract:
A rules-based data quality assessment system in electronic health record was explored through compilation of over six thousand data quality rules and twenty-two rule templates. To overcome the lack of knowledge sources and identify additional rules or rule templates, thirty-three anesthesia (perioperative period) EHR screens were reviewed. We analyzed the data elements appearing on anesthesia screens and relationships between them to identify new data quality rules and rule templates relevant to anesthesia care. We present the review process as well as new rules and rule templates identified. We found decomposition and analysis of EHR screens a viable mechanism for acquisition of new data quality rules and proved the number of rules likely tractable and their management scalable.
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