Implementation of a data accuracy plan to improve data extraction yield in the Axon Registry®

M. Cristina C. Victorio, Karen Lundgren, Melissa Johnston-Gross, Amy Bennett, Brandon Magliocco, Aditya Deshpande, Lyell K. Jones

Research output: Contribution to journalArticlepeer-review


ObjectiveTo conduct a data quality improvement project to improve the quality measure data mapping and to measure key phrase logic in the Axon Registry.®MethodsPrior validation analysis of the Axon Registry identified 2 main areas for remediation: methodology for mapping data from electronic health record (EHR) into the registry clinical data record (CDR) and key phrase logic for each measure. Practice groups participating in Axon Registry and 6 Axon Registry quality measures were selected for intervention. Mapping of measure elements and measure performances for each of the selected measures and practices were reviewed before intervention. The Data Accuracy Plan (DAP) was performed, and documentation data and visit data counts and data yield after intervention were calculated and analyzed.ResultsDocumentation data and visit data counts and data yield increased for all 6 quality measures and all practices in the DAP. Increase in documentation data count ranged from 815 to 15,782 occurrences, while visit data count increase ranged from 519 to 16,383 visits. Average data yield range was 7.22% to 33.46% before intervention and increased to a range from 15.34% to 74.40% after intervention.ConclusionThere was substantial improvement in the accuracy of data extraction for quality measure elements after intervention to improve methodology for mapping EHR data into CDR and key phrase logic. Implementation of changes and continued review of data mapping and data dictionary are important to ensure accurate measure performance and to improve reliability and validity of Axon Registry data.

Original languageEnglish (US)
Pages (from-to)E310-E319
Issue number3
StatePublished - Jul 21 2020

ASJC Scopus subject areas

  • Clinical Neurology


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