ArticleHealthcare (Amsterdam, Netherlands)2017
Does adding clinical data to administrative data improve agreement among hospital quality measures?
Article in Healthcare (Amsterdam, Netherlands), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 3 citations in OpenAlex.
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Authors and funding
10 authors at 6 institutions in 1 country.
Funding
Abstract
backgroundHospital performance measures based on patient mortality and readmission have indicated modest rates of agreement. We examined if combining clinical data on laboratory tests and vital signs with administrative data leads to improved agreement with each other, and with other measures of hospital performance in the nation's largest integrated health care system.
methodsWe used patient-level administrative and clinical data, and hospital-level data on quality indicators, for 2007-2010 from the Veterans Health Administration (VA). For patients admitted for acute myocardial infarction (AMI), heart failure (HF) and pneumonia we examined changes in hospital performance on 30-d mortality and 30-d readmission rates as a result of adding clinical data to administrative data. We evaluated whether this enhancement yielded improved measures of hospital quality, based on concordance with other hospital quality indicators.
resultsFor 30-d mortality, data enhancement improved model performance, and significantly changed hospital performance profiles; for 30-d readmission, the impact was modest. Concordance between enhanced measures of both outcomes, and with other hospital quality measures - including Joint Commission process measures, VA Surgical Quality Improvement Program (VASQIP) mortality and morbidity, and case volume - remained poor.
conclusionsAdding laboratory tests and vital signs to measure hospital performance on mortality and readmission did not improve the poor rates of agreement across hospital quality indicators in the VA.
interpretationEfforts to improve risk adjustment models should continue; however, evidence of validation should precede their use as reliable measures of quality.
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