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Does adding clinical data to administrative data improve agreement among hospital quality measures?

Authors :
Amy K. Rosen
Ann M. Borzecki
Mary Jo Pugh
Amresh D. Hanchate
Michael Shwartz
Priti Shokeen
Kelly Stolzmann
Aaron S. Fink
Hassen Abdulkerim
Arlene S. Ash
Source :
Healthcare. 5:112-118
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

Background Hospital 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. Methods We 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. Results For 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. Conclusions Adding 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. Interpretation Efforts to improve risk adjustment models should continue; however, evidence of validation should precede their use as reliable measures of quality.

Details

ISSN :
22130764
Volume :
5
Database :
OpenAIRE
Journal :
Healthcare
Accession number :
edsair.doi.dedup.....2fb5fa4e125275b4fca9eeb90fbea91f
Full Text :
https://doi.org/10.1016/j.hjdsi.2016.10.001