Developing a template matching algorithm for benchmarking hospital performance in a diverse, integrated healthcare system. Issue 24 (12th June 2020)

• Record Type: Journal Article
• Authors: Molling, Daniel; Vincent, Brenda M.; Wiitala, Wyndy L.; Escobar, Gabriel J.; Hofer, Timothy P.; Liu, Vincent X.; Rosen, Amy K.; Ryan, Andrew M.; Seelye, Sarah; Prescott, Hallie C.
• Other Names: Phan. Phil section editor.
• Is Part Of: Medicine. Volume 99:Issue 24(2020)
• Publication Date: 2020-06-12
• Subjects: health care research -- mortality -- outcomes research -- quality of care; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000020385
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: Template matching is a proposed approach for hospital benchmarking, which measures performance based on matching a subset of comparable patient hospitalizations from each hospital. We assessed the ability to create the required matched samples and thus the feasibility of template matching to benchmark hospital performance in a diverse healthcare system. Nationwide Veterans Affairs (VA) hospitals, 2017. Observational cohort study. We used administrative and clinical data from 668, 592 hospitalizations at 134 VA hospitals in 2017. A standardized template of 300 hospitalizations was selected, and then 300 hospitalizations were matched to the template from each hospital. There was substantial case-mix variation across VA hospitals, which persisted after excluding small hospitals, hospitals with primarily psychiatric admissions, and hospitalizations for rare diagnoses. Median age ranged from 57 to 75 years across hospitals; percent surgical admissions ranged from 0.0% to 21.0%; percent of admissions through the emergency department, 0.1% to 98.7%; and percent Hispanic patients, 0.2% to 93.3%. Characteristics for which there was substantial variation across hospitals could not be balanced with any matching algorithm tested. Although most other variables could be balanced, we were unable to identify a matching algorithm that balanced more than ∼20 variables simultaneously. We were unable to identify a template matching approach that could balance hospitals on all measured characteristics potentially important to benchmarking. Given the magnitude of case-mix variation across VA hospitals, a single template is likely not feasible for general hospital benchmarking. Abstract : Supplemental Digital Content is available in the text