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Vincent BM, Molling D, Escobar GJ, et al. Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System. Med Care. 2021;59(12):1090-1098doi: 10.1097/MLR.0000000000001645.
Vincent, B. M., Molling, D., Escobar, G. J., Hofer, T. P., Iwashyna, T. J., Liu, V. X., Rosen, A. K., Ryan, A. M., Seelye, S., Wiitala, W. L., & Prescott, H. C. (2021). Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System. Medical care, 59(12), 1090-1098. https://doi.org/10.1097/MLR.0000000000001645
Vincent, Brenda M, et al. "Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System." Medical care vol. 59,12 (2021): 1090-1098. doi: https://doi.org/10.1097/MLR.0000000000001645
Vincent BM, Molling D, Escobar GJ, Hofer TP, Iwashyna TJ, Liu VX, Rosen AK, Ryan AM, Seelye S, Wiitala WL, Prescott HC. Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System. Med Care. 2021 Dec 01;59(12):1090-1098. doi: 10.1097/MLR.0000000000001645. PMID: 34629424.
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Med Care. 2021 Dec 01;59(12):1090-1098. doi: 10.1097/MLR.0000000000001645.

Hospital-specific Template Matching for Benchmarking Performance in a Diverse Multihospital System.

Medical care

Brenda M Vincent, Daniel Molling, Gabriel J Escobar, Timothy P Hofer, Theodore J Iwashyna, Vincent X Liu, Amy K Rosen, Andrew M Ryan, Sarah Seelye, Wyndy L Wiitala, Hallie C Prescott

Affiliations

  1. VA Center for Clinical Management Research, Ann Arbor, MI.
  2. Division of Research, Kaiser Permanente Northern California, Oakland, CA.
  3. Department of Internal Medicine, University of Michigan.
  4. Survey Research Center, Institute for Social Research, Ann Arbor, MI.
  5. VA Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA.
  6. Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI.

PMID: 34629424 DOI: 10.1097/MLR.0000000000001645

Abstract

BACKGROUND: Hospital-specific template matching is a newer method of hospital performance measurement that may be fairer than regression-based benchmarking. However, it has been tested in only limited research settings.

OBJECTIVE: The objective of this study was to test the feasibility of hospital-specific template matching assessments in the Veterans Affairs (VA) health care system and determine power to detect greater-than-expected 30-day mortality.

RESEARCH DESIGN: Observational cohort study with hospital-specific template matching assessment. For each VA hospital, the 30-day mortality of a representative subset of hospitalizations was compared with the pooled mortality from matched hospitalizations at a set of comparison VA hospitals treating sufficiently similar patients. The simulation was used to determine power to detect greater-than-expected mortality.

SUBJECTS: A total of 556,266 hospitalizations at 122 VA hospitals in 2017.

MEASURES: A number of comparison hospitals identified per hospital; 30-day mortality.

RESULTS: Each hospital had a median of 38 comparison hospitals (interquartile range: 33, 44) identified, and 116 (95.1%) had at least 20 comparison hospitals. In total, 8 hospitals (6.6%) had a significantly lower 30-day mortality than their benchmark, 5 hospitals (4.1%) had a significantly higher 30-day mortality, and the remaining 109 hospitals (89.3%) were similar to their benchmark. Power to detect a standardized mortality ratio of 2.0 ranged from 72.5% to 79.4% for a hospital with the fewest (6) versus most (64) comparison hospitals.

CONCLUSIONS: Hospital-specific template matching may be feasible for assessing hospital performance in the diverse VA health care system, but further refinements are needed to optimize the approach before operational use. Our findings are likely applicable to other large and diverse multihospital systems.

Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

Conflict of interest statement

The authors declare no conflict of interest.

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