Template matching for auditing hospital cost and quality

Health Serv Res. 2014 Oct;49(5):1446-74. doi: 10.1111/1475-6773.12156. Epub 2014 Mar 3.


Objective: Develop an improved method for auditing hospital cost and quality.

Data sources/setting: Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, Texas, and New York between 2004 and 2006.

Study design: A template of 300 representative patients was constructed and then used to match 300 patients at hospitals that had a minimum of 500 patients over a 3-year study period.

Data collection/extraction methods: From each of 217 hospitals we chose 300 patients most resembling the template using multivariate matching.

Principal findings: The matching algorithm found close matches on procedures and patient characteristics, far more balanced than measured covariates would be in a randomized clinical trial. These matched samples displayed little to no differences across hospitals in common patient characteristics yet found large and statistically significant hospital variation in mortality, complications, failure-to-rescue, readmissions, length of stay, ICU days, cost, and surgical procedure length. Similar patients at different hospitals had substantially different outcomes.

Conclusion: The template-matched sample can produce fair, directly standardized audits that evaluate hospitals on patients with similar characteristics, thereby making benchmarking more believable. Through examining matched samples of individual patients, administrators can better detect poor performance at their hospitals and better understand why these problems are occurring.

Keywords: Quality of care; cost; health care research; outcomes research.

Publication types

  • Comparative Study
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Benchmarking / methods*
  • Clinical Audit / statistics & numerical data*
  • Female
  • General Surgery / statistics & numerical data
  • Hospital Costs / statistics & numerical data*
  • Hospitals, High-Volume / statistics & numerical data
  • Hospitals, Low-Volume / statistics & numerical data
  • Humans
  • Illinois
  • Male
  • Medicare / statistics & numerical data*
  • Middle Aged
  • Models, Statistical
  • New York
  • Orthopedics / statistics & numerical data
  • Outcome Assessment, Health Care / statistics & numerical data*
  • Quality of Health Care / statistics & numerical data*
  • Texas
  • United States