Volume 49 | Number 5 | October 2014

Abstract List

Jeffrey H. Silber M.D., Ph.D., Paul R. Rosenbaum Ph.D., Richard N. Ross M.S., Justin M. Ludwig M.A., Wei Wang Ph.D., Bijan A. Niknam B.S., Nabanita Mukherjee Ph.D., Philip A. Saynisch A.B., Orit Even‐Shoshan M.S., Rachel R. Kelz M.D., Lee A. Fleisher M.D.


Develop an improved method for auditing hospital cost and quality.

Data Sources/Setting

Medicare claims in general, gynecologic and urologic surgery, and orthopedics from llinois, exas, and ew ork 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, days, cost, and surgical procedure length. Similar patients at different hospitals had substantially different outcomes.


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.