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J Vasc Surg. 2011 Jan;53(1):1-5. doi: 10.1016/j.jvs.2010.08.031. Epub 2010 Nov 18.

The impact of adjusting for reliability on hospital quality rankings in vascular surgery.

Author information

1
Department of Surgery, University of Michigan, Ann Arbor, MI, USA. nichosbo@umich.edu

Abstract

BACKGROUND:

Hospital quality in vascular surgery is often measured using mortality. We sought to determine whether adjusting mortality for statistical reliability changes hospital quality rankings for vascular surgery.

METHODS:

Patients undergoing five common vascular surgery procedures (open and endovascular abdominal aortic aneurysm repair, carotid endarterectomy, lower extremity bypass, and aorto-femoral bypass) in the National Surgical Quality Improvement Project (NSQIP) in 2007 were identified (n = 14,559). For each hospital, we first calculated a ratio of observed to expected mortality (O-E ratio) using standard NSQIP techniques. We then adjusted these estimates for statistical noise using empirical Bayes methods, a technique known as reliability adjustment. We then compared rankings based on the standard O-E ratio to the rankings after reliability adjustment.

RESULTS:

A total of 172 hospitals reported an average adjusted mortality rate of 2.4% for the five procedures, varying from 0% to 17%. After adjusting for statistical noise using reliability adjustment, hospital mortality was greatly diminished, varying only from 1.7% to 4.1%. This adjustment for reliability had a dramatic effect on hospital rankings. Overall, 43% of hospitals were reclassified into either a higher or lower quartile of performance using traditional methods of risk-adjustment. Fifty-one percent all hospitals in the "best" quartile of performance according to traditional O-E ratios are not classified in the "best" quartile after adjusting for statistical noise. Twenty-six percent of hospitals in the "worst" quartile were no longer classified as such after adjusting for noise.

CONCLUSIONS:

Adjusting mortality for reliability reduces statistical noise and provides more stable estimates of hospital quality. Reliability adjustment should be standard for comparing hospital quality.

PMID:
21093202
DOI:
10.1016/j.jvs.2010.08.031
[Indexed for MEDLINE]
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