Literature DB >> 18722939

Ranking hospitals on surgical quality: does risk-adjustment always matter?

Justin B Dimick1, John D Birkmeyer.   

Abstract

BACKGROUND: It is a widely held belief that detailed risk-adjustment is always necessary in comparative reports of surgical performance. We sought to evaluate the importance of risk-adjustment for two cardiac surgery report cards in New York and Pennsylvania. STUDY
DESIGN: We abstracted data directly from publicly available cardiac surgery report cards from New York State (2001 and 2002) and Pennsylvania (2000 and 2002). We first estimated the correlation between unadjusted and risk-adjusted mortality rates. We then divided hospitals into three groups of historic performance (best, average, and worst) for both unadjusted and risk-adjusted mortality rankings. We then calculated the risk-adjusted mortality within each of these groups using data from the report card from the subsequent year.
RESULTS: Risk-adjusted and unadjusted mortality rates were highly correlated for both New York (Pearson's r=0.95; Spearman's r=0.91) and Pennsylvania (Pearson's r=0.87; Spearman's r=0.89). For both states, risk-adjusted and unadjusted rankings were equally good at predicting subsequent mortality. In New York State, mortality for hospitals in the worst group was 50% higher than that in the best group regardless of whether unadjusted (relative risk [RR], 1.51) or adjusted (RR, 1.49) rankings were used. The same was found in Pennsylvania, where the results for unadjusted (RR, 1.53) and adjusted (RR, 1.45) rankings were nearly identical.
CONCLUSIONS: Based on data from two prominent state registries, risk-adjusted and unadjusted mortality rates provide nearly identical estimates of hospital performance with coronary artery bypass. Risk-adjustment may not always be important for identifying high quality hospitals.

Mesh:

Year:  2008        PMID: 18722939     DOI: 10.1016/j.jamcollsurg.2008.04.014

Source DB:  PubMed          Journal:  J Am Coll Surg        ISSN: 1072-7515            Impact factor:   6.113


  8 in total

1.  Risk adjustment for comparing hospital quality with surgery: how many variables are needed?

Authors:  Justin B Dimick; Nicholas H Osborne; Bruce L Hall; Clifford Y Ko; John D Birkmeyer
Journal:  J Am Coll Surg       Date:  2010-04       Impact factor: 6.113

2.  Causes of late mortality after endovascular and open surgical repair of infrarenal abdominal aortic aneurysms.

Authors:  Philip P Goodney; Dale Tavris; F Lee Lucas; Thomas Gross; Elliott S Fisher; Samuel R G Finlayson
Journal:  J Vasc Surg       Date:  2010-04-10       Impact factor: 4.268

3.  Summary perioperative risk metrics within the electronic medical record predict patient-level cost variation in pancreaticoduodenectomy.

Authors:  Christopher C Stahl; Patrick B Schwartz; Glen E Leverson; James R Barrett; Taylor Aiken; Alexandra W Acher; Sean M Ronnekleiv-Kelly; Rebecca M Minter; Sharon M Weber; Daniel E Abbott
Journal:  Surgery       Date:  2020-04-26       Impact factor: 3.982

4.  Hospital Variation in Geriatric Surgical Safety for Emergency Operation.

Authors:  Robert D Becher; Nitin Sukumar; Michael P DeWane; Marilyn J Stolar; Thomas M Gill; Kevin M Schuster; Adrian A Maung; Cheryl K Zogg; Kimberly A Davis
Journal:  J Am Coll Surg       Date:  2020-02-04       Impact factor: 6.113

5.  Evaluating mortality outlier hospitals to improve the quality of care in emergency general surgery.

Authors:  Robert D Becher; Michael P DeWane; Nitin Sukumar; Marilyn J Stolar; Thomas M Gill; Adrian A Maung; Kevin M Schuster; Kimberly A Davis
Journal:  J Trauma Acute Care Surg       Date:  2019-08       Impact factor: 3.313

6.  Outlier payments for cardiac surgery and hospital quality.

Authors:  Onur Baser; Zhahoui Fan; Justin B Dimick; Douglas O Staiger; John D Birkmeyer
Journal:  Health Aff (Millwood)       Date:  2009 Jul-Aug       Impact factor: 6.301

7.  Composite measures for rating hospital quality with major surgery.

Authors:  Justin B Dimick; Douglas O Staiger; Nicholas H Osborne; Lauren H Nicholas; John D Birkmeyer
Journal:  Health Serv Res       Date:  2012-03-30       Impact factor: 3.402

8.  Risk adjustment for cesarean delivery rates: how many variables do we need? An observational study using administrative databases.

Authors:  Elisa Stivanello; Paola Rucci; Elisa Carretta; Giulia Pieri; Maria P Fantini
Journal:  BMC Health Serv Res       Date:  2013-01-10       Impact factor: 2.655

  8 in total

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