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Empirically Derived Composite Measures of Surgical Performance

Datos Bibliográficos

ID9104491
AutoresDouglas O Staiger (0009-0005-4711-2629, Dartmouth College, autor de correspondencia), Justin B Dimick (0000-0002-4796-6641, University of Michigan), Onur Baser (0000-0001-7447-5672, University of Michigan), Zhaohui Fan (University of Michigan), John D Birkmeyer (University of Michigan)
Año2009
Volumen47
Número2
Páginas226-233
Fecha de publicación2009-02-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaMedical Care (JOURNAL)
Identificadores de la revistaISSN: 0025-7079 • E-ISSN: 1537-1948
EditorialOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0b013e3181847574
PMID19169124
OpenAlexW2063620352
IdiomaEN
Citas recibidas5
Referencias citadas18

BACKGROUND: Individual quality measures have significant limitations for assessing surgical performance. Despite growing interest in composite measures, empirically-based methods for combining multiple domains of surgical quality are not well established. OBJECTIVE: To develop and validate a composite measure of surgical performance that best describes variation in hospital mortality rates and forecasts future performance. RESEARCH DESIGN: Using the national Medicare claims database, we identified all patients undergoing aortic valve replacement in 2000 to 2001 (n = 53,120). To serve as input variables, we identified hospital-level predictors of mortality with aortic valve replacement, including hospital volume, complication rates, and mortality with other procedures. Hospital-specific predicted mortality rates were then determined using Bayesian-derived modeling techniques and assessed against subsequent hospital mortality (2002-2003). RESULTS: Our composite measure explained 78% of the variation in aortic valve replacement mortality rates (2000-2001). The most important input variables were hospital volume, mortality with aortic valve replacement, and mortality for other high-risk cardiac procedures. The composite measure forecasted 70% of future hospital-level variation in mortality rates (2002-2003), and was substantially better in this regard than individual measures. Hospitals scoring in the bottom quintile on the composite measure in 2000 to 2001 had 2-fold higher mortality rates in 2002 to 2003 than hospitals in the top quintile (adjusted odds ratio, 1.97; 95% CI, 1.73-2.23). CONCLUSIONS: Compared with individual surgical quality indicators, empirically derived composite measures are superior in explaining variation in hospital mortality rates and in forecasting future performance. Such measures could be useful for public reporting, value-based purchasing, or benchmarking for quality improvement purposes

Aortic valve replacement · Logistic regression · Mortality rate · Odds · Odds ratio · Stenosis · Valve replacement · Cardiac Valve Diseases and Treatments · Cardiac, Anesthesia and Surgical Outcomes · Emergency Medicine · Internal Medicine · Medicine · Sepsis Diagnosis and Treatment · Surgery

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Obras citantes distintas5
Citas por año0,31
Intervalo de citas2010 - 2017 (8)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 5
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