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Statistical issues in the analysis and interpretation of outcomes for congenital cardiac surgery

Part of: The International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD)

Published online by Cambridge University Press:  01 December 2008

Sean M. O’Brien  and
Kimberlee Gauvreau
Sean M. O’Brien*
Affiliation:
Department of Biostatistics and Bioinformatics and Duke Clinical Research Institute, Duke University Medical Center, Durham North Carolina, United States of America
Kimberlee Gauvreau
Affiliation:
Department of Cardiology, Children’s Hospital; Department of Pediatrics, Harvard Medical School; and Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America
*
Correspondence to: Sean M. O’Brien PhD, Box 17969, Duke Clinical Research Institute, Durham, NC 27715, United States of America. Tel: 919 668 8754; Fax: 919 668 7053; E-mail: obrie027@mc.duke.edu
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Abstract

It is universally agreed that efforts to improve quality benefit from the analysis of outcomes. Yet, it is challenging to compare results across institutions because factors other than performance also impact outcomes. Two factors that complicate the analysis of outcomes after congenital cardiac surgery are case-mix and random statistical variation. Case-mix refers to differences in the mix of patients and their risk-factors at different institutions that may cause some centres to have more frequent complications and lower survival regardless of their true performance. Random statistical variation refers to fluctuations in outcomes that occur at random and follow the laws of probability. A variety of statistical methods exist to address these issues and make provider comparisons more fair. We explain a few common approaches including stratification, regression analysis, and confidence intervals. Concepts are illustrated using artificial data from two hypothetical hospitals, as well as real data from a multi-institution registry.

Keywords

Congenital heart surgerycongenital cardiac diseasecase-mix adjustmentperformance assessmentquality improvement

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References

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