Quantifying risk and assessing outcome in cardiac surgery.
Quality improvement, research, and reporting of outcome results can be stratified by preoperative risk by using a logistic regression equation or scores to correct for multiple risk factors. The more than 30-fold mortality differences between lowest and highest risk patients make it critical to stratify outcome results by patient severity. Probabilities are not predictions, however, and caution must be exercised when applying scores to individuals. Outcome assessment will grow in its importance to professionals, initially in the guise of quality reporting and improvement, but increasingly as a tool for risk assessment, patient counseling, and directing therapeutic decisions based on more complete information about patient subgroups. Physicians may be called on for recommendations in choosing systems for their hospitals and communities. Therefore, it is important to have an understanding of how such systems are developed, what factors indicate adequate performance of a system, and how such systems of risk stratification should be applied in practice.
Higgins
T L
TL
Department of Medicine, Baystate Medical Center, Springfield, MA 01199, USA.
D002170:Canada / Q000453:epidemiology; D006348:Cardiac Surgical Procedures / Q000401:mortality*; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D011237:Predictive Value of Tests; D018570:Risk Assessment; D015996:Survival Rate; D016896:Treatment Outcome; D014481:United States / Q000453:epidemiology