Laurent G Glance1, Edward L Hannan, Lee A Fleisher, Michael P Eaton, Richard P Dutton, Stewart J Lustik, Yue Li, Andrew W Dick. 1. From the *Department of Anesthesiology, University of Rochester School of Medicine, Rochester, New York; †Department of Health Policy, Management and Behavior, School of Public Health, University at Albany, Albany, New York; ‡Department of Anesthesiology, University of Pennsylvania Health System, Philadelphia, Pennsylvania; §U.S. Anesthesia Partners; ‖Department of Public Health Sciences, University of Rochester School of Medicine, Rochester, New York; and ¶RAND Health, Boston, Massachusetts.
Abstract
BACKGROUND: In creating the Merit-Based Incentive Payment System, Congress has mandated pay-for-performance (P4P) for all physicians, including anesthesiologists. There are currently no National Quality Forum-endorsed risk-adjusted outcome metrics for anesthesiologists to use as the basis for P4P. METHODS: Using clinical data from the New York State Cardiac Surgery Reporting System, we conducted a retrospective observational study of 55,436 patients undergoing cardiac surgery between 2009 and 2012. Hierarchical logistic regression modeling was used to examine the variation in in-hospital mortality or major complications (Q-wave myocardial infarction, renal failure, stroke, and respiratory failure) among anesthesiologists, controlling for patient demographics, severity of disease, comorbidities, and hospital quality. RESULTS: Although the variation in performance among anesthesiologists was statistically significant (P = 0.025), none of the anesthesiologists in the sample was classified as a high- or low-performance outliers. The contribution of anesthesiologists to outcomes represented 0.51% of the overall variability in patient outcomes (intraclass correlation coefficient [ICC] = 0.0051; 95% confidence interval [CI], 0.002-0.014), whereas the contribution of hospitals to patient outcomes was 2.90% (ICC = 0.029; 95% CI, 0.017-0.050). The anesthesiologist median odds ratio (MOR) was 1.13 (95% CI, 1.08-1.24), suggesting that the variation between anesthesiologist was modest, whereas the hospital MOR was 1.35 (95% CI, 1.25-1.48). In a separate analysis, the contribution of surgeons to overall outcomes represented 1.76% of the overall variability in patient outcomes (ICC = 0.018, 95% CI, 0.010-0.031), and the surgeon MOR was 1.26 (95% CI, 1.19-1.37). Twelve of the surgeons were identified as performance outliers. CONCLUSIONS: The impact of anesthesiologists on the total variability in cardiac surgical outcomes was probably about one-fourth as large as the surgeons' contribution. None of the anesthesiologists caring for cardiac surgical patients in New York State over a 3+ year period were identified as performance outliers. The use of a performance metric based on death or major complications for P4P may not be feasible for cardiac anesthesiologists.
BACKGROUND: In creating the Merit-Based Incentive Payment System, Congress has mandated pay-for-performance (P4P) for all physicians, including anesthesiologists. There are currently no National Quality Forum-endorsed risk-adjusted outcome metrics for anesthesiologists to use as the basis for P4P. METHODS: Using clinical data from the New York State Cardiac Surgery Reporting System, we conducted a retrospective observational study of 55,436 patients undergoing cardiac surgery between 2009 and 2012. Hierarchical logistic regression modeling was used to examine the variation in in-hospital mortality or major complications (Q-wave myocardial infarction, renal failure, stroke, and respiratory failure) among anesthesiologists, controlling for patient demographics, severity of disease, comorbidities, and hospital quality. RESULTS: Although the variation in performance among anesthesiologists was statistically significant (P = 0.025), none of the anesthesiologists in the sample was classified as a high- or low-performance outliers. The contribution of anesthesiologists to outcomes represented 0.51% of the overall variability in patient outcomes (intraclass correlation coefficient [ICC] = 0.0051; 95% confidence interval [CI], 0.002-0.014), whereas the contribution of hospitals to patient outcomes was 2.90% (ICC = 0.029; 95% CI, 0.017-0.050). The anesthesiologist median odds ratio (MOR) was 1.13 (95% CI, 1.08-1.24), suggesting that the variation between anesthesiologist was modest, whereas the hospital MOR was 1.35 (95% CI, 1.25-1.48). In a separate analysis, the contribution of surgeons to overall outcomes represented 1.76% of the overall variability in patient outcomes (ICC = 0.018, 95% CI, 0.010-0.031), and the surgeon MOR was 1.26 (95% CI, 1.19-1.37). Twelve of the surgeons were identified as performance outliers. CONCLUSIONS: The impact of anesthesiologists on the total variability in cardiac surgical outcomes was probably about one-fourth as large as the surgeons' contribution. None of the anesthesiologists caring for cardiac surgical patients in New York State over a 3+ year period were identified as performance outliers. The use of a performance metric based on death or major complications for P4P may not be feasible for cardiac anesthesiologists.