Reliability of surgical outcomes for predicting future hospital performance.
BACKGROUND
Because of small sample sizes and low event rates, risk-adjusted surgical outcomes often do not meet reliability benchmarks for distinguishing hospital performance. Nonetheless, it is unclear whether these measures may still be useful for predicting future hospital surgical performance.


METHODS
We used national Medicare data to analyze patients undergoing colectomy from 2007 to 2010 (n=462,959 patients). We first quantified 2007-2008 outcome reliability (ability to differentiate quality differences) and ranked hospitals based on their 2007-2008 risk-adjusted outcome rates. To assess the ability of adjusted outcomes to predict true performance, we evaluated future (2009-2010) outcomes across quintiles of past performance. We then systematically sampled 2007-2008 cases to evaluate performance prediction when hospitals' past performance was measured with progressively lower reliability levels.


RESULTS
Outcomes in 2007-2008 were good predictors of outcomes in the next 2 years (2009-2010), but predictive strength depended upon reliability. With progressive sampling of 2007-2008 caseloads, outcome reliability and predictive strength decreased. With 100% sampling of 2007-2008 caseloads, the worst versus best hospital quintile based on past performance had 1.52 [95% confidence interval (CI), 1.44-1.60] times the odds of mortality and 1.50 (95% CI, 1.44-1.56) times the odds of complications in 2009-2010. With 10% sampling, outcome reliability was well below commonly accepted benchmarks, but the worst quintile of hospitals in 2007-2008 still had 1.12 (95% CI, 1.06-1.19) times the odds of mortality and 1.16 (95% CI, 1.11-1.21) times the odds of complications in 2009-2010 compared with the best quintile of hospitals.


CONCLUSIONS
Even at very low reliability levels, risk-adjusted outcome measures may distinguish best and worst hospitals' surgical performance. This study suggests that commonly accepted reliability thresholds may be too high, especially in the context of selective referral.
*Department of Surgery, University of Michigan Health System, Ann Arbor, MI †Department of Economics, Dartmouth College, Hanover, NH.
Robert W
RW
Krell
Douglas O
DO
Staiger
Justin B
JB
Dimick
D000368:Aged; D000369:Aged, 80 and over; D019985:Benchmarking; D003082:Colectomy / Q000401:mortality*; D005260:Female; D005544:Forecasting; D017052:Hospital Mortality / Q000639:trends*; D006761:Hospitals / Q000592:standards* / Q000639:trends; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D015999:Multivariate Analysis; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D011183:Postoperative Complications / Q000401:mortality / Q000601:surgery; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D012086:Reoperation / Q000401:mortality / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D020379:Risk Adjustment; D014481:United States