Evaluating inter-hospital variability in mortality rates over time, allowing for time-varying effects.
In outcome studies, quality of care in various institutions is typically assessed by comparing observed to expected outcome rates, after adjusting for patients' case-mix factors in logistic regression models. However, differences in patterns of outcome rates over time, especially when there is a distinction between the determinants affecting early and later events, are rarely studied. We use six-month mortality after coronary artery bypass graft operation (CABG) as an example. We present a statistically valid approach to estimate expected survival curves for different subgroups, based on a Cox survival model with time-varying effects. Bootstrap confidence intervals around the expected survival curves are constructed. This approach is applied for examining the pattern of deviation of high-mortality hospitals after CABG. Implications for quality assessment in comparative outcome studies are discussed.
Galai
Noya
N
Department of Health Services Research, Ministry of Health, Jerusalem, Israel. ngalai@cc.huji.ac.il
Simchen
Elisheva
E
Braun
Dalit
D
Mandel
Micha
M
Zitser-Gurevich
Yana
Y
D000368:Aged; D001026:Coronary Artery Bypass / Q000401:mortality / Q000592:standards; D005260:Female; D006761:Hospitals / Q000592:standards*; D006801:Humans; D007557:Israel; D008297:Male; D016016:Proportional Hazards Models; D011787:Quality of Health Care / Q000592:standards*; D012307:Risk Factors; D013997:Time Factors