Search

Background: Rising health care costs have prompted careful review of comparative hospital resource use. Length of stay after bypass surgery has received particular attention. However, many providers assert that these variations are caused by differences in the clinical mix of patients treated. Our goals were to identify the major clinical predictors of postoperative length of stay (PLOS) after coronary artery bypass graft surgery (CABG), document variations in PLOS among 28 hospitals, and assess the degree to which patient characteristics account for hospital variations in PLOS., Methods: Detailed clinical data on 3605 Medicare patients undergoing CABG in 28 Alabama and Iowa hospitals were analyzed by stepwise linear regression to identify significant clinical predictors of PLOS. Analysis of variance was used to compare hospitals' PLOS while controlling for significant patient risk factors., Results: The mean age was 72.1 years, 34.7% were female, and the in-hospital mortality rate was 5.6%. The median and mean PLOS were 8 and 11.1 days, respectively. Significant predictors of longer PLOS included increasing age, female sex, history of chronic obstructive pulmonary disease, cerebrovascular disease, or mitral valve disease, elevated admission blood urea nitrogen, and preoperative placement of an intraaortic balloon pump. Hospitals varied significantly (P =.0001) in their unadjusted PLOS. These hospital-level variations persisted despite adjustment for both preoperative patient characteristics (P =.0001) and postoperative complications and death (P =.0001)., Conclusions: This study found significant between-hospital variations in PLOS that were not explained by patient factors. This finding suggests the potential for increased efficiency in the care of patients undergoing CABG at many institutions. Further research is needed to determine the practice patterns contributing to variations in length of stay after bypass surgery.

Risk-adjustment and provider profiling have become common terms as the medical profession attempts to measure quality and assess value in health care. One of the areas of care most thoroughly developed in this regard is quality assessment for coronary artery bypass grafting (CABG). Because in-hospital mortality following CABG has been studied extensively, risk-adjustment mechanisms are already being used in this area for provider profiling. This study compares eight different risk-adjustment methods as applied to a CABG surgery population of 28 providers. Five of the methods use an external risk-adjustment algorithm developed in an independent population, while the other three rely on an internally developed logistic model. The purposes of this study are to: (i) create a common metric by which to display the results of these various risk-adjustment methodologies with regard to dichotomous outcomes such as in-hospital mortality, and (ii) to compare how these risk-adjustment methods quantify the 'outlier' standing of providers. Section 2 describes the data, the external and internal risk-adjustment algorithms, and eight approaches to provider profiling. Section 3 then demonstrates the results of applying these methods on a data set specifically collected for quality improvement.