Comparison of “Risk-Adjusted” Hospital Outcomes

Abstract

Background— A frequent challenge in outcomes research is the comparison of rates from different populations. One common example with substantial health policy implications involves the determination and comparison of hospital outcomes. The concept of “risk-adjusted” outcomes is frequently misunderstood, particularly when it is used to justify the direct comparison of performance at 2 specific institutions. Methods and Results— Data from 14 Massachusetts hospitals were analyzed for 4393 adults undergoing isolated coronary artery bypass graft surgery in 2003. Mortality estimates were adjusted using clinical data prospectively collected by hospital personnel and submitted to a data coordinating center designated by the state. The primary outcome was hospital-specific, risk-standardized, 30-day all-cause mortality after surgery. Propensity scores were used to assess the comparability of case mix (covariate balance) for each Massachusetts hospital relative to the pool of patients undergoing coronary artery bypass grafting surgery at the remaining hospitals and for selected pairwise comparisons. Using hierarchical logistic regression, we indirectly standardized the mortality rate of each hospital using its expected rate. Predictive cross-validation was used to avoid underidentification of true outlying hospitals. Overall, there was sufficient overlap between the case mix of each hospital and that of all other Massachusetts hospitals to justify comparison of individual hospital performance with that of the remaining hospitals. As expected, some pairwise hospital comparisons indicated lack of comparability. This finding illustrates the fallacy of assuming that risk adjustment per se is sufficient to permit direct side-by-side comparison of healthcare providers. In some instances, such analyses may be facilitated by the use of propensity scores to improve covariate balance between institutions and to justify such comparisons. Conclusions— Risk-adjusted outcomes, commonly the focus of public report cards, have a specific interpretation. Using indirect standardization, these outcomes reflect a provider’s performance for its specific case mix relative to the expected performance of an average provider for that same case mix. Unless study design or post hoc adjustments have resulted in reasonable overlap of case-mix distributions, such risk-adjusted outcomes should not be used to directly compare one institution with another.