title: The evaluation of treatment when center-specific selection criteria vary with respect to patient risk.
abstract: Many standards of medical care are based on the demonstrated effects of various treatment strategies or processes. Unlike pharmacological treatments, these strategies or processes are not necessarily subjected to rigorous clinical trials and their benefit is frequently assessed from observational data. For evaluating the influence of such medical processes on patient outcomes, not only is risk adjustment an issue, but also the "center effect" represents an important, often overlooked consideration. Both the quality of care and the tendency to use certain treatments or processes vary from one center to another. The induced similarity in outcomes within center, as well as the potential for confounding by center, needs to be addressed within the context of risk adjustment. In addition, center-specific selection criteria for a treatment strategy can vary with respect to patient risk. Because of these considerations, it is important to adequately separate the within-center effects of the treatment or strategy from the across-center effects, which relate more to center performance. The primary objective of this article is to explore and extend current methods of dealing with center confounding for dichotomous outcomes, primarily for the situation where selection on the basis of patient risk can vary from center to center. A simulation study compares results from several different analytic methods and provides evidence for the importance of considering confounding due to both risk and center when evaluating the effectiveness of a process. An example that examines the effect of early extubation after bypass surgery is also presented.
authors.affiliation: The Outcomes Research and Assessment Group, Duke Clinical Research Institute, Durham, North Carolina 27710, USA.
authors.forename: Elizabeth R
authors.initials: ER
authors.lastname: DeLong
authors.forename: Laura P
authors.initials: LP
authors.lastname: Coombs
authors.forename: T Bruce
authors.initials: TB
authors.lastname: Ferguson
authors.forename: Eric D
authors.initials: ED
authors.lastname: Peterson
mesh_terms: D003198:Computer Simulation; D015986:Confounding Factors, Epidemiologic; D001026:Coronary Artery Bypass; D003627:Data Interpretation, Statistical; D006801:Humans; D015337:Multicenter Studies as Topic / Q000379:methods*; D018579:Patient Selection; D012121:Respiration, Artificial; D020379:Risk Adjustment; D016896:Treatment Outcome