Beschreibung:
<p>It has become common to adopt a hierarchical model structure when comparing the performance of multiple health-care providers. This structure allows some variation in such measures, beyond that explained by sampling variation, to be "normal," in recognition of the fact that risk-adjustment is never perfect. The shrinkage estimates arising from such a model structure also have appealing properties. It is not immediately clear, however, how "unusual" providers, that is, any with particularly high or low rates, can be identified based on such a model. Given that some variation in underlying rates is assumed to be the norm, we argue that it is not generally appropriate to identify a provider as interesting based only on evidence of it lying above or below the population mean. We note with concern, however, that this practice is not uncommon. We examine in detail three possible strategies for identifying unusual providers, carefully distinguishing between statistical "outliers" and "extremes." A two-level normal model is used for mathematical simplicity, but we note that much of the discussion also applies to alternative data structures. Further, we emphasize throughout that each approach can be viewed as resulting from a Bayesian or a classical perspective. Three worked examples provide additional insight.</p>