Outlier detection for a hierarchical Bayes model in a study of hospital variation in surgical procedures.

One of the most important aspects of profiling healthcare providers or services is constructing a model that is flexible enough to allow for random variation. At the same time, we wish to identify those institutions that clearly deviate from the usual standard of care. Here, we propose a hierarchical Bayes model to study the choice of surgical procedure for rectal cancer using data previously analysed by Simons et al.