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Medicare Providers are selected for audit based on a wide variety of tools, including comparisons to their peers in terms of utilization for various procedures. We use decision trees to examine the efficacy of these peer-comparison statistics in predicting which Providers will be shown to have high overpayments – that is, to owe money back to the Trust… (More)
We propose a Bayesian model for clustered outliers in multiple regression. In the literature, outliers are frequently modeled as coming from a subgroup where the variance of the errors is much larger than in the rest of the data. By contrast, when a cluster of outliers exists, we show that it can be more informative to model them as coming from a subgroup… (More)