Samptest 4.0

Music City Center 

When a U.S. healthcare provider is suspected of billing abuse, a population of payments made to that provider over a specified period of time is isolated. A certified medical reviewer can determine the overpayment associated with any payment. There are usually too many payments in the population to examine all, so a probability sample is selected and the sample overpayments used to "extrapolate": to calculate a 90% lower confidence bound for the total population overpayment. This lower bound is the amount demanded for recovery. For more than 20 years a freely-distributed R function known as samptest has been used to determine whether a proposed sampling-and-extrapolation plan will succeed in providing the 90% confidence level, and to estimate the plan's expected overpayment recovery. This talk introduces the 4th version of samptest: a suite of functions including srstest for testing simple random samples and strstest for testing stratified random samples. The functions have been streamlined and made more user-friendly than past versions. They can simultaneously examine multiple extrapolation methods in addition to the mean-per-unit method, including the minimum-sum method, conservative pennysampling, and an empirical likelihood algorithm.

Medicare / Medicaid investigations