Probe samples and the minimum sum method for medicare fraud investigations

Abstract

Random sampling of paid medicare claims has been legally acceptable for investigating suspicious billing practices by health care providers since 1986. A population of payments made to a given provider during a given time frame is isolated and a probability sample selected for investigation. A lower confidence bound for the total amount overpaid to the provider is then used as a recoupment demand. Edwards et al. (Health Serv Outcomes Res Methodol 4:241-263, 2005) show that methods based on the Central Limit Theorem can fail badly and propose an alternative method, called the minimum sum method, for fixed sample sizes. In this paper the sampling is performed in two stages. In case of little abuse in the first stage the investigation is stopped; otherwise a second sample is examined. Based on this strategy a lower confidence bound for the total number of universe payments in error and a corresponding lower bound for the total overpayment amount are defined. Criteria for choosing the sampling parameters are considered. Relative efficiencies are studied.