Appraising Auditor Error in Medicaid Audits

Abstract

Medicaid conducts statistical audits to determine whether providers appropriately billed for Medicaid services. The basis for any claimed liability is an audit based on statistical extrapolation derived from a sample drawn from the totality of claims filed by the provider. Auditor error may be present in nearly every Medicaid audit, yet it is rarely explicitly taken into account in favor of a focus on survey error. It is demonstrated that for commonplace, plausible, audit conditions the presence of audit-error may result in coverage percentages that fall short of those derived via the classical Central Limit Theorem-based method. This data artifact may impeach the Medicaid auditor’s examination of the claimant. The methodology here is not necessarily specific to Medicaid audits; rather, it may generalize to every statistical sampling-based health-care forensic audit.