Targeting Healthcare Fraud by Data Mining
The Department of Justice continues to trumpet its healthcare fraud program. Just last week, the Justice Department and HHS announced another nationwide sweep resulting in the arrest of 91 individuals.
The Justice Department has dropped its “war on drugs” and replaced it with “war on healthcare fraud.” The Affordable Care Act recognized that aggressive prosecution of fraud would help to reduce health care costs. Even while investigating potential fraud, HHS has the authority to suspend all Medicare or Medicaid payments to a service provider.
Law enforcement relies on data mining of Medicare and Medicaid claims to identify potential fraudsters for investigation. Statistics are thought to be a reliable indicator of fraud patterns for overbilling or billing for nonexistent services. This targeting approach has been the bread and butter of the government’s healthcare fraud initiative.
But what if the data being combed is unreliable and inaccurate? That is exactly what some in the industry are claiming. HHS Secretary Sebilius has acknowledged that there may be inaccuracies in the reliability of Medicaid claims data. If that is true, then is it fair for the government to launch civil and criminal investigations based on this inaccurate information.
Private insurers and the government share claims data pursuant to a recent partnership, which was announced by the Justice Department and HHS. This new initiative did not address the problem of inaccuracies in the government’s data.
Aside from unreliable Medicaid data, questions have been raised as to the incentives of “Benefit Integrity Contractors” who are paid to review claims data to detect potential fraud in Medicare and Medicaid programs. The Benefit Integrity Contractors act as bounty hunters combing through the data to find potential fraud.
The Senate Finance Committee has raised concerns about the public-private data analysis program. The Committee has requested specific information about the methodology it would use, and a description of the criteria for the selection of potential targets for investigation. Once identified, service providers, including doctors, hospitals, skilled nursing facilities and others, incur significant costs responding to audits initiated as a a result of the data mining process.
HHS is trying to reduce the impact of these audits on service providers. This is a welcome development since unreliable targeting directly causes unfair audit costs on service providers.
HHS is required to issue a public report regarding the implementation of the Fraud Prevention System’s claims-based methodology, the results of its first year of use, and an analysis of any monetary savings that the program has brought about. This report will be an interesting read and may lead to changes in the data mining and targeting process. Service providers may be able to avoid unfair, costly and lengthy audits and investigations.