At a recent DC Bar program called “The Use of Data by the OIG-DHHS and CMS/CPI in Medicare Program Integrity, Investigations and Compliance,” representatives from CMS and the OIG provided their perspectives on the evolving capabilities of government agencies to review and analyze large datasets related to the provision and reimbursement of healthcare services.

The government representatives also suggested best practices for providers, including that they know their data and take proactive steps to identify and address potential billing issues.

 Nature and scope of data review

Both CMS and the OIG review and analyze large datasets to identify and pursue potential improper billing to federal healthcare programs, and the OIG may also leverage the resources of its Consolidated Data Analysis Center.

According to the government representatives, their investigations may be prompted by billing patterns that emerge after a change in reimbursement policy, as well as flags in the data that may suggest potential improper billing.

  • For example, the government representatives discussed the potential scrutiny of certain modifiers used to bill for the same service repeatedly, especially after a change in reimbursement policy (e.g., reimbursing a series of drug tests for the same patient on the same day after a change that would provide for reimbursement on a per-patient encounter rather than per-substance-tested basis).
  • The government representatives also discussed focusing on flags in the data that could suggest improper billing, such as emergency ambulance trips that end at patient residences – rather than at hospital emergency departments – or physicians who provide services in non-bordering states on the same day.

In addition to mining single data sets, the government has also synthesized Part D and Part B data to analyze duplicate billing for claims.

 Results of data review

Whereas many of the DOJ’s investigations focuses on whistleblower complaints, the OIG often generates cases in-house through its data analysis.  From one government representative’s perspective, submitting an improper claim itself – even if the government denied the claim for payment – could create Civil Monetary Penalty Law liability based on that submission.

The government representatives viewed data analysis as a starting point for investigation, rather than as conclusive evidence of fraud.  For example, the government representatives acknowledged that providers may make billing errors based on reliance on incomplete published datasets, noting that they often look for recurring issues before investigating a provider.  But gaps in available data (e.g., government data that has not yet reflected the death of a Medicare beneficiary) would not likely be taken into account until later in the investigation.

 Recommended best practices

The government representatives urged providers to make data analysis part of their compliance program.

Among other best practices, the government representatives:

  • Advised providers to know their data, to identify potential issues with outlier codes in their own billing, and to benchmark their billing patterns against their peers; and
  • Cautioned that when small-dollar reimbursement codes generate most of a provider’s revenue, or when the provider is a top biller of a service nationwide, the provider’s billing practices may need to be explored and validated.

We are happy to help our clients analyze their data to identify potential outliers that will enable proactive action and early resolution of potential billing issues.