Physicians and clinical laboratories that do business with other healthcare providers who have been denied enrollment in Medicare or had their enrollment revoked are under increased scrutiny
Efforts by the Centers for Medicare and Medicaid Services (CMS) to crack down on fraud could soon be bolstered by artificial intelligence (AI) tools, placing new pressure on medical laboratories and anatomic pathology groups to ensure that their billing practices are fully compliant with current federal “affiliations” regulations.
This is why, last October, CMS issued a Request for Information (RFI) seeking feedback from vendors, providers, and suppliers about the potential use of AI tools to identify cases of fraud, waste, and abuse in billing for healthcare services. Statements from CMS indicate that the agency plans to deepen its investigation into the affiliations physicians and clinical laboratories have with healthcare providers that been involved in fraudulent behavior within the Medicare program.
At present, CMS uses a variety of approaches to spot improper claims, the RFI notes, including the use of human medical reviewers. However, this is a costly process that allows review of less than 1% of claims. AI tools would increase the speed and accuracy of those investigations exponentially.
The RFI notes that AI technology could “help CMS identify potentially problematic affiliations upon initial screening and through continuous monitoring. One example would be a new tool or technology that would allow easy, seamless access to state and local business ownership and registration information that could improve CMS’ line-of-sight to potentially problematic business relationships.”
CMS’ New Affiliations Rule Affects Clinical Laboratories
One area where CMS sought input relates to the new anti-fraud rule, titled, “Medicare, Medicaid, and Children’s Health Insurance Programs; Program Integrity Enhancements to the Provider Enrollment Process.” This final rule, which took effect Nov. 4, 2019, requires providers, including medical laboratories, to disclose affiliations with entities that may have engaged in past fraudulent activities.
Our sister publication, The Dark Report (TDR), provided in-depth coverage of this rule, which allows CMS “to revoke or deny enrollment if it finds that a provider’s or supplier’s current or previous affiliations pose an undue risk of fraud.” (See TDR, “Labs Must Respond to New CMS Anti-Fraud Rule,” October 14, 2019.)
“For too many years, we have played an expensive and inefficient game of ‘whack-a-mole’ with criminals—going after them one at a time—as they steal from our programs,” CMS Administrator Seema Verma said in a statement about the new rule. “These fraudsters temporarily disappear into complex, hard-to-track webs of criminal entities, and then re-emerge under different corporate names. These criminals engage in the same behaviors again and again.”
As TDR reported, the rule defines four “disclosable events” that trigger the disclosure requirements:
- Uncollected debt to Medicare, Medicaid, or CHIP;
- Payment suspension under a federal healthcare program;
- Exclusion by the Office of Inspector General from participation in Medicare, Medicaid, or CHIP; and
- Termination, revocation, or denial of Medicare, Medicaid, or CHIP enrollment.
If disclosure is required, CMS described five definitions of an affiliation, using a five-year look-back:
- Direct or indirect ownership of 5% or more in another organization;
- A general or limited partnership interest, regardless of the percentage;
- An interest in which an individual or entity “exercises operational or managerial control over, or directly conducts” the daily operations of another organization, “either under direct contract or through some other arrangement;”
- When an individual is acting as an officer or director of a corporation; and
- Any reassignment relationship.
One interesting consequence of these definitions is that individuals or companies that invest and own an interest in a provider organization that has one or more “disclosable events” would be flagged by the provider at time of enrollment or re-enrollment in the Medicare program. Over the years, some very prominent private equity companies have been investors and owners of medical laboratory companies that owed money to Medicare or entered into civil settlements with the federal government where the full amount of the alleged overpayments was not recovered and the provider neither admitted nor denied guilt. These affiliations would need to be disclosed and could be used by CMS to deny enrollment in the Medicare program.
“Lab companies that engage in fraud and abuse—often paying illegal inducements to physicians to encourage them to order medically-unnecessary tests—distort the lab testing marketplace and capture lab test referrals that would otherwise go to compliant clinical labs and pathology groups,” stated Robert Michel, Editor-In-Chief of The Dark Report. “So, honest labs will recognize how the new rule can help suppress various types of fraud that constantly plague the clinical lab industry.” (See TDR, “Is New Medicare Affiliation Rule Good, Bad, or Ugly?” November 4, 2019.)
Other AI Applications in Healthcare
The CMS RFI also suggests other areas in which artificial intelligence could help identify fraudulent activity, including real-time monitoring of electronic health records (EHR), risk adjustment data validation (RADV) audits, and value-based payment systems.
“These tools hold the promise of more expeditious, seamless and accurate review of chart documentation during medical review to ensure that we are paying for what we get and getting what we pay for,” the RFI states. “However, concerns about potential improper payments and bad actors remain. We need to determine whether innovative new strategies, tools, and technologies presently exist that can increase data accuracy and integrity and consequently reduce improper payments.”
Clinical laboratories should not be surprised by any of this. Artificial intelligence and machine learning are increasingly becoming vital tools in today’s modern healthcare system. Nevertheless, lab leaders should closely monitor CMS’ use of these technologies to root out fraud, as labs are often caught up in their investigations.