Alex Woodruff is a Policy Analyst at Boston University School of Public Health. He tweets at @aewoodru. Research for this piece was supported by the Laura and John Arnold Foundation.
Over the past few years, fraud related to the opioid crisis has been in the spotlight. There have been many news reports of doctors committing fraud by taking advantage of patients and families for financial gain. Perhaps the most famous example is Kenneth Chatman who used “sober homes” in South Florida as money-making machines by setting up kickbacks with labs that ran urine screenings and forcing some clients into prostitution.
When providers commit fraud, they take money and resources form patients, health plans (and, through them, other consumers) and taxpayers and leave people with an undertreated deadly disease. A few common medical fraud schemes are:
- Billing for tests or treatments that were never completed
- Performing medically unnecessary services
- “Unbundling” — using multiple billing codes for a procedure when one comprehensive code is available
- “Upcoding” — inaccurately billing a more expensive version of a procedure than what was completed
- “Patient Brokering” – encouraging a patient to sign up for insurance that benefits a treatment center and then referring to that center
These fraudulent activities are difficult for patients to recognize and avoid. Patients seeking treatment for substance use disorders often face limited treatment options and have little way of knowing if they are receiving low quality care for their condition. These factors make people with substance use disorders (SUD) a target for predatory behavior.
Overall, national health care fraud is estimated to cost between $60 billion and $230 billion per year. Confronting this problem could generate savings for taxpayers and health insurers. To date, there has not been a national estimate of the fraud specific to SUD treatment.
But aggressive legal action is being taken to reduce this criminal SUD fraud. The Department of Justice’s (DOJ) Opioid Fraud and Abuse Detection Unit, created in 2017, has already brought hundreds of cases against SUD providers. Unfortunately, the cases the DOJ prosecutes are likely only the tip of the iceberg; they can only prosecute the fraud they can find.
A basic understanding of the current SUD treatment system may help contextualize why fraud is so prevalent. First, there is large variation in the types of treatments provided at different facilities. For example, many facilities do not provide evidence-based medication treatment even though robust research shows these treatments are the most effective method for recovery.
Second, low reimbursement rates leave providers struggling financially and eager to make more money for the care they do provide. Third, providers may feel that the unnecessary services they are providing — requiring multiple urine screenings a week, for example — are not harmful to the patient.
These points closely mirror the three pillars of the fraud triangle — perceived opportunity, perceived financial need, and rationalization of behavior.
Current fraud detection techniques flag suspect patterns in claims data but little is known about how accurate these methods are or how they could be improved. The few existing evaluations of fraud prevention programs show that current fraud detection techniques are limited in their ability to identify this behavior. For example, one study looked for deviations in clinical practice to detect when providers are engaging in fraudulent behavior.
But the reality of clinical practice is that each patient is different and may require different treatment. Another study analyzed submitted claims but could only verify the findings against instances of fraud already known to exist, leaving undetected methods still undiscovered.
Part of the challenge is that fraud is dynamic; there are constantly new schemes and detection systems can’t keep up. Additionally, detection efforts are often limited to only a subset of health care information. Insurance companies may search for fraudulent behavior in their database but may not be able to detect fraud that is occurring across multiple insurance networks.
New approaches are needed to help detect and reduce fraud in the SUD treatment system more effectively and efficiently. One major avenue for growth in fraud detection is to utilize more sophisticated data mining techniques. A well-designed data mining program would use indicators of suspicious activity to search through medical records to identify unusual records and clusters of records that are likely to be fraudulent.
The identified records could then be verified and investigated. The records that did contain fraud could then be used to further refine the program and make it better at identifying illicit behavior. Through this process of learning and refinement, these programs might be able to keep up with fraudulent behavior as it changes and evolves.
In the meantime, policymakers can act to prevent fraud within the SUD treatment system. For example, passing legislation to improve patient protection might go a long way to deterring fraudulent activities. The National Alliance for Model State Drug Laws recently crafted a template for legislation that states could use to protect people with SUD while seeking treatment.
This legislation aims to create a set of ethical standards that will protect patients and prevent facilities willing to engage in dubious practice from gaining a market advantage. Some of the key areas that it targets are: marketing practices, drug testing, managed care, kickbacks and transparency.
Addressing the three pillars of the fraud triangle may also help to decrease fraudulent activity. This could be achieved by: 1) state licensing requirements that facilities offer evidence based care to reduce the allowable deviation from best practices; 2) ensuring providers are compensated fairly for evidence-based treatment so that financial needs do not drive treatment decisions; and 3) educating providers on the negative impacts of fraud on their patients.
SUD fraud exploits the vulnerability of patients and their families. Refining existing fraud detection techniques is necessary to protecting patients with this life-threatening condition.