Dosing Discrimination: Regulating PDMP Risk Scores

California Law Review

In "Dosing Discrimination: Regulating PDMP Risk Scores," Professor Jennifer D. Oliva explores how risk scores from Prescription Drug Monitoring Programs can deter treatment for patients who are deemed to be at high risk of drug misuse, exacerbating discrimination against certain marginalized populations. Author: Jennifer D. Oliva is the Associate Dean for Faculty Research and Development, Professor of Law, and Director of the Center for Health & Pharmaceutical Law at Seton Hall University School of Law. Host: Carter Jansen Technology Editors: NoahLani Litwinsella (Volume 110 Senior Technology Editor), Carter Jansen (Volume 110 Technology Editor), Hiep Nguyen (Volume 111 Senior Technology Editor), Taylor Graham (Volume 111 Technology Editor), Benji Martinez (Volume 111 Technology Editor) Other Editors: Ximena Velazquez-Arenas (Volume 111 Senior Diversity Editor), Jacob Binder (Volume 111 Associate Editor), Michaela Park (Volume 111 Associate Editor), Kat King (Volume 111 Publishing Editor) Soundtrack: Composed and performed by Carter Jansen Article Abstract: Prescription drug monitoring program (PDMP) predictive surveillance platforms were designed for—and funded by—law enforcement agencies. PDMPs use proprietary algorithms to determine a patient’s risk for prescription drug misuse, diversion, and overdose. The proxies that PDMPs utilize to calculate patient risk scores likely produce artificially inflated scores for marginalized patients, including women and racial minorities with complex, pain-related conditions; poor, uninsured, under-insured, and rural individuals; and patients with co-morbid disabilities or diseases, including substance use disorder and mental health conditions. Law enforcement conducts dragnet sweeps of PDMP data to target providers that the platform characterizes as “overprescribers” and patients that it deems as high risk of drug diversion, misuse, and overdose. Research demonstrates that PDMP risk scoring coerces clinicians to force medication tapering, discontinue prescriptions, and even abandon patients without regard for the catastrophic collateral consequences that attend to those treatment decisions. PDMPs, therefore, have the potential to exacerbate discrimination against patients with complex and stigmatized medical conditions by generating flawed, short-cut assessment tools that incentivize providers to deny these patients indicated treatment. The Federal Food and Drug Administration (FDA) is authorized to regulate PDMP predictive diagnostic software platforms as medical devices, and the agency recently issued guidance that provides a framework for such oversight. Thus far, however, the FDA has failed to regulate PDMP platforms. This Article contends that the FDA should exercise its regulatory authority over PDMP risk scoring software to ensure that such predictive diagnostic tools are safe and effective for patients.