Characterizing industry payments for FDA-approved AI medical devices

Journal article

Introduction: Artificial intelligence-enabled medical devices (AIMDs) are increasing in use, but this growth has raised concerns about inequities in access across well-resourced and under-resourced settings. Little is known about industry–clinician partnerships in the AIMD ecosystem. Methods: We examined the value, specialty distribution, market concentration, and institutional profile of payments made by industry to clinicians for Food and Drug Administration-approved AIMDs using the Open Payments Database. We linked payments to the affiliated hospital of the clinician using the Medicare Provider Data catalog. We performed a regression to explain the association of payments with hospital and county-level factors. Results: We found $59.3 million was spent on payments to 46 315 clinicians for AIMDs between 2017 and 2023, representing an increasing share of total medical device payments over time. We saw high payment concentration in technologically intensive medical specialties and among clinicians affiliated with large, urban teaching hospitals. Conclusion: Industry payments for AIMDs are increasing and concentrated among technology-intensive specialties. Payments are more likely to flow to clinicians affiliated with teaching hospitals that are larger and in non-rural areas. This may reflect or mediate increased AI utilization in these settings. Continued monitoring of payments, transparent reporting, and targeted resource support may be needed to promote equitable access to AIMDs.

Authors: Bergman, A; Patel, TA; Shah, KP

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Oxford University Press
• Journal: Health Affairs Scholar
• Volume: 3
• Issue: 12
• Pages: qxaf211
• Article number: qxaf211
• Publication date: 2025-11-10
• Acceptance date: 2025-11-05
• DOI: 10.1093/haschl/qxaf211
• EISSN: 2976-5390
• ISSN: 2976-5390
• Language: English
• Keywords: open payments; medical devices; conflicts; physicians; digital divide; artificial intelligence