AI/ML-enabled medical device firms paid $39.7 million for radiology devices from 2017–2023, raising transparency concerns.
Key Details
- 1AI/ML-enabled medical device developers paid $39.7M for radiology devices over seven years.
- 2Total industry payments to healthcare entities reached $179M in the same period; only cardiovascular devices saw more ($59.4M).
- 3Researchers identified 846 FDA-listed AI/ML-enabled medical devices, but only 79 (9.3%) disclosed payment data.
- 4Annual payments rose from $17.3M in 2017 to $24.6M in 2023, with general payments doubling from $6.6M to $13.3M.
- 5The number of physician and hospital payment recipients more than doubled, but most manufacturers reported no payments.
- 6Study suggests underreporting may occur due to differing device clearance, reimbursement, and classification pathways.
Why It Matters
Financial incentives from AI device manufacturers may influence adoption and promotion decisions in radiology, underlining the importance of transparency. Calls for modernized disclosure requirements could affect radiology-AI industry practices and regulatory oversight.
Source
AuntMinnie
Related News
•AuntMinnie
AI Model Shows Promise for Detecting Meningiomas on Skull X-rays
South Korean researchers developed an AI model that detects meningiomas on skull x-rays, showing high accuracy in initial tests.
•AuntMinnie
AI and Collaborative Strategies Advance Lung Cancer Screening Uptake
Collaborative initiatives and novel AI tools are helping to advance lung cancer screening, but participation barriers and disparities persist despite guideline expansions.
•AuntMinnie
AI Advances Push Opportunistic Imaging Into Clinical Focus
AI-powered opportunistic screening is transforming routine radiological images into proactive tools for risk detection of major diseases.