ArticlePolicy studies (Policy Studies Institute)2025
An ecosystem approach to governing commercial actors in healthcare AI.
Article in Policy studies (Policy Studies Institute), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- A global call to action on the digital determinants of health.NPJ digital medicine · 2026Review
- Preventing Diffusion of Moral Responsibility in Big Team Science: Taking an Ecosystem Approach.The Hastings Center reportArticle
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The ever-increasing attention to artificial intelligence applications in medicine and healthcare requires us to critically evaluate the effectiveness of the current U.S. regulatory environment in this arena. We outline a series of challenges facing the governance of healthcare AI, including an overreliance on self-regulation when many AI developers lack knowledge of relevant regulation or acknowledge their role in preventing harms, lack of shared responsibility for healthcare AI harms, and the lack of transparency and availability of evidence to assess healthcare AI's safety and effectiveness. We advocate for an ecosystem approach to developing potential solutions to these governance challenges. In particular, we identify actions that civil society organizations, funders, healthcare system purchasers, and payers can take to advance healthcare AI governance. We argue that these actors should make coordinated efforts toward advancing transparency and independent assessment of healthcare AI, and therefore can help fill gaps created by the emphasis on self-regulation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.