Authors
Sena Kpodzro, Jee Young Kim, Alifia Hasan, Ciera Thomas, Michael Draugelis, Scott Morgan Jeffries, Ashley Beecy, Corinne Stroum, Alexandra Valladares, Zev Eigen, Danny Tobey, David E Vidal, Mark A Lifson, Deirdre Mulligan, Suresh Balu, Mark Sendak
Published in
NEJM AI. Volume 3. Issue 5. Pages AIp2500985. Epub Apr 23, 2026.
Abstract
AbstractHealth care delivery organizations (HDOs) face significant challenges in evaluating vendor-developed artificial intelligence (AI) systems owing to limited guidance on what information to request from vendors during procurement. As a result, vendors often provide inconsistent or incomplete responses, making it difficult to assess clinical relevance, safety, and implementation readiness. To address this gap, we developed the Health AI Partnership (HAIP) AI Vendor Disclosure Framework, a community-informed tool designed to support responsible AI system procurement. The framework identifies essential information across five core domains that HDOs should request - and vendors should disclose - to effectively evaluate vendor-developed AI systems: (1) system capabilities and intended use, (2) system performance and compliance, (3) data stewardship, (4) integration requirements, and (5) life cycle management. By standardizing expectations for the information needed in procurement decision-making, the framework aims to enhance transparency and promote safer health care AI adoption. It serves both as a best practice guide and a customizable resource to support HDOs in procuring vendor-developed AI systems. (Funded by the Gordon and Betty Moore Foundation.).
PMID:
42932684
Bibliographic data and abstract were imported from PubMed on 27 Oct 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 24
- Comments 0