Aligning AI principles and healthcare delivery organization best practices to navigate the shifting regulatory landscape
As artificial intelligence (AI) becomes further embedded in healthcare, healthcare delivery organizations (HDOs) must navigate a complex regulatory landscape. Health AI Partnership (HAIP) has created 31 best practice guides to inform the development, validation, and implementation of AI products. Here, we map the most common principles found in 8 key AI regulatory frameworks to HAIP recommended best practices to provide practical insights for compliance with expanding AI regulations.
Authors
- Alexandra Valladares
- Suresh Balu (ORCID: https://orcid.org/0000-0003-4929-9130)
- Manesh R. Patel (ORCID: https://orcid.org/0000-0002-2393-0855)
- Shreya Rao (ORCID: https://orcid.org/0009-0008-9823-7263)
- Keo Shaw (ORCID: https://orcid.org/0009-0001-7923-3952)
- Mark A. Lifson (ORCID: https://orcid.org/0000-0003-4717-7930)
- Jee Young Kim (ORCID: https://orcid.org/0000-0003-4850-9757)
- Shira Zilberstein (ORCID: https://orcid.org/0000-0001-7564-727X)
- Alifia Hasan (ORCID: https://orcid.org/0009-0000-1361-3744)
- Noah Prizant (ORCID: https://orcid.org/0009-0006-8629-0978)
- Danny Tobey
- Mark Sendak (ORCID: https://orcid.org/0000-0001-5828-4497)
- David Vidal (ORCID: https://orcid.org/0009-0009-6268-8481)
Institutions
- Duke University (US)
- Durham Technical Community College (US)
- Harvard University Press (US)
- North Carolina Nursery and Landscape Association (US)
- Duke Institute for Health Innovation (US)
- Mayo Clinic in Arizona (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1038/s41746-025-01605-2
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.96
Funders
- Gordon and Betty Moore Foundation