Collaborative Develops AI Vendor Disclosure Framework

Why It Matters

Standardizing AI vendor disclosures reduces procurement risk and accelerates responsible AI deployment across health systems, addressing a critical gap in current evaluation practices.

Key Takeaways

• HAIP released free AI Vendor Disclosure Framework in NEJM AI.
• Framework covers five domains: capabilities, performance, data stewardship, integration, lifecycle.
• Aims to improve transparency and safety in healthcare AI procurement.
• Developed with input from leaders like Vega Health CEO Mark Sendak.
• Initial funding came from Gordon and Betty Moore Foundation in 2022.

Pulse Analysis

Healthcare organizations face mounting pressure to adopt artificial‑intelligence tools, yet the lack of consistent vendor information hampers sound decision‑making. Traditional model‑cards provide high‑level summaries for clinicians, but they fall short when procurement teams need detailed metrics on performance, bias, and regulatory status. By consolidating these data points into a single framework, HAIP fills a crucial void, enabling CIOs and CMIOs to compare solutions on a level playing field and mitigate hidden risks.

The AI Vendor Disclosure Framework structures vendor communication across five domains: system capabilities and intended use, performance and compliance, data stewardship, integration requirements, and lifecycle management. Each domain prompts vendors to disclose operational metrics, bias assessments, security protocols, total cost of ownership, and post‑implementation support plans. This granular approach transforms vague promises into actionable criteria, allowing health systems to align AI investments with strategic objectives and compliance mandates. Compared with existing model‑cards, the framework offers a procurement‑focused lens that bridges the gap between clinical utility and operational feasibility.

Adoption of the framework could reshape the competitive landscape for AI vendors, incentivizing greater transparency and rigorous validation. As health systems increasingly tie AI procurement to value‑based care goals, standardized disclosures become a differentiator for vendors seeking market share. Moreover, the collaborative nature of HAIP—backed by the Gordon and Betty Moore Foundation and anchored at Duke’s Institute for Health Innovation—signals a broader industry shift toward shared governance and community‑driven standards. In the long term, such frameworks may pave the way for regulatory bodies to reference best‑practice disclosures, further embedding responsible AI practices into the fabric of healthcare delivery.