HAIP works with a diverse group of expert practitioners to surface and develop guidance that supports the development, evaluation, and integration of AI solutions in healthcare. These insights are organized and presented to be easily retrievable and consumable guides.

Why does it matter?

• Easy to use. We want to do as much work as we can to make things simple for our audience. We want to make it easy for healthcare organizations to use AI safely, effectively, and equitably.
• Build trust. Our topic guide editors are hand-picked to be experts in the field. They have experience on the ground to be able to share specific guidance.
• Learn as you go. Over time, we hope to build capabilities among a broad community of US healthcare organizations. Our content is highly structured and directional. We point out dependencies and help guide how projects should progress.

How to do this?

Step 1. For each guide, a team of research support staff pulls together material from:

• Primary qualitative data was gathered through interviews with practitioners, expert key informants, and community members from across the network. Where possible, we embed de-identified quotes to emphasize the role that on-the-ground experience plays in developing content.
• Reviews of published literature, policy documents, and standards.

Step 2. Expert topic editors contribute their expertise to flesh out the guidance.

Step 3. Project team members reformat and distill the guides into a common structure:

• “Why does it matter” with bullets
• “How to do this” with steps broken out

Step 4. The leadership team reviews all topic guide updates to sign off on changes.

Step 5. Topic guides get published and updated on our resource page.

Step 6. Our audience (i.e., you!) help improve the content by letting us know what’s missing, where things can be done differently, and contributing case studies.