AI Transparency on FHIR (Jira PSS-2579)

The AI Transparency in FHIR Project is necessary to establish standards for documenting and tracking the use of outputs from AI systems or inference algorithms, including generative AI and Large Language Models (LLMs), within FHIR resources and operations. This project may help to inform regulatory requirements such as the Assistant Secretary for Technology Policy/Office of the National Coordinator for Health Information Technology (ASTP/ONC) Health Technology Infrastructure (HTI-1) final rule requirements for AI transparency in certified health IT. Design patterns identified in this project may also apply to its representation in other HL7 product families like Clinical Document Architecture (CDA) and HL7v2.

Artificial Intelligence (AI) represents amazing potential to improve outcomes in healthcare. However, it comes with a number of challenges, such as it is generally probabilistic in nature, can be influenced by bias, and can suffer from AI-generated hallucinations (inaccurate or misleading information). It is critical that we provide guidance for how to tag data coming from AI in a way that it can be used responsibly by downstream systems and users.