On December 13, the U.S. Department of Health and Human Services (HHS) through the Office of the National Coordinator for Health Information Technology (ONC) finalized its Health Data, Technology, and Interoperability: Certification Program Updates, Algorithm Transparency, and Information Sharing (HTI-1) rule.

Among other things, the rule establishes the first transparency requirements for artificial intelligence and other predictive algorithms that are part of certified health IT.

High-level highlights include:

• The rule introduces transparency requirements for AI and other predictive algorithms used in certified health IT.
• These requirements aim to promote responsible AI allowing clinical users to access a consistent, baseline set of information about algorithms they use to support their decision making and to assess such algorithms for fairness, appropriateness, validity, effectiveness, and safety.
• HHS is concerned with AI and machine learning technology used to aid decision-making, including clinical decision support and decision support interventions. The rule focuses on a definition of AI/ML as “predictive decision support interventions” (or Predictive DSIs) which means “technology intended to support decision-making based on algorithms or models that derive relationships from training or example data and then are used to produce an output or outputs related to, but not limited to, prediction, classification, recommendation, evaluation, or analysis.”
• Transparency requires developers to provide details on software development and functionality, including funding sources, decision-making role, and whether the output is a prediction, classification, recommendation, evaluation, analysis, or other type of output.

In addition to AI transparency the rule revises some information blocking definitions and exceptions (including clarifying the infeasibility exception process) and adds an additional exemption for the Trusted Exchange Framework and Common Agreement.