Core Issues for Federal AI Regulations

By Tina Joros, JD (Veradigm), Chair, and Stephen Speicher, MD, MS (Flatiron Health), Vice Chair, EHR Association AI Task Force

The regulatory landscape for AI is on the cusp of dramatic change. As we await the release of the AI Action Plan called for in the January 2025 Removing Barriers to American AI Innovation Executive Order and as federal agencies review their existing AI policies, we have seen an influx of proposed laws at the state level to address concerns about the use of AI in healthcare technology. This increase in state-level activity may lead to regulatory fragmentation that makes it more complex for EHR vendors and health systems to build and support AI tools designed to help advance patient care.

This increased focus on AI is highly relevant to EHR Association members who continue to deploy software capabilities that comply with EHR certification program transparency requirements for the use of Decision Support Interventions (DSI) involving AI and machine learning (ML) capabilities. Most of our member companies are also developing, piloting, or have already deployed generative AI solutions that can be leveraged to resolve many challenges confronting the healthcare industry.

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Finding the Right Balance: Smart Deregulation in Health IT

by Leigh Burchell (Altera Digital Health), Chair, EHR Association Executive Committee

The current administration has made deregulation a central policy priority, aiming to reduce burden and costs in as many sectors of the economy as possible, including health care. This is exemplified by the January 2025 Executive Order 14192: Unleashing Prosperity Through Deregulation, which requires federal agencies to eliminate ten regulations for each new one introduced. 

As the trade association for health IT developers, we believe that smart deregulation should focus on removing outdated, redundant, and low-value requirements with ASTP/ONC and CMS playing a role more focused on driving improvements in standardized interoperability and health data exchange. Health IT regulation should support—not hinder—the industry’s collective ability to deliver safe, effective, and innovative technology solutions, without compromising the progress made or devaluing the investments in health IT over the last fifteen years. As always, we remain committed to working alongside federal agencies within the construct of a regulatory environment that benefits providers, developers, and—most importantly—patients.

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HTI-1 Falls Short with DSI and Predictive Decision Support Proposals

By David Bucciferro, Chair, EHR Association

In other installments of this five-part blog series on the EHR Association’s issues with ONC’s Health Data, Technology, and Interoperability: Certification Program Updates, Algorithm Transparency, and Information Sharing Proposed Rule (HTI-1), we discussed our overarching concerns, as well as concerns with the Insights Condition program, transition to USCDI v3, and Patient Requested Restrictions. In this installment, we examine the considerable issues we have identified with provisions related to Decision Support Interventions (DSI) and Predictive Models.

According to ONC, the existing scope and structure of the Health IT Certification Program are to enhance transparency around predictive decision support, with requirements to make transparent information regarding the authorship, bibliographic, and other kinds of “source attribute” information for evidence-based decision support and linked referential interventions. Noting that AI/ML in healthcare “is often best considered a form of decision support or ‘augmented intelligence’,” ONC says its goal with the proposed rule related to DSI and predictive models is to update the existing decision support criterion to directly include predictive decision support, inclusive of ML technologies.

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