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Appl Clin Inform 2025; 16(03): 612-613
DOI: 10.1055/a-2556-4698
Letter to the Editor

AI in Health Care: The Leadership Role of Board-Certified Clinical Informaticists

Keith E. Morse   *
1   Department of Pediatrics, Stanford School of Medicine, Stanford, California, United States
2   Digital Information Solutions, Stanford Medicine Children's Health, Palo Alto, California, United States
,
Natalie M. Pageler   *
1   Department of Pediatrics, Stanford School of Medicine, Stanford, California, United States
2   Digital Information Solutions, Stanford Medicine Children's Health, Palo Alto, California, United States
,
Nigam H. Shah
3   Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, United States
4   Clinical Excellence Research Center, Stanford School of Medicine, Stanford, California, United States
5   Technology and Digital Solutions, Stanford Healthcare, Palo Alto, California, United States
,
Tanya Townsend
2   Digital Information Solutions, Stanford Medicine Children's Health, Palo Alto, California, United States
,
Christopher Sharp
5   Technology and Digital Solutions, Stanford Healthcare, Palo Alto, California, United States
6   Department of Medicine, Stanford School of Medicine, Stanford, California, United States
,
Michael A. Pfeffer
5   Technology and Digital Solutions, Stanford Healthcare, Palo Alto, California, United States
6   Department of Medicine, Stanford School of Medicine, Stanford, California, United States
› Author Affiliations
Funding None.
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Health systems are gaining early experience with artificial intelligence (AI) as AI tools are implemented in hospitals. AI-savvy leaders are needed to oversee these tools and clinical informatics is an ideal background for such leaders.[1] This letter highlights the relevant expertise of board-certified clinical informaticists (BCIs) and offers recommendations for how organizations can leverage this expertise to ensure their AI adoption aligns with the “FAVES” (fair, appropriate, valid, effective, safe) principles endorsed by US Department of Health and Human Services (HHS).[2]

Clinical informatics, officially recognized by the American Board of Medical Specialties (ABMS) in 2011, centers on using data and technology to enhance patient care.[3] Specialized training through a 2-year clinical informatics fellowship is now offered at over 60 institutions nationally.[4] This subspecialty demands proficiency in areas such as health information systems, data governance, and change management. While its practitioners have historically been tapped to lead the implementation of electronic health record (EHR) systems, their skill set makes them uniquely qualified to lead the successful adoption of AI technologies. These skills are outlined explicitly in requirements for training[5] [6] [7] and board certification,[8] [9] as well as evidenced in the real-world experience of its practitioners.[10] [11]

Critically, BCIs are among the few medical professionals trained in the fundamentals of AI and data science. AI is a core content area on board examinations and a perennial focus at national conferences. A recent survey showed that, during their 2 years of fellowship, 37% of trainees built AI tools themselves.[11] This experience in AI is augmented by expertise in the health data fed into models. BCIs understand the ontologies and coding schema (e.g., SNOMED, LOINC) that organize the data, the database systems that store it, and the interoperability building blocks (e.g., FHIR, HL7) that move it.

BCIs are adept at designing and implementing clinical workflows to integrate new technologies. As clinicians, they understand the frustration of poorly designed interventions and can develop AI systems that enhance rather than disrupt existing clinical processes.[12] Once implemented, they can apply best practices from EHR optimization by monitoring for common issues arising from workflow disruptions, alert fatigue, or automation bias. Finally, they can evaluate the AI system's ultimate impact on the care process, quantifying its overall impact on patient outcomes and provider experience.[13]

More broadly, BCIs bring essential leadership skills needed to guide health care organizations through AI integration. Deployment relies heavily on successful change management and BCIs are skilled in managing the human elements of technology adoption, fostering stakeholder buy-in through interdisciplinary communication, comprehensive training, and feedback collection. They are uniquely positioned to lead multidisciplinary teams bridging gaps among clinicians, data scientists, IT departments, and operational leaders.

The novel regulatory and ethical challenges posed by AI require coordination among disciplines, with health policy, compliance, and ethical experts now vital contributors to AI governance.[14] Experts advocate for a more defined role for BCIs in AI regulatory oversight, such as at a recent FDA Digital Health Advisory Committee meeting, calling for formal clinical informaticist review of model safety information prior to integration into patient care.[15]

To take advantage of BCIs skill sets, health system leaders should consider recruitment, new role creation, and ongoing training. To recruit BCIs, consider both dedicated efforts to hire qualified BCIs and including “clinical informatics” as a desirable ancillary experience in traditional clinical job postings. Interested early career physicians can be encouraged (and funded) to complete clinical informatics fellowship and board certification. And finally, define new, clear job descriptions in which the BCI will serve.

New roles must be created that both reflect the organization's needs and provide a reasonable chance for the candidate's success. Depending on strategic priorities, this role could focus on the development of an AI roadmap, leading AI governance, coordinating the creation of core AI infrastructure, identifying high-priority applications of AI, or evaluating the efficacy of deployed AI tools.[1] It should also lead the efforts to educate and train those expected to use the AI algorithms. Success in these tasks relies heavily on collaboration among medical specialties and health system roles, thus the role should sit at a system-wide level to enable multidisciplinary engagement. Such expansive responsibilities cannot be met without funded support, typically starting at 1 to 2 days per week. This role should report to executive leadership with strong ties to the organization's IT Department, typically the CIO, CMIO, or Chief AI Officer.

Finally, because of the rapid evolution of AI's capabilities and its applications, ongoing training opportunities are needed. This comes in the form of regular conference attendance, online coursework, vendor demonstrations, and informal engagement with other AI leaders.

In an era where much of the health care workforce needs AI upskilling, BCIs are already well-prepared. These individuals stand ready to lead the comprehensive integration of AI into patient care as well as ensure its ongoing monitoring and evaluation as envisioned by regulators. It is incumbent upon health systems to recruit these leaders to ensure that health care innovation proceeds not by chance, but by deliberate design.

* co-first authors.




Publication History

Received: 01 December 2024

Accepted: 11 March 2025

Article published online:
02 July 2025

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