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Researchers create first-of-its-kind index of evolving policy landscape around health care AI

06.01.26 | The Mount Sinai Hospital / Mount Sinai School of Medicine

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New York, NY — [June 1, 2026] —As hospitals and health systems rapidly adopt artificial intelligence (AI) technologies, a new study by investigators at the Icahn School of Medicine at Mount Sinai finds that the policies governing health care AI are expanding quickly but remain fragmented across regulators, governments, and standards organizations.

Their findings were published in today’s online issue of npj Digital Medicine [https://doi.org/10.1038/s41746-026-02734-y].

The researchers analyzed 240 health care AI-related policies published between 2016 and 2025 using their newly developed framework called the Health & AI Policy Index . The analysis found that oversight efforts are accelerating worldwide, though no single, unified framework currently exists to guide how AI should be deployed, monitored, and governed in clinical settings.

The findings come as AI tools are increasingly being used in patient care, diagnostics, administrative workflows, and clinical decision support, raising growing questions about safety, accountability, transparency, and implementation standards.

“Artificial intelligence is moving into health care faster than many organizations can fully evaluate or govern it,” says lead author Will Moss, a health care AI policy intern at the Icahn School of Medicine at Mount Sinai. “Our goal was to create a clearer picture of the rapidly evolving policy landscape and help health systems better understand the governance challenges emerging alongside AI adoption.”

The researchers found that governance efforts are developing through a patchwork of regulations, institutional guidance, technical standards, and policy initiatives rather than through a centralized system. The authors say this fragmented environment may create operational and compliance challenges for health systems attempting to responsibly integrate AI technologies.

“Health systems are increasingly recognizing that successful AI adoption requires more than just implementing new tools,” says senior author Girish N. Nadkarni, MD, MPH , Chair of the Windreich Department of Artificial Intelligence and Human Health , Director of the Hasso Plattner Institute for Digital Health , and Irene and Dr. Arthur M. Fishberg Professor of Medicine at the Icahn School of Medicine at Mount Sinai, and Chief AI Officer of the Mount Sinai Health System. “It also depends on strong oversight, internal governance structures, and clear accountability around how these technologies are used.”

The study also highlights the growing role academic medical centers and large health systems may play in shaping real-world AI governance practices as adoption accelerates.

“Questions around transparency, patient safety, and accountability are becoming central to the future of health care AI,” says Dr. Nadkarni. “Our work helps identify where policy efforts are growing, where gaps remain, and where additional coordination may be needed.”

To conduct the study, researchers used the Health & AI Policy Index to catalog and analyze health care AI-related policies published over nearly a decade. The framework was designed to help track emerging policy trends and better organize the rapidly growing body of AI policy activity affecting health care delivery.

The authors say the findings may help policymakers, researchers, and health systems better navigate the increasingly complex governance environment surrounding clinical AI technologies.

Future work may include analyzing how governance approaches differ across jurisdictions and how health systems operationalize AI governance in real-world clinical settings.

The paper is titled “Mapping AI regulation in health care with the Health & AI Policy Index.”

The authors, as listed in the journal, are Will Moss, Benjamin S. Glicksberg, Sabina Lim, Alexis Zebrowski, and Girish N. Nadkarni.

To view competing interests, see the paper at https://doi.org/10.1038/s41746-026-02734-y .

For more Mount Sinai artificial intelligence news, visit https://icahn.mssm.edu/about/artificial-intelligence .

About Mount Sinai's Windreich Department of AI and Human Health

Led by Girish N. Nadkarni, MD, MPH—an international authority on the safe, effective, and ethical use of AI in health care—Mount Sinai’s Windreich Department of AI and Human Health is the first of its kind at a U.S. medical school, pioneering transformative advancements at the intersection of artificial intelligence and human health.

The Department is committed to leveraging AI in a responsible, effective, ethical, and safe manner to transform research, clinical care, education, and operations. By bringing together world-class AI expertise, cutting-edge infrastructure, and unparalleled computational power, the department is advancing breakthroughs in multi-scale, multimodal data integration while streamlining pathways for rapid testing and translation into practice.

The Department benefits from dynamic collaborations across Mount Sinai, including with the Hasso Plattner Institute for Digital Health at Mount Sinai—a partnership between the Hasso Plattner Institute for Digital Engineering in Potsdam, Germany, and the Mount Sinai Health System—which complements its mission by advancing data-driven approaches to improve patient care and health outcomes.

At the heart of this innovation is the renowned Icahn School of Medicine at Mount Sinai, which serves as a central hub for learning and collaboration. This unique integration enables dynamic partnerships across institutes, academic departments, hospitals, and outpatient centers, driving progress in disease prevention, improving treatments for complex illnesses, and elevating quality of life on a global scale.

In 2024, the Department's innovative NutriScan AI application, developed by the Mount Sinai Health System Clinical Data Science team in partnership with Department faculty, earned Mount Sinai Health System the prestigious Hearst Health Prize. NutriScan is designed to facilitate faster identification and treatment of malnutrition in hospitalized patients. This machine learning tool improves malnutrition diagnosis rates and resource utilization, demonstrating the impactful application of AI in health care.

For more information on Mount Sinai's Windreich Department of AI and Human Health, visit: ai.mssm.edu

About the Hasso Plattner Institute at Mount Sinai

At the Hasso Plattner Institute for Digital Health at Mount Sinai, the tools of data science, biomedical and digital engineering, and medical expertise are used to improve and extend lives. The Institute represents a collaboration between the Hasso Plattner Institute for Digital Engineering in Potsdam, Germany, and the Mount Sinai Health System.

Under the leadership of Girish Nadkarni, MD, MPH, who directs the Institute, and Professor Lothar Wieler, a globally recognized expert in public health and digital transformation, they jointly oversee the partnership, driving innovations that positively impact patient lives while transforming how people think about personal health and health systems.

The Hasso Plattner Institute for Digital Health at Mount Sinai receives generous support from the Hasso Plattner Foundation. Current research programs and machine learning efforts focus on improving the ability to diagnose and treat patients.

About the Icahn School of Medicine at Mount Sinai

The Icahn School of Medicine at Mount Sinai is internationally renowned for its outstanding research, educational, and clinical care programs. It is the sole academic partner for the seven member hospitals* of the Mount Sinai Health System, one of the largest academic health systems in the United States, providing care to New York City’s large and diverse patient population.

The Icahn School of Medicine at Mount Sinai offers highly competitive MD, PhD, MD-PhD, and master’s degree programs, with enrollment of more than 1,200 students. It has the largest graduate medical education program in the country, with more than 2,700 clinical residents and fellows training throughout the Health System. The Graduate School of Biomedical Sciences offers 13 degree-granting programs, conducts innovative basic and translational research, and trains more than 4705 postdoctoral research fellows.

Ranked 11th nationwide in National Institutes of Health (NIH) funding, the Icahn School of Medicine at Mount Sinai is among the 90th percentile of U.S. private medical schools in Sponsored Programs Direct Expenditures per Principal Investigator, according to the Association of American Medical Colleges. More than 6,900 scientists, educators, and clinicians work within and across dozens of academic departments and multidisciplinary institutes with an emphasis on translational research and therapeutics. Through Mount Sinai Innovation Partners (MSIP), the Health System facilitates the real-world application and commercialization of medical breakthroughs made at Mount Sinai.

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* Mount Sinai Health System member hospitals: The Mount Sinai Hospital; Mount Sinai Brooklyn; Mount Sinai Morningside; Mount Sinai Queens; Mount Sinai South Nassau; Mount Sinai West; and New York Eye and Ear Infirmary of Mount Sinai.

npj Digital Medicine

10.1038/s41746-026-02734-y

Observational study

Not applicable

Mapping AI regulation in health care with the Health & AI Policy Index

1-Jun-2026

Keywords

Article Information

Contact Information

Karin Eskenazi
The Mount Sinai Hospital / Mount Sinai School of Medicine
karin.eskenazi@mssm.edu

How to Cite This Article

APA:
The Mount Sinai Hospital / Mount Sinai School of Medicine. (2026, June 1). Researchers create first-of-its-kind index of evolving policy landscape around health care AI. Brightsurf News. https://www.brightsurf.com/news/19N6WZ01/researchers-create-first-of-its-kind-index-of-evolving-policy-landscape-around-health-care-ai.html
MLA:
"Researchers create first-of-its-kind index of evolving policy landscape around health care AI." Brightsurf News, Jun. 1 2026, https://www.brightsurf.com/news/19N6WZ01/researchers-create-first-of-its-kind-index-of-evolving-policy-landscape-around-health-care-ai.html.