Ensuring use of AI to improve health meets its full potential reliably and safely

Regenstrief research scientist is co-editor of National Academy of Medicine draft Code of Conduct for AI use

INDIANAPOLIS – Artificial intelligence (AI) is playing an ever-increasing role in health and healthcare in myriad arenas including disease diagnosis, imaging interpretation, clinician support, drug development, treatment advances and numerous data retrieval and analysis functions.

Andrew A. Gonzalez, M.D., J.D., MPH, of the Regenstrief Institute and the Indiana University School of Medicine, is a co-editor, on behalf of the National Academy of Medicine and its Artificial Intelligence Code of Conduct initiative, of a draft Code of Conduct to ensure that the use of AI to revolutionize healthcare and improve health outcomes meets its full potential reliably and safely.

Based on an extensive review of existing literature surrounding AI guidelines, frameworks and principles, Dr. Gonzalez and colleagues identify a series of 10 Code Principles and six Code Commitments to ensure that best practices maximize AI’s benefits to human health and well-being while minimizing potential risks.

“Artificial intelligence can contribute to health and healthcare in a variety of ways,” said Dr. Gonzalez. “For example, our lab is focusing on using AI for tasks it’s really good at, such as administrative work, and on narrow but superhuman assignments like tracking a large number of variables – including the contents of electronic health records — and then coming up with an answer for the clinician to review regarding next steps, including diagnosis and treatment.

“In deploying AI-based systems in real clinical settings, you want to ensure that the systems are reliable, accurate and safe. We have identified equity or rather lack of equity as a key challenge as artificial intelligence in healthcare becomes increasingly ubiquitous. That’s equity in the sense of making sure that the data upon which these AI systems are trained represent the patient populations in which they might be used.

“Outside of equity reliability concerns, there’s the accuracy concern, particularly with generative models that have the ability to create new text or new data. The third big area is safety. As these systems get more and more used, we want to make sure that we have a separate system in place that evaluates the safety of, basically, the overall healthcare system.”

Dr. Gonzalez and co-editors of the draft Code of Conduct note that other challenges presented by the use of AI in the healthcare environment include engagement, effectiveness, efficiency, accessibility, transparency, accountability, security and adaptiveness.

The proposed National Academy of Medicine AI use code commitments are:

1. Focus: Protect and advance human health and human connection as the primary aims.
2. Benefits: Ensure equitable distribution of benefit and risk for all.
3. Involvement: Engage people as partners with agency in every stage of the life cycle.
4. Workforce well-being: Renew the moral well-being and sense of shared purpose to the healthcare workforce.
5. Monitoring: Monitor and openly and comprehensively share methods and evidence of AI’s performance and impact on health and safety.
6. Innovation: Innovate, adopt, collaboratively learn, continuously improve and advance the standard of clinical practice.

The goal, as noted in the paper, “is that all decisions associated with, and actions taken, to develop and deploy AI in the health sector will be consisted with these Commitments to develop and foster trust.”

“Artificial Intelligence in Health, Health Care, and Biomedical Science: An AI Code of Conduct Principles and Commitments Discussion Draft” is published in NAM Perspectives and is publicly available on the National Academy of Medicine website.

Editors as listed in the publication

• Laura Adams, M.S., is a Senior Advisor at the National Academy of Medicine.
• Elaine Fontaine, B.S., is a Consultant at the National Academy of Medicine. 
• Steven Lin, M.D., is a Clinical Professor of Medicine, the Section Chief of General Primary Care, and the Director of the Stanford Healthcare AI Applied Research Team Division of Primary Care and Population Health at Stanford University School of Medicine.
• Trevor Crowell, B.A., is a Research Associate with the Stanford Healthcare AI Applied Research Team (HEA3RT) at the Stanford University School of Medicine.
• Vincent C. H. Chung, PhD, is an Associate Professor at the JC School of Public Health and Primary Care, The Chinese University of Hong Kong.
• Andrew A. Gonzalez, M.D., J.D., MPH, is Associate Director for Data Science at the Regenstrief Institute Center for Health Services Research and Co-Director of the Indiana University School of Medicine’s Center for Surgical Outcomes & Quality Improvement Center.

This work was conducted with the support of the California Healthcare Foundation, Epic, Gordon and Betty Moore Foundation, National Institutes of Health and Patrick J. McGovern Foundation.

Read the National Academy of Medicine press release.

Andrew A. Gonzalez, M.D., J.D., MPH
In addition to his role as a research scientist and associate director for data science with the William M. Tierney Center for Health Services Research at Regenstrief Institute, Andrew Gonzalez, M.D., J.D., MPH, is a practicing vascular surgeon and an assistant professor of surgery at the Indiana University School of Medicine. Dr. Gonzalez is also a faculty affiliate with the Regenstrief Center for Healthcare Engineering at Purdue University.