Artificial Intelligence and Health

Our faculty are examining the benefits and potential pitfalls of using Artificial Intelligence (AI) in health care and policy. They are investigating biases behind algorithms and the accuracy and transparency of machine learning, while studying ethical issues that arise as AI tools are integrated into hospital care, and exploring legal and regulatory strategies to protect patient safety, data privacy, and patients' and health-care practitioners' interests.

Michelle Mello testifies before U.S. Senate Committee on Finance

Testifying Before the U.S. Senate

In her testimony before the U.S. Senate Finance Committee, SHP's Michelle Mello emphasized the need for federal guardrails and standards regarding the use of artificial intelligence in health care.

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TRIPOD+AI: Guidelines for Clinical Prediction Models

Sherri Rose joins global network of health experts to improve the transparency and accuracy of prediction algorithms.

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Applying Machine-Learning Approaches to Antibiotic Resistance

Jonathan Chen and Mary K. Goldstein are using data science and machine learning to help doctors and health-care facilities make better informed decisions to combat antimicrobial resistance.

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Health Equity and AISherri Rose explains the importance of equity and fairness when using AI and machine learning tools to develop health-care platforms.

Understanding Liability Risks from Healthcare AI ToolsMichelle Mello examines how courts are grappling with the challenges of adjudicating liability for software-related injuries and how health systems and clinicians can assess and manage AI liability risk. 

Health Policy ForumSherri Rose and Bob Kocher of Venrock Healthcare debate and discuss the future of AI in health care. 

SHP Faculty Policy Briefs with Stanford Institute for Human-Centered Artificial Intelligence

Understanding Liability Risk from Healthcare AI

Balancing Fairness and Efficiency in Health Plan Payments

The Safe Inclusion of Pediatric Data in AI-Driven Medical Research

AI algorithms often are trained on adult data, which can skew results when evaluating children. A perspective piece by SHP's Sherri Rose and several Stanford Medicine colleagues lays out an approach for pediatric populations.

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Developing Ethics in AI

Michelle Mello and colleagues are using award from the Patient-Centered Outcomes Research Institute (PCORI) to build a practical, patient-centered method for ethical review of AI tools.

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Removing Race Adjustment in Chronic Kidney Disease Care

A new study led by Stanford Health Policy researchers finds that algorithmic changes to a chronic kidney disease care equation are likely insufficient to achieve health equity as many other structural inequities remain.

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Using Artificial Intelligence Tools and Health Insurance Coverage Decisions

It would seem like AI would be a logical tool to help evaluate insurance coverage and claims. But results so far have been sobering, leading to class-action lawsuits and congressional committees demanding answers.

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Exploring Liability Risks of Using AI Tools in Patient Care

SHP's Michelle Mello and co-author analyzed more than 800 tort cases involving both AI and conventional software in health care and non-health-care contexts to see how decisions related to AI and liability might play out in the courts.

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AI Alone Will Not Reduce the Administrative Burden of Health Care

In this JAMA Network Viewpoint, Stanford Health Policy's Kevin Schulman and Perry Nielsen Jr. look at the impact Large Language Models could have on our complex health-care billing system.

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Biden’s Executive Order on AI—Implications for Health Care Organizations

Michelle Mello and colleagues write in the journal JAMA that President Biden's recent executive order on Artificial Intelligence could have significant implications for health-care organizations.

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