Session Description 

This talk will showcase a recent study published in JAMA Internal Medicine that demonstrated the effectiveness of an AI-enabled intervention using the Epic Deterioration Index (EDI) in reducing care escalations among hospitalized patients. The study found a significant 10.4% absolute risk reduction in rapid response team activations and ICU transfers. This cohort study found that the implementation of an artificial intelligence deterioration model–enabled intervention was associated with a significantly decreased risk of escalations in care among inpatients.

Video Recording

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Speaker

Dr. Ron Li, MD | Clinical Associate Professor, Department of Medicine, Stanford University, Stanford, California

Ron Li is a Clinical Associate Professor of Medicine in the Division of Hospital Medicine and Center for Biomedical Informatics Research at Stanford University School of Medicine. As the Medical Informatics Director for Digital Health at Stanford Health Care, he provides medical and informatics direction for the health system’s enterprise digital health portfolio, including expanding digital referral networks and virtual care modalities. He is the co-founder and Director for the Stanford Emerging Applications Lab (SEAL), which helps clinicians and staff build ideas into novel digital products that are prototyped and tested for care delivery at Stanford Health Care.

Ron’s academic interests focus on the “delivery science” of new technological capabilities such as digital and artificial intelligence in healthcare and how to design, implement, and evaluate new tech enabled models of care delivery. Ron’s work spans across multiple disciplines, including clinical medicine, data science, digital health, information technology, design thinking, process improvement, and implementation science. He has consulted for various companies in the digital health and artificial intelligence space. He is an attending physician on the inpatient medicine teaching service at Stanford Hospital and is the Associate Program Director for the Stanford Clinical Informatics Fellowship.

Featured Discussant

Dr. Gabriel Escobar, MD | Kaiser Permanente Northern California Division of Research

Gabriel J. Escobar, MD, is a retired research scientist at the Kaiser Permanente Northern California Division of Research. He was director of the Division of Research Systems Research Initiative (a research program focusing on adult hospital processes and outcomes, informatics, and program evaluation); and Regional Director for Hospital Operations Research for Kaiser Permanente Northern California, in which capacity he worked to improve Kaiser Permanente’s internal reporting and quality measurement capabilities. Dr. Escobar received his medical degree from Yale University School of Medicine; completed his pediatrics residency at University of California, San Francisco; and was a Robert Wood Johnson Clinical Scholar at Stanford University School of Medicine.  He is board certified in Clinical Informatics.

Dr. Escobar’s research interests included risk adjustment, predictive modeling, severity-of-illness scoring, the use of comprehensive inpatient and outpatient electronic medical records for health services research, and the use of real-time decision support tools that are embedded in the electronic record. Between 1991 and 2001, Dr. Escobar developed a research program in neonatology for Kaiser Permanente Northern California. In 2009 he turned over the neonatology research program to Michael Kuzniewicz, MD, at the Division of Research so that he could focus on the work of the Systems Research Initiative. Dr. Escobar also worked as a pediatric hospitalist at the Kaiser Permanente Walnut Creek, Antioch, and Oakland Medical Centers between 1984 and 2016.

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