As the inaugural chief data scientist for Stanford Health Care, Nigam Shah will lead an effort to advance the use of artificial intelligence in patient care and hospital administration.
March 3, 2022 - By Hanae Armitage
Nigam Shah, MBBS, PhD, professor of medicine and of biomedical data science, has been appointed Stanford Health Care’s inaugural chief data scientist.
The appointment was effective March 1.
Reporting to Michael Pfeffer, MD, associate dean and chief information officer at Stanford Health Care and the Stanford School of Medicine, Shah will lead an effort to integrate artificial intelligence into patient care, medical research and administrative services.
“There’s been a lot of excitement around using AI, algorithms and data to improve health care,” Shah said. “But broadly speaking, there’s been more talk about using AI than actual implementation of AI in health care delivery. Now, it’s time to change that.”
With Shah at the helm of Stanford Health Care’s AI and data science effort, the long-term vision is to harness artificial intelligence to support and enhance every aspect of health care delivery, AI research and medical education. Think smoother patient check-ins and discharges, automated symptom-monitoring and tailored care recommendations based on real-time data.
Shah will lead the effort, working with the Stanford Medicine Technology and Digital Solutions team to make the vision a reality. “To really execute on this successfully, you need a team of data scientists and information technologists — and someone who really, deeply understands both the artificial intelligence side and the business and technology side,” Pfeffer said. “That’s where the chief data scientist role comes in. And Nigam is a perfect fit.”
Shah will collaborate extensively with individuals across clinical specialties and operational areas to deploy algorithms that can lead to better patient outcomes, add efficiencies and lower cost, said Michael Halaas, chief operating officer at the School of Medicine and associate dean. “There is a great deal of hype in this area, so having a leader who can help guide strategy and provide expertise in the field will help Stanford Health Care deploy AI in a thoughtful, well-managed way,” he said.
It’s all about improving patient care.
At its core, the effort will center on how Stanford Health Care accelerates innovations around artificial intelligence — from development and implementation to maintenance and optimization, Pfeffer said. David Entwistle, president and CEO of Stanford Health Care; Lloyd Minor, MD, dean of the School of Medicine; and Robert Harrington, MD, chair of the Department of Medicine, “have all made significant contributions in thinking through this role and how we can best integrate it into the care delivery system at Stanford Health Care,” Pfeffer added. “It’s fair to say we’re all very excited to see this come to fruition.”
Enhancing care delivery
As the new role gets underway, Shah described three main areas of impact for AI in health care: advancing the scientific understanding of disease, improving the practice of clinical medicine and orchestrating the delivery of health care. In achieving some of these goals, he plans to collaborate with academic groups at the Stanford School of Medicine, such as the Center for Biomedical Informatics Research, the Department of Biomedical Data Science, the Clinical Excellence Research Center, the Center for AI in Medicine and Imaging and the Human Centered AI Institute.
For instance, researchers at Stanford Medicine already are demonstrating how algorithms could help doctors differentiate new subtypes of disease, allowing them to precisely treat individual patients. AI could help health care teams provide better end-of-life counseling or help smooth out wrinkles in scheduling, anticipating who might miss an appointment and sending additional reminders. Algorithms could help physicians proactively monitor patient record and flag patients who might have undiagnosed genetic disorders.
“It’s all about improving patient care,” Shah said. “I want patients to say, ‘This was the most proactive care I’ve ever had,’ or ‘Scheduling was a breeze,’ or ‘My surgery ran late, but thank goodness my wife was informed that she should come an hour later.’ These things aren’t necessarily going to be the basis for big flashy papers, but that’s okay.”
Implementation of artificial intelligence across the health delivery system undoubtedly will be a boon to patients and providers alike, Shah said. The trick, he added, is to integrate AI in a way that does not disrupt an already stretched health care ecosystem.
“In addition, we need to be cognizant of equity and fairness when considering adopting AI-guided decision making and be open to the possibility that there will be situations in which we should not be using AI,” Shah said. “Building and integrating an algorithm into any workflow will have ripple effects that are beyond just what the algorithm does. So we’re thinking about AI integration as an overall delivery science. It’s not just the algorithms we need to consider; the algorithms and clinicians must work as partners.”
The aim is not to have every decision made by an algorithm but to have every decision supported by one, he added.
A (hypothetical) case in point
Shah further illustrates the potential of artificial intelligence through a somewhat futuristic, hypothetical patient scenario. Vera, a 60-year-old woman with a history of high blood pressure and asthma, comes to the hospital. She arrives with shortness of breath. Her physician must diagnose and treat her condition and consider how to monitor her future health risks, such as heart failure, as well as evaluate her risk for chronic diseases, such as heart attack, stroke and kidney failure. That’s a lot of data to collect.
But what if Vera could don a wearable device that monitors her heart rhythm, respiration, blood glucose levels and blood pressure? This continuous flow of data would provide a real-time view of Vera’s health, and with AI-powered algorithms, her care-team could precisely and accurately monitor her health. (Perhaps an extended, irregular heart rhythm would trigger an alert for her doctor, and a scheduling system would automatically contact her with times for an available appointment.)
While this case is hypothetical, and Vera fictional, the situation she finds herself in is common for both patients and providers.
“What if we could do that — and more — for every single patient? Broadly speaking, part of this is looking at how AI can support personalization of health care at a massive scale,” Shah said. “The point is to bring AI into clinical use safely, ethically and cost effectively, writ large.”
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