Introducing Dr. Nigam Shah, Chief Data Scientist at Stanford Health Care, as an Advisor to Define Ventures

We are thrilled to welcome Dr. Nigam Shah as an AI advisor to Define Ventures. A distinguished leader in healthcare AI, Dr. Shah serves as Chief Data Scientist at Stanford Health Care and is a Professor of Medicine and Biomedical Data Science at Stanford University,  where he oversees responsible use of artificial intelligence for advancing the scientific understanding of disease, improving the practice of clinical medicine and orchestrating the delivery of healthcare.

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His research focuses on safely, ethically, and cost-effectively translating AI into clinical practice. His work has been funded by four NIH institutes and has resulted in more than 350 publications (h-index 88), including in JAMA, The Lancet, Nature Digital Medicine, and The New England Journal of Medicine and has received over 38,000 citations.

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In addition to his academic contributions, Dr. Shah is an inventor on eight patents, has co-founded three companies, and serves as co-founder and board member of the Coalition for Health AI (CHAI). His pioneering work applying computational methods to complex healthcare problems, combined with his entrepreneurial experience, will provide invaluable insights to our partner companies.

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Ahead of this announcement, we spoke with Dr. Shah about his career, his vision for the future of AI in healthcare, and his advice for health tech entrepreneurs.

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Can you tell us about your career path and what led you to become the Chief Data Scientist at Stanford Health Care and Professor of Medicine?

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My career path has been a series of "fortunate accidents". After finishing medical school, I was on track to become an orthopedic surgeon, but a family friend encouraged me to consider research. The human genome project was just finishing, and the idea of using computation for human biology was gaining traction. I switched my focus to computation, building a reasoning engine for molecular biology as my PhD. Everybody told me that physicians who get into AI stuff all go to Stanford, so that’s where I went. I came to the campus as a postdoc in 2005 and never left.

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From 2005 to 2010, I worked as a postdoc and then a staff scientist, focusing on knowledge representation and building software systems at the Center for Biomedical Informatics Research. In 2010, I made the assumption that EHRs might become widely available, as the HI TECH Act had just passed and EHR adoption was taking off. This led me to build a research program focused on making sense of large amounts of EHR data. In 2015, I began to build a platform for this work, which became Atropos Health. Along the way, I also spun out two other companies.

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In 2020, I focused on using data science to help the health system navigate the pandemic. The following year, I wrote a two-page vision for data science in a health system, which caught the eye of our Dept. Chair, the Dean and CEO. That's how my current role as Chief Data Scientist was created in 2022.

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What inspired you to co-found three companies along the way?

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Through a year-and-a-half of training at the Stanford Medicine Leadership Academy, I reflected on the idea of “catching your own pass.” A university is an amazing place to research an idea into a peer-reviewed paper, but the journey of taking research to a product belongs in a company. Companies are a logical next step in the evolution of an idea and the only vehicle that can make something financially sustainable in the long term.

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What have been some of the most rewarding moments throughout your career?

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The most fun and consistent reward is working with people who are smarter than you and call them students. It’s often unclear who is teaching whom. Another major reward is when something we’ve built gets deployed and helps patients. For example, we used a simple AI model for advanced care planning for patients, and 6,000 to 7,000 patients have received better care because of it. When it was deployed and helped real people, and our quality metrics and patient experience went up, that was a fun and rewarding moment. Another one was when physicians started sharing stories of how another tool – ChatEHR – equipped them to deliver better care to our patients.

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Why are you interested in advising Define partner companies at this point in your career?

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There are so many good ideas that could benefit from the mistakes I’ve made in the past. One of the easiest ways to pay it forward is to share those mistakes. No one wants to write a paper about their mistakes, but they are often more valuable than the wins.

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What excites you the most about AI and healthcare today?

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What personally excites me is the potential to make a real difference in problems we have been talking about for 20 years. We are in the midst of a third AI hype cycle, and this wave is bigger than before. There’s a chance the disappointment could be equally big, but the best you can do is make use of it to swing for a few home runs. Never waste a crisis or a bubble.

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What advice do you have for startups trying to build lasting partnerships with health systems?

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Startups need to understand the anatomy of a healthcare system: who the decision makers are, and how the budgets work. The mistake I see over and over is that people read about advancements in the science of medicine and assume it directly translates to the business of medicine. To succeed, you must first understand who pays whom, how much, when and why. This is the single most important thing to learn before you even write a single line of Python code for AI in healthcare.

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We are incredibly excited to welcome Dr. Shah to our team of advisors. His experience and unique perspective on the intersection of data science, entrepreneurship, and clinical care will be an immense asset to our partner companies. We look forward to working with him to build the next generation of great healthcare companies.

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