Becker’s Healthcare Podcast - Detailed Summary
Episode: Dr. Nigam Shah, Chief Data Scientist at Stanford Health Care
Release Date: July 5, 2025
Host: Jacob Emerson
Introduction
In this episode of the Becker’s Healthcare Podcast, host Jacob Emerson welcomes Dr. Nigam Shah, the Chief Data Scientist at Stanford Health Care. The conversation delves into Dr. Shah's role, his background in healthcare data science, and the innovative ambient AI pilot project Stanford is launching in collaboration with Atropos Health.
Dr. Nigam Shah’s Background and Role
Dr. Shah provides an insightful overview of his journey in healthcare data science:
“I often joke I've never had a real job. I got my PhD from Penn State, came to Stanford as a postdoc in 2005 and never left. Been on the faculty since 2011, tenured in 2015... and got sucked into working on things during the pandemic in the health system and found it very rewarding to do things in an operational environment.” (00:27)
In 2022, Stanford established the role of Chief Data Scientist to bridge the gap between data science and practical patient care, aiming to translate complex data analytics into actionable insights that directly benefit patient outcomes.
Ambient AI Pilot with Atropos Health
A significant portion of the discussion centers around Stanford’s ambient AI pilot project in collaboration with Atropos Health. This initiative integrates real-world evidence within the Electronic Health Record (EHR) system using ambient AI technology provided by Microsoft Dax.
Dr. Shah explains the evolution and functionality of this project:
“We did a project here called the Green Button Project that took that nine month time frame down and got it to under two days... Atropos took those 48 hours, turned around and got it down to under three to four hours.” (01:46)
The collaboration aims to further reduce the response time to under five minutes by combining real-time transcription of patient-physician conversations with automated generation of observational studies. This allows physicians to receive relevant, evidence-based reports almost instantaneously during patient encounters.
Impact on Physicians and Patient Care
The integration of ambient AI is poised to transform both physician workflows and patient interactions. Dr. Shah outlines the anticipated benefits:
“Ambient scribes are used in the outpatient setting... this will be the first time that real world evidence will be offered in the outpatient setting on demand, at the point of care.” (05:05)
By automating documentation and evidence generation, physicians can focus more on patient care rather than administrative tasks. The technology enables real-time access to relevant studies and data-driven insights, enhancing decision-making processes.
From the patient’s perspective, Dr. Shah paints a picture of a more interactive and attentive visit:
“In normal encounter, everything is fine. This automation describing does the job... the physician being able to pay attention to you.” (06:34)
Patients can expect shorter wait times for evidence-based answers to their queries, fostering a more engaging and informative healthcare experience.
Challenges in Integrating Ambient AI Technology
Despite the promising advancements, Dr. Shah acknowledges several challenges in the integration of ambient AI into existing healthcare workflows:
“There are two broad buckets of challenges... technical challenges like API integrations, latency, security, privacy... and challenges we haven't yet thought of, like evaluating how it's adding value.” (08:47)
Technical hurdles include ensuring seamless integration with current systems, maintaining data security, and achieving low latency in data processing. Additionally, there is a need for robust evaluation metrics to assess the true impact and value addition of the technology in clinical settings.
Future Evolution and Broader Impact on the Healthcare Industry
Looking ahead, Dr. Shah anticipates significant advancements and broader applications of ambient AI in healthcare:
“We’re collecting a new kind of data in electronic form that we never had before... documentation for billing could be completely automated... summaries directed to the patient.” (10:21)
He envisions ambient AI not only enhancing clinical decision-making but also streamlining administrative processes such as billing and coding. Moreover, the technology could facilitate personalized patient follow-ups and monitoring, thereby expanding the scope of patient care beyond the traditional clinical encounter.
Dr. Shah emphasizes the potential for AI to enable new care activities that were previously unimaginable, suggesting a transformative impact on both patient outcomes and healthcare operations.
Final Thoughts and Parting Words
In concluding the discussion, Dr. Shah shares a thought-provoking concept inspired by Eric Brynjolfsson’s “Turing Trap”:
“The Turing trap is the opposite of the Turing Test, where we as humans only imagine doing with the computer what we already know how to do... What actions should we be taking that can be done for cheap and fast with AI.” (13:24)
He encourages healthcare leaders and IT executives to explore innovative applications of AI that extend beyond current expectations, leveraging technology to enhance patient care in novel ways.
Host Jacob Emerson wraps up the episode by expressing gratitude to Dr. Shah for sharing his expertise and insights, highlighting the transformative work underway at Stanford Health Care.
Conclusion
This episode offers a comprehensive look into the forefront of healthcare data science and AI integration. Dr. Nigam Shah’s insights shed light on how ambient AI technologies are revolutionizing clinical workflows, enhancing patient-provider interactions, and paving the way for future innovations in healthcare. For healthcare professionals and enthusiasts, this discussion underscores the pivotal role of data science in shaping the future of patient care.
Listen to more episodes of Becker’s Healthcare Podcast at Becker's Hospital Review.