Latest from MCiM

What if the prescription for better health wasn’t just medication, but a safe home and a warm meal? In his latest article, Dr. Kevin Schulman spotlights Stanford Medicine’s groundbreaking partnerships tackling social drivers of health, from providing permanent supportive housing to delivering medically tailored meals. These collaborations are redefining what hospital care can be, proving that healing doesn’t end at discharge.

From insulin pumps to continuous glucose monitors, diabetes technology has the power to transform inpatient care — but how well is it actually working in U.S. hospitals? In his latest publication, MCiM '25 alum Dr. Michael Hughes surveys the real-world experiences of users on the front lines, revealing surprising gaps, successes, and opportunities for improvement.

Clinical trial enrollment is a bottleneck in cancer research, but MCiM '26 candidate Rahul Guli and his team at Stanford have built a game-changing solution: an EMR-integrated trial matching system that connects patients to the right studies at the point of care. The result? A more than 10x jump in screening referrals and higher enrollment rates, bringing cutting-edge treatments to patients faster.

In a field where sustaining healthy blood sugar levels can be an uphill battle, MCiM Faculty Dr. David Scheinker and his team have cracked part of the code. By combining early continuous glucose monitoring, intensive education, and remote patient monitoring, the Pilot 4T Study didn’t just improve HbA1c in youth with T1D, it kept those gains for three years. The results are game-changing for long-term care.

As generative AI races into hospitals and clinics worldwide, MCiM Faculty Dr. Nigam Shah sounds the alarm on both the groundbreaking potential and the hidden dangers of this technology. From life-saving innovations to uncharted regulatory risks, his latest Nature piece calls for a bold international partnership to govern AI before it governs us.

MCiM Program Director Kevin Schulman explores how Hurricane Helene’s destruction of Baxter’s North Carolina plant, responsible for 60% of U.S. IV saline, exposed the fragility of our healthcare supply chain. The crisis led to emergency measures like rationing fluids, using oral rehydration, and importing from abroad. Schulman calls for a more resilient, distributed supply strategy to protect patients and providers in an era of increasingly extreme weather.

What if a simple wearable could alert doctors before a child’s condition spirals into another urgent hospital visit? In his latest study, MCiM Faculty Dr. David Scheinker explores how real-time remote patient monitoring could revolutionize pediatric care, catching problems early, cutting costs, and keeping kids out of the hospital. The future of follow-up care might already be here.

Learn from Dr. Kevin Schulman, MCiM Program Director, as he explores how European governments negotiate with pharmaceutical companies to lower drug prices. This report sheds light on why Americans pay more for prescription drugs and offers insights into potential solutions.

In a powerful STAT article, MCiM Program Director Kevin Schulman highlights how skyrocketing U.S. health care costs, not tariffs, are a major obstacle to reshoring American industry. While policymakers focus on trade and tariffs to bring jobs back home, Schulman argues that the real challenge lies in the unsustainable burden of employer-sponsored health insurance, which puts American companies at a global disadvantage. If the U.S. truly wants to compete, tackling health care affordability must be part of the strategy.

A study led by Stanford researchers, including MCiM Program Director Kevin Schulman, reveals that some generic versions of methylphenidate (Ritalin) fail to dissolve properly, either too fast or too slow, impacting how the drug is absorbed and potentially leading to ADHD symptoms returning or new side effects. Generics from Mallinckrodt, Granules India, and Lannett were among those that underperformed, while others like Sun Pharma and Patriot Pharmaceuticals scored well. Alarmingly, 7 out of 15 tablets tested also contained high levels of a likely cancer-causing chemical, raising serious questions about manufacturing quality.

In a groundbreaking randomized controlled trial, MCiM Program Director Kevin Schulman and MCiM Alum ’23 Ethan Goh, along with colleagues, explored how clinicians and AI can collaborate, not just coexist, in diagnostic workflows. Using a custom GPT-based system, the study tested two models: AI-first and AI-second. The study highlights how AI can evolve from a passive tool to an active teammate, enhancing clinical decision-making through thoughtful integration and collaboration.

MCiM Mentor Rene Caissie launched a platform, Medeloop.ai, that allows public health departments, researchers, and life sciences companies to ask research questions and get instant, transparent answers, backed by real data. Now partnering with HealthVerity and used by the NYC Department of Health, Medeloop is helping agencies like the FDA, NIH, and CDC gain faster insights into public health trends. Caissie’s mission? Make research as fast and powerful as the AI driving it.

Imagine if clinicians could talk to a patient’s chart and instantly get the answers they need. MCiM Faculty Dr. Nigam Shah and his team at Stanford Medicine have built ChatEHR, a secure, AI-powered tool that can summarize hundreds of pages, pull key details, and streamline time-critical decisions, all without leaving the electronic health record. It’s like having a medical data concierge at your fingertips.

Dr. Nigam Shah shares how Microsoft’s multiagent AI is easing workloads and boosting care for oncology teams.

MCiM faculty Dr. David Scheinker explores the financial sustainability of a fully virtual clinic model combining CGM + RPM.

Who's responsible for all that patient-generated data? MCiM '24 alum & instructor Meagan Moyer tackles this question in Nature, offering a sociotechnical roadmap for integrating PGHD into care.

Can AI scribes help fight clinician burnout? MCiM ’24 alum Gabriel Tse dives into the impact of AI-powered documentation tools in a new systematic review.

MCiM faculty David Scheinker makes the case for replacing outdated EMRs with AI-native systems built from the ground up.

MCiM Director Kevin Schulman and faculty David Scheinker co-author this Newsweek piece arguing that modernizing health infrastructure could reduce administrative costs by over 60%.

MCiM faculty Nigam Shah discusses how to evaluate large language models (LLMs) for real-world health care needs in this Stanford Medicine interview.

MCiM'24 alum Phoebe Crosthwaite explores how subscription models can reshape healthcare delivery in the AI era.

MCiM faculty Dr. Nigam Shah explores a smarter way to stratify patients by combining disease risk and outcome severity. A case study in sepsis.

MCiM Faculty Director Dr. Kevin Schulman leads a consensus effort to identify practical, clinically usable domains for diagnosing multidimensional frailty.

MCiM Alum ’24 Crystal Chang highlights critical gaps in safety, accuracy, and bias through red teaming ChatGPT in clinical contexts.

MCiM Alum ’23 Ethan Goh explores how AI assistance influences physician decision-making and potential bias in clinical triage.

MCiM Director Kevin Schulman examines the FTC’s investigation into PBMs and why their opaque practices matter for physicians and patients.

Can AI really handle real-world medicine? MCiM faculty, alumni & Microsoft researchers team up to build a benchmark grounded in real healthcare needs.

MCiM Director Kevin Schulman weighs in on a $265 billion health care question in this Stanford Business Insider piece on transforming old ideas into creative solutions for today’s challenges.

MCiM Program Faculty Director, Dr. Kevin Schulman shares his perspective on direct primary care, describing it as "better than nothing," but far from a comprehensive solution

In this Health Affairs article, MCiM faculty Nigam Shah outlines critical priorities to ensure AI is used safely, effectively, and equitably in health care.

This NEJM AI piece by MCiM Director Kevin Schulman explores how ambient intelligence and computer vision can be used to build a behavioral atlas for ICU care.

This Viewpoint argues that standardizing and streamlining administrative tasks could decrease health care costs and have a direct positive effect on patients and clinicians.

The experience of cancer and the cost of cancer care rise to the level of a catastrophic event, and thus, patients with cancer disproportionately suffer from this fundamental failure of health care cost containment. In fact, the failure of health insurance to provide this basic financial protection in the setting of these rising costs has generated its own characterization, financial toxicity.

MCiM faculty Nigam Shah contributes to this groundbreaking study on Med-PaLM 2, a large language model that advances expert-level performance in medical question answering.

As burnout rises and more doctors trade private practice for corporate jobs, unionization is emerging as a powerful force in medicine. In this JAMA piece, Dr. Kevin Schulman dives into the surprising trends, motivations, and shifting landscape of physician unions from 2000 to today. You might be shocked by what’s driving this movement — and what it could mean for the future of health care.

Check out John Wilson, MCiM ‘24, and his first published article in Harvard Public Health magazine. Currently pursuing his MPH at Harvard T.H. Chan School of Public Health, John recently wrote an insightful piece on the evolution of the U.S. marijuana industry and the pressing need for federal oversight and regulation.

In this paper, Dr. Kevin Schulman, introduces Precedents Thinking as a solution to the $265 billion annual administrative waste in U.S. healthcare. The authors propose standardized digital contracts and a uniform digital transaction platform as key strategies to reduce transaction costs.

Crowe, Chen, and colleagues address the ethical and practical considerations for integrating generative AI into healthcare. They present recommendations for clinicians, technologists, and healthcare organizations on using generative AI responsibly, with emphasis on clinical decision-making, health system optimization, and the patient-physician relationship.

In this cross-sectional study, Tse, Zahedivash, Anoshiravani, and colleagues investigate the application of large language models (LLMs) in handling pediatric in-basket messages. The research focuses on distinct challenges within pediatric care, particularly when processing clinical messages from adolescent patients and their proxies. The study highlights the nuances and implications of using LLMs in sensitive pediatric settings.

Explore this insightful paper by MCiM faculty, Linda Hoff and Nigam H. Shah, which examines the misalignment between regulatory frameworks, reimbursement structures, and business models for AI in healthcare. The authors highlight how these gaps can lead to rising costs without improving outcomes.

In this paper, Dr. Kevin Schulman and MCiM alumna Crystal Tin-Tin Chang, MCiM '24, explore the shortcomings of value-based care models, which continue to dominate policy discussions and private health insurance markets. The authors argue that policymakers must adopt a more holistic, market-level view to effectively address the deficiencies in the U.S. health system’s value payment program.

Exploring solutions for 'surprise' medical bills, Schulman and Richman discuss potential approaches to managing out-of-network pricing challenges in healthcare to reduce patient financial burden in their latest JAMA article.

Schulman, Narayan, and Bhushan analyze India’s rapidly advancing digital health strategy, highlighting its impact on accessibility, patient engagement, and system efficiency in the latest npj Digital Medicine article.

A recent Milbank Quarterly study, co-authored by Schulman, compares international frameworks for drug price negotiation, suggesting that the U.S. could improve Medicare outcomes by incorporating practices from other countries to negotiate more effectively on high-cost medications.

Nayak, Savage, Gallo, Rangan, and Chen address a key barrier in using large language models (LLMs) for clinical decision-making. They develop diagnostic reasoning prompts to study whether LLMs can imitate clinical reasoning while accurately forming a diagnosis.

Research study that assesses how well GPT-3.5 and GPT-4 address healthcare-related queries from a clinical informatics consultation service. Authored by Dash, Chen, Pedreira, Goh, Arnaout, Morris, Magon, Shah, and colleagues, it explores the safety and concordance of model responses to real-world healthcare questions.