About
Titles
Associate Dean, Digital Strategy & Transformation, Yale School of Medicine; Professor in Biomedical Informatics & Data Science and Professor of Neurology, Yale School of Medicine; Senior Vice President & Chief Digital Health Officer, Yale New Haven Health System
Biography
Lee H. Schwamm, MD is Associate Dean for Digital Strategy and Transformation for Yale School of Medicine, and Senior Vice President and Chief Digital Health Officer for Yale New Haven Health System. In this role, he leads the development of a new digital health strategy for the school and the health system, and serves as an influential physician leader guiding the equitable and responsible implementation of artificial intelligence and digital enablement in healthcare throughout the enterprise.
Before joining Yale, Dr. Schwamm spent three decades at the Mass General Brigham Health System, serving in senior academic and administrative leadership roles. He was the inaugural C. Miller Fisher Chair in Vascular Neurology and director of the Center for TeleHealth at Massachusetts General Hospital; vice president for Digital Patient Experience and Virtual Care and chief digital advisor for the Mass General Brigham Health System; and a professor of neurology at Harvard Medical School.
Dr. Schwamm is an internationally recognized expert in stroke diagnosis, treatment, and prevention, a pioneer in telestroke and a leading national voice in healthcare AI implementation. Under his leadership, the American Heart Association’s Get with the Guidelines–Stroke Registry has grown into the world’s largest stroke registry with over eight million patient encounters; it has changed stroke practice at hospitals across the U.S. and set a global standard for stroke care.
A graduate of both Harvard College and Harvard Medical School, Dr. Schwamm completed residency training in neurology, serving as chief resident, and fellowship training in stroke and neurocritical care, all at Massachusetts General Hospital. He has spent the past 2 decades in digital health, as a pioneer in telestroke, and as a leading stroke volunteer, healthcare AI expert and policy advisor for the American Heart Association. An internationally recognized expert in cerebrovascular disease, he is an elected Fellow of the American Heart Association, American Academy of Neurology and the American Neurological Association and led the development of the AHA Get with the Guidelines–Stroke Registry, now the world’s largest stroke registry with over 8M patient encounters. His research has been funded by NIH, AHA, PCORI, AHRQ, HRSA, CDC and has been recognized with over 500 peer-reviewed articles as well as numerous awards for innovation, leadership, and advocacy in the field of stroke and digital health. He has served on multiple editorial boards, including as the digital health section editor for Stroke, and on the international advisory board for Lancet Digital Health.
Appointments
Office of the Dean, School of Medicine
Associate DeanDualBiomedical Informatics & Data Science
ProfessorSecondaryNeurology
ProfessorSecondary
Other Departments & Organizations
- Biomedical Informatics & Data Science
- Digital Technology Solutions Leadership
- Neurology
- Office of the Dean, School of Medicine
- Virtual Care Consensus
- Yale Medicine
- Yale New Haven Health System
Education & Training
- Fellowship
- Massachusetts General Hospital (1996)
- Residency
- Massachusetts General Hospital (1995)
- Internship
- Beth Israel Hospital (1992)
- MD
- Harvard Medical School, Medicine (1991)
- AB
- Harvard University, Philosophy (1985)
Research
Publications
2026
Impact of an Ambient AI Scribe on Medical Student Objective Structured Clinical Examination Notes: Nonrandomized Clinical Trial
Talwalkar J, Wright D, Schwamm L, Leydon G, Shabanova V. Impact of an Ambient AI Scribe on Medical Student Objective Structured Clinical Examination Notes: Nonrandomized Clinical Trial. JMIR Medical Education 2026, 12: e88264. PMID: 42125891, PMCID: PMC13273210, DOI: 10.2196/88264.Peer-Reviewed Original ResearchThis study investigates the impact of an AI scribe on medical student clinical notes, showing little effect on note quality overall but potential benefits for lower-performing students.Ambient AI Scribes to Create Educational Feedback Notes for Medical Students: Randomized Trial
Talwalkar J, Chartash D, Zhang L, Makutonin M, Safranek C, Sidamon-Eristoff A, Schwamm L, Wright D. Ambient AI Scribes to Create Educational Feedback Notes for Medical Students: Randomized Trial. JMIR Medical Education 2026, 12: e89996. PMID: 42208058, PMCID: PMC13218648, DOI: 10.2196/89996.Peer-Reviewed Original ResearchConceptsIntervention groupTask loadMedical studentsLanguage modelNASA Task Load IndexDevelopment of clinical competenceFeedback notesArtificial intelligenceTask Load IndexFirst-year medical studentsSource transcriptsHuman-onlyCapture toolRandomized to controlDocumentation burdenClinical competenceNarrative feedbackUsabilityMedical educationFactual accuracyWritten feedbackNarrativesTaskInstructor effortVerbal exchangesRural-Urban Disparity in Postacute Care and 1-Year Outcomes After Ischemic Stroke
Man S, Sun J, Alhanti B, Mac Grory B, Uchino K, Messé S, Smith E, Schwamm L, Bhatt D, Saver J, Xian Y, Putnam T, Fonarow G. Rural-Urban Disparity in Postacute Care and 1-Year Outcomes After Ischemic Stroke. Stroke 2026, 57: 2138-2149. PMID: 42206363, DOI: 10.1161/strokeaha.125.054423.Peer-Reviewed Original ResearchConceptsInpatient rehabilitation facilityRural patientsHome-timePostacute careSkilled nursing facilityUrban patientsUrban hospitalsRural-urban gapRural hospitalsNursing facilitiesRehabilitation facilityGuidelines-Stroke participating hospitalsSkilled nursing facility utilizationCohort studyDischarged homeRural-urban disparitiesCox proportional hazards modelsGuidelines-StrokeStroke mortalityIschemic strokeProportional hazards modelHospital characteristicsRural residentsCareFacility utilizationNational Evaluation of Racial, Ethnic, and Insurance-Based Disparities in Interhospital Transfer of Patients With Ischemic Stroke
Turner A, Li S, Wahab F, Zhao J, Thomas K, Poudel R, Reeves M, Smith E, Messé S, Fonarow G, Schwamm L, Zachrison K. National Evaluation of Racial, Ethnic, and Insurance-Based Disparities in Interhospital Transfer of Patients With Ischemic Stroke. Stroke 2026, 57: 2165-2176. PMID: 42095234, DOI: 10.1161/strokeaha.125.054333.Peer-Reviewed Original ResearchConceptsNon-Hispanic white patientsGuidelines-Stroke registryInsurance statusTransfer of patientsGuidelines-StrokeHospital characteristicsInterfacility transferInterhospital transferAcute ischemic strokeStroke severityWhite patientsInterhospital transfer of patientsInterfacility transfer of patientsIschemic strokePatient insurance statusPatients admitted with acute ischemic strokeHospital-level confoundersInsurance-based disparitiesStroke careLinear mixed-effects modelsRace/ethnic groupsUnadjusted modelsHigher oddsHispanic patientsMedicare patientsAmbient AI Scribes to Create Educational Feedback Notes for Medical Students: A Randomized Trial.
Talwalkar JS, Chartash D, Zhang L, Makutonin M, Safranek CW, Sidamon-Eristoff AE, Schwamm LH, Wright DS. Ambient AI Scribes to Create Educational Feedback Notes for Medical Students: A Randomized Trial. JMIR Med Educ 2026 PMID: 42052923, DOI: 10.2196/89996.Peer-Reviewed Original ResearchThis study investigates how ambient AI scribes enhance written feedback quality for medical students, finding improved narrative detail without increasing instructor effort, despite usability challenges.Cost-effectiveness of an insertable cardiac monitor to detect atrial fibrillation in large- or small-vessel disease ischaemic stroke in the USA
Reynolds M, Pollit V, Schwamm L, Witte K, Yaghi S, Rose D, Cudworth S, Carpenter J, Rosemas S, Ziegler P, Neisen K, Franco N, Bernstein R. Cost-effectiveness of an insertable cardiac monitor to detect atrial fibrillation in large- or small-vessel disease ischaemic stroke in the USA. BMJ Open 2026, 16: e103766. PMID: 42044956, PMCID: PMC13158597, DOI: 10.1136/bmjopen-2025-103766.Peer-Reviewed Original ResearchConceptsQuality-adjusted life yearsHealth-related qualitySmall vessel occlusive diseaseLifetime incremental costHealth-related quality of lifeSecondary preventionIschaemic strokeLarge-artery atherosclerotic diseaseSecondary stroke prevention treatmentCost-effective interventionHypothetical cohortRisk of ischaemic strokeInsertable cardiac monitorCost-effectiveQuality of lifePayer perspectiveCost-effectiveness of insertable cardiac monitorsConventional follow-upStroke prevention treatmentHealthcare costsUS payer perspectiveLife yearsLifetime Markov modelStroke riskAtrial fibrillationTreatment Patterns of Antiseizure Medication for Poststroke Prophylaxis Among Older Adults
Sun S, de Medeiros R, Brooks J, Newhouse J, Schwamm L, Haneuse S, Moura L. Treatment Patterns of Antiseizure Medication for Poststroke Prophylaxis Among Older Adults. Journal Of The American Heart Association 2026, 15: e046583. PMID: 41944176, PMCID: PMC13279140, DOI: 10.1161/jaha.125.046583.Peer-Reviewed Original ResearchConceptsProportion of daysTreatment patternsNonadherence to treatmentAntiseizure medicationsTreatment strategiesLatent class mixed modelsOlder adultsMedication treatment patternsAcute ischemic strokeAdherence to treatmentLevetiracetam initiationLong-term useDays of dischargeClinical factorsOutpatient initiationWhite patientsLevetiracetamClinical guidancePatientsUS Medicare beneficiariesIschemic strokePrescription overlapPoststroke seizuresMedicationTreatmentInfarct growth rate and tenecteplase benefit in ischemic stroke at 4.5 to 24 h without thrombectomy-A secondary analysis of the TRACE-III randomized trial.
Wang L, Zhou L, Yin J, Jin A, Campbell B, Fisher M, Schwamm L, Parsons M, Meng X, Duan C, Zong L, Ye W, Che F, Wang L, Dai H, Wang H, Wang Z, Hao M, Cao Z, Wu S, Wang Y, Xiong Y. Infarct growth rate and tenecteplase benefit in ischemic stroke at 4.5 to 24 h without thrombectomy-A secondary analysis of the TRACE-III randomized trial. International Journal Of Stroke 2026, 17474930261443408. PMID: 41944559, DOI: 10.1177/17474930261443408.Peer-Reviewed Original ResearchInfarct growth rateStandard medical treatmentModified Rankin ScaleMedical treatmentBaseline ischemic core volumeIschemic strokeIschemic core volumeIncidence of sICHLarge-vessel occlusionSecondary analysisOpen-labelSlow progressorsTreatment regimensInfarct growthEligible patientsReperfusion therapyRandomized trialsRankin ScalePrimary outcomeStroke onset timeTenecteplaseTreatment effectsEndovascular thrombectomyPatientsFunctional statusChanges in Clinician Time Expenditure and Visit Quantity With Adoption of Artificial Intelligence–Powered Scribes
Rotenstein L, Holmgren A, Thombley R, Sriram A, Dbouk R, Jost M, Aizenberg D, MacDonald S, Kanaparthy N, Williams B, Hsiao A, Schwamm L, Murray S, Byron M, You J, Centi A, Iannaccone C, Frits M, Landman A, Singh K, Tai-Seale M, Cao J, Lawrence K, Mann D, Holland C, Blanchette B, Ehrenfeld J, Melnick E, Bates D, Adler-Milstein J, Mishuris R. Changes in Clinician Time Expenditure and Visit Quantity With Adoption of Artificial Intelligence–Powered Scribes. JAMA: The Journal Of The American Medical Association 2026, 335: 1408-1417. PMID: 41920565, PMCID: PMC13044793, DOI: 10.1001/jama.2026.2253.Peer-Reviewed Original ResearchConceptsEHR timeElectronic health recordsAdvanced practice cliniciansLongitudinal cohort studyVisit volumeDocumentation timeAcademic health care institutionsPrimary care specialistsPracticing cliniciansHealth care institutionsDifference-in-differences analysisPrimary careEligible physiciansClinician satisfactionHealth recordsClinician characteristicsClinician groupsResident physiciansCare specialistsPatient hoursAmbulatory cliniciansCare institutionsFemale cliniciansAssociation resultsPhysiciansEffect of a clinical decision support system on stroke care quality and outcomes in patients with acute ischaemic stroke (GOLDEN BRIDGE II): cluster randomised clinical trial
Zhang X, Ding L, Jing J, Wang C, Gu H, Jiang Y, Meng X, Liu T, Xie X, Xu M, Hu M, Zhang Y, Fu H, Liu P, Du C, Du K, Wang M, Li H, Gong X, Dong K, Xiong Y, Wang Y, Liu L, Zhang Z, Zang Y, Yang C, Xian Y, Peterson E, Fonarow G, Schwamm L, Zhao X, Wang Y, Li Z. Effect of a clinical decision support system on stroke care quality and outcomes in patients with acute ischaemic stroke (GOLDEN BRIDGE II): cluster randomised clinical trial. The BMJ 2026, 392: e085810. PMID: 41862204, PMCID: PMC13003563, DOI: 10.1136/bmj-2025-085810.Peer-Reviewed Original ResearchConceptsStroke care qualityClinical decision support systemsCluster randomised clinical trialCare qualityIntervention groupAcute ischaemic strokeIschaemic strokeVascular eventsCluster-level analysisComposite measureLong-term vascular eventsControl groupAdmitted to hospitalUsual careSymptom onsetIntervention effectsRandomised clinical trialsSecondary outcomesPrimary outcomeInterventionHospitalDecision support systemTreatment recommendationsSupport systemStroke
Clinical Care
Overview
Lee H. Schwamm, MD, is an internationally recognized expert in the prevention, diagnosis, and treatment of stroke and transient ischemic attack (TIA). His research and clinical interests focus on stroke in the young and those whose strokes are without apparent cause (called cryptogenic strokes). He has been a leader in stroke clinical research, and has participated in the design or conduct of major trials that have defined how stroke is currently measured and treated, and how the guideline-recommended treatments are actually administered when patients are hospitalized for stroke. He deeply enjoys mentoring emerging leaders in academic medicine, and his work has been recognized by major grants and awards, including several of the highest volunteer awards from the American Heart Association.
In addition to his expertise in stroke, Dr. Schwamm is a leader in digital health and digital transformation. He realized early on that his work as a neurologist could be augmented with the infusion of big data, technology, and focusing on improving the processes of how health care is delivered. This translates to redesigning care delivery through the human-centered lens of the experiences of patients and providers, and letting the clinical problem drive what technology can be used to make things better (and not the other way around). “We have a real opportunity now to start capturing a lot more information about our patients in the parts of their life beyond the clinic and the hospital, such as with monitors, sensors, and smartphones, to regularly collect weight, activity, or blood pressure and transmit those results to the electronic medical record,” Dr. Schwamm says. By doing so, doctors can build a smarter profile of their patients, tailor treatments to them as individuals, and get their risk factors under control faster and more safely.
“I’ve always been drawn to the brain,” says Dr. Schwamm. “This fascination began when I chose to major in philosophy in college, and it drove me to choose neurology as my specialty. Within neurology, I gravitated to stroke because of the new treatments that had just emerged that could halt or reverse the damage being caused to the brain. I was able to make a major contribution by developing the ability to leverage technology to increase access to stroke specialists and improve outcomes for all stroke patients, not just those lucky enough to live near a major stroke center.”
Dr. Schwamm also serves as senior vice president and chief digital health officer for Yale New Haven Health (YNHH) and as a professor in Biomedical Informatics & Data Sciences at Yale School of Medicine (YSM). As the associate dean for digital strategy and transformation, he is leading the development of a new digital health strategy for YSM and YNHH. Dr. Schwamm has done extensive research and is especially interested in patterns of care delivery for stroke in the United States; how patients move from one health system to another during emergencies, before or after their stroke; and opportunities to identify and eliminate inequities in care.
“I often say, my car gets better health care than I do. Most patients show up in my office when they have the equivalent of a flat tire, or have run out of gas, or have an engine that is overheated, metaphorically speaking,” he says, “Our job as health care providers is to intervene before those critical events happen.”
All my goals really boil down to removing the barriers between patients and the care they need, Dr. Schwamm adds. “One way is to build high-reliability systems wherever we can so that we don't rely on people doing the right thing every time with good intention, but rather, we have systems that support us in doing that right thing every time.”
Clinical Specialties
Board Certifications
Vascular Neurology
- Certification Organization
- AB of Psychiatry & Neurology
- Original Certification Date
- 2008
Neurology
- Certification Organization
- AB of Psychiatry & Neurology
- Original Certification Date
- 1996
News
News
- April 15, 2026Source: Everyday Health (with Lee Schwamm, MD)
AI Tools Offer Problematic Health Advice About Half the Time, Study Finds
- November 12, 2025
Twenty-Seven YSM Faculty Members Recognized for Highly Cited Research
- November 08, 2025Source: Barron's
AI won't be your doctor. It could make you a better patient.
- October 17, 2025
AI Scribes Reduce Physician Burnout and Return Focus to the Patient
Get In Touch
Contacts
Yale School of Medicine
333 Cedar Street - SHM - I-213 , (PO Box 208067)
New Haven, CT 06520-8067
United States
Administrative Support
Locations
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