Teaching Doctors in Training to Reason With Artificial Intelligence (TEACH-AI)
Teaching Internal Medicine and Family Medicine Residents to Reason With Generative AI: A Multi-Site Randomized Controlled Trial (TEACH-AI)
The purpose of the TEACH-AI study is to assess whether a brief, structured workshop on artificial intelligence can improve the performance of medicine doctors in training (i.e. residents) in their diagnostic and management reasoning.
In this multi-site randomized controlled trial, internal medicine and family medicine residents are assigned either to receive an in-person workshop on safe, effective LLM use before a standardized AI-assisted assessment, or to complete the same assessment before receiving the workshop. Residents will review clinical cases that are fully synthetic, no protected health information is used, using a password protected LLM interface.
Studienübersicht
Status
Bedingungen
Intervention / Behandlung
Detaillierte Beschreibung
Large language models (LLMs) have rapidly entered routine use in medical education and clinical practice. Prior randomized trials have shown that, although LLMs can outperform individual clinicians on some reasoning benchmarks, providing physicians with access to an LLM does not necessarily improve their diagnostic or management performance, and LLMs alone may perform better than physician-plus-LLM teams. These findings suggest that human-AI collaboration is fraught, non-trivial and may require explicit training.
TEACH-AI is a pragmatic, multi-site, two-arm randomized controlled trial embedded within protected residency didactic time. The primary objective is to determine whether a single in-person workshop on the basics of LLMs and best practices of prompting/verification strategies improves residents' performance on an AI-assisted assessment, compared with residents who complete the simulation before receiving the workshop. All participants will ultimately receive the same workshop and the same assessment (either workshop-first vs assessment-first).
The simulation consists of multiple fully synthetic vignettes delivered via a password protected LLM interface. Residents interact freely with the LLM using natural-language prompts and then submit structured final responses regarding aspects such as leading diagnosis, differential, management plan, and/or justification. The platform will record prompts, model outputs, final answers, and timing. Vignette scoring combines correctness of the final diagnosis or management plan. Scoring is conducted by blinded faculty using standardized rubrics and then any discrepancies will be resolved through multiple rounds of discussions.
The trial will enroll up to 200 residents across four ACGME-accredited programs (internal medicine at Beth Israel Deaconess Medical Center, Stanford University, and Cambridge Health Alliance; family medicine at AdventHealth Orlando).
Studientyp
Einschreibung (Geschätzt)
Phase
- Unzutreffend
Kontakte und Standorte
Studienkontakt
- Name: Jacob M Koshy, MD, MPH
- Telefonnummer: 617-754-4677
- E-Mail: jkoshy@bidmc.harvard.edu
Studienorte
-
-
California
-
Palo Alto, California, Vereinigte Staaten, 94305
- Stanford University
-
Kontakt:
- Kevin Keet, MD
- Telefonnummer: 650-498-4559
- E-Mail: kkeet@stanford.edu
-
Hauptermittler:
- Kevin R Keet, MD
-
-
Florida
-
Orlando, Florida, Vereinigte Staaten, 32804
- AdventHealth
-
Kontakt:
- Raj Mehta, MD
- Telefonnummer: 407-845-8383
- E-Mail: raj.mehta.md@adventhealth.com
-
Hauptermittler:
- Raj Mehta, MD
-
-
Massachusetts
-
Boston, Massachusetts, Vereinigte Staaten, 02215
- Beth Israel Deaconess Medical Center
-
Kontakt:
- Jacob M Koshy, MD, MPH
- Telefonnummer: 617-754-4677
- E-Mail: jkoshy@bidmc.harvard.edu
-
Hauptermittler:
- Jacob M Koshy, MD, MPH
-
Cambridge, Massachusetts, Vereinigte Staaten, 02139
- Cambridge Health Alliance
-
Kontakt:
- Priyank Jain, MD
- Telefonnummer: 617-665-1000
-
Hauptermittler:
- Priyank Jain, MD
-
-
Teilnahmekriterien
Zulassungskriterien
Studienberechtigtes Alter
- Kind
- Erwachsene
- Älterer Erwachsener
Akzeptiert gesunde Freiwillige
Beschreibung
Inclusion Criteria:
- Participants must be licensed physicians and have started at least post-graduate year 1 (PGY1) of medical training.
- Training in Internal medicine or family medicine or emergency medicine.
- Able to provide informed consent and complete assessments in English.
Exclusion Criteria:
- Not currently practicing clinically.
- Resident directly involved in the design of the study, development of the workshop, or creation/piloting of the assessment vignettes.
- Resident who declines or withdraws consent.
Studienplan
Wie ist die Studie aufgebaut?
Designdetails
- Hauptzweck: Diagnose
- Zuteilung: Zufällig
- Interventionsmodell: Parallele Zuordnung
- Maskierung: Single
Waffen und Interventionen
Teilnehmergruppe / Arm |
Intervention / Behandlung |
|---|---|
|
Kein Eingriff: Assessment-First
Participants assigned to this group will be tasked with completing the assessment using a password protected LLM interface first in advance of the workshop.
The workshop will be delivered during a scheduled mandatory didactic time slot.
|
|
|
Experimental: Workshop-first
Participants assigned to this group will be tasked with completing the assessment using a password protected LLM interface after they participate in a scheduled mandatory didactic time slot.
|
Participants will attend a workshop during their didactic time that will review various aspects of large language models including fundamentals and best practices of interacting and interpreting their outputs.
|
Was misst die Studie?
Primäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
Total Score on Expert-Development Rubrics
Zeitfenster: Within 24 hours of assessment completion.
|
The primary outcome will be the number of correct responses for all cases using select questions from expert-developed scoring rubrics.
The rubrics were developed using a Delphi consensus process by expert physicians as established by Goh et al (Nature Medicine, 2025; DOI: 10.1038/s41591-024-03456-y). The primary outcome will be analyzed at the case level, comparing performance between the randomized study groups, with a higher number of correct responses indicating a better outcome.
|
Within 24 hours of assessment completion.
|
Sekundäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
Time Spent on Management
Zeitfenster: Within 24 hours of assessment completion.
|
Comparison of time spent per case between the two study groups.
|
Within 24 hours of assessment completion.
|
|
Prompt Count
Zeitfenster: Within 24 hours of assessment completion.
|
Comparison of the number of resident-initiated prompts to the LLM per case between the two study groups.
|
Within 24 hours of assessment completion.
|
|
Management Reasoning Using Expert-Derived Rubrics
Zeitfenster: Within 24 hours of assessment completion.
|
Comparison of management reasoning accuracy based on the number of correct responses per case between the two groups on expert-developed scoring rubrics.
The rubrics were developed using a Delphi consensus process by expert physicians as established by Goh et al (Nature Medicine, 2025; DOI: 10.1038/s41591-024-03456-y). The primary outcome will be analyzed at the case level, comparing performance between the randomized study groups with more correct responses indicating a better outcome.
|
Within 24 hours of assessment completion.
|
|
Diagnostic Reasoning
Zeitfenster: Within 24 hours of assessment completion.
|
Comparison of diagnostic reasoning accuracy based on the number of correct responses per case between the two groups.
|
Within 24 hours of assessment completion.
|
Mitarbeiter und Ermittler
Studienaufzeichnungsdaten
Haupttermine studieren
Studienbeginn (Geschätzt)
Primärer Abschluss (Geschätzt)
Studienabschluss (Geschätzt)
Studienanmeldedaten
Zuerst eingereicht
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
Zuerst gepostet (Tatsächlich)
Studienaufzeichnungsaktualisierungen
Letztes Update gepostet (Tatsächlich)
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
Zuletzt verifiziert
Mehr Informationen
Begriffe im Zusammenhang mit dieser Studie
Schlüsselwörter
Andere Studien-ID-Nummern
- 2026P000369
- 63901784-350738 (Andere Zuschuss-/Finanzierungsnummer: Macy Foundation)
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