Testing large language models in real clinics to help with acute conditions
Official title: Massive Online Open Validation and Evaluation of Large Language Models for Resource Constrained Settings - a Study of Contextual Awareness, Safety, and Accuracy
Run by Ecole Polytechnique Fédérale de Lausanne · NCT07914140 · Data updated 2026-11-12
This study tests whether large language models can safely assist clinicians in real, resource-limited acute-care settings by comparing their outputs with what human clinicians decide.
Quick facts
| Study type | Observational |
|---|---|
| Ages | Any age to 1 Day |
| Sex | All |
| Enrollment | 3000 (estimated) |
| Sponsor | Ecole Polytechnique Fédérale de Lausanne Academic / other |
| Locations | 4 sites (Nairobi, Nairobi County and 3 other locations) |
| Status | Recruiting |
| Started | August 31, 2026 |
| Main results expected | December 31, 2026 |
| Study ends | December 31, 2026 |
| Registry record updated | November 3, 2026 |
| Trial ID | NCT07914140 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Patients presenting with an acute condition at participating outpatient facilities who can provide informed consent and meet study-specific criteria.
✕Probably not a fit
Patients with prolonged or immediate life-threatening conditions requiring emergency intervention or those not meeting inclusion criteria may not benefit from this analysis.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This non-interventional study collects routine clinical data from patients seen at participating facilities in low- and middle-income countries. LLM outputs are generated from anonymized patient information and evaluated by a panel of independent clinicians against the human care plan and patient outcomes. The goal is to measure safety, accuracy, and suitability for future implementation, while keeping patient care guided by clinicians. The study also gathers usability and implementation-readiness insights for prompting interfaces. Outcomes are tracked at 7 and 28 days to establish a baseline for performance comparisons.
Why it matters
Potential benefit: If successful, the approach could inform safer, context-appropriate use of LLMs to support clinicians in acute care where resources are limited.
How similar studies have gone: Previous work has shown mixed results with LLMs in medicine; this study aims to provide context-specific real-world evidence in low-resource settings.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Presentation at a participating facility for a distinct care seeking episode related to a clinical condition. * Use case specific inclusion criteria * Willing and able to provide written informed consent. Exclusion Criteria: * Prolonged care-seeking episode. * Previously enrolled in the same study. * Use case specific exclusion criteria * Immediate life-threatening condition requiring emergency intervention precluding study procedures.
Where it's running
-
Malawi University of Business and Applied Sciences (MUBAS)
Blantyre, Blantyre, Malawi Recruiting -
Ifakara Health Institute (IHI)
Dodoma, Dodoma, Tanzania Recruiting -
University of Nairobi College of health sciences
Nairobi, Nairobi County, Kenya Not yet recruiting -
Muhimbili University of Health and Allied Sciences (MUHAS)
Dar es Salaam, Dar es Salaam Region, Tanzania Not yet recruiting
Study contacts
- Principal investigator: Mary-Anne Hartley — Light
- Study coordinator: Mary-Anne Hartley
- Email: mary-anne.hartley@epfl.ch
- Phone: +41216930828
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.