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NCT Number: NCT07406919

AI Telemedicine Support for Primary Care Physicians in El Salvador

The goal of this clinical trial is to learn whether access to an artificial intelligence (AI) clinical decision support assistant can improve diagnostic accuracy during real-world telemedicine consultations among primary care physicians in El Salvador.

The main questions it aims to answer are:

* Does access to the AI assistant increase the proportion of correct diagnoses compared to telemedicine without AI assistance? * Does the effect of the AI assistant differ according to the physician's prior experience using AI in telemedicine?

Researchers will compare physicians with the AI assistant enabled to physicians with the AI assistant temporarily disabled to see if access to AI improves diagnostic accuracy.

Participants (physicians) will:

* Provide telemedicine consultations as part of their routine clinical duties. * Be randomly assigned to either have the AI assistant enabled or disabled during the study period. * Continue documenting clinical encounters in the electronic platform as usual. * Have their anonymized consultation notes reviewed by an independent expert panel to determine diagnostic accuracy.

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Key information

Conditions

Artificial Intelligence (AI) in Diagnosis

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Must be a physician employed by the DoctorSV telemedicine program
  • Must provide written informed consent to participate in the study
  • Consultations must be for acute pathologies of the digestive, respiratory, or urinary systems, or acute ophthalmic infections manageable in primary care
  • Consultation must be the first medical contact (first visit) for the current acute episode
  • The condition must correspond to specific ICD-11 codes defined in the study protocol

Exclusion criteria

  • Physicians who are inactive on the platform for more than 4 consecutive weeks
  • Physicians who transition to work modalities other than telemedicine or reduce their working hours to less than 20 hours per week
  • Physicians whose employment contract ends (resignation, dismissal, or contract completion) during the data collection period
  • Consultations classified by the physician as requiring immediate in-person attention
  • Consultations requiring referral to another level of care or specialty for definitive management
  • Consultations interrupted or incomplete due to connectivity or system failures
  • Consultations solely for administrative purposes (e.g., certificates, repeat prescriptions without clinical evaluation)
  • Consultations that are follow-up visits or controls for a previously evaluated episode

Treatment and study plan

DoctorSV AI Assistant

Device

An AI tool integrated into the telemedicine platform, built on Google's Gemini Large Language Models (LLMs). The system operates via two modules:

(1) a clinical history assistant that supports structured documentation of patient information in real-time and (2) a pre-diagnosis tool that analyzes documented clinical data to generate differential diagnosis suggestions for the physician's consideration. The model uses contextual prompting to ensure suggestions are culturally and clinically appropriate for El Salvador.

Standard Telemedicine Workflow (No AI)

Other

Standard primary care consultation via videocall without the assistance of artificial intelligence tools. Physicians rely solely on their own clinical judgment and manual documentation without automated summaries or diagnostic prompts.

Primary outcomes

  1. Diagnostic Accuracy

    Time frame: Through study completion, ~ 12-16 weeks

    The proportion of consultations where the primary diagnosis recorded by the participating physician matches the "gold standard" reference diagnosis. The reference diagnosis is established by a panel of three independent, blinded expert evaluators reviewing the anonymized clinical notes. A diagnosis is considered "correct" (value = 1) if it matches the reference diagnosis within the same clinically equivalent diagnostic group; otherwise, it is considered "incorrect" (value = 0). The analysis will compare the proportion of correct diagnoses between the AI-enabled and AI-disabled arms.

Secondary outcomes

  1. Diagnostic Concordance

    Time frame: Through study completion, ~12-16 weeks

    The level of agreement between the physician's diagnosis and the expert reference diagnosis, measured using Cohen's Kappa coefficient. This measure evaluates the reliability of the diagnoses beyond simple percentage agreement, accounting for agreement occurring by chance.

  2. Diagnostic Accuracy Stratified by Physician Experience Level

    Time frame: Through study completion, ~12-16 weeks

    Evaluation of diagnostic accuracy (proportion of correct diagnoses) compared between subgroups of physicians with "High Experience" (≥1 year in the program or ≥20 consultations) versus "Low Experience" (<1 year in the program or <20 consultations).

  3. Diagnostic Accuracy Stratified by Clinical System

    Time frame: Through study completion, ~12-16 weeks.

    The proportion of correct diagnoses stratified by the physiological system of the pathology: Respiratory, Digestive, Urinary, or Ophthalmic. This outcome assesses if the AI's performance or utility varies depending on the specific type of clinical condition.

Study contacts

Contact information is provided by the study sponsor or research team.

Principal Investigator

CONTACT

[email protected]

212-203-3323

Sponsors and collaborators

Lead sponsor

Hospital El Salvador

Other Gov

Registry information

Official study title

Pragmatic Randomized Clinical Trial of AI-Assisted Telemedicine to Improve Diagnostic Accuracy Among Primary Care Physicians in El Salvador

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Feb 12, 2026
Registry last updated
Feb 17, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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