Health Trials

AI Telemedicine Support for Primary Care Physicians in El Salvador

ConditionArtificial Intelligence (AI) in Diagnosis
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorHospital El Salvador

About this trial

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.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

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

Disqualifiers

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

Trial design

Design model

Parallel

Treatments tested in this trial

  • 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 intervention

    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.

Treatment groups

180 Participants
are divided into 2 treatment groups
Group A: AI Disabled (Standard Telemedicine)Experimental treatment 1 intervention
Group B: AI Enabled (AI-Assisted Telemedicine)Active comparator 1 intervention

Trial outcomes

Primary outcomes

1

Diagnostic Accuracy

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.

Time frame
Through study completion, ~ 12-16 weeks

Secondary outcomes

1

Diagnostic Concordance

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.

Time frame
Through study completion, ~12-16 weeks
2

Diagnostic Accuracy Stratified by Physician Experience Level

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).

Time frame
Through study completion, ~12-16 weeks
3

Diagnostic Accuracy Stratified by Clinical System

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.

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

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Hospital El Salvador

Lead sponsor

Source ClinicalTrials.gov

This trial is not recruiting at the moment. You can still explore other options: