AI Telemedicine Support for Primary Care Physicians in El Salvador

Pragmatic Randomized Clinical Trial of AI-Assisted Telemedicine to Improve Diagnostic Accuracy Among 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.

Study Overview

• Status: Not yet recruiting
• Conditions: Artificial Intelligence (AI) in Diagnosis
• Intervention / Treatment: Other: Standard Telemedicine Workflow (No AI); Device: DoctorSV AI Assistant

• Study Type: Interventional
• Enrollment (Estimated): 180
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Principal Investigator; Phone Number: 212-203-3323; Email: stella@saglobalhealth.org

Study Locations

• El Salvador
  • San Salvador, El Salvador
    • Hospital Nacional El Salvador
    • Contact: Manuel Bello, MD; Phone Number: 503 78885563; Email: manuel.bello@doctorsv.gob.sv

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: AI Disabled (Standard Telemedicine); Physicians in this arm will conduct telemedicine consultations with the AI assistant features temporarily disabled. They will perform the standard clinical workflow without automated support for history taking or diagnostic suggestions. This arm represents the removal of the AI tool to measure its impact.	Other: Standard Telemedicine Workflow (No AI); 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.
Active Comparator: AI Enabled (AI-Assisted Telemedicine); Physicians in this arm will conduct telemedicine consultations with full access to the DoctorSV AI assistant.	Device: DoctorSV AI Assistant; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	Through study completion, ~ 12-16 weeks

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	Through study completion, ~12-16 weeks
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).	Through study completion, ~12-16 weeks
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.	Through study completion, ~12-16 weeks.

Collaborators and Investigators

• Sponsor: Hospital El Salvador
• Investigators: Principal Investigator: Manuel Bello, MD, Hospital Nacional El Salvador

Study record dates

Study Major Dates

• Study Start (Estimated): February 1, 2026
• Primary Completion (Estimated): August 1, 2026
• Study Completion (Estimated): August 1, 2026

Study Registration Dates

• First Submitted: February 6, 2026
• First Submitted That Met QC Criteria: February 6, 2026
• First Posted (Actual): February 12, 2026

Study Record Updates

• Last Update Posted (Actual): February 17, 2026
• Last Update Submitted That Met QC Criteria: February 13, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Other Study ID Numbers: CNEIS/2025/32

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: The data will not be sent or shared to servers external to those used by the DoctorSV platform to ensure security and privacy of the participants (physicians) as well as the patients. The data is restricted to the research team and the specific objectives of this study.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No