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Bangladesh PRODUCTIVity in Eyecare Trial

NCT05182580 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 993

Last updated 2024-02-06

Study results available
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Summary

The purpose of this study is to assess the impact of using autonomous artificial intelligence (AI) system for identification of diabetic retinopathy (DR) and diabetic macular edema on productivity of retina specialists in Bangladesh.

Globally, the number of people with diabetes mellitus is increasing. Diabetic retinopathy is a chronic, progressive complication of diabetes mellitus that affects the microvasculature of the retina, which if left untreated can potentially result in vision loss. Early detection and treatment of diabetic retinopathy can prevent potential blindness.

Study Aim: To assess the impact of using autonomous artificial intelligence (AI) system for detection of diabetic retinopathy (DR) and diabetic macular edema on physician productivity in Bangladesh.

Main study question: Will ophthalmologists with clinic days randomized to use autonomous AI DR detection for all persons with diabetes (diagnosed or un-diagnosed) visiting their clinic system have a greater number of examined patients with diabetes (by either AI or clinical exam), and a greater complexity of examined patients on a recognized grading scale, per physician working hour than those randomized not to have autonomous AI screening for their diabetes population?

The investigators anticipate that this study will demonstrate an increase in physician productivity, supporting efficiency for both physicians and patients, while also addressing increased access for DR screening; ultimately, preventing vision loss amongst diabetic patients. The study has the potential to contribute to the evidence base on the benefits of AI for physicians and patients. Additionally, the study has the potential to demonstrate the benefits (and/or challenges) of implementing AI in resource-constrained settings, such as Bangladesh.

Conditions

Interventions

DIAGNOSTIC_TEST

Results utilized from autonomous AI diagnostic system for diabetic retinopathy and/or diabetic macular edema

If patients receive a negative result they do not see the retina specialist

Sponsors & Collaborators

  • Digital Diagnostics, Inc.

    collaborator INDUSTRY

  • Deep Eye Care Foundation (DECF)

    collaborator OTHER

  • Orbis

    lead OTHER

Principal Investigators

  • Nathan Congdon, MD, MPH · Orbis

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
DOUBLE
Model
PARALLEL

Eligibility

Min Age
22 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-03-20
Primary Completion
2022-07-31
Completion
2022-07-31
FDA Device
Yes

Countries

  • Bangladesh

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05182580 on ClinicalTrials.gov