Bangladesh PRODUCTIVity in Eyecare Trial (B-PRODUCTIVE)

February 1, 2024 updated by: Orbis

Assessing the Impact of Using Autonomous Artificial Intelligence (AI) for Pre-screening of Diabetic Retinopathy (DR) and Diabetic Macular Edema on Physician Productivity in Bangladesh

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.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

Bangladesh PRODUCTIVity in Eyecare (B-PRODUCTIVE) Trial

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

Hypothesis: Autonomous AI increases retina specialist productivity

Main Study Question: Will retina specialists complete a greater number of diabetic eye exams per working hour (including persons reviewed by AI whom the retina specialist does not need to see personally) when they use autonomous AI in a randomized clinical trial?

Design: Cluster-randomized (by clinic day) controlled trial.

Randomization: By clinic day. Each morning the clinic manager will open an opaque envelope, which informs the manager if it is an Intervention (AI) or Control (non-AI) day.

Interventions: All patients in both groups go through the eligibility checklist. If approved, they will be evaluated by autonomous AI. This is done to decrease potential bias (neither patients nor physicians know the group assignment of participants) and concealment (so that neither patients nor doctors can arrange visits on a known "Intervention Day").

Intervention Group: On randomly selected "Intervention" clinic days, if patients screen positive or have insufficient image quality, they continue to the ophthalmologist. If not eligible for autonomous AI, they proceed straight to the ophthalmologist without autonomous AI evaluation. If patients receive a negative result, they do not see the retina specialist, and are referred for a visit at the regular eye clinic (not the retina clinic) in 3 months.

Control Group: On randomly-selected "Control Days," all patients see the ophthalmologist, irrespective of the results of autonomous AI evaluation.

Masking: The retina doctors are masked both patient group assignment (that is, whether autonomous AI was used for pre-screening or not on the particular clinic day) and also masked to the results of the AI on Intervention days. Patients are also masked to group assignment and autonomous AI results.

Study Type

Interventional

Enrollment (Actual)

993

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • Bangladesh
      • Rangpur, Bangladesh
        • Deep Eye Care Foundation

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

22 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

Retina specialists regularly seeing patients with DR

  • Routinely examines >= 20 patients with diabetes without known diabetic retinopathy or diabetic macular edema per week
  • Routinely provides laser treatment or intravitreal injections to >= 3 DR patients/month

Patients

  • Diagnosed with type 1 or 2 diabetes
  • Presenting visual acuity >= 6/18 best corrected visual acuity in the better-seeing eye

Exclusion Criteria:

Retina specialists

  • Currently using an AI system integrated into their clinical care and/or inability to provide informed consent.

Patients

  • Inability to provide informed consent or understand the study; persistent vision loss, blurred vision or floaters; previously diagnosed with diabetic retinopathy or diabetic macular edema; history of laser treatment of the retina or injections into either eye, or any history of retinal surgery; contraindicated for imaging by fundus imaging systems

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

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

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Intervention Group
Autonomous AI results are used to evaluate if the participant needs to see the retina specialist (positive result) or not (negative result).
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
No Intervention: Control Group
All participants see the retina specialist irrespective of the results of their autonomous AI evaluation.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Number of Completed Care Encounters Among Clinic Patients With Diabetes Per Retina Specialist Clinic Hour
Time Frame: 105 randomized clinic days
Number of completed care encounters among clinic patients with diabetes per retina specialist clinic hour. Numerator is the number of care encounters among patients with diabetes (including persons evaluated by autonomous AI on Intervention Days who are determined not to need to see the retina specialist). The denominator is retina specialist clinic time in hours.
105 randomized clinic days
Number of Completed Care Encounters Among All Clinic Patients (With and Without Diabetes) Per Retina Specialist Clinic Hour
Time Frame: 105 randomized clinic days
Number of completed care encounters among all clinic patients (with and without diabetes) per retina specialist clinic hour. Numerator is the number of completed care encounters (including persons evaluated by autonomous AI on Intervention Days who are determined not to need to see the retina specialist). The denominator is retina specialist clinic working time in hours.
105 randomized clinic days

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Specialist Productivity Adjusted for Patient Complexity for Patients With Diabetes
Time Frame: 105 randomized clinic days

Specialist productivity (care encounters / specialist clinic hour) adjusted for patient complexity for patients with diabetes.

The complexity score for each patient participant was calculated by a masked United Kingdom National Health Service grader using the International Grading system, adapted from Wilkinson et al. International Clinical Diabetic Retinopathy and Diabetic Macular Edema Severity Scales (no DED = 0 points, mild non-proliferative DED = 0 points, moderate or severe non-proliferative DED = 1 point, proliferative DED = 3 points and diabetic macular edema = 2 points.) The patient participant complexity score was summed across both eyes. The average complexity score for each arm was calculated.

Complexity adjusted specialist productivity was calculated for intervention and control arms by multiplying the respective overall productivity (care encounters per specialist clinic hour) calculation by the respective average complexity score.
105 randomized clinic days
Number of Participants Who Were Very Satisfied or Satisfied With Autonomous AI
Time Frame: 105 randomized clinic days
After the patient participant completed the autonomous AI process, a survey with a 4-point Likert scale ("very satisfied," "satisfied," "dissatisfied," "very dissatisfied") was administered, concerning the participant's satisfaction with interactions with the healthcare team, time to receive examination results, and receiving their diagnosis from the autonomous AI system.
105 randomized clinic days

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Orbis

Collaborators

Deep Eye Care Foundation (DECF)
Digital Diagnostics, Inc.

Investigators

  • Study Chair: Nathan Congdon, MD, MPH, Orbis

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

March 20, 2022

Primary Completion (Actual)

July 31, 2022

Study Completion (Actual)

July 31, 2022

Study Registration Dates

First Submitted

November 16, 2021

First Submitted That Met QC Criteria

December 20, 2021

First Posted (Actual)

January 10, 2022

Study Record Updates

Last Update Posted (Estimated)

February 6, 2024

Last Update Submitted That Met QC Criteria

February 1, 2024

Last Verified

January 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • ORBIS-DXS-DECF-2021

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

We do not plan to share IPD

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

Yes

product manufactured in and exported from the U.S.

Yes

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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