Bangladesh PRODUCTIVity in Eyecare Trial

NCT05182580 | Completed Results FDA Device

• 1 other identifier: ORBIS-DXS-DECF-2021
• Study Type: interventional
• Target: 993
• Locations: 1 country
• Sites: 1

Brief 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

Diabetic Retinopathy; Diabetic Macular Edema

Outcome Measures

Primary Outcomes (2)

• Number of Completed Care Encounters Among Clinic Patients With Diabetes Per Retina Specialist Clinic Hour

  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

  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 Outcomes (2)

• Specialist Productivity Adjusted for Patient Complexity for Patients With Diabetes

  105 randomized clinic days

• Number of Participants Who Were Very Satisfied or Satisfied With Autonomous AI

  105 randomized clinic days

Study Arms (2)

Intervention Group

EXPERIMENTAL

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

Control Group

NO INTERVENTION

All participants see the retina specialist irrespective of the results of their autonomous AI evaluation.

Interventions

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

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

Intervention Group

Eligibility Criteria

• Age: 22 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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

You may not qualify if:

• 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

Sponsors & Collaborators

• Orbis: lead
• Digital Diagnostics, Inc.: collaborator
• Deep Eye Care Foundation (DECF): collaborator

Study Sites (1)

Deep Eye Care Foundation

Rangpur City, Bangladesh

Location

Related Publications (1)

• Abramoff MD, Whitestone N, Patnaik JL, Rich E, Ahmed M, Husain L, Hassan MY, Tanjil MSH, Weitzman D, Dai T, Wagner BD, Cherwek DH, Congdon N, Islam K. Autonomous artificial intelligence increases real-world specialist clinic productivity in a cluster-randomized trial. NPJ Digit Med. 2023 Oct 4;6(1):184. doi: 10.1038/s41746-023-00931-7.

  PMID: 37794054 DERIVED

MeSH Terms

Conditions

Diabetic Retinopathy

Condition Hierarchy (Ancestors)

Retinal Diseases; Eye Diseases; Diabetic Angiopathies; Vascular Diseases; Cardiovascular Diseases; Diabetes Complications; Diabetes Mellitus; Endocrine System Diseases

Results Point of Contact

• Title: Dr. Nathan Congdon, Director of Research
• Organization: Orbis International

ncongdon1@gmail.com

646-674-5514

Study Officials

• Nathan Congdon, MD, MPH

  Orbis

  STUDY CHAIR

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, CARE PROVIDER
• Masking Details: The retina specialists are masked both to patient group assignment (that is, whether autonomous AI results were used or not on the particular clinic day) and also masked to the results of the autonomous AI on Intervention days. Patients are also masked to group assignment and autonomous AI screening results.
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

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

Study Record Dates

• First Submitted: November 16, 2021
• First Posted: January 10, 2022
• Study Start: March 20, 2022
• Primary Completion: July 31, 2022
• Study Completion: July 31, 2022
• Last Updated: February 6, 2024
• Results First Posted: February 6, 2024

Record last verified: 2024-01

Data Sharing

• IPD Sharing: Will not share

Locations

BA (1)