Leveraging Artificial Intelligence to Prevent Vision Loss From Diabetes

Multicenter National Parallel Cluster Randomized Controlled Superiority Trial Comparing an Artificial Intelligence-Based Screening Strategy to Usual Care for Improving Eye-Care Follow-Up Among Patients With Diabetes (AI-BRIDGE Trial)

This study aims to investigate whether a novel artificial intelligence based screening strategy (AI-Based point of caRe, Incorporating Diagnosis, SchedulinG, and Education or AI-BRIDGE), which allows primary care providers to screen patients for vision-threatening diabetic eye disease in the primary care clinic, improves screening and follow-up care rates across race/ethnicity groups and reduces racial/ethnic disparities in screening.

Study Overview

• Status: Not yet recruiting
• Conditions: Diabetes Mellitus; Diabetic Retinopathy
• Intervention / Treatment: Other: AI

Detailed Description

This is a multicenter clinical trial and University of Wisconsin is the coordinating center of the study.

A stepped-wedge cluster randomized clinical trial will be conducted. The investigators will evaluate the effectiveness of two standard diabetic retinopathy screening strategies at primary care clinics; (1) AI-based eye screening program called AI-BRIDGE, eye photos of the patients will be obtained in the primary care clinic by trained clinic staff. Images will be reviewed using autonomous artificial-intelligence (AI) algorithm (Digital Diagnostics). Patients with referrable diabetic retinopathy are detected within minutes and patients with referrable disease will be assisted with scheduling an in-person follow-up eye care visit (2) usual care screening, primary care providers refer patients with diabetes to an eye care provider for an in-person dilated eye exam.

After adapting AI-BRIDGE protocols to clinics and training of clinic personnel, stepped wedge randomized clinical trial begins with sites transitioning from usual-care to AI-BRIDGE in 4 steps.

Primary Objective:

• Compare the proportion of patients, by race and ethnicity, who follow-up with recommended eye care in the AI-BRIDGE and usual-care arms within 6 months of the recommendation.

Secondary Objectives:

• Compare the difference in proportion of White vs Hispanic and White vs Black patients who get screening in the AI-BRIDGE and usual-care arms within 6 months of the recommendation.
• Compare proportion of patients, by race and ethnicity, who receive eye screening in the AI-BRIDGE and usual-care arms within 6 months of the recommendation.

• Study Type: Interventional
• Enrollment (Estimated): 4000
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Mozhdeh Bahrainian; Phone Number: 608-262-9955; Email: bahrainian@wisc.edu
• Study Contact Backup: Name: Roomasa Channa; Email: rchanna@wisc.edu

Study Locations

• United States
  • Wisconsin
    • Madison, Wisconsin, United States, 53792
      • UW School of Medicine and Public Health

Participation Criteria

Eligibility Criteria

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

Description

Inclusion Criteria:

• Diagnosed with type 1 or 2 diabetes
• No known diabetic eye disease
• Medicaid as their primary insurance
• Not had an eye exam in the prior year

Exclusion Criteria:

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Sequential Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: Usual Care Screening; Primary care providers refer patients with diabetes to an eye care provider for a dilated eye exam. Patients are provided with culturally adapted diabetic eye disease educational materials similar to that provided to patients in the AI-BRIDGE group.
Experimental: AI-BRIDGE; AI-based eye screening program called AI-Based point of caRe, Incorporating Diagnosis, SchedulinG, and Education (AI-BRIDGE). Eye photos of the patients will be obtained in the primary care clinic during a patient's regular primary care visit by a trained technician. Images will be reviewed using autonomous artificial-intelligence (AI) algorithm (Digital Diagnostics). Patients with referrable diabetic retinopathy are detected, and assisted with scheduling an in-person follow-up eye care visits. All patients irrespective of diabetic retinopathy status are also provided culturally adapted educational material on diabetic eye disease.	Other: AI; AI-based eye screening program

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Proportion of Participants Who Follow Up With Recommended Eye Care	Proportion of patients, by race and ethnicity, who follow-up with recommended eye care in the AI-BRIDGE and usual-care arms within 6 months of the recommendation.	up to 6 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Difference in Proportion of White vs Hispanic and White vs Black Participants Who Get Eye Screening	Difference in proportion of White vs Hispanic and White vs Black patients who get AI-BRIDGE and usual-care screening within 6 months of the recommendation.	up to 6 months
Proportion of Participants By Race and Ethnicity Who Get Eye Screening	Proportion of Participants by race and ethnicity who get eye screening in the AI-BRIDGE and usual-care arms within 6 months of the recommendation.	up to 6 months

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Level of Diabetic Retinopathy	The rate of diabetic retinopathy, count of unique diabetic retinopathy diagnosis divided by count of all enrolled patients, stratified by intervention, intervention and race and ethnicity groups, and intervention, race and ethnicity group, and clinic.	up to 6 months

Collaborators and Investigators

• Sponsor: University of Wisconsin, Madison
• Collaborators: National Eye Institute (NEI)
• Investigators: Principal Investigator: Roomasa Channa, UW School of Medicine and Public Health

Study record dates

Study Major Dates

• Study Start (Estimated): August 1, 2026
• Primary Completion (Estimated): May 1, 2030
• Study Completion (Estimated): May 1, 2030

Study Registration Dates

• First Submitted: December 26, 2024
• First Submitted That Met QC Criteria: January 7, 2025
• First Posted (Actual): January 8, 2025

Study Record Updates

• Last Update Posted (Actual): April 29, 2026
• Last Update Submitted That Met QC Criteria: April 27, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: Artificial Intelligence; pragmatic trial; AI; cluster randomized trial; diabetic eye disease
• Additional Relevant MeSH Terms: Endocrine System Diseases; Vascular Diseases; Cardiovascular Diseases; Metabolic Diseases; Glucose Metabolism Disorders; Eye Diseases; Diabetic Angiopathies; Diabetes Complications; Retinal Diseases; Nutritional and Metabolic Diseases; Diabetic Retinopathy; Diabetes Mellitus
• Other Study ID Numbers: 2026-0446; A536000 (Other Identifier: UW Madison); 2024-0030 (Other Identifier: UW Madison); 1R01EY035994 (U.S. NIH Grant/Contract); Protocol Version 2/20/26 (Other Identifier: UW Madison)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No