Clinical trial NCT06763952: Leveraging Artificial Intelligence to Prevent Vision Loss From Diabetes Among Socioeconomically Disadvantaged Communities
Official title: Leveraging Artificial Intelligence to Prevent Vision Loss From Diabetes Among Socioeconomically Disadvantaged Communities
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Vision
Diabetes
Keywords: Artificial Intelligence
AI
diabetic eye disease
cluster randomized trial
pragmatic trial
Lead sponsor: University of Wisconsin, Madison
Sponsor class: OTHER
Collaborators: name: National Eye Institute (NEI)
First posted: 2025-01-08
Enrollment: 4000
Sex: ALL
Minimum age (years): 22
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: SEQUENTIAL
Intervention model description: A stepped-wedge cluster randomized clinical trial will be conducted to evaluate the effectiveness of two standard diabetic retinopathy screenings across 9 underserved primary care clinics.
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: 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.

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.

Eligibility criteria: Inclusion Criteria:

* Eligible patients include patients older than 21 years
* 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:

-

Primary outcomes:
measure: Proportion of Participants Who Follow Up With Recommended Eye Care
timeFrame: up to 6 months
Secondary outcomes:
measure: Difference in Proportion of White vs Hispanic and White vs Black Participants Who Get Eye Screening
timeFrame: up to 6 months
measure: Proportion of Participants By Race and Ethnicity Who Get Eye Screening
timeFrame: up to 6 months
Other outcomes:
measure: Level of Diabetic Retinopathy
timeFrame: up to 6 months
Locations:
city: Madison
country: United States
facility: UW School of Medicine and Public Health
state: Wisconsin
Study officials:
affiliation: UW School of Medicine and Public Health
name: Roomasa Channa
role: PRINCIPAL_INVESTIGATOR
References: