Diabetic Retinopathy Screening Point-of-Care Artificial Intelligence

NCT ID: NCT06721351

Last Updated: 2025-11-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Clinical Phase

NA

Total Enrollment

548 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-07-27

Study Completion Date

2026-04-30

Brief Summary

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This research study is being conducted to improve eye care by using artificial intelligence (AI) to make diabetic eye screenings faster and more accessible. AI technology mimics human decision-making, enabling computers and systems to analyze medication information. Specifically for this screening, AI examines digital images of the eye and based on that information, may identify if a participant has diabetic retinopathy. It can assist doctors in making decisions about a participant's diagnosis, treatment or care plans to improve patient care. This is a collaboration between San Ysidro Health (SYHealth), University of California, San Diego (UC San Diego), and Eyenuk. The Kaiser Permanente Augmented Intelligence in Medicine and Healthcare Initiative (AIM-HI) awarded SYHealth funds to demonstrate the value of AI technologies in diverse, real-world settings.

Detailed Description

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This study is intended to address unmet medical needs in diabetic eye care in a community health center setting by enhancing and modifying existing clinical practices with the integration of point-of-care (POC) artificial intelligence (AI) technology for Diabetic Retinopathy (DR) screening. Using a special camera and a computer system called EyeArt® to make diabetic eye screenings faster and more accessible. EyeArt®, is a Food Drug and Administration (FDA)-cleared device system for fast, non-invasive Diabetic retinopathy screening. This non-invasive DR screening does not require dilation and provides immediate results and facilitates informed discussions with their primary care provider. This study will optimize, implement, and test the impact of a multicomponent intervention that includes: 1) autonomous DR screening, a fast and non-invasive retinal exam into the primary care settings with 2) integration of the results into the EHR and 3) health education/care coordination support (e.g., patient education). Primary Objective (Clinical): Evaluate the implementation and effectiveness of a multicomponent AI clinical intervention on DR screenings rate, early stages of DR detection, and referrals to the specialist for follow up on abnormal results. Secondary Objectives: Evaluate the implementation and effectiveness of a multicomponent AI clinical intervention on DR knowledge, attitudes, self-efficacy, and patient satisfaction.

Participants will be active SYHealth patients 22 years of age or older with diabetes mellitus (DM) who have not had a retinal exam in the last 11 months, and have a medical visit scheduled during the intervention period and are able to read and understand either English or Spanish in order to provide informed consent and complete study surveys. Exclusion criteria: 1) have a prior diagnosis of DR, macular edema, or retinal vascular occlusion; 2) have persistent visual Impairment in one or both eyes; 3) history of ocular injections, laser treatment of the retina, or intraocular surgery (excluding cataract surgery); 4) pregnant women; and 5) diagnosis of mental or degenerative disease that prevents self-consent for the study. The study will recruit a cohort of 848 adults from two SYHealth clinic sites.

Once the potential participants arrive at their study visit appointment, they will complete the consent process, pre-survey (knowledge, attitudes and self-efficacy about diabetes and eye health). Participants will be randomized into either the DR screening-AI-intervention or retinal screening usual care groups and continue study activities as follows:

1. Participants assigned to the DR screening-AI-intervention group will undergo DR screening in-clinic prior to the medical visit using a special camera and the EyeArt® Artificial Intelligence (AI) system (Eyenuk, Inc.), an FDA-cleared AI device for fast, non-invasive DR screening. This screening, which does not require dilation, uses a camera with a smart computer technology using AI that can detect signs of significant diabetic retinopathy in less than five minutes. These results will be immediately integrated into the electronic health record (EHR), enabling informed discussions with their primary care provider at the time of their medical visit and will automatically generate the referrals to an eye specialist for participants with abnormal findings. Participants will receive a copy of the results immediately after completion of the screening. After the screening, participants will receive a copy of the results of the screening, health education information on DR and eye health before completing their baseline study visit. Subsequently, they will proceed with their medical visit to ensure continuity of their diabetes care.
2. Participants in the retinal screening usual care group will receive assistance from the RA to schedule the appointment with an eye care provider according to SYHealth's protocols for routine retinal screening, which includes dilation. After the RA scheduled the visit with the eye care provider, participants will receive health education information on DR and eye health before completing their baseline study visit. Subsequently, they will proceed with their medical visit to ensure continuity of their diabetes care.

Appointments with the eye care provider are usually at a different clinic location based on availability, and the retinal screenings are not completed on the same day of the medical visit with their primary care provider. At the time of the visit with the eye care provider will discuss the retinal screening results with the participant and may conduct a comprehensive eye exam, submitting referrals for any abnormal results.

Conditions

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Diabetic Retinopathy (DR)

Keywords

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Point-of-care (POC) artificial intelligence (AI) technology for DR screening Diabetic Retinopathy (DR) Screening Diabetes

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

The DRES-POCAI study uses a randomized controlled, open-label, parallel superiority trial.

Randomization: Participants will be randomized into two groups: usual care (receive a retinal screening by an optometrist) or intervention group (receive a retinal screening using a special camera and FDA-cleared EyeArt® system, an autonomous AI-based DR screening).

Open-label Design: Blinding participants and providers to the autonomous DR screening is logistically difficult. The intervention's immediate results and potential impact on the workflow necessitate an open-label approach.

Parallel Design: The parallel design allows for a clear, side-by-side comparison of outcomes between the intervention and usual care groups over time.

Superiority Evaluation: The primary objective is to determine if the multi-component DRES-POCAI intervention is superior to usual care in increasing DR screenings, early detection, referrals, and patient knowledge/self-efficacy.
Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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Usual care

The usual care group will complete the DR screening with an eye care provider on a different day and at a different location. The study staff will facilitate this process for participants in the usual care group by assisting them in scheduling appointments for their routine retinal screening.

Group Type NO_INTERVENTION

No interventions assigned to this group

Diabetic Retinopathy Screening

The intervention group will complete the DR screening using a special camera and the AI system (EyeArt®), the same day of the study visit. Participants assigned to the intervention group will also receive a retinal screening without dilation using the EyeArt® AI system; the DR screening will be completed before their medical provider visits. The results will be available immediately after the screening, allowing participants to learn about and discuss their eye health with their care provider.

Group Type EXPERIMENTAL

Diabetic Retinopathy screening Point of Care Artificial Intelligence

Intervention Type DIAGNOSTIC_TEST

Random assignment of participants to intervention and control groups minimizes confounding variables. This ensures that any observed differences in outcomes are likely due to the intervention itself and not pre-existing differences between the groups. Participants of the DRES-POCAI study will be randomized into two groups: usual care (receive a retinal screening by an optometrist) or intervention group (receive a retinal screening using a special camera and EyeArt® system, an autonomous AI-based DR screening). The randomization will occur after consenting and completing the surveys, prior to conducting the DR screening process (for those randomized to the intervention group).

Interventions

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Diabetic Retinopathy screening Point of Care Artificial Intelligence

Random assignment of participants to intervention and control groups minimizes confounding variables. This ensures that any observed differences in outcomes are likely due to the intervention itself and not pre-existing differences between the groups. Participants of the DRES-POCAI study will be randomized into two groups: usual care (receive a retinal screening by an optometrist) or intervention group (receive a retinal screening using a special camera and EyeArt® system, an autonomous AI-based DR screening). The randomization will occur after consenting and completing the surveys, prior to conducting the DR screening process (for those randomized to the intervention group).

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

1. Capacity to provide informed consent. Individuals must have the capacity to understand the study information, risks, and benefits and voluntarily provide informed consent.
2. Stated willingness to comply with all study procedures and availability for the duration of the study.
3. Established and active patient of SYHealth-CV and KC (having a medical appointment in the last 18 months).
4. Person aged 22 and older.
5. Established diagnosis of DM.
6. Medical appointment(s) (in-person or telehealth) scheduled during the intervention period.
7. Has not completed a dilated eye exam or retinal exam in the last 11months.

Exclusion Criteria

1. have a prior diagnosis of DR, macular edema, or retinal vascular occlusion;
2. have persistent visual Impairment in one or both eyes;
3. history of ocular injections, laser treatment of the retina, or intraocular surgery (excluding cataract surgery);
4. pregnant women; and
5. diagnosis of mental or degenerative disease that prevents self-consent for the study.
Minimum Eligible Age

22 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Eyenuk, Inc.

INDUSTRY

Sponsor Role collaborator

University of California, San Diego

OTHER

Sponsor Role collaborator

Centro De Salud La Comunidad De San Ysidro Inc DBA: San Ysidro Health

OTHER

Sponsor Role lead

Responsible Party

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Fatima Muñoz

Associate Vice President Health Support Services

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Fatima Muñoz, MD, MPH

Role: PRINCIPAL_INVESTIGATOR

San Ysidro Health

Nicole Stadnick, PhD

Role: PRINCIPAL_INVESTIGATOR

University of California, San Diego

Locations

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San Ysidro Health Chula Vista

Chula Vista, California, United States

Site Status

San Ysidro Health - Comprehensive Health Center - Ocean View

San Diego, California, United States

Site Status

San Ysidro Health King-Chavez Health Center

San Diego, California, United States

Site Status

Countries

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United States

References

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Diaz EA, Seifert ML, Gruning V, Stadnick NA, Lugo-Butler E, Servin AN, Rodriguez-Rosales CI, Geremia C, Ramachandra C, Bhaskaranand M, Howard D, Solis O, Velasquez S, Snook B, Tucker S, Munoz FA. Diabetic Retinopathy Screening Among Federally Qualified Health Center Patients Using Point-of-Care AI: DRES-POCAI: A Trial Protocol. JAMA Netw Open. 2025 Oct 1;8(10):e2538114. doi: 10.1001/jamanetworkopen.2025.38114.

Reference Type DERIVED
PMID: 41118165 (View on PubMed)

Other Identifiers

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212825-SYH-04

Identifier Type: OTHER

Identifier Source: secondary_id

RHP-091323-159

Identifier Type: -

Identifier Source: org_study_id