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Enrolling by invitation NCT07559292

Implementing Artificial Intelligence to Prevent Vision Loss From Diabetes

No phase Interventional Vision Disorders Diabetes

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: AI, Usual Practice.
Who it may be relevant to
Registry conditions: Vision Disorders, Diabetes. Basic parameters: from 22 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
United States
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Implementing Artificial Intelligence (AI) to Prevent Vision Loss From Diabetes

Overview

This pragmatic clinical trial is being conducted to test the effectiveness of AI in improving screening and follow-up eye care compared to usual-care among patients with diabetes across 4 primary care clinics. This is an autonomous AI-based screening to detect diabetic eye disease at primary care visits.

Detailed description

Four clinics from two health systems will be recruited, with two clinics from each health system and randomly assigned to either usual-care or the AI Intervention with 2 clinics assigned to each arms. Beginning in month 3, a 6-week baseline period will be conducted in all clinics, followed by a 4-month intervention period for the two clinics assigned to AI.

Primary Objective:

Compare the odds of patients, who get eye screening in the AI and usual-care arms within 5 months of the recommendation

Secondary Objective:

1. Compare the odds of patients, who completed follow-up with recommended eye care in the AI and usual-care arms within 5 months of the recommendation 2. Compare the odds of patients in different demographic groups who receive eye screening in the AI and usual-care arms within 5 months of the recommendation

Interventions

  • Other AI
    AI-based eye screening program
  • Other Usual Practice
    PCP recommends annual vision screening, a separate visit entirely

Primary outcome measures

  • Proportion of patients who get eye screening in the AI and usual-care arms within 5 months of the recommendation [Time frame: up to 5 months]
Secondary outcome measures (2)
  • Proportion of patients, who completed follow-up with recommended eye care in the AI and usual-care arms within 5 months of the recommendation [Time frame: up to 5 months]
  • Proportion of patients in different demographic groups who receive eye screening in the AI and usual-care arms within 5 months of the recommendation [Time frame: up to 5 months]

Eligibility criteria

Clinic Inclusion Criteria:

  • Serve at least 267 patients with diabetes during the study period
  • No point-of-care screening system in use for diabetic eye disease
  • Agree to share limited identifiers data as requested

Patient Inclusion Criteria:

  • Age 22 years or older
  • Diagnosis of type 1 or 2 diabetes
  • No known diabetic eye disease
  • No diabetic eye exam in the past 12 months

Exclusion criteria

  • Have a documented eye exam in the electronic health record within 12 months of the date of the primary care visit.
  • Contraindication includes diagnosed with macular edema, severe non-proliferative retinopathy, proliferative retinopathy, radiation retinopathy, or retinal vein occlusion.
  • Pregnant

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Health services research

Study locations

United States · 1 center
  • University of Wisconsin — Madison

Identifiers

NCT: NCT07559292 · 2025-1248 · SMPH | Ophthal and Visual · Protocol Version 4/2/24

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗