Artificial Intelligence (AI) - Assisted Visual Impairment Screening Model: Community-based Implementation and Evaluation of Performance, Feasibility and Costs.

March 10, 2026 updated by: Tham Yih Chung, Singapore Eye Research Institute

The goal of this observational study is to evaluate the performance, operational efficiency, acceptability, feasibility, and cost-effectiveness of an AI-assisted screening model for visual impairment in a community setting. The main questions it aims to answer are:

  • Can the AI-assisted screening model improve screening and referral accuracy compared to the current traditional screening approach?
  • Does the AI-assisted model enhance operational efficiency and reduce healthcare costs in a community setting?

Researchers will compare the AI-assisted model with the current traditional screening approach to assess its impact on screening accuracy, operational efficiency, and cost-effectiveness.

Participants will:

  • Undergo vision screening using either the AI-assisted model or the traditional model.
  • Provide feedback on the acceptability of the screening approach.
  • Contribute to evaluating the feasibility and costs associated with each screening method.

Study Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

400

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Singapore
    • Singapore
      • Singapore, Singapore, Singapore, 648201
        • Pioneer Polyclinic

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Individuals aged 50 years old and above.

Exclusion Criteria:

  • Individuals aged below 50 years old.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Double

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI-assisted
Participants will undergo visual impairment screening using AVIRI model (AI for Disease-related Visual Impairment Screening Using Retinal Imaging). This intervention involves automated fundus image analysis through artificial intelligence to screen and identify individuals with high probability of visual impairment.
Device: AI
Retinal photography-based deep learning algorithm for detection of disease-related visual impairment cases
Other Names:
  • AVIRI (AI for Disease-related Visual Impairment Screening Using Retinal Imaging)
No Intervention: Traditional
Participants will receive visual impairment screening using the traditional screening model, which involves optometrists performing initial assessments, followed by referral decisions based on manual fundus image evaluation.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Performance of AVIRI on the detection of visual impairment
Time Frame: through study completion, an average 1 year
The primary outcome is the detection performance for VI (refractive error-related and disease-related VI) and the rate of correct referral, with reference to the expert panels' diagnosis . To assess whether the new AI-assisted model has better referral accuracy than the current traditional model, the accuracy, AUC values, sensitivity, specificity and other performance metrics of the two models will be calculated and compared.
through study completion, an average 1 year

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Operational efficiency
Time Frame: through study completion, an average 1 year
Evaluation includes (i) average screening time per patient and (ii) average number of patients screened per session.
through study completion, an average 1 year
Patient acceptability
Time Frame: through study completion, an average 1 year
Patient Acceptability is assessed via a 6-item questionnaire (4-point Likert scale: 'Satisfaction' or 'Likelihood') administered by trained coordinators.
through study completion, an average 1 year
Perceptions of feasibility
Time Frame: through study completion, an average 1 year
Perceptions of feasibility is evaluated through at least two focus groups with optometrists and one with service providers will be conducted, guided by the Consolidated Framework for Implementation Research (CFIR). Discussions will explore barriers and facilitators influencing the AI screening model's adoption. Data will be inductively and deductively coded by two researchers using CFIR constructs; discrepancies resolved through consensus or a third researcher.
through study completion, an average 1 year
Cost savings of implementing the AI-assisted screening model
Time Frame: through study completion, an average 1 year
Researchers will quantify the incremental cost savings of implementing the AI-assisted screening model over the PSS model using an Activity Based Costing (ABC) approach that quantifies all non-sunk costs (including labor, materials and supplies, and amortized technology and space utility/ rental costs) required to conduct each assessment stratified by key activities of each screening model (e.g., conduct screening examinations, operationalize the AVIRI algorithm, on-site generation of test results etc.). Fixed costs will be amortized over the inputs' expected useful life (i.e. involved fixed assets' life expectancy). For the cost of clinical assessments, researchers will use non-subsidized bill sizes as these are expected to approximate actual costs.
through study completion, an average 1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Singapore Eye Research Institute

Collaborators

National University Polyclinics, Singapore
Institute of High Performance Computing (IHPC), A*STAR Research Institutes

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 27, 2024

Primary Completion (Actual)

February 27, 2026

Study Completion (Estimated)

March 31, 2026

Study Registration Dates

First Submitted

March 7, 2025

First Submitted That Met QC Criteria

March 10, 2025

First Posted (Actual)

March 14, 2025

Study Record Updates

Last Update Posted (Actual)

March 11, 2026

Last Update Submitted That Met QC Criteria

March 10, 2026

Last Verified

March 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2024/2297

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

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

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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