Visual ImpairmentNCT06877988
Artificial Intelligence (AI) - Assisted Visual Impairment Screening Model: Community-based Implementation and Evaluation of Performance, Feasibility and Costs.
A study testing AI in people with Visual Impairment, run by Singapore Eye Research Institute at 1 site in Singapore.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 50 years and olderHealthy volunteers can take part
- Conditions the study is for
- Visual Impairment
- What is being tested?
- AI
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 400 participants
- Where
- 1 siteSingapore
- Study dates
- 27 Jun 2024to 31 Mar 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 50 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Individuals aged 50 years old and above.
Who cannot join
- Individuals aged below 50 years old.
Trial locations and contacts
1 site in 1 country.
About this study
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?
Read more
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.
- Conditions
- Visual Impairment
- Being tested
- AI
- Keywords
- Visual impairment, Community Screening, Randomized Controlled Trial (RCT), Artificial Intelligence (AI)
- Medical subject headings
- Vision Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AIDevice
Also called AVIRI (AI for Disease-related Visual Impairment Screening Using Retinal Imaging)
Retinal photography-based deep learning algorithm for detection of disease-related visual impairment cases
| Study group | Role | What they receive |
|---|---|---|
| AI-assisted | Experimental | 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. Receives: Device: AI |
| Traditional | No intervention | 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 being measured
The primary outcome is the main question the study is designed to answer.
Performance of AVIRI on the detection of visual impairment
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.
Measured: through study completion, an average 1 year
Secondary outcomes (4)
Operational efficiency
Evaluation includes (i) average screening time per patient and (ii) average number of patients screened per session.
Measured: through study completion, an average 1 year
Patient acceptability
Patient Acceptability is assessed via a 6-item questionnaire (4-point Likert scale: 'Satisfaction' or 'Likelihood') administered by trained coordinators.
Measured: through study completion, an average 1 year
Perceptions of feasibility
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.
Measured: through study completion, an average 1 year
Cost savings of implementing the AI-assisted screening model
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.
Measured: through study completion, an average 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Mar 2025
- Study start27 Jun 2024
- Primary completion27 Feb 2026
- Study completion31 Mar 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Visual ImpairmentStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Singapore Eye Research Institute
- Sponsor type
- University, hospital or other
- Collaborators
- Institute of High Performance Computing (IHPC), A*STAR Research Institutes, National University Polyclinics, Singapore
- Responsible party
- Principal investigator, Tham Yih Chung, Singapore Eye Research Institute
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06877988
- Sponsor's protocol ID
- 2024/2297
- Status last verified
- Mar 2026
- First submitted
- 7 Mar 2025
- Last updated
- 11 Mar 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Chen Y, Koh KH, Ho JWC, Yew SME, Goh JHL, Lum E, Tham YC. Evaluation of a Community-Based AI-Assisted Visual Impairment Screening Model for Performance, Operational Efficiency, Acceptability, Feasibility, and Costs: Protocol for a 2-Arm Pragmatic Randomized Controlled Trial. JMIR Res Protoc. 2026 Mar 2;15:e74164. doi: 10.2196/74164.
PubMed 41773693
Study at a glance
From the registry record, last updated by the sponsor on 11 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence (AI) - Assisted Visual Impairment Screening Model: Community-based Implementation and Evaluation of Performance, Feasibility and Costs.
- ClinicalTrials.gov ID
- NCT06877988
- Acronym / sponsor ID
- 2024/2297
- Conditions
- Visual Impairment
- Keywords
- Visual impairment, Community Screening, Randomized Controlled Trial (RCT), Artificial Intelligence (AI)
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 400 participants (estimated)
- Lead sponsor
- Singapore Eye Research InstituteUniversity, hospital or other
- Collaborators
- Institute of High Performance Computing (IHPC), A*STAR Research Institutes, National University Polyclinics, Singapore
- Study start
- 27 Jun 2024 (actual)
- Primary completion
- 27 Feb 2026 (actual)
- Study completion
- 31 Mar 2026 (estimated)
- First posted
- 14 Mar 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-assisted | Experimental | Device: AIParticipants 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. |
| Traditional | No intervention | –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. |
Who may qualify
- Ages
- 50 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- Individuals aged 50 years old and above.
Key exclusion criteria (1 listed)
- Individuals aged below 50 years old.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AIAlso: AVIRI (AI for Disease-related Visual Impairment Screening Using Retinal Imaging)Retinal photography-based deep learning algorithm for detection of disease-related visual impairment cases | Device | AI-assisted |
Primary outcome
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.
4 secondary outcomes
Operational efficiency
Time frame: through study completion, an average 1 year
Patient acceptability
Time frame: through study completion, an average 1 year
Perceptions of feasibility
Time frame: 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
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Mar 2026.
- Derived from this study: PubMed 41773693Chen Y, Koh KH, Ho JWC, Yew SME, Goh JHL, Lum E, Tham YC. Evaluation of a Community-Based AI-Assisted Visual Impairment Screening Model for Performance, Operational Efficiency, Acceptability, Feasibility, and Costs: Protocol for a 2-Arm Pragmatic Randomized Controlled Trial. JMIR Res Protoc. 2026 Mar 2;15:e74164. doi: 10.2196/74164.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI in people with Visual Impairment, run by Singapore Eye Research Institute at 1 site in Singapore.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 11 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Singapore. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Performance of AVIRI on the detection of visual impairment (time frame: through study completion, an average 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06877988, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 Mar 2026; AzTrials last refreshed its copy on 26 Oct 2026.