Expansion of Integrated AI Solution for Diabetic Retinopathy Screening in Thailand

Study Overview
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Brief Summary
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Efficiency and effectiveness of real-world diabetic retinopathy screening by artificial intelligent (AI) are limited. Investigators will implement AI for diabetic retinopathy screening in 13 health districts in Thailand and investigate the efficiency, effectiveness as well as patients and health care personnel's satisfaction by an implementation research.

Official Title
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Expansion of Integrated AI Solution for Diabetic Retinopathy Screening in Thailand: An Implementation Research

Conditions
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Diabetic Retinopathy

Intervention / Treatment
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* Diagnostic Test: Diabetic retinopathy screening by artificial intelligence
* Diagnostic Test: Diabetic retinopathy screening by healthcare personnel


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Type 1 or 2 diabetes mellitus patients whose name are in primary hospital record No full-time ophthalmologists in those primary hospital Age more than or equal to 18 years Eligible for fundus photo imaging at least 1 eye Exclusion Criteria: Type 1 or 2 diabetes mellitus patients whose name are in primary hospital record that have full-time ophthalmologists Patients who previously diagnosed with other causes of macular edema, for example, Age-related Macular Degeneration, Radiation Retinopathy, Retinal Vein Occlusion etc. History of retinal laser or surgery Other ocular diseases that require referral to ophthalmologists Not eligible for fundus photo imaging for both eyes (any causes)

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| AI screening group<br>Diabetes mellitus patients undergo diabetic retinopathy screening by AI | Diagnostic Test: Diabetic retinopathy screening by artificial intelligence<br>* Screening diabetic patients' eyes with AI through digital health platform<br>|
| Manual screening group<br>Diabetes mellitus patients undergo diabetic retinopathy screening by health care personnel | Diagnostic Test: Diabetic retinopathy screening by healthcare personnel<br>* Screening diabetic patients' eyes by conventional method (healthcare personnel)<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Effectiveness of AI in diabetic retinopathy screening | Referral adherance of patients in AI group in percentage | Throughout the whole period of screening, approximately 6 months | 
| Efficiency of AI in diabetic retinopathy screening | Down time and failure rate of AI system | Throughout the whole period of screening, approximately 6 months | 
| Efficiency of AI in diabetic retinopathy screening | Cost in development and implement of AI system in Thai baht unit | Throughout the whole period of screening, approximately 6 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Satisfaction of patients and health care personnel in AI-based screening | Measurement of health care personnel's satisfaction by well-developed questionnaire | At the end of the screening, approximately at Month 6 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Diabetic Retinopathy, Screening, Deep Learning Algorithm, Human Grader