Expansion of Integrated AI Solution for Diabetic Retinopathy Screening in Thailand

• Conditions: Diabetic Retinopathy
• Interventions: Diagnostic Test: Diabetic retinopathy screening by artificial intelligence; Diagnostic Test: Diabetic retinopathy screening by healthcare personnel

• Registration Number: NCT05527535
• Lead Sponsor: Rajavithi Hospital

Brief Summary

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.

Detailed Description

Not available

Study Timeline

• Status Verified: 2022-08
• Study First Submitted: 2022-08-25
• Study First Submitted QC: 2022-08-31
• Last Update Submitted: 2022-08-31
• Study First Posted: 2022-09-02
• Last Update Posted: 2022-09-02
• Study Start: 2022-10-03
• Primary Completion: 2023-03-31
• Study Completion: 2023-09-30

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 34500

Inclusion Criteria

1. Type 1 or 2 diabetes mellitus patients whose name are in primary hospital record
2. No full-time ophthalmologists in those primary hospital
3. Age more than or equal to 18 years
4. Eligible for fundus photo imaging at least 1 eye

Exclusion Criteria

1. Type 1 or 2 diabetes mellitus patients whose name are in primary hospital record that have full-time ophthalmologists
2. Patients who previously diagnosed with other causes of macular edema, for example, Age-related Macular Degeneration, Radiation Retinopathy, Retinal Vein Occlusion etc.
3. History of retinal laser or surgery
4. Other ocular diseases that require referral to ophthalmologists
5. Not eligible for fundus photo imaging for both eyes (any causes)

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
AI screening group	Diabetic retinopathy screening by artificial intelligence	Diabetes mellitus patients undergo diabetic retinopathy screening by AI
Manual screening group	Diabetic retinopathy screening by healthcare personnel	Diabetes mellitus patients undergo diabetic retinopathy screening by health care personnel

Primary Outcome Measures

Name	Time	Method
Effectiveness of AI in diabetic retinopathy screening	Throughout the whole period of screening, approximately 6 months	Referral adherance of patients in AI group in percentage
Efficiency of AI in diabetic retinopathy screening	Throughout the whole period of screening, approximately 6 months	Cost in development and implement of AI system in Thai baht unit

Secondary Outcome Measures

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