Expansion of Integrated AI Solution for Diabetic Retinopathy Screening in Thailand
1 other identifier
observational
34,500
0 countries
N/A
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Oct 2022
Shorter than P25 for all trials
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
August 25, 2022
CompletedFirst Posted
Study publicly available on registry
September 2, 2022
CompletedStudy Start
First participant enrolled
October 3, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 31, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
September 30, 2023
CompletedSeptember 2, 2022
August 1, 2022
6 months
August 25, 2022
August 31, 2022
Conditions
Keywords
Outcome Measures
Primary Outcomes (3)
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 Outcomes (1)
Satisfaction of patients and health care personnel in AI-based screening
At the end of the screening, approximately at Month 6
Study Arms (2)
AI screening group
Diabetes mellitus patients undergo diabetic retinopathy screening by AI
Manual screening group
Diabetes mellitus patients undergo diabetic retinopathy screening by health care personnel
Interventions
Screening diabetic patients' eyes with AI through digital health platform
Screening diabetic patients' eyes by conventional method (healthcare personnel)
Eligibility Criteria
All diabetes mellitus patients who visit for diabetic retinopathy screening at selected primary care units and hospitals in 13 health districts in Thailand
You may qualify if:
- 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
You may not qualify if:
- 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)
Contact the study team to confirm eligibility.
Sponsors & Collaborators
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- OTHER
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER GOV
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
August 25, 2022
First Posted
September 2, 2022
Study Start
October 3, 2022
Primary Completion
March 31, 2023
Study Completion
September 30, 2023
Last Updated
September 2, 2022
Record last verified: 2022-08
Data Sharing
- IPD Sharing
- Will not share
Fear of inappropriate use of data