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The global distribution of primary ophthalmic medical resources is uneven, and the traditional eye disease screening model has problems such as low efficiency, high cost and limited coverage. With the development of artificial intelligence and other technologies, it provides technical support for the construction of intelligent mobile screening model for eye diseases. The investigator's team has developed the 5G intelligent ophthalmic vehicle and served tens of thousands of people in 108 cities nationwide, initially verifying the feasibility of the new intelligent mobile screening model. However, the application effect, acceptance and influencing factors of this model in different regions are not clear, and there is a lack of economic benefit analysis based on real-world data. In this study, the investigators will conduct a cross-sectional study of large-scale population screening for blinding eye diseases in grassroots areas through the smart mobile screening model, focusing on the screening effectiveness and cost-effectiveness of the smart mobile screening model, integrating real-world multimodal eye health data, developing multiple smart screening analysis models, and exploring its adaptability and direction of improvement in grassroots areas.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intelligent Mobile Group | Participants were first screened for mobile eye health risk classification, and those who met the requirements were further screened by eye examination on the mobile clinic and suspected cases were recommended to be referred to higher level hospitals for consultation, and corresponding data were collected at different visit points. |
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| Measure | Description | Time Frame |
|---|---|---|
| Cost-effectiveness | Incremental Cost per True Positive Case Detected | Baseline,6months,12months |
| Measure | Description | Time Frame |
|---|---|---|
| Eye disease detection rate | Baseline,6months,12months | |
| Accuracy of multiple intelligent screening analysis models | Baseline | |
| Screening participation rate |
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Inclusion Criteria:
Exclusion Criteria:
-Inability to complete the required examinations with the help of others due to old age, infirmity, poor general condition, etc.
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community sample or primary care clinic
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Lin Haotian | Contact | 86-13802793086 | haot.lin@hotmail.com | |
| Xiao Wei | Contact | 86-13535160850 | xiaow33@mail2.sysu.edu.cn |
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| baseline |
| ID | Term |
|---|---|
| D002386 | Cataract |
| D012030 | Refractive Errors |
| D003930 | Diabetic Retinopathy |
| D008268 | Macular Degeneration |
| ID | Term |
|---|---|
| D007905 | Lens Diseases |
| D005128 | Eye Diseases |
| D012164 | Retinal Diseases |
| D003925 | Diabetic Angiopathies |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D048909 | Diabetes Complications |
| D003920 | Diabetes Mellitus |
| D004700 | Endocrine System Diseases |
| D012162 | Retinal Degeneration |
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