AI-Powered DIY Screening System for Diabetic Retinopathy

Success rate of using the DIY screening booth help will be determined by the number of successful screening runs without active assistant help divided by the total number of screening runs.

Assessment of consumer acceptability will be determined by the positive response rate/screening rate (i.e. the total number of eligible patients who agree to screening (numerator) divided by the total number of eligible individuals (denominator)).

All retinal images will be re-graded by two independent ophthalmologists, with any disagreements adjudicated by a third ophthalmologist (gold standard). This grading result will be considered as gold standard reference for the diagnostic accuracy of the automated screening. The indicators for diagnostic accuracy include: sensitivity.

The detection rate is defined as the proportion of newly diagnosed DR cases divided by the total number of eligible individuals.

Patient adherence to referral will be measured as the proportion of patients who attend an ophthalmology service among the total number of referred patients.

The investigators will use a standardized checklist to assess the quality of images acquired during the study. This checklist will include criteria resolution, clarity, and completeness of the images. A sample of images will be reviewed by a panel of experts to ensure consistency and reliability in the assessment.

The cost-effective analyses will involve using the incremental cost-effectiveness ratio (ICER) as the key indicator to identify whether DIY screening model is a good investment.

The responses to the 5-point Likert scale question will be analysed using the "document variable statistics" function in MAXQDA software. Data from the open-ended questionnaire will be analysed thematically. All themed information will be shared for review by project steering committee. The Likert scale ranges from 1 to 5. The content includes 5 options, including strongly disagree, disagree, neural, agree, strongly agree. The higher scores (e.g., 4 or 5) indicate a stronger agreement or a more positive attitude towards the statement, while lower scores (e.g., 1 or 2) indicate disagreement or a more negative attitude.

All retinal images will be re-graded by two independent ophthalmologists, with any disagreements adjudicated by a third ophthalmologist (gold standard). This grading result will be considered as gold standard reference for the diagnostic accuracy of the automated screening. The indicators for diagnostic accuracy include: specificity.

All retinal images will be re-graded by two independent ophthalmologists, with any disagreements adjudicated by a third ophthalmologist (gold standard). This grading result will be considered as gold standard reference for the diagnostic accuracy of the automated screening. The indicators for diagnostic accuracy include: accuracy.

All retinal images will be re-graded by two independent ophthalmologists, with any disagreements adjudicated by a third ophthalmologist (gold standard). This grading result will be considered as gold standard reference for the diagnostic accuracy of the automated screening. The indicators for diagnostic accuracy include: positive/negative predictive values.

All retinal images will be re-graded by two independent ophthalmologists, with any disagreements adjudicated by a third ophthalmologist (gold standard). This grading result will be considered as gold standard reference for the diagnostic accuracy of the automated screening. The indicators for diagnostic accuracy include: area under curve.

The investigators will conduct time-motion studies to evaluate the impact of the new imaging process on clinic flow. This will track the time taken for image acquisition, processing, and reporting and record the total time spent.

The investigators will involve track any delays or disruptions in the clinic schedule.

The investigators will maintain a log of technical errors encountered during the image acquisition process. This log will include the type of error.

The investigators will maintain a log of technical errors encountered during the image acquisition process. This log will record the frequency of each type of technical errors.

The investigators will maintain a log of technical errors encountered during the image acquisition process. This log will document any corrective actions taken in response to technical errors. Regular review meetings will be held to analyze these errors and implement strategies to minimize their occurrence.