Artificial Intelligence-Enabled Referral Pathways for Early Diagnosis of Complications Arising from Diabetes: Application to Diabetic Retinopathy
Background
Diabetic Retinopathy (DR) is one of the leading causes of vision loss among diabetic patients. A complication of diabetes, DR is preventable through timely screening and diagnosis. To combat the delay in diagnosis through traditional methods, our project aims to implement AI-enabled systematic screening at diabetic clinics to enhance accuracy of diagnosis. Timely and accurate diagnosis and streamlined referral system for the diagnosed diabetics can help minimize vision loss in them.
About the Study
AI-enabled screening systems will be installed in IDEA clinics where diabetic patients are monitored and treated. The study will assess whether these systems assist in earlier detection of visual impairment in patients in comparison to traditional tertiary care methods. Other than the effectiveness of AI enabled screening, its cost-effectiveness and its impact on follow-up adherence will also be assessed.
Methodology
The study will use a prospective cohort design that means studying a group of people over a period of time to assess their response to exposure to a factor over that period. Then a relationship between the outcome and factor they were exposed to is derived. Similarly, Diabetic patients at these clinics will be screened with AI-enabled systems by trained staff. Outcomes for the study cohort will then be compared to the patients at regular eye clinics. Key metrics will include:
- Accuracy of DR diagnosis
- Referral rates
- Treatment uptake
- Patient satisfaction
- Cost effectiveness to ascertain the economic viability of AI assisted screenings
In nutshell, the study aims to establish the usefulness and economic viability of AI technology in DR screening and diagnosis.
Intended Outcomes
By establishing the efficiency of AI-enabled screening for DR, the study will generate evidence to facilitate early detection and thus reduce the risk of vision loss among diabetics. Also, the study will generate insights to support policies and practices for enhanced DR management. Ethical considerations like informed consent and participant welfare, will be paramount to ensure sustainable healthcare advancement and responsible use of technology.