Cut costs and time
DSI (now KORA), the Danish Institute of Health, and Signifikans, a CRO in statistical analysis, concluded that RetinaLyze could severely decrease the time and money spent on manual grading in societies.
Purpose
To implement an operational economic evaluation of the Retinalyze software system used for the automated detection of the diabetic eye disease, retinopathy, by means of fundus photography.
Methods
Review of the present relevant literature. Comparison and analysis of RetinaLyze-related studies.
Results
The marginal cost per screening is between DKK 13.10 and DKK 27.16 with the automated analysis instead of the visual. At e.g. annual screenings at a typical eye doctor’s practice, the costs total between DKK 60,800 and DKK 87,300, varying with the number of patients screened positive. This presupposes internalization of savings achieved through task-shifting (time release for doctors).
The total costs must be compared to an expected activity progress in the number of eye screenings caused by the task-shifting and the related incomes in the form of e.g. health insurance services. In addition to this, there are non-quantified gains in the form qualitative implications of the screenings, improved opportunities for time-series studies accompanied by image database development as well as improved opportunities for tele-screening.
With conservative model assumptions, about 11.1 full-time eye doctor positions are used on examinations per year in connection with diabetic retinopathy, with the present number of diabetics and with the use of ophthalmoscopy and/or visual image analysis.
With the use of the Retinalyze software system for automated image analysis, the task-shifting will influence the number of eye doctor positions used for examinations in connection with diabetic retinopathy on the decline and causes a saving potential in the form of released time corresponding to 8.4 full-time eye doctor position per year, based on conservative conditions.
Sensitivity analysis do not change the conclusion of the analysis significantly, as the saving potential obtained as time release is still estimated to be important in a situation with eye doctor shortage, relatively long waiting lists and an expected increase in the demand for screenings.
Conclusions
With the review of the present literature, it is concluded that the detection of diabetic retinopathy by means of automated image analysis can be achieved with a system performance directly comparable 19 to the one for experienced ophthalmologists with visual image analysis. The results prove further examination of automated fundus image analysis as a screening tool. Automated image analysis instead of visual image analysis causes a task-shifting, with a shift of tasks from ophthalmologists to nurses / specially trained paramedical personnel.