Health Economics (Further details)

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There is resource use associated with diabetic retinopathy in screening, follow-up appointments and treatment. We seek to capture all resource use for patients that relates directly to diabetic eye disease. This is primarily achieved using data from the Data Warehouse, which captures information on attendance at photographic screening, follow-up attendance at assessment clinics, and all treatment in secondary care. Additionally, we are administering a questionnaire to the first 700 participants randomised in the trial. This is self-completed by patients in this group whenever they attend a screening appointment, and it will allow us to estimate the personal expenses associated with screening. The questionnaire itself can be downloaded from the Database of Instruments for Resource Use Measurement. In attaching costs to resource use, we seek to go beyond unit prices and assess costs at a local level. In order to achieve this we will arrange visits to the screening clinics and the hospital eye service.

Quality of Life

It is important to consider the quality of life impact of risk-based screening. We are collecting the EQ-5D-5L and the Health Utilities Index Mark 3 (HUI3) questionnaires from the first 700 participants recruited to the trial. The same group will complete the questionnaires at each screening appointment that they attend. The EQ-5D-5L and HUI3 are descriptive systems of health-related quality of life and facilitate the estimation of a preference-based measure of health and thus quality-adjusted life years (QALYs). These health state utility values will also be combined with a meta-analysis of previously published estimates. A protocol for this review has been published in the journal Systematic Reviews


We will evaluate the cost-effectiveness of risk-based screening (as implemented in the ISDR trial) of 6 months, 1 year (the current policy) and 2 year recall. Our primary outcome will be the cost-per-QALY, but we will also explore other outcomes such as visual acuity and cost per year of sight saved. We will carry out an economic evaluation alongside the clinical trial to estimate the incremental costs and effects observed in our trial sample. However, our primary analyses will be based on decision analytic models. We have constructed a cohort state transition (Markov) model designed to evaluate policies within the NHS Diabetic Eye Screening Programme. This model will be populated with the data described above and used to evaluate the cost-effectiveness of risk-based screening compared with annual screening. Furthermore, we will build a discrete event simulation (DES) model. In addition to being able to evaluate a set of policy options, the DES can be used to explore a wider set of decision problems. The DES will be dependent on a set of time-to-event estimates, which will be estimated alongside the cohort study