Using routine healthcare data to inform cost-effectiveness analysis of complex pathways: case study of cost-effectiveness analysis of cascade testing protocols for familial hypercholesterolaemia

Cascade screening refers to the systematic testing of relatives of people known to have the disease with the aim of starting cholesterol-lowering treatment early, hence prevent heart disease.
We will present how we conducted the cost-effectiveness analysis of cascade testing protocols to make the best use of the available routinely collected healthcare data. The performance of different elements of the diagnostic pathways modelled was informed by two UK datasets describing current cascade services. The long-term outcomes in the cost-effectiveness model were informed by an analysis of cardiovascular outcomes using primary care data linked to hospital care data and mortality statistics.
We will discuss how we approach issues with data availability (e.g., one of the planned databases was unexpectedly not available, another database did not include key data fields), issues with relating the available data to the decision problem (e.g., generalisability of the data to the performance of the diagnostic pathways), and how the features of the data informed the analytical approach (e.g., limitations of using routine data to estimate treatment effect and alternative approaches).