Screening to detect diseases early is attractive as it can improve the prognosis and decrease costs, but it is often a problematic concept and there are several pitfalls. Many healthy individuals have to be investigated to avoid a disease in a few, which results in a dilemma because to save a few, many are exposed to a procedure that could potentially harm them. Other examples of problems associated with screening are latent diseases and over-treating. The question of optimal design of a screening program is another source of uncertainty for decision-makers, as a screening program may potentially be implemented in very different ways. This highlights the need for structured analyses that weigh benefits against the harms and costs that occur as consequences of the screening.

The aim of this thesis is, therefore, to explore, develop and implement methods for health economic evaluations of screening programs. This is done to identify problems and suggest solutions to improve future evaluations and in extension policy making.

This aim was analysed using decision analytic cost-effectiveness analyses constructed as Markov models. These are well-suited for this task given the sequential management approach where all relevant data are unlikely to come from a single source of evidence. The input data were in this thesis obtained from the published literature and were complemented with data from Swedish registries and the included case studies. The case studies were two different types of screening programs; a program of screening for unknown atrial fibrillation and a program to detect colorectal cancer early. Further, the implementation of treatment with thrombectomy and novel oral anticoagulants were used to illustrate how factors outside the screening program itself have an impact on the evaluations.

As shown by the result of the performed analyses, the major contribution of this thesis was that it provided a simple and systematic approach for the economic evaluation of multiple screening designs to identify an optimal design.

In both the included case studies, the screening was considered costeffective in detecting the disease; unknown atrial fibrillation and colorectal cancer, respectively. Further, the optimal way to implement these screening programs is dependent on the threshold value for cost-effectiveness in the health care sector and the characteristics of the investigated cohort. This is because it is possible to gain increasingly more health benefits by changing the design of the screening program, but that the change in design also results in higher marginal costs. Additionally, changes in the screening setting were shown to be important as they affect the cost-effectiveness of the screening. This implies that flexible modelling with continuously updated models are necessary for an optimal resource allocation.