Rationale of cost-effectiveness analysis in diagnostic imaging
A cost-effectiveness analysis is the comparative analysis of alternative courses of action in terms of both their costs and consequences. In imaging, these alternative courses of action can be utilization of different imaging techniques, or, more generally, imaging versus no imaging. The rationale of CEA in DI is that the choice of DI test influences both costs as well as effectiveness of disease management. In a conceptual framework developed by Fineberg et al. [18] and modified by others [19], effectiveness of a diagnostic test is expressed on subsequent hierarchical levels: technical performance, diagnostic accuracy, diagnostic impact, therapeutic impact and health outcome. Effectiveness in terms of patients’ health outcome is indirectly influenced by the diagnostic test due to medical care decisions based on imaging. The health outcome can also directly be affected by the imaging test itself. Health effects can be physical, for example because of altered treatment, and psychological, for example because of receiving a diagnosis. Direct and indirect health effects can be measured in utility scores, from which Quality Adjusted Life Years (QALYs) can be derived, combining survival and quality of life. Both physical and psychological health conditions are incorporated in a QALY. Looking at costs, these are directly affected by the costs of the diagnostic test itself as well as indirectly influenced by costs of treatment chosen based on imaging and resulting costs of patients’ health outcome. Figure 1 illustrates the concept of these direct and indirect effects used in CEA in DI.
Fig. 1 Comprehensive framework of cost-effectiveness analysis in diagnostic imaging
When assessing the cost-effectiveness of DI, the initial question is whether adding an imaging test in a medical pathway does improve medical decision-making. Taking a hypothetical 100 % accuracy for a test would be used to assess changes in outcome by adding this particular test to the medical pathway. Only if the perfectly accurate test provides added value, it is reasonable to continue the analysis with the actual sensitivity and specificity of the test [20]. However, in many clinical situations imaging is already an existing standard part of the particular disease management. CEA is, therefore, used to compare potential new imaging technologies or imaging strategies to each other as well as to the current reference standard. We will focus on this second model throughout the article.