Introduction
Increasing scrutiny of healthcare costs leads to a demand for proof of value for all medical expenditures. Cost-effectiveness analyses (CEA) intend to provide additional information about the possibilities of maximizing health effects, taking into account limited health care resources [1]. CEA have already become common practice in the evaluation of disease treatment strategies and diagnostic screening programs [2]. Diagnostic imaging (DI) is currently the fastest growing category in medical expenditure [3, 4]. Over the last years, an increasing number of CEA of DI technologies have been published [5–12], though broad application has yet to happen. The distinct central role diagnostic imaging plays in medical decision-making, as well as the continued emergence of new and varied imaging technologies, increases the importance of cost-effectiveness evaluation in imaging technology assessment. Several articles provide an overview on the theory of CEA in DI [13–15]. Although they contain excellent technical background, radiologists and other DI professionals still might feel insecure in performing and interpreting CEA, as economic evaluation is not part of medical training. Even for those doctors who received additional training, performing CEA analyses in DI is challenging due to missing standardized methodologies. Furthermore, the effects both on costs and health outcome largely depend on the treatment strategy decisions that are made based on the imaging results themselves. Consideration of these remote indirect effects requires more complex methodologies for CEA in DI compared to CEA in therapeutic services [16]. Synthesis of available evidence incorporated in decision analytic modelling forms the link between a diagnostic test and its effects in terms of costs and health outcome. A comprehensive practical guide to the use of decision modelling techniques can be found in the book of Briggs et al. [17]. The aim of this article is to provide an introduction to the tools necessary to perform and interpret CEA. We thereby transfer the theory of evidence synthesis and decision analytic modelling to practical clinical research by demonstrating key principles and steps of CEA in diagnostic imaging.