Cost-effectiveness modelling in diagnostic imaging: a stepwise approach

Abstract

Diagnostic imaging (DI) is the fastest growing sector in medical expenditures and takes a central role in medical decision-making. The increasing number of various and new imaging technologies induces a growing demand for cost-effectiveness analysis (CEA) in imaging technology assessment. In this article we provide a comprehensive framework of direct and indirect effects that should be considered for CEA in DI, suitable for all imaging modalities. We describe and explain the methodology of decision analytic modelling in six steps aiming to transfer theory of CEA to clinical research by demonstrating key principles of CEA in a practical approach. We thereby provide radiologists with an introduction to the tools necessary to perform and interpret CEA as part of their research and clinical practice.

Key points: • DI influences medical decision making, affecting both costs and health outcome. • This article provides a comprehensive framework for CEA in DI. • A six-step methodology for conducting and interpreting cost-effectiveness modelling is proposed.

Keywords: Cost Effectiveness; Decision Modelling; Diagnostic Imaging; Economics; Technology Assessment.

Fig. 1

Comprehensive framework of cost-effectiveness analysis in diagnostic imaging

Fig. 2

Schematic example of a decision tree model

Fig. 3

Schematic example of a Markov model

Fig. 4

Cost-effectiveness graph. QALY: Quality adjusted live years. ICER: Incremental cost-effectiveness ratio

Fig. 5

Schematic example of cost-effectiveness acceptability curves (CEACs). The probability of cost-effectiveness of three investigated imaging tests is plotted against the willingness to pay for a quality adjusted life year (QALY) [6]