Abstract: In decision making regarding optimal resource allocation to safeguard public health, policymakers and healthcare providers rely on the availability and reliability of data about the relative costs and benefits of competing treatment options. One such an approach is based on cost effectiveness analysis (CEA) which is intended to be used as a combined metric of both the costs and health outcomes of alternative intervention strategies. However, the usual measures used in CEA are not readily analyzable based on standard statistical paradigms for inference. Further, reliable data may not always be available to estimate relevant parameters. Accordingly, it is essential to employ nonstandard procedures to compensate for information gaps and to address inferential difficulties. In this paper, we outline the issues associated with some of the commonly used techniques, with particular emphasis on the so-called network meta-analysis and indirect comparisons. Additional reference is made to the complexities introduced when data are used from observational studies. It is concluded that effective use of CEA in healthcare policy presupposes a careful appreciation of the underlying issues, and implementation of robust remedial measures to mitigate their impacts.
Keywords: Cost-Effectiveness Analysis, Network Meta-analysis, Indirect Comparisons, Health Economics