A Systematic Review of Discrete-Choice Experiments and Conjoint Analysis Studies in People with Multiple Sclerosis

Discrete-choice experiments (DCEs) have become a commonly used instrument in health economics and patient-preference analysis, addressing a wide range of policy questions. An important question when setting up a DCE is the size of the sample needed to answer the research question of interest. Although theory exists as to the calculation of sample size requirements for stated choice data, it does not address the issue of minimum sample size requirements in terms of the statistical power of hypothesis tests on the estimated coefficients. The purpose of this paper is threefold: (1) to provide insight into whether and how researchers have dealt with sample size calculations for healthcare-related DCE studies; (2) to introduce and explain the required sample size for parameter estimates in DCEs; and (3) to provide a step-by-step guide for the calculation of the minimum sample size requirements for DCEs in health care. Electronic supplementary material The online version of this article (doi:10.1007/s40271-015-0118-z) contains supplementary material, which is available to authorized users.

Complex and highly sensitive electronic literature search strategies are required for systematic reviews; however, no guidelines exist for their peer review. Poor searches may fail to identify existing evidence because of inadequate recall (sensitivity) or increase the resource requirements of reviews as a result of inadequate precision. Our objective was to create an annotated checklist for electronic search strategy peer review. A systematic review of the library and information retrieval literature for important elements in electronic search strategies was conducted, along with a survey of individuals experienced in systematic review searching. Six elements with a strong consensus as to their importance in peer review were accurate translation of the research question into search concepts, correct choice of Boolean operators and of line numbers, adequate translation of the search strategy for each database, inclusion of relevant subject headings, and absence of spelling errors. Seven additional elements had partial support and are included in this guideline. This evidence-based guideline facilitates the improvement of search quality through peer review, and thus the improvement in quality of systematic reviews. It is relevant for librarians/information specialists, journal editors, developers of knowledge translation tools, research organizations, and funding bodies.