Factors associated with treatment escalation among MS specialists and general neurologists: Results from an International cojoint study

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Abstract

Previous studies in multiple sclerosis (MS) showed that therapeutic inertia (TI) affects 60-90% of neurologists and up to 25% of daily treatment decisions. The objective of this study was to determine the most common factors and attribute levels associated with decisions to treatment escalation in an international study in MS care.

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Conjoint analysis applications in health--a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force.

John F. P. Bridges, A. Brett Hauber, Deborah Marshall … (2011)

The application of conjoint analysis (including discrete-choice experiments and other multiattribute stated-preference methods) in health has increased rapidly over the past decade. A wider acceptance of these methods is limited by an absence of consensus-based methodological standards. The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Good Research Practices for Conjoint Analysis Task Force was established to identify good research practices for conjoint-analysis applications in health. The task force met regularly to identify the important steps in a conjoint analysis, to discuss good research practices for conjoint analysis, and to develop and refine the key criteria for identifying good research practices. ISPOR members contributed to this process through an extensive consultation process. A final consensus meeting was held to revise the article using these comments, and those of a number of international reviewers. Task force findings are presented as a 10-item checklist covering: 1) research question; 2) attributes and levels; 3) construction of tasks; 4) experimental design; 5) preference elicitation; 6) instrument design; 7) data-collection plan; 8) statistical analyses; 9) results and conclusions; and 10) study presentation. A primary question relating to each of the 10 items is posed, and three sub-questions examine finer issues within items. Although the checklist should not be interpreted as endorsing any specific methodological approach to conjoint analysis, it can facilitate future training activities and discussions of good research practices for the application of conjoint-analysis methods in health care studies. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

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Discrete Choice Experiments in Health Economics: Past, Present and Future

Vikas Soekhai, Esther W. de Bekker-Grob, Alan R. Ellis … (2018)

Objectives Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990–2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges. Methods A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated. Results Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels. Conclusions The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers’ confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research. Electronic supplementary material The online version of this article (10.1007/s40273-018-0734-2) contains supplementary material, which is available to authorized users.

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Discrete choice experiments in health economics: a review of the literature.

Esther W. de Bekker-Grob, Mandy Ryan, Karen Gerard (2012)

Discrete choice experiments (DCEs) have become a commonly used instrument in health economics. This paper updates a review of published papers between 1990 and 2000 for the years 2001-2008. Based on this previous review, and a number of other key review papers, focus is given to three issues: experimental design; estimation procedures; and validity of responses. Consideration is also given to how DCEs are applied and reported. We identified 114 DCEs, covering a wide range of policy questions. Applications took place in a broader range of health-care systems, and there has been a move to incorporating fewer attributes, more choices and interview-based surveys. There has also been a shift towards statistically more efficient designs and flexible econometric models. The reporting of monetary values continues to be popular, the use of utility scores has not gained popularity, and there has been an increasing use of odds ratios and probabilities. The latter are likely to be useful at the policy level to investigate take-up and acceptability of new interventions. Incorporation of interactions terms in the design and analysis of DCEs, explanations of risk, tests of external validity and incorporation of DCE results into a decision-making framework remain important areas for future research. Copyright © 2010 John Wiley & Sons, Ltd.