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      Patient Preference and Adherence (submit here)

      This international, peer-reviewed Open Access journal by Dove Medical Press focuses on the growing importance of patient preference and adherence throughout the therapeutic process. Sign up for email alerts here.

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      Setting Organ Allocation Priorities: A Discrete Choice Experiment with German Patients and Their Relatives

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          Abstract

          Purpose

          Organ transplantation systems benefit from guidelines that are harmonious with the preferences of the people involved. Discrete choice experiments are useful tools for eliciting preferences.

          Patients and Methods

          This study evaluated the preferences of patients and their relatives (n=285) to identify their priorities in organ allocation using a discrete choice experiment. In eight hypothetical allocation decisions, the participants were asked to select the candidate they considered the most suitable The candidates differed in years of life gained after transplantation, quality of life after transplantation, waiting time until transplantation, age, compliance and social support.

          Results

          The most important aspects for setting priority in organ allocation were lack of compliance (β= −2.5, p<0.001) and good quality of life after transplantation (β = +1.4, p<0.001). The lack of social support (ß = −0.8, p<0.05) and the more years of life gained after transplantation (β = +0.5, p<0.001) had less but still a significant amount of influence on this decision, while the waiting list was not considered significantly important (β = 0.1, p>0.05). The comparison of the different relations to transplantation showed that life years gained after transplantation was of high relevance to posttransplant patients (+10 years: β = +0.709, p<0.001 / +15 years: β = +0.700, p<0.001) and of no importance to waitlisted patients (+10 years: β = +0.345, p>0.05 / + 15 years: β = +0.173, p>0.05) and relatives (+ 10 years: β = +0.063, p>0.05 / +15 years: β = +0.304, p>0.05).

          Conclusion

          This study provides useful insights into the unique perspective of patients and their relatives on priority-setting in the allocation of donor organs that should be reflected in improved donor organ allocation rules.

          Most cited references23

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          Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force.

          Stated-preference methods are a class of evaluation techniques for studying the preferences of patients and other stakeholders. While these methods span a variety of techniques, conjoint-analysis methods-and particularly discrete-choice experiments (DCEs)-have become the most frequently applied approach in health care in recent years. Experimental design is an important stage in the development of such methods, but establishing a consensus on standards is hampered by lack of understanding of available techniques and software. This report builds on the previous ISPOR Conjoint Analysis Task Force Report: Conjoint Analysis Applications in Health-A Checklist: A Report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. This report aims to assist researchers specifically in evaluating alternative approaches to experimental design, a difficult and important element of successful DCEs. While this report does not endorse any specific approach, it does provide a guide for choosing an approach that is appropriate for a particular study. In particular, it provides an overview of the role of experimental designs for the successful implementation of the DCE approach in health care studies, and it provides researchers with an introduction to constructing experimental designs on the basis of study objectives and the statistical model researchers have selected for the study. The report outlines the theoretical requirements for designs that identify choice-model preference parameters and summarizes and compares a number of available approaches for constructing experimental designs. The task-force leadership group met via bimonthly teleconferences and in person at ISPOR meetings in the United States and Europe. An international group of experimental-design experts was consulted during this process to discuss existing approaches for experimental design and to review the task force's draft reports. In addition, ISPOR members contributed to developing a consensus report by submitting written comments during the review process and oral comments during two forum presentations at the ISPOR 16th and 17th Annual International Meetings held in Baltimore (2011) and Washington, DC (2012). Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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            Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

            Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two recent task force reports from the International Society for Pharmacoeconomics and Outcomes Research, has aided in improving the quality of conjoint analyses and DCEs in outcomes research. Nevertheless, uncertainty regarding good research practices for the statistical analysis of data from DCEs persists. There are multiple methods for analyzing DCE data. Understanding the characteristics and appropriate use of different analysis methods is critical to conducting a well-designed DCE study. This report will assist researchers in evaluating and selecting among alternative approaches to conducting statistical analysis of DCE data. We first present a simplistic DCE example and a simple method for using the resulting data. We then present a pedagogical example of a DCE and one of the most common approaches to analyzing data from such a question format-conditional logit. We then describe some common alternative methods for analyzing these data and the strengths and weaknesses of each alternative. We present the ESTIMATE checklist, which includes a list of questions to consider when justifying the choice of analysis method, describing the analysis, and interpreting the results.
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              Discrete choice experiments in health economics: a review of the literature.

              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.
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                Author and article information

                Journal
                Patient Prefer Adherence
                Patient Prefer Adherence
                ppa
                Patient preference and adherence
                Dove
                1177-889X
                24 March 2023
                2023
                : 17
                : 827-838
                Affiliations
                [1 ]Hannover Medical School, Institute of Epidemiology, Social Medicine and Health Systems Research , Hannover, Germany
                [2 ]Center for Health Economics Research Hannover , Hannover, Germany
                [3 ]General, Visceral and Transplant Surgery, Medical University Graz , Graz, Austria
                [4 ]Department of Methods of Community Medicine, Institute for Community Medicine, University of Greifswald , Greifswald, Germany
                Author notes
                Correspondence: Tim Bartling, Medizinische Hochschule Hannover / Hannover Medical School, Institute of Epidemiology, Social Medicine and Health Systems Research , Carl-Neuberg-Str, 1, Hannover, Lower Saxony, 30625, Germany, Tel +49 511 532 9462, Fax +49 511 532 5376, Email bartling.tim@mh-hannover.de
                Author information
                http://orcid.org/0000-0002-2867-8396
                http://orcid.org/0000-0002-5070-284X
                Article
                402203
                10.2147/PPA.S402203
                10044066
                30b53aaf-e1ea-4ab1-a533-7df50780bc09
                © 2023 Bartling et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 06 January 2023
                : 09 March 2023
                Page count
                Figures: 2, Tables: 4, References: 25, Pages: 12
                Funding
                Funded by: German Federal Ministry of Education and Research;
                Funded by: the Deutsche Forschungsgemeinschaft (DFG) as part of the “Open Access Publikationskosten” program;
                This study was funded by the German Federal Ministry of Education and Research (grant number: 01EH1603B). This publication is funded by the Deutsche Forschungsgemeinschaft (DFG) as part of the “Open Access Publikationskosten” program.
                Categories
                Original Research

                Medicine
                organ transplantation,health priorities,health resources,ethics,patient involvement,resource allocation,discrete choice experiment

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