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      Potential impact of the implementation of multiple-criteria decision analysis (MCDA) on the Polish pricing and reimbursement process of orphan drugs

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          The objective of this study was to assess the potential impact of the implementation of multiple-criteria decision analysis (MCDA) on the Polish pricing and reimbursement (P&R) process with regard to orphan drugs.


          A four step approach was designed. Firstly, a systematic literature review was conducted to select the MCDA criteria. Secondly, a database of orphan drugs was established. Thirdly, health technology appraisals (HTA recommendations) were categorized and an MCDA appraisal was conducted. Finally, a comparison of HTA and MCDA outcomes was carried out. An MCDA outcome was considered positive if more than 50 % of the maximum number of points was reached (base case). In the sensitivity analysis, 25 % and 75 % thresholds were tested as well.


          Out of 2242 publications, 23 full-text articles were included. The final MCDA tool consisted of ten criteria. In total, 27 distinctive drug-indication pairs regarding 21 drugs were used for the study. Six negative and 21 positive HTA recommendations were issued. In the base case, there were 19 positive MCDA outcomes. Of the 27 cases, there were 12 disagreements between the HTA and MCDA outcomes, the majority of which related to positive HTA guidance for negative MCDA outcomes. All drug-indication pairs with negative HTA recommendations were appraised positively in the MCDA framework. Economic details were available for 12 cases, of which there were 9 positive MCDA outcomes. Amongst the 12 drug-indication pairs, two were negatively appraised in the HTA process, with positive MCDA guidance, and two were appraised in the opposite direction.


          An MCDA approach may lead to different P&R outcomes compared to a standard HTA process. On the one hand, enrichment of the list of decision making criteria means further scrutiny of a given health technology and as such increases the odds of a negative P&R outcome. On the other hand, it may uncover additional values and as such increase the odds of positive P&R outcomes.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13023-016-0388-0) contains supplementary material, which is available to authorized users.

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          Most cited references 26

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          Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

           James Dolan (2009)
          Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).
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            Cost-effectiveness analysis and the consistency of decision making: evidence from pharmaceutical reimbursement in australia (1991 to 1996).

            The principle aim of this study was to generate a league table of drugs considered by the Australian Pharmaceutical Benefits Advisory Committee (PBAC) for reimbursement. The table was used to test the hypothesis that decisions made by the PBAC are consistent with the maxim of economic efficiency. In addition, we explored whether the past decisions by the PBAC revealed a threshold incremental cost-effectiveness ratio beyond which the PBAC is not prepared to recommend reimbursement of a drug. All 355 submissions made to the PBAC between January 1991 and June 1996 were reviewed. Submissions using cost per life-year gained (26 submissions) or the cost per quality adjusted life-year (QALY) gained (9 submissions) were ranked in a league table and compared with advice given by the PBAC about that drug. The confidentiality restrictions for the submissions require that the individual drug details cannot be revealed in this article. There was a statistically significant difference between the cost per life-year gained for drugs that were recommended for listing and those that were not, suggesting that the PBAC has been broadly consistent with the use of economic efficiency as a criterion for decision making. We did not find an explicit threshold beyond which the PBAC was unwilling to pay for additional life years gained. However, between 1992 and 1996 the PBAC appears to have been unlikely to recommend a drug for listing if the additional cost per life-year exceeded 76 000 Australian dollars [$AU] (1998/1999 values) and was unlikely to reject a drug for which the additional cost per life-year gained was less than $AU42 000. The cost-effectiveness ratio was not the only factor determining the reimbursement decision. The results of this preliminary study indicate that decisions to recommend a drug for listing by the PBAC in the last few years have, by and large, been consistent with the notion of economic efficiency.
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              Exploring the social value of health-care interventions: a stated preference discrete choice experiment.

              Much of the literature on distributive preferences covers specific considerations in isolation, and recent reviews have suggested that research is required to inform on the relative importance of various key considerations. Responding to this research recommendation, we explore the distributive preferences of the general public using a set of generic social value judgments. We report on a discrete choice experiment (DCE) survey, using face-to-face interviews, in a sample of the general population (n=259). The context for the survey was resource allocation decisions in the UK National Health Service, using the process of health technology appraisal as an example. The attributes used covered health improvement, value for money, severity of health, and availability of other treatments, and it is the first such survey to use cost-effectiveness in scenarios described to the general public. Results support the feasibility and acceptability of the DCE approach for the elicitation of public preferences. Choice data are used to consider the relative importance of changes across attribute levels, and to model utility scores and relative probabilities for the full set of combinations of attributes and levels in the experimental design used (n=64). Results allow the relative social value of health technology scenarios to be explored. Findings add to a sparse literature on 'social' preferences, and show that DCE data can be used to consider the strength of preference over alternative scenarios in a priority-setting context.

                Author and article information

                +48 781 881 007 ,
                Orphanet J Rare Dis
                Orphanet J Rare Dis
                Orphanet Journal of Rare Diseases
                BioMed Central (London )
                10 March 2016
                10 March 2016
                : 11
                [ ]Department of Health Economics, Nicolaus Copernicus University Collegium Medicum, Sandomierska 16, 85-830 Bydgoszcz, Poland
                [ ]Advanced Management Training Programme in Pharmacoeconomics, Pharmaceutical Marketing and Law, Warsaw University of Technology Business School, Warsaw, Poland
                [ ]Department of Health Policy & Health Economics, Faculty of Social Sciences, Eötvös Loránd University (ELTE), Budapest, Hungary
                © Kolasa et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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                Infectious disease & Microbiology


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