Background: Patient access to orphan medicinal products (OMPs) is limited and varies between countries, reimbursement decisions on OMPs are complex, and there is a need for more transparent processes to know which criteria should be considered to inform these decisions. This study aimed to determine the most relevant criteria for the reimbursement of OMPs in Spain, from a multi-stakeholder perspective, and using multicriteria decision analysis (MCDA).
Methods: An MCDA was developed in 3 phases and included 28 stakeholders closely related to the field of rare diseases (6 physicians, 5 hospital pharmacists, 7 health economists, 4 patient representatives and 6 members from national and regional health authorities). Initially [phase A], a bibliographic review was conducted to identify the potential reimbursement criteria. Then, a reduced advisory board (8 members) proposed, selected, and defined the final list of criteria that could be relevant for reimbursement. A discrete choice experiment (DCE) [phase B] was developed to determine the relevance and relative importance weight of such criteria according to the stakeholders' preferences by choosing between pairs of hypothetical financing scenarios. A multinomial logit model was fitted to analyze the DCE responses. Finally [phase C], the advisory board review the results using a deliberative process.
Results: Thirteen criteria were selected, related to 4 dimensions: patient population, disease, treatment, and economic evaluation. Nine criteria were deemed relevant for decision-making and associated with a higher relative importance: Health-related quality of life (HRQL) (23.53%), treatment efficacy (14.64%), availability of treatment alternatives (13.51%), disease severity (12.62%), avoided costs (11.21%), age of target population (7.75%), safety (seriousness of adverse events) (4.72%), quality of evidence (3.82%) and size of target population (3.12%). The remaining criteria had a < 3% relative importance: economic burden of disease (2.50%), cost of treatment (1.73%), cost-effectiveness (0.83%) and safety (frequency of adverse events) (0.03%).
Conclusion: The reimbursement of OMPs in Spain should be determined by its effect on patient's HRQL, the extent of its therapeutic benefit from efficacy and the availability of other therapeutic options. Furthermore, the severity of the rare disease should also influence the decision along with the potential of the treatment to avoid associated costs.
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http://dx.doi.org/10.1186/s13023-021-01809-1 | DOI Listing |
Foods
December 2024
Chemical Engineering Faculty, Centro de Estudios y de Investigación en Biotecnología (CIBIOT), Universidad Pontificia Bolivariana, Medellín 050031, Colombia.
This study evaluated the desorption of cadmium (Cd) from cocoa waste-derived flour using organic acids. Cocoa pods were collected from Antioquia and Casanare, Colombia, to analyze the geographical Cd content and its distribution within the pod tissues. Acid selection was performed using a multi-criteria decision-making (MCDM) matrix, and Cd desorption was assessed through a full factorial 2 experimental design, considering acid concentration, pulp density, and agitation speed.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Civil Engineering Department, Engineering School, Pontificia Universidad Javeriana, Colombia; Ciencia e Ingeniería del agua y el ambiente Research Group, Pontificia Universidad Javeriana, Colombia; Instituto Javeriano del Agua, Pontificia Universidad Javeriana, Carrera 7a No. 40-62, Bogotá, Colombia.
Coastal areas face significant challenges due to natural and anthropogenic changes, such as sea level rise, extreme events and coastal erosion. The coastal management requires the consideration of socioeconomic and environmental factors to address these variables. The selection of an appropriate Decision Support Tool (DST) based on decision matrix method plays a crucial role in implementing coastal management strategies to tackle climate change-related issues.
View Article and Find Full Text PDFSci Rep
January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Mathematics, Dambi Dollo University, Dambi Dollo, Oromia, Ethiopia.
A novel method for solving the multiple-attribute decision-making problem is proposed using the complex Diophantine interval-valued Pythagorean normal set (CDIVPNS). This study aims to discuss aggregating operations and how they are interpreted. We discuss the concept of CDIVPN weighted averaging (CDIVPNWA), CDIVPN weighted geometric (CDIVPNWG), generalized CDIVPN weighted averaging (CGDIVPNWA) and generalized CGDIVPN weighted geometric (CGDIVPNWG).
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8572, Japan.
Conventional power generation methods have led to adverse environmental impacts. Thus, the need for a strategic transition to alternative energy sources arises. This study presents a comprehensive approach to sustainable solar energy deployment using multi-criteria decision-making (MCDM) techniques.
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