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A Decision Support Tool Facilitating Medicine Design for Optimal Acceptability in The Older Population

PURPOSE: Medicine acceptability, which is of the utmost importance for vulnerable patients’ adherence, is driven by both user and product characteristics. Herein, a novel multivariate approach integrating the many aspects of acceptability is used to discriminate positively and negatively accepted me...

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Autores principales: Vallet, Thibault, Belissa, Emilie, Laribe-Caget, Sandra, Chevallier, Alain, Chedhomme, François-Xavier, Leglise, Patrick, Piccoli, Matthieu, Michelon, Hugues, Bloch, Vanessa, Meaume, Sylvie, Grancher, Anne-Sophie, Bachalat, Nathalie, Boulaich, Imad, Abdallah, Fattima, Rabus, Maite, Rwabihama, Jean-Paul, Ribemont, Annie-Claude, Lachuer, Celia, Perquy, Ines, Lechowski, Laurent, Delahaye, Anne, Depoisson, Mathieu, Orven, Yann, Guinot, Caroline, Gibaud, Stephane, Michel, Corinne, Mahiou, Abdel, Belbachir, Sid-Ahmed, Trouvin, Jean-Hugues, Dufaÿ-Wojcicki, Amelie, Boudy, Vincent, Ruiz, Fabrice
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5938307/
https://www.ncbi.nlm.nih.gov/pubmed/29736594
http://dx.doi.org/10.1007/s11095-018-2424-3
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author Vallet, Thibault
Belissa, Emilie
Laribe-Caget, Sandra
Chevallier, Alain
Chedhomme, François-Xavier
Leglise, Patrick
Piccoli, Matthieu
Michelon, Hugues
Bloch, Vanessa
Meaume, Sylvie
Grancher, Anne-Sophie
Bachalat, Nathalie
Boulaich, Imad
Abdallah, Fattima
Rabus, Maite
Rwabihama, Jean-Paul
Ribemont, Annie-Claude
Lachuer, Celia
Perquy, Ines
Lechowski, Laurent
Delahaye, Anne
Depoisson, Mathieu
Orven, Yann
Guinot, Caroline
Gibaud, Stephane
Michel, Corinne
Mahiou, Abdel
Belbachir, Sid-Ahmed
Trouvin, Jean-Hugues
Dufaÿ-Wojcicki, Amelie
Boudy, Vincent
Ruiz, Fabrice
author_facet Vallet, Thibault
Belissa, Emilie
Laribe-Caget, Sandra
Chevallier, Alain
Chedhomme, François-Xavier
Leglise, Patrick
Piccoli, Matthieu
Michelon, Hugues
Bloch, Vanessa
Meaume, Sylvie
Grancher, Anne-Sophie
Bachalat, Nathalie
Boulaich, Imad
Abdallah, Fattima
Rabus, Maite
Rwabihama, Jean-Paul
Ribemont, Annie-Claude
Lachuer, Celia
Perquy, Ines
Lechowski, Laurent
Delahaye, Anne
Depoisson, Mathieu
Orven, Yann
Guinot, Caroline
Gibaud, Stephane
Michel, Corinne
Mahiou, Abdel
Belbachir, Sid-Ahmed
Trouvin, Jean-Hugues
Dufaÿ-Wojcicki, Amelie
Boudy, Vincent
Ruiz, Fabrice
author_sort Vallet, Thibault
collection PubMed
description PURPOSE: Medicine acceptability, which is of the utmost importance for vulnerable patients’ adherence, is driven by both user and product characteristics. Herein, a novel multivariate approach integrating the many aspects of acceptability is used to discriminate positively and negatively accepted medicines in the older population. METHODS: An observational study was carried out in eight hospitals and eight nursing homes to collect a large set of real-life data on medicines uses in older patients (≥65 years). Mapping and clustering explored these multiple observational measures and summarised the main information into an intelligible reference framework. Resampling statistics were used to validate the model’s reliability. RESULTS: A three-dimensional map and two clusters defining acceptability profiles, as positive or negative, emerged from the 1079 evaluations. Factors of interest (medicines, user features…) were positioned on the map at the barycentre of their evaluations and assigned to an acceptability profile. Focusing on patients’ ability to swallow, we have highlighted the tool’s efficacy in demonstrating the impact of user features on medicine acceptability. CONCLUSIONS: This multivariate approach provides a relevant judgement criterion for this multi-dimensional concept. Facilitating the choice of the most appropriate dosage form to achieve optimal acceptability in a targeted population, this tool is of real potential to improve clinical decisions.
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spelling pubmed-59383072018-05-11 A Decision Support Tool Facilitating Medicine Design for Optimal Acceptability in The Older Population Vallet, Thibault Belissa, Emilie Laribe-Caget, Sandra Chevallier, Alain Chedhomme, François-Xavier Leglise, Patrick Piccoli, Matthieu Michelon, Hugues Bloch, Vanessa Meaume, Sylvie Grancher, Anne-Sophie Bachalat, Nathalie Boulaich, Imad Abdallah, Fattima Rabus, Maite Rwabihama, Jean-Paul Ribemont, Annie-Claude Lachuer, Celia Perquy, Ines Lechowski, Laurent Delahaye, Anne Depoisson, Mathieu Orven, Yann Guinot, Caroline Gibaud, Stephane Michel, Corinne Mahiou, Abdel Belbachir, Sid-Ahmed Trouvin, Jean-Hugues Dufaÿ-Wojcicki, Amelie Boudy, Vincent Ruiz, Fabrice Pharm Res Research Paper PURPOSE: Medicine acceptability, which is of the utmost importance for vulnerable patients’ adherence, is driven by both user and product characteristics. Herein, a novel multivariate approach integrating the many aspects of acceptability is used to discriminate positively and negatively accepted medicines in the older population. METHODS: An observational study was carried out in eight hospitals and eight nursing homes to collect a large set of real-life data on medicines uses in older patients (≥65 years). Mapping and clustering explored these multiple observational measures and summarised the main information into an intelligible reference framework. Resampling statistics were used to validate the model’s reliability. RESULTS: A three-dimensional map and two clusters defining acceptability profiles, as positive or negative, emerged from the 1079 evaluations. Factors of interest (medicines, user features…) were positioned on the map at the barycentre of their evaluations and assigned to an acceptability profile. Focusing on patients’ ability to swallow, we have highlighted the tool’s efficacy in demonstrating the impact of user features on medicine acceptability. CONCLUSIONS: This multivariate approach provides a relevant judgement criterion for this multi-dimensional concept. Facilitating the choice of the most appropriate dosage form to achieve optimal acceptability in a targeted population, this tool is of real potential to improve clinical decisions. Springer US 2018-05-07 2018 /pmc/articles/PMC5938307/ /pubmed/29736594 http://dx.doi.org/10.1007/s11095-018-2424-3 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), 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.
spellingShingle Research Paper
Vallet, Thibault
Belissa, Emilie
Laribe-Caget, Sandra
Chevallier, Alain
Chedhomme, François-Xavier
Leglise, Patrick
Piccoli, Matthieu
Michelon, Hugues
Bloch, Vanessa
Meaume, Sylvie
Grancher, Anne-Sophie
Bachalat, Nathalie
Boulaich, Imad
Abdallah, Fattima
Rabus, Maite
Rwabihama, Jean-Paul
Ribemont, Annie-Claude
Lachuer, Celia
Perquy, Ines
Lechowski, Laurent
Delahaye, Anne
Depoisson, Mathieu
Orven, Yann
Guinot, Caroline
Gibaud, Stephane
Michel, Corinne
Mahiou, Abdel
Belbachir, Sid-Ahmed
Trouvin, Jean-Hugues
Dufaÿ-Wojcicki, Amelie
Boudy, Vincent
Ruiz, Fabrice
A Decision Support Tool Facilitating Medicine Design for Optimal Acceptability in The Older Population
title A Decision Support Tool Facilitating Medicine Design for Optimal Acceptability in The Older Population
title_full A Decision Support Tool Facilitating Medicine Design for Optimal Acceptability in The Older Population
title_fullStr A Decision Support Tool Facilitating Medicine Design for Optimal Acceptability in The Older Population
title_full_unstemmed A Decision Support Tool Facilitating Medicine Design for Optimal Acceptability in The Older Population
title_short A Decision Support Tool Facilitating Medicine Design for Optimal Acceptability in The Older Population
title_sort decision support tool facilitating medicine design for optimal acceptability in the older population
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5938307/
https://www.ncbi.nlm.nih.gov/pubmed/29736594
http://dx.doi.org/10.1007/s11095-018-2424-3
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