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Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study

(1) Background: Some medications may be dangerous for older patients. Potentially inappropriate medication prescribing (PIP) among older patients represents a significant cause of morbidity. The aim of this study was to create an algorithm to detect PIP in a geriatric database (Multidomain Alzheimer...

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Autores principales: Pagès, Arnaud, Rouch, Laure, Costa, Nadège, Cestac, Philippe, De Souto Barreto, Philipe, Rolland, Yves, Vellas, Bruno, Molinier, Laurent, Juillard-Condat, Blandine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628967/
https://www.ncbi.nlm.nih.gov/pubmed/34842835
http://dx.doi.org/10.3390/pharmacy9040189
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author Pagès, Arnaud
Rouch, Laure
Costa, Nadège
Cestac, Philippe
De Souto Barreto, Philipe
Rolland, Yves
Vellas, Bruno
Molinier, Laurent
Juillard-Condat, Blandine
author_facet Pagès, Arnaud
Rouch, Laure
Costa, Nadège
Cestac, Philippe
De Souto Barreto, Philipe
Rolland, Yves
Vellas, Bruno
Molinier, Laurent
Juillard-Condat, Blandine
author_sort Pagès, Arnaud
collection PubMed
description (1) Background: Some medications may be dangerous for older patients. Potentially inappropriate medication prescribing (PIP) among older patients represents a significant cause of morbidity. The aim of this study was to create an algorithm to detect PIP in a geriatric database (Multidomain Alzheimer Preventive Trial (MAPT) study), and then to assess the algorithm construct validity by comparing the prevalence of PIP and associated factors with literature data. (2) Methods: An algorithm was constructed to detect PIP and was based on different explicit criteria among which the European list of potentially inappropriate medications (EU(7)-PIM), the STOPP and START version 2 tools. For construct validity assessment, logistic mixed-effects model repeated measures analyses were used to identify factors associated with PIP. (3) Results: Prevalence of PIP was 59.0% with the EU(7)-PIM list criteria, 43.2% with the STOPP criteria and 51.3% with the START criteria. Age, polypharmacy, and higher Charlson comorbidity index were associated with PIP. (4) Conclusions: Prevalence of PIP and associated factors are consistent with literature data, supporting the construct validity of our algorithm. This algorithm opens up interesting perspectives both in terms of analysis of very large databases and integration into e-prescribing or pharmaceutical validation software.
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spelling pubmed-86289672021-11-30 Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study Pagès, Arnaud Rouch, Laure Costa, Nadège Cestac, Philippe De Souto Barreto, Philipe Rolland, Yves Vellas, Bruno Molinier, Laurent Juillard-Condat, Blandine Pharmacy (Basel) Article (1) Background: Some medications may be dangerous for older patients. Potentially inappropriate medication prescribing (PIP) among older patients represents a significant cause of morbidity. The aim of this study was to create an algorithm to detect PIP in a geriatric database (Multidomain Alzheimer Preventive Trial (MAPT) study), and then to assess the algorithm construct validity by comparing the prevalence of PIP and associated factors with literature data. (2) Methods: An algorithm was constructed to detect PIP and was based on different explicit criteria among which the European list of potentially inappropriate medications (EU(7)-PIM), the STOPP and START version 2 tools. For construct validity assessment, logistic mixed-effects model repeated measures analyses were used to identify factors associated with PIP. (3) Results: Prevalence of PIP was 59.0% with the EU(7)-PIM list criteria, 43.2% with the STOPP criteria and 51.3% with the START criteria. Age, polypharmacy, and higher Charlson comorbidity index were associated with PIP. (4) Conclusions: Prevalence of PIP and associated factors are consistent with literature data, supporting the construct validity of our algorithm. This algorithm opens up interesting perspectives both in terms of analysis of very large databases and integration into e-prescribing or pharmaceutical validation software. MDPI 2021-11-24 /pmc/articles/PMC8628967/ /pubmed/34842835 http://dx.doi.org/10.3390/pharmacy9040189 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pagès, Arnaud
Rouch, Laure
Costa, Nadège
Cestac, Philippe
De Souto Barreto, Philipe
Rolland, Yves
Vellas, Bruno
Molinier, Laurent
Juillard-Condat, Blandine
Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study
title Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study
title_full Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study
title_fullStr Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study
title_full_unstemmed Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study
title_short Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm among Older Patients: Results from the MAPT Study
title_sort potentially inappropriate medication prescribing detected by computer algorithm among older patients: results from the mapt study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628967/
https://www.ncbi.nlm.nih.gov/pubmed/34842835
http://dx.doi.org/10.3390/pharmacy9040189
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