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Defining Potentially Inappropriate Prescriptions for Hypoglycaemic Agents to Improve Computerised Decision Support: A Study Protocol
In France, around 5% of the general population are taking drug treatments for diabetes mellitus (mainly type 2 diabetes mellitus, T2DM). Although the management of T2DM has become more complex, most of these patients are managed by their general practitioner and not a diabetologist for their antidia...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8622925/ https://www.ncbi.nlm.nih.gov/pubmed/34828585 http://dx.doi.org/10.3390/healthcare9111539 |
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author | Quindroit, Paul Baclet, Nicolas Gerard, Erwin Robert, Laurine Lemaitre, Madleen Gautier, Sophie Delannoy-Rousselière, Chloé Décaudin, Bertrand Vambergue, Anne Beuscart, Jean-Baptiste |
author_facet | Quindroit, Paul Baclet, Nicolas Gerard, Erwin Robert, Laurine Lemaitre, Madleen Gautier, Sophie Delannoy-Rousselière, Chloé Décaudin, Bertrand Vambergue, Anne Beuscart, Jean-Baptiste |
author_sort | Quindroit, Paul |
collection | PubMed |
description | In France, around 5% of the general population are taking drug treatments for diabetes mellitus (mainly type 2 diabetes mellitus, T2DM). Although the management of T2DM has become more complex, most of these patients are managed by their general practitioner and not a diabetologist for their antidiabetics treatments; this increases the risk of potentially inappropriate prescriptions (PIPs) of hypoglycaemic agents (HAs). Inappropriate prescribing can be assessed by approaches that are implicit (expert judgement based) or explicit (criterion based). In a mixed, multistep process, we first systematically reviewed the published definitions of PIPs for HAs in patients with T2DM. The results will be used to create the first list of explicit definitions. Next, we will complete the definitions identified in the systematic review by conducting a qualitative study with two focus groups of experts in the prescription of HAs. Lastly, a Delphi survey will then be used to build consensus among participants; the results will be validated in consensus meetings. We developed a method for determining explicit definitions of PIPs for HAs in patients with T2DM. The resulting explicit definitions could be easily integrated into computerised decision support tools for the automated detection of PIPs. |
format | Online Article Text |
id | pubmed-8622925 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86229252021-11-27 Defining Potentially Inappropriate Prescriptions for Hypoglycaemic Agents to Improve Computerised Decision Support: A Study Protocol Quindroit, Paul Baclet, Nicolas Gerard, Erwin Robert, Laurine Lemaitre, Madleen Gautier, Sophie Delannoy-Rousselière, Chloé Décaudin, Bertrand Vambergue, Anne Beuscart, Jean-Baptiste Healthcare (Basel) Protocol In France, around 5% of the general population are taking drug treatments for diabetes mellitus (mainly type 2 diabetes mellitus, T2DM). Although the management of T2DM has become more complex, most of these patients are managed by their general practitioner and not a diabetologist for their antidiabetics treatments; this increases the risk of potentially inappropriate prescriptions (PIPs) of hypoglycaemic agents (HAs). Inappropriate prescribing can be assessed by approaches that are implicit (expert judgement based) or explicit (criterion based). In a mixed, multistep process, we first systematically reviewed the published definitions of PIPs for HAs in patients with T2DM. The results will be used to create the first list of explicit definitions. Next, we will complete the definitions identified in the systematic review by conducting a qualitative study with two focus groups of experts in the prescription of HAs. Lastly, a Delphi survey will then be used to build consensus among participants; the results will be validated in consensus meetings. We developed a method for determining explicit definitions of PIPs for HAs in patients with T2DM. The resulting explicit definitions could be easily integrated into computerised decision support tools for the automated detection of PIPs. MDPI 2021-11-11 /pmc/articles/PMC8622925/ /pubmed/34828585 http://dx.doi.org/10.3390/healthcare9111539 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 | Protocol Quindroit, Paul Baclet, Nicolas Gerard, Erwin Robert, Laurine Lemaitre, Madleen Gautier, Sophie Delannoy-Rousselière, Chloé Décaudin, Bertrand Vambergue, Anne Beuscart, Jean-Baptiste Defining Potentially Inappropriate Prescriptions for Hypoglycaemic Agents to Improve Computerised Decision Support: A Study Protocol |
title | Defining Potentially Inappropriate Prescriptions for Hypoglycaemic Agents to Improve Computerised Decision Support: A Study Protocol |
title_full | Defining Potentially Inappropriate Prescriptions for Hypoglycaemic Agents to Improve Computerised Decision Support: A Study Protocol |
title_fullStr | Defining Potentially Inappropriate Prescriptions for Hypoglycaemic Agents to Improve Computerised Decision Support: A Study Protocol |
title_full_unstemmed | Defining Potentially Inappropriate Prescriptions for Hypoglycaemic Agents to Improve Computerised Decision Support: A Study Protocol |
title_short | Defining Potentially Inappropriate Prescriptions for Hypoglycaemic Agents to Improve Computerised Decision Support: A Study Protocol |
title_sort | defining potentially inappropriate prescriptions for hypoglycaemic agents to improve computerised decision support: a study protocol |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8622925/ https://www.ncbi.nlm.nih.gov/pubmed/34828585 http://dx.doi.org/10.3390/healthcare9111539 |
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