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Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications

PURPOSE: The emergence of electronic prescribing devices with clinical decision support systems (CDSS) is able to significantly improve management pharmacological treatments. We developed a web application available on smartphones in order to help clinicians monitor prescription and further propose...

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Autores principales: Berrouiguet, Sofian, Barrigón, Maria Luisa, Brandt, Sara A., Ovejero-García, Santiago, Álvarez-García, Raquel, Carballo, Juan Jose, Lenca, Philippe, Courtet, Philippe, Baca-García, Enrique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5072715/
https://www.ncbi.nlm.nih.gov/pubmed/27764107
http://dx.doi.org/10.1371/journal.pone.0163796
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author Berrouiguet, Sofian
Barrigón, Maria Luisa
Brandt, Sara A.
Ovejero-García, Santiago
Álvarez-García, Raquel
Carballo, Juan Jose
Lenca, Philippe
Courtet, Philippe
Baca-García, Enrique
author_facet Berrouiguet, Sofian
Barrigón, Maria Luisa
Brandt, Sara A.
Ovejero-García, Santiago
Álvarez-García, Raquel
Carballo, Juan Jose
Lenca, Philippe
Courtet, Philippe
Baca-García, Enrique
author_sort Berrouiguet, Sofian
collection PubMed
description PURPOSE: The emergence of electronic prescribing devices with clinical decision support systems (CDSS) is able to significantly improve management pharmacological treatments. We developed a web application available on smartphones in order to help clinicians monitor prescription and further propose CDSS. METHOD: A web application (www.MEmind.net) was developed to assess patients and collect data regarding gender, age, diagnosis and treatment. We analyzed antipsychotic prescriptions in 4345 patients attended in five Psychiatric Community Mental Health Centers from June 2014 to October 2014. The web-application reported average daily dose prescribed for antipsychotics, prescribed daily dose (PDD), and the PDD to defined daily dose (DDD) ratio. RESULTS: The MEmind web-application reported that antipsychotics were used in 1116 patients out of the total sample, mostly in 486 (44%) patients with schizophrenia related disorders but also in other diagnoses. Second generation antipsychotics (quetiapine, aripiprazole and long-acting paliperidone) were preferably employed. Low doses were more frequently used than high doses. Long acting paliperidone and ziprasidone however, were the only two antipsychotics used at excessive dosing. Antipsychotic polypharmacy was used in 287 (26%) patients with classic depot drugs, clotiapine, amisulpride and clozapine. CONCLUSIONS: In this study we describe the first step of the development of a web application that is able to make polypharmacy, high dose usage and off label usage of antipsychotics visible to clinicians. Current development of the MEmind web application may help to improve prescription security via momentary feedback of prescription and clinical decision support system.
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spelling pubmed-50727152016-10-27 Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications Berrouiguet, Sofian Barrigón, Maria Luisa Brandt, Sara A. Ovejero-García, Santiago Álvarez-García, Raquel Carballo, Juan Jose Lenca, Philippe Courtet, Philippe Baca-García, Enrique PLoS One Research Article PURPOSE: The emergence of electronic prescribing devices with clinical decision support systems (CDSS) is able to significantly improve management pharmacological treatments. We developed a web application available on smartphones in order to help clinicians monitor prescription and further propose CDSS. METHOD: A web application (www.MEmind.net) was developed to assess patients and collect data regarding gender, age, diagnosis and treatment. We analyzed antipsychotic prescriptions in 4345 patients attended in five Psychiatric Community Mental Health Centers from June 2014 to October 2014. The web-application reported average daily dose prescribed for antipsychotics, prescribed daily dose (PDD), and the PDD to defined daily dose (DDD) ratio. RESULTS: The MEmind web-application reported that antipsychotics were used in 1116 patients out of the total sample, mostly in 486 (44%) patients with schizophrenia related disorders but also in other diagnoses. Second generation antipsychotics (quetiapine, aripiprazole and long-acting paliperidone) were preferably employed. Low doses were more frequently used than high doses. Long acting paliperidone and ziprasidone however, were the only two antipsychotics used at excessive dosing. Antipsychotic polypharmacy was used in 287 (26%) patients with classic depot drugs, clotiapine, amisulpride and clozapine. CONCLUSIONS: In this study we describe the first step of the development of a web application that is able to make polypharmacy, high dose usage and off label usage of antipsychotics visible to clinicians. Current development of the MEmind web application may help to improve prescription security via momentary feedback of prescription and clinical decision support system. Public Library of Science 2016-10-20 /pmc/articles/PMC5072715/ /pubmed/27764107 http://dx.doi.org/10.1371/journal.pone.0163796 Text en © 2016 Berrouiguet et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Berrouiguet, Sofian
Barrigón, Maria Luisa
Brandt, Sara A.
Ovejero-García, Santiago
Álvarez-García, Raquel
Carballo, Juan Jose
Lenca, Philippe
Courtet, Philippe
Baca-García, Enrique
Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications
title Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications
title_full Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications
title_fullStr Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications
title_full_unstemmed Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications
title_short Development of a Web-Based Clinical Decision Support System for Drug Prescription: Non-Interventional Naturalistic Description of the Antipsychotic Prescription Patterns in 4345 Outpatients and Future Applications
title_sort development of a web-based clinical decision support system for drug prescription: non-interventional naturalistic description of the antipsychotic prescription patterns in 4345 outpatients and future applications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5072715/
https://www.ncbi.nlm.nih.gov/pubmed/27764107
http://dx.doi.org/10.1371/journal.pone.0163796
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