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Validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines
BACKGROUND: The review of pharmacotherapy can be conceptualized as a service in which the drugs used by the patient are reviewed to control the risks as well as to improve the results of the drug therapy, detecting, solving, and preventing issues associated with the drug, readjusting the doses and t...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245235/ https://www.ncbi.nlm.nih.gov/pubmed/35773651 http://dx.doi.org/10.1186/s12911-022-01914-6 |
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author | Zapelini, Clávison Martinelli Galato, Dayani Alano, Graziela Modolon de Carvalho Martins, Karina Saviatto Trauthman, Silvana Cristina Soares, Alessandra Schuelter-Trevisol, Fabiana Trevisol, Daisson José |
author_facet | Zapelini, Clávison Martinelli Galato, Dayani Alano, Graziela Modolon de Carvalho Martins, Karina Saviatto Trauthman, Silvana Cristina Soares, Alessandra Schuelter-Trevisol, Fabiana Trevisol, Daisson José |
author_sort | Zapelini, Clávison Martinelli |
collection | PubMed |
description | BACKGROUND: The review of pharmacotherapy can be conceptualized as a service in which the drugs used by the patient are reviewed to control the risks as well as to improve the results of the drug therapy, detecting, solving, and preventing issues associated with the drug, readjusting the doses and times (schedule) so that the treatment is not incompatible or in duplicity. METHODS: The aim of the study was to validate an intelligent information system, which was developed to assist the scheduling activity in the pharmacotherapy review. The system used the concept of Genetic Algorithms. To validate the system, hypothetical cases were elaborated considering various aspects of pharmacotherapy such as underdose, overdose, drug interactions and contraindications. These cases were tested in the system and were also analyzed by pharmaceutical experts with clinical and research experience in the pharmacotherapy review process. The degree of agreement between the assessments of the appointments carried out by the pharmaceutical specialists and by the system were measured using the Kappa index with a 95% confidence interval. RESULTS: In detecting errors and make propositions, the system was able to identify 80% of errors, with pharmaceutical experts identifying between 20 and 70% of errors. In relation the results of kappa between the cases, the system had 87,3% of concordance, whereas the best pharmaceutical expert had 75,5% of concordance, considering the correct answer. CONCLUSION: It can be concluded that with the methodology used, the investigation met the objectives and confirmed the system is effective for pharmaceutical review process. There are indications that the system can help in the Pharmacotherapy review process, being able to find prescription errors as well as to establish times for the use of medications according to the patient’s routine. |
format | Online Article Text |
id | pubmed-9245235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92452352022-07-01 Validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines Zapelini, Clávison Martinelli Galato, Dayani Alano, Graziela Modolon de Carvalho Martins, Karina Saviatto Trauthman, Silvana Cristina Soares, Alessandra Schuelter-Trevisol, Fabiana Trevisol, Daisson José BMC Med Inform Decis Mak Research BACKGROUND: The review of pharmacotherapy can be conceptualized as a service in which the drugs used by the patient are reviewed to control the risks as well as to improve the results of the drug therapy, detecting, solving, and preventing issues associated with the drug, readjusting the doses and times (schedule) so that the treatment is not incompatible or in duplicity. METHODS: The aim of the study was to validate an intelligent information system, which was developed to assist the scheduling activity in the pharmacotherapy review. The system used the concept of Genetic Algorithms. To validate the system, hypothetical cases were elaborated considering various aspects of pharmacotherapy such as underdose, overdose, drug interactions and contraindications. These cases were tested in the system and were also analyzed by pharmaceutical experts with clinical and research experience in the pharmacotherapy review process. The degree of agreement between the assessments of the appointments carried out by the pharmaceutical specialists and by the system were measured using the Kappa index with a 95% confidence interval. RESULTS: In detecting errors and make propositions, the system was able to identify 80% of errors, with pharmaceutical experts identifying between 20 and 70% of errors. In relation the results of kappa between the cases, the system had 87,3% of concordance, whereas the best pharmaceutical expert had 75,5% of concordance, considering the correct answer. CONCLUSION: It can be concluded that with the methodology used, the investigation met the objectives and confirmed the system is effective for pharmaceutical review process. There are indications that the system can help in the Pharmacotherapy review process, being able to find prescription errors as well as to establish times for the use of medications according to the patient’s routine. BioMed Central 2022-06-30 /pmc/articles/PMC9245235/ /pubmed/35773651 http://dx.doi.org/10.1186/s12911-022-01914-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zapelini, Clávison Martinelli Galato, Dayani Alano, Graziela Modolon de Carvalho Martins, Karina Saviatto Trauthman, Silvana Cristina Soares, Alessandra Schuelter-Trevisol, Fabiana Trevisol, Daisson José Validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines |
title | Validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines |
title_full | Validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines |
title_fullStr | Validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines |
title_full_unstemmed | Validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines |
title_short | Validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines |
title_sort | validation of a computerized decision support system to review pharmacotherapy treatment: scheduling guidelines |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245235/ https://www.ncbi.nlm.nih.gov/pubmed/35773651 http://dx.doi.org/10.1186/s12911-022-01914-6 |
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