Cargando…

Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review

OBJECTIVE: Clinical decision support systems (CDSSs) can reduce medical errors increasing drug prescription appropriateness. Deepening knowledge of existing CDSSs could increase their use by healthcare professionals in different settings (ie, hospitals, pharmacies, health research centres) of clinic...

Descripción completa

Detalles Bibliográficos
Autores principales: Armando, Lucrezia Greta, Miglio, Gianluca, de Cosmo, Pierluigi, Cena, Clara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163516/
https://www.ncbi.nlm.nih.gov/pubmed/37130626
http://dx.doi.org/10.1136/bmjhci-2022-100683
_version_ 1785037898659135488
author Armando, Lucrezia Greta
Miglio, Gianluca
de Cosmo, Pierluigi
Cena, Clara
author_facet Armando, Lucrezia Greta
Miglio, Gianluca
de Cosmo, Pierluigi
Cena, Clara
author_sort Armando, Lucrezia Greta
collection PubMed
description OBJECTIVE: Clinical decision support systems (CDSSs) can reduce medical errors increasing drug prescription appropriateness. Deepening knowledge of existing CDSSs could increase their use by healthcare professionals in different settings (ie, hospitals, pharmacies, health research centres) of clinical practice. This review aims to identify the characteristics common to effective studies conducted with CDSSs. MATERIALS AND METHODS: The article sources were Scopus, PubMed, Ovid MEDLINE and Web of Science, queried between January 2017 and January 2022. Inclusion criteria were prospective and retrospective studies that reported original research on CDSSs for clinical practice support; studies should describe a measurable comparison of the intervention or observation conducted with and without the CDSS; article language Italian or English. Reviews and studies with CDSSs used exclusively by patients were excluded. A Microsoft Excel spreadsheet was prepared to extract and summarise data from the included articles. RESULTS: The search resulted in the identification of 2424 articles. After title and abstract screening, 136 studies remained, 42 of which were included for final evaluation. Most of the studies included rule-based CDSSs that are integrated into existing databases with the main purpose of managing disease-related problems. The majority of the selected studies (25 studies; 59.5%) were successful in supporting clinical practice, with most being pre–post intervention studies and involving the presence of a pharmacist. DISCUSSION AND CONCLUSION: A number of characteristics have been identified that may help the design of studies feasible to demonstrate the effectiveness of CDSSs. Further studies are needed to encourage CDSS use.
format Online
Article
Text
id pubmed-10163516
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BMJ Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-101635162023-05-07 Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review Armando, Lucrezia Greta Miglio, Gianluca de Cosmo, Pierluigi Cena, Clara BMJ Health Care Inform Review OBJECTIVE: Clinical decision support systems (CDSSs) can reduce medical errors increasing drug prescription appropriateness. Deepening knowledge of existing CDSSs could increase their use by healthcare professionals in different settings (ie, hospitals, pharmacies, health research centres) of clinical practice. This review aims to identify the characteristics common to effective studies conducted with CDSSs. MATERIALS AND METHODS: The article sources were Scopus, PubMed, Ovid MEDLINE and Web of Science, queried between January 2017 and January 2022. Inclusion criteria were prospective and retrospective studies that reported original research on CDSSs for clinical practice support; studies should describe a measurable comparison of the intervention or observation conducted with and without the CDSS; article language Italian or English. Reviews and studies with CDSSs used exclusively by patients were excluded. A Microsoft Excel spreadsheet was prepared to extract and summarise data from the included articles. RESULTS: The search resulted in the identification of 2424 articles. After title and abstract screening, 136 studies remained, 42 of which were included for final evaluation. Most of the studies included rule-based CDSSs that are integrated into existing databases with the main purpose of managing disease-related problems. The majority of the selected studies (25 studies; 59.5%) were successful in supporting clinical practice, with most being pre–post intervention studies and involving the presence of a pharmacist. DISCUSSION AND CONCLUSION: A number of characteristics have been identified that may help the design of studies feasible to demonstrate the effectiveness of CDSSs. Further studies are needed to encourage CDSS use. BMJ Publishing Group 2023-05-02 /pmc/articles/PMC10163516/ /pubmed/37130626 http://dx.doi.org/10.1136/bmjhci-2022-100683 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Review
Armando, Lucrezia Greta
Miglio, Gianluca
de Cosmo, Pierluigi
Cena, Clara
Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review
title Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review
title_full Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review
title_fullStr Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review
title_full_unstemmed Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review
title_short Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review
title_sort clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163516/
https://www.ncbi.nlm.nih.gov/pubmed/37130626
http://dx.doi.org/10.1136/bmjhci-2022-100683
work_keys_str_mv AT armandolucreziagreta clinicaldecisionsupportsystemstoimprovedrugprescriptionandtherapyoptimisationinclinicalpracticeascopingreview
AT migliogianluca clinicaldecisionsupportsystemstoimprovedrugprescriptionandtherapyoptimisationinclinicalpracticeascopingreview
AT decosmopierluigi clinicaldecisionsupportsystemstoimprovedrugprescriptionandtherapyoptimisationinclinicalpracticeascopingreview
AT cenaclara clinicaldecisionsupportsystemstoimprovedrugprescriptionandtherapyoptimisationinclinicalpracticeascopingreview