Strengths and weaknesses of computerized clinical decision support systems: insights from a digital control center (C3 COVID-19) for early and personalized treatment for COVID-19.
Artificial Intelligence
COVID-19
Clinical Decision Support Systems
Journal
Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia
ISSN: 1988-9518
Titre abrégé: Rev Esp Quimioter
Pays: Spain
ID NLM: 9108821
Informations de publication
Date de publication:
29 Oct 2024
29 Oct 2024
Historique:
medline:
29
10
2024
pubmed:
29
10
2024
entrez:
29
10
2024
Statut:
aheadofprint
Résumé
Clinical Decision Support Systems (CDSS) are computer-based tools that leverage the analysis of large volumes of health data to assist healthcare professionals in making clinical decisions, whether preventive, diagnostic, or therapeutic. This review examines the impact of CDSS on clinical practice, highlighting both their potential benefits and their limitations and challenges. We detail the experience of clinical medical professionals in the development of a virtual control center for COVID-19 patients (C3 COVID-19) in Spain during the SARS-CoV-2 pandemic. This tool enabled real-time monitoring of clinical data for hospitalized COVID-19 patients, optimizing personalized and informed medical decision-making. CDSS can offer significant advantages, such as improving the quality of inpatient care, promoting evidence-based clinical and therapeutic decision-making, facilitating treatment personalization, and enhancing healthcare system efficiency and productivity. However, the implementation of CDSS presents challenges, including the need for physicians to become familiar with the systems and software, and the necessity for ongoing updates and technical support of the systems.
Identifiants
pubmed: 39469850
doi: 10.37201/req/088.2024
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
©The Author 2024. Published by Sociedad Española de Quimioterapia. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)(https://creativecommons.org/licenses/by-nc/4.0/).