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Clinical application of clinical decision support systems in the management of patients with atrial fibrillation

2Citations signalées — pas une note de qualité
5Institutions déclarées
2Pays d’affiliation déclarés

Résumé fourni par la source

Cardiology, like other branches of medicine, is increasingly faced with the need not only to optimize patient treatment, reduce financial costs, but also to improve long-term outcomes. The volume of information required for such tasks is significant, and a doctor’s time is severely limited. Additional software capable of processing large amounts of data in a short period can assist doctors. Clinical decision support system (CDSS) is a type of software that, based on numerous clinical characteristics, provides doctors with information on the most likely diagnosis, patient risk profile, most suitable therapy, and more. Nowadays, CDSS finding more and more applications in cardiology and cardiovascular medicine. The experience of its clinical use has also been accumulated in the Russian Federation. The problem of the correct choice of anticoagulant therapy remains relevant in clinical practice. In addition, despite the proven benefit of prescribing anticoagulants in patients with atrial fibrillation (AF) at a high risk, the frequency of "underprescription" of oral anticoagulants (OACs) remains relatively high. The introduction of a strategy for a personalized approach to the selection of anticoagulants, based on individual patient characteristics, can significantly improve adherence to clinical guidelines and, as a result, reduce the risk of thromboembolic complications. This article discusses the positive and negative aspects of using CDSS in the management of patients with AF, highlighting the main limitations when using them in conditions close to real clinical practice.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Clinical application of clinical decision support systems in the management of patients with atrial fibrillation
Date Crossref
02/09/2024
Éditeur
Silicea - Poligraf
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Sujets associés

Electronic Health Records SystemsBiomedical Text Mining and OntologiesArtificial Intelligence in Healthcare

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