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An Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation

OBJECTIVE: Clinical decision support systems that notify providers of abnormal test results have produced mixed results. We sought to develop, implement, and evaluate the impact of a computer-based clinical alert system intended to improve atrial fibrillation stroke prophylaxis, and identify reasons...

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Autores principales: Cook, David A., Enders, Felicity, Caraballo, Pedro J., Nishimura, Rick A., Lloyd, Farrell J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388495/
https://www.ncbi.nlm.nih.gov/pubmed/25849969
http://dx.doi.org/10.1371/journal.pone.0122153
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author Cook, David A.
Enders, Felicity
Caraballo, Pedro J.
Nishimura, Rick A.
Lloyd, Farrell J.
author_facet Cook, David A.
Enders, Felicity
Caraballo, Pedro J.
Nishimura, Rick A.
Lloyd, Farrell J.
author_sort Cook, David A.
collection PubMed
description OBJECTIVE: Clinical decision support systems that notify providers of abnormal test results have produced mixed results. We sought to develop, implement, and evaluate the impact of a computer-based clinical alert system intended to improve atrial fibrillation stroke prophylaxis, and identify reasons providers do not implement a guideline-concordant response. MATERIALS AND METHODS: We conducted a cohort study with historical controls among patients at a tertiary care hospital. We developed a decision rule to identify newly-diagnosed atrial fibrillation, automatically notify providers, and direct them to online evidence-based management guidelines. We tracked all notifications from December 2009 to February 2010 (notification period) and applied the same decision rule to all patients from December 2008 to February 2009 (control period). Primary outcomes were accuracy of notification (confirmed through chart review) and prescription of warfarin within 30 days. RESULTS: During the notification period 604 notifications were triggered, of which 268 (44%) were confirmed as newly-diagnosed atrial fibrillation. The notifications not confirmed as newly-diagnosed involved patients with no recent electrocardiogram at our institution. Thirty-four of 125 high-risk patients (27%) received warfarin in the notification period, compared with 34 of 94 (36%) in the control period (odds ratio, 0.66 [95% CI, 0.37–1.17]; p = 0.16). Common reasons to not prescribe warfarin (identified from chart review of 151 patients) included upcoming surgical procedure, choice to use aspirin, and discrepancy between clinical notes and the medication record. CONCLUSIONS: An automated system to identify newly-diagnosed atrial fibrillation, notify providers, and encourage access to management guidelines did not change provider behaviors.
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spelling pubmed-43884952015-04-21 An Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation Cook, David A. Enders, Felicity Caraballo, Pedro J. Nishimura, Rick A. Lloyd, Farrell J. PLoS One Research Article OBJECTIVE: Clinical decision support systems that notify providers of abnormal test results have produced mixed results. We sought to develop, implement, and evaluate the impact of a computer-based clinical alert system intended to improve atrial fibrillation stroke prophylaxis, and identify reasons providers do not implement a guideline-concordant response. MATERIALS AND METHODS: We conducted a cohort study with historical controls among patients at a tertiary care hospital. We developed a decision rule to identify newly-diagnosed atrial fibrillation, automatically notify providers, and direct them to online evidence-based management guidelines. We tracked all notifications from December 2009 to February 2010 (notification period) and applied the same decision rule to all patients from December 2008 to February 2009 (control period). Primary outcomes were accuracy of notification (confirmed through chart review) and prescription of warfarin within 30 days. RESULTS: During the notification period 604 notifications were triggered, of which 268 (44%) were confirmed as newly-diagnosed atrial fibrillation. The notifications not confirmed as newly-diagnosed involved patients with no recent electrocardiogram at our institution. Thirty-four of 125 high-risk patients (27%) received warfarin in the notification period, compared with 34 of 94 (36%) in the control period (odds ratio, 0.66 [95% CI, 0.37–1.17]; p = 0.16). Common reasons to not prescribe warfarin (identified from chart review of 151 patients) included upcoming surgical procedure, choice to use aspirin, and discrepancy between clinical notes and the medication record. CONCLUSIONS: An automated system to identify newly-diagnosed atrial fibrillation, notify providers, and encourage access to management guidelines did not change provider behaviors. Public Library of Science 2015-04-07 /pmc/articles/PMC4388495/ /pubmed/25849969 http://dx.doi.org/10.1371/journal.pone.0122153 Text en © 2015 Cook 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Cook, David A.
Enders, Felicity
Caraballo, Pedro J.
Nishimura, Rick A.
Lloyd, Farrell J.
An Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation
title An Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation
title_full An Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation
title_fullStr An Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation
title_full_unstemmed An Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation
title_short An Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation
title_sort automated clinical alert system for newly-diagnosed atrial fibrillation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388495/
https://www.ncbi.nlm.nih.gov/pubmed/25849969
http://dx.doi.org/10.1371/journal.pone.0122153
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