Literature DB >> 29385655

Implementation of a Novel Algorithm to Decrease Unnecessary Hospitalizations in Patients Presenting to a Community Emergency Department With Atrial Fibrillation.

Susanne DeMeester1, Rebecca A Hess1, Bradley Hubbard2, Kara LeClerc1, Jane Ferraro1, Jeremy J Albright3.   

Abstract

OBJECTIVES: Atrial fibrillation (AFib) is the most common dysrhythmia in the United States. Patients seen in the emergency department (ED) in rapid AFib are often started on intravenous rate-controlling agents and admitted for several days. Although underlying and triggering illnesses must be addressed, AFib, intrinsically, is rarely life-threatening and can often be safely managed in an outpatient setting. At our academic community hospital, we implemented an algorithm to decrease hospital admissions for individuals presenting with a primary diagnosis of AFib. We focused on lenient oral rate control and discharge home. Our study evaluates outcomes after implementation of this algorithm.
METHODS: Study design is a retrospective cohort analysis pre- and postimplementation of the algorithm. The primary outcome was hospital admissions. Secondary outcomes were 3- and 30-day ED visits and any associated hospital admissions. These outcomes were compared before (March 2013-February 2014) and after (March 2015-February 2016) implementation. Chi-square tests and logistic regressions were run to test for significant changes in the three outcome variables.
RESULTS: A total of 1,108 individuals met inclusion criteria with 586 patients in the preimplementation group and 522 in the postimplementation group. Cohorts were broadly comparable in terms of demographics and health histories. Admissions for persons presenting with AFib after implementation decreased significantly (80.4% pre vs. 67.4% post, adjusted odds ratio [OR] = 3.4, p < 0.001). Despite this difference there was no change in ED return rates within 3 or 30 days (adjusted ORs = 0.93 and 0.89, p = 0.91 and 0.73, respectively).
CONCLUSIONS: Implementation of a novel algorithm to identify and treat low-risk patients with AFib can significantly decrease the rate of hospital admissions without increased ED returns. This simple algorithm could be adopted by other community hospitals and help lower costs.
© 2018 by the Society for Academic Emergency Medicine.

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Year:  2018        PMID: 29385655     DOI: 10.1111/acem.13383

Source DB:  PubMed          Journal:  Acad Emerg Med        ISSN: 1069-6563            Impact factor:   3.451


  3 in total

1.  Predictors of Acute Atrial Fibrillation and Flutter Hospitalization across 7 U.S. Emergency Departments: A Prospective Study.

Authors:  Bory Kea; E Margaret Warton; Dustin W Ballard; Dustin G Mark; Mary E Reed; Adina S Rauchwerger; Steven R Offerman; Uli K Chettipally; Patricia C Ramos; Daphne D Le; David S Glaser; David R Vinson
Journal:  J Atr Fibrillation       Date:  2021-02-28

2.  Impact of a Multidisciplinary Treatment Pathway for Atrial Fibrillation in the Emergency Department on Hospital Admissions and Length of Stay: Results of a Multi-Center Study.

Authors:  Leon M Ptaszek; Christopher W Baugh; Steven A Lubitz; Jeremy N Ruskin; Grace Ha; Margaux Forsch; Samer A DeOliveira; Samia Baig; E Kevin Heist; Jason H Wasfy; David F Brown; Paul D Biddinger; Ali S Raja; Benjamin Scirica; Benjamin A White; Moussa Mansour
Journal:  J Am Heart Assoc       Date:  2019-09-12       Impact factor: 5.501

3.  Improving care for patients with atrial fibrillation through the use of a personal electrocardiogram.

Authors:  Teresa Praus; Jonathan Li; Svetlana Barbarash; Manuel Proenza; Mary D Bondmass
Journal:  J Am Assoc Nurse Pract       Date:  2021-01-12       Impact factor: 1.165

  3 in total

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