Literature DB >> 27264216

Impact of an Atrial Fibrillation Decision Support Tool on thromboprophylaxis for atrial fibrillation.

Mark H Eckman1, Gregory Y H Lip2, Ruth E Wise3, Barbara Speer4, Megan Sullivan5, Nita Walker3, Brett Kissela6, Matthew L Flaherty6, Dawn Kleindorfer6, Peter Baker7, Robert Ireton7, Dave Hoskins7, Brett M Harnett7, Carlos Aguilar8, Anthony C Leonard4, Lora Arduser9, Dylan Steen10, Alexandru Costea10, John Kues4.   

Abstract

BACKGROUND: Appropriate thromboprophylaxis for patients with atrial fibrillation (AF) remains a national challenge.
METHODS: We hypothesized that provision of decision support in the form of an Atrial Fibrillation Decision Support Tool (AFDST) would improve thromboprophylaxis for AF patients. We conducted a cluster randomized trial involving 15 primary care practices and 1,493 adults with nonvalvular AF in an integrated health care system between April 2014 and February 2015. Physicians in the intervention group received patient-level treatment recommendations made by the AFDST. Our primary outcome was the proportion of patients with antithrombotic therapy that was discordant from AFDST recommendation.
RESULTS: Treatment was discordant in 42% of 801 patients in the intervention group. Physicians reviewed reports for 240 patients. Among these patients, thromboprophylaxis was discordant in 63%, decreasing to 59% 1 year later (P = .02). In nonstratified analyses, changes in discordant care were not significantly different between the intervention group and control groups. In multivariate regression models, assignment to the intervention group resulted in a nonsignificant trend toward decreased discordance (P = .29), and being a patient of a resident physician (P = .02) and a higher HAS-BLED score predicted decreased discordance (P = .03), whereas female gender (P = .01) and a higher CHADSVASc score (P = .10) predicted increased discordance.
CONCLUSIONS: Among patients whose physicians reviewed recommendations of the decision support tool discordant therapy decreased significantly over 1 year. However, in nonstratified analyses, the intervention did not result in significant improvements in discordant antithrombotic therapy.
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 27264216     DOI: 10.1016/j.ahj.2016.02.009

Source DB:  PubMed          Journal:  Am Heart J        ISSN: 0002-8703            Impact factor:   4.749


  13 in total

1.  Ischemic Stroke and Bleeding: Clinical Benefit of Anticoagulation in Atrial Fibrillation After Intracerebral Hemorrhage.

Authors:  Robert J Stanton; Mark H Eckman; Daniel Woo; Charles J Moomaw; Mary Haverbusch; Matthew L Flaherty; Dawn O Kleindorfer
Journal:  Stroke       Date:  2020-01-31       Impact factor: 7.914

2.  The Effect of a Clinical Decision Support System on Improving Adherence to Guideline in the Treatment of Atrial Fibrillation: An Interrupted Time Series Study.

Authors:  Reza Sheibani; Mehdi Sheibani; Alireza Heidari-Bakavoli; Ameen Abu-Hanna; Saeid Eslami
Journal:  J Med Syst       Date:  2017-12-23       Impact factor: 4.460

3.  Atrial fibrillation decision support tool: Population perspective.

Authors:  Mark H Eckman; Alexandru Costea; Mehran Attari; Jitender Munjal; Ruth E Wise; Carol Knochelmann; Matthew L Flaherty; Pete Baker; Robert Ireton; Brett M Harnett; Anthony C Leonard; Dylan Steen; Adam Rose; John Kues
Journal:  Am Heart J       Date:  2017-08-23       Impact factor: 4.749

4.  Effect of an artificial intelligence-assisted tool on non-valvular atrial fibrillation anticoagulation management in primary care: protocol for a cluster randomized controlled trial.

Authors:  Xueying Ru; Lan Zhu; Yunhui Ma; Tianhao Wang; Zhigang Pan
Journal:  Trials       Date:  2022-04-15       Impact factor: 2.728

5.  Thromboprophylaxis for Patients with High-risk Atrial Fibrillation and Flutter Discharged from the Emergency Department.

Authors:  David R Vinson; E Margaret Warton; Dustin G Mark; Dustin W Ballard; Mary E Reed; Uli K Chettipally; Nimmie Singh; Sean Z Bouvet; Bory Kea; Patricia C Ramos; David S Glaser; Alan S Go
Journal:  West J Emerg Med       Date:  2018-02-12

6.  Uptake of a primary care atrial fibrillation screening program (AF-SMART): a realist evaluation of implementation in metropolitan and rural general practice.

Authors:  Jessica Orchard; Jialin Li; Robyn Gallagher; Ben Freedman; Nicole Lowres; Lis Neubeck
Journal:  BMC Fam Pract       Date:  2019-12-06       Impact factor: 2.497

7.  Electronic physician notifications to improve guideline-based anticoagulation in atrial fibrillation: a randomized controlled trial.

Authors:  Jeffrey M Ashburner; Steven J Atlas; Shaan Khurshid; Lu-Chen Weng; Olivia L Hulme; Yuchiao Chang; Daniel E Singer; Patrick T Ellinor; Steven A Lubitz
Journal:  J Gen Intern Med       Date:  2018-08-03       Impact factor: 6.473

8.  Atrial Fibrillation Screen, Management And Guideline Recommended Therapy (AF SMART II) in the rural primary care setting: an implementation study protocol.

Authors:  Jessica J Orchard; Lis Neubeck; Ben Freedman; Ruth Webster; Anushka Patel; Robyn Gallagher; Jialin Li; Charlotte Mary Hespe; Caleb Ferguson; Nicholas Zwar; Nicole Lowres
Journal:  BMJ Open       Date:  2018-10-31       Impact factor: 2.692

9.  eHealth Tools to Provide Structured Assistance for Atrial Fibrillation Screening, Management, and Guideline-Recommended Therapy in Metropolitan General Practice: The AF - SMART Study.

Authors:  Jessica Orchard; Lis Neubeck; Ben Freedman; Jialin Li; Ruth Webster; Nicholas Zwar; Robyn Gallagher; Caleb Ferguson; Nicole Lowres
Journal:  J Am Heart Assoc       Date:  2019-01-08       Impact factor: 5.501

10.  Improving the quality of care for patients with or at risk of atrial fibrillation: an improvement initiative in UK general practices.

Authors:  Yewande Adeleke; Dionne Matthew; Bradley Porter; Thomas Woodcock; Jayne Yap; Sophia Hashmy; Ammu Mathew; Ron Grant; Agnes Kaba; Brigitte Unger-Graeber; Sadia Khan; Derek Bell; Martin R Cowie
Journal:  Open Heart       Date:  2019-10-15
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