Literature DB >> 29273997

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

Reza Sheibani1,2, Mehdi Sheibani3, Alireza Heidari-Bakavoli4, Ameen Abu-Hanna5, Saeid Eslami6,7,8.   

Abstract

To evaluate the effect of a computerized Decision Support System (CDSS) on improving adherence to an anticoagulation guideline for the treatment of atrial fibrillation (AF). This study had an interrupted time series design. The adherence to the guideline was assessed at fortnightly (two weeks) intervals from January 2016 to January 2017, 6 months before and 6 months after intervention. Newly diagnosed patients with AF were included in the offices of ten cardiologists. Stroke and major bleeding risks were calculated by the CDSS which was implemented via a mobile application. Treatment recommendations based on the guideline were shown to cardiologists. The segmented regression model was used to evaluate the effect of CDSS on level and trend of guideline adherence for the treatment of AF. In our analysis, 373 patients were included. The trend of adherence to the anticoagulation guideline for the treatment of AF was stable in the pre-intervention phase. After the CDSS intervention, mean of the adherence to the guideline significantly increased from 48% to 65.5% (P-value < 0.0001). The trend of adherence to the guideline was stable in the post-intervention phase. Our results showed that the CDSS can improve adherence to the anticoagulation guideline for the treatment of AF. Registration ID: IRCT2016052528070N1.

Entities:  

Keywords:  Atrial fibrillation; Cardiologist; Clinical decision support system; Guideline adherence; Interrupted time series

Mesh:

Substances:

Year:  2017        PMID: 29273997     DOI: 10.1007/s10916-017-0881-6

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  33 in total

1.  Segmented regression analysis of interrupted time series studies in medication use research.

Authors:  A K Wagner; S B Soumerai; F Zhang; D Ross-Degnan
Journal:  J Clin Pharm Ther       Date:  2002-08       Impact factor: 2.512

2.  Executive Summary: Heart Disease and Stroke Statistics--2016 Update: A Report From the American Heart Association.

Authors:  Dariush Mozaffarian; Emelia J Benjamin; Alan S Go; Donna K Arnett; Michael J Blaha; Mary Cushman; Sandeep R Das; Sarah de Ferranti; Jean-Pierre Després; Heather J Fullerton; Virginia J Howard; Mark D Huffman; Carmen R Isasi; Monik C Jiménez; Suzanne E Judd; Brett M Kissela; Judith H Lichtman; Lynda D Lisabeth; Simin Liu; Rachel H Mackey; David J Magid; Darren K McGuire; Emile R Mohler; Claudia S Moy; Paul Muntner; Michael E Mussolino; Khurram Nasir; Robert W Neumar; Graham Nichol; Latha Palaniappan; Dilip K Pandey; Mathew J Reeves; Carlos J Rodriguez; Wayne Rosamond; Paul D Sorlie; Joel Stein; Amytis Towfighi; Tanya N Turan; Salim S Virani; Daniel Woo; Robert W Yeh; Melanie B Turner
Journal:  Circulation       Date:  2016-01-26       Impact factor: 29.690

3.  2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society.

Authors:  Craig T January; L Samuel Wann; Joseph S Alpert; Hugh Calkins; Joaquin E Cigarroa; Joseph C Cleveland; Jamie B Conti; Patrick T Ellinor; Michael D Ezekowitz; Michael E Field; Katherine T Murray; Ralph L Sacco; William G Stevenson; Patrick J Tchou; Cynthia M Tracy; Clyde W Yancy
Journal:  Circulation       Date:  2014-03-28       Impact factor: 29.690

Review 4.  Are cost benefits of anticoagulation for stroke prevention in atrial fibrillation underestimated?

Authors:  Paul S J Miller; Fredrik L Andersson; Lalit Kalra
Journal:  Stroke       Date:  2005-01-06       Impact factor: 7.914

5.  Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation.

Authors:  Robert G Hart; Lesly A Pearce; Maria I Aguilar
Journal:  Ann Intern Med       Date:  2007-06-19       Impact factor: 25.391

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

Authors:  Mark H Eckman; Gregory Y H Lip; Ruth E Wise; Barbara Speer; Megan Sullivan; Nita Walker; Brett Kissela; Matthew L Flaherty; Dawn Kleindorfer; Peter Baker; Robert Ireton; Dave Hoskins; Brett M Harnett; Carlos Aguilar; Anthony C Leonard; Lora Arduser; Dylan Steen; Alexandru Costea; John Kues
Journal:  Am Heart J       Date:  2016-02-19       Impact factor: 4.749

Review 7.  Underuse of anticoagulation in patients with atrial fibrillation.

Authors:  Ajay Vallakati; William R Lewis
Journal:  Postgrad Med       Date:  2016-01-08       Impact factor: 3.840

8.  Guideline-adherent antithrombotic treatment is associated with improved outcomes compared with undertreatment in high-risk patients with atrial fibrillation. The Euro Heart Survey on Atrial Fibrillation.

Authors:  Robby Nieuwlaat; S Bertil Olsson; Gregory Y H Lip; A John Camm; Günter Breithardt; Alessandro Capucci; Joan G Meeder; Martin H Prins; Samuel Lévy; Harry J G M Crijns
Journal:  Am Heart J       Date:  2007-06       Impact factor: 4.749

9.  Clinical decision support improves physician guideline adherence for laboratory monitoring of chronic kidney disease: a matched cohort study.

Authors:  Jennifer Ennis; Daniel Gillen; Arthur Rubenstein; Elaine Worcester; Mark E Brecher; John Asplin; Fredric Coe
Journal:  BMC Nephrol       Date:  2015-10-15       Impact factor: 2.388

10.  Automated Risk Assessment for Stroke in Atrial Fibrillation (AURAS-AF)--an automated software system to promote anticoagulation and reduce stroke risk: study protocol for a cluster randomised controlled trial.

Authors:  Tim A Holt; David A Fitzmaurice; Tom Marshall; Matthew Fay; Nadeem Qureshi; Andrew R H Dalton; F D Richard Hobbs; Daniel S Lasserson; Karen Kearley; Jenny Hislop; Jing Jin
Journal:  Trials       Date:  2013-11-13       Impact factor: 2.279

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  4 in total

1.  The impact of a multifaceted intervention to reduce potentially inappropriate prescribing among discharged older adults: a before-and-after study.

Authors:  Muhammad Eid Akkawi; Mohamad Haniki Nik Mohamed; Mohd Aznan Md Aris
Journal:  J Pharm Policy Pract       Date:  2020-07-17

2.  Coordinating Health Care With Artificial Intelligence-Supported Technology for Patients With Atrial Fibrillation: Protocol for a Randomized Controlled Trial.

Authors:  Liliana Laranjo; Tim Shaw; Ritu Trivedi; Stuart Thomas; Emma Charlston; Harry Klimis; Aravinda Thiagalingam; Saurabh Kumar; Timothy C Tan; Tu N Nguyen; Simone Marschner; Clara Chow
Journal:  JMIR Res Protoc       Date:  2022-04-13

Review 3.  Smartphone Apps for Managing Antithrombotic Therapy: Scoping Literature Review.

Authors:  Friederike Praus; Bartosz Krzowski; Tabea Walther; Christian Gratzke; Paweł Balsam; Arkadiusz Miernik; Philippe Fabian Pohlmann
Journal:  JMIR Cardio       Date:  2022-06-21

4.  Use of interrupted time series methods in the evaluation of health system quality improvement interventions: a methodological systematic review.

Authors:  Celestin Hategeka; Hinda Ruton; Mohammad Karamouzian; Larry D Lynd; Michael R Law
Journal:  BMJ Glob Health       Date:  2020-10
  4 in total

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