Literature DB >> 29250222

Effects of Computerized Decision Support Systems on Management of Atrial Fibrillation: A Scoping Review.

Reza Sheibani1, Ehsan Nabovati2, Mehdi Sheibani3, Ameen Abu-Hanna4, Alireza Heidari-Bakavoli5, Saeid Eslami1,4.   

Abstract

BACKGROUND: Potential role of computerized decision support system on management of atrial fibrillation is not well understood.
OBJECTIVES: To systematically review studies that evaluate the effects of computerized decision support systems and decision aids on aspects pertaining to atrial fibrillation. DATA SOURCES: We searched Medline, Scopus and Cochrane database. Last date of search was 2016, January 10. SELECTION CRITERIA: Computerized decision support systems that help manage atrial fibrillation and decision aids that provide useful knowledge for patients with atrial fibrillation and help them to self-care. DATA COLLECTION AND ANALYSIS: Two reviewers extracted data and summarized findings. Due to heterogeneity, meta-analysis was not feasible; mean differences of outcomes and confidence intervals for a difference between two Means were reported.
RESULTS: Seven eligible studies were included in the final review. There was one observational study without controls, three observational studies with controls, one Non-Randomized Controlled Trial and two Randomized Controlled Trials. The interventions were three decision aids that were used by patients and four computerized decision support systems. Main outcomes of studies were: stroke events and major bleeding (one article), Changing doctor-nurse behavior (three articles), Time in therapeutic International Normalized Ratio range (one article), decision conflict scale (two articles), patient knowledge and anxiety about stroke and bleeding (two articles).
CONCLUSIONS: A computerized decision support system may decrease decision conflict and increase knowledge of patients with atrial fibrillation (AF) about risks of AF and AF treatments. Effect of computerized decision support system on outcomes such as changing doctor-nurse behavior, anxiety about stroke and bleeding and stroke events could not be shown.We need more studies to evaluate the role of computerized decision support system in patients with atrial fibrillation.

Entities:  

Keywords:  Atrial fibrillation; Computerized decision support system; Decision aid; Medical informatics; Scoping review

Year:  2017        PMID: 29250222      PMCID: PMC5673328          DOI: 10.4022/jafib.1579

Source DB:  PubMed          Journal:  J Atr Fibrillation        ISSN: 1941-6911


  40 in total

Review 1.  Evaluation of outpatient computerized physician medication order entry systems: a systematic review.

Authors:  Saeid Eslami; Ameen Abu-Hanna; Nicolette F de Keizer
Journal:  J Am Med Inform Assoc       Date:  2007-04-25       Impact factor: 4.497

2.  Use of the CHA(2)DS(2)-VASc and HAS-BLED scores to aid decision making for thromboprophylaxis in nonvalvular atrial fibrillation.

Authors:  Deirdre A Lane; Gregory Y H Lip
Journal:  Circulation       Date:  2012-08-14       Impact factor: 29.690

Review 3.  The impact of health information technology on the quality of medical and health care: a systematic review.

Authors:  Aziz Jamal; Kirsten McKenzie; Michele Clark
Journal:  Health Inf Manag       Date:  2009       Impact factor: 3.185

4.  Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review.

Authors:  D L Hunt; R B Haynes; S E Hanna; K Smith
Journal:  JAMA       Date:  1998-10-21       Impact factor: 56.272

5.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

Authors:  David Moher; Alessandro Liberati; Jennifer Tetzlaff; Douglas G Altman
Journal:  Int J Surg       Date:  2010-02-18       Impact factor: 6.071

6.  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

7.  A pilot randomized controlled trial of a decision support tool to improve the quality of communication and decision-making in individuals with atrial fibrillation.

Authors:  Liana Fraenkel; Richard L Street; Virginia Towle; John R O'Leary; Lynne Iannone; Peter H Van Ness; Terri R Fried
Journal:  J Am Geriatr Soc       Date:  2012-08-02       Impact factor: 5.562

8.  Pilot study of a novel patient self-management program for warfarin therapy using venipuncture-acquired international normalized ratio monitoring.

Authors:  Brandon J Simmons; Kathleen M Jenner; Thomas Delate; Nathan P Clark; Deanna Kurz; Daniel M Witt
Journal:  Pharmacotherapy       Date:  2012-10-30       Impact factor: 4.705

9.  A patient decision aid to support shared decision-making on anti-thrombotic treatment of patients with atrial fibrillation: randomised controlled trial.

Authors:  Richard G Thomson; Martin P Eccles; I Nick Steen; Jane Greenaway; Lynne Stobbart; Madeleine J Murtagh; Carl R May
Journal:  Qual Saf Health Care       Date:  2007-06

Review 10.  The role of Decision Support System (DSS) in prevention of cardiovascular disease: a systematic review and meta-analysis.

Authors:  Raghupathy Anchala; Maria P Pinto; Amir Shroufi; Rajiv Chowdhury; Jean Sanderson; Laura Johnson; Patricia Blanco; Dorairaj Prabhakaran; Oscar H Franco
Journal:  PLoS One       Date:  2012-10-10       Impact factor: 3.240

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  1 in total

1.  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

  1 in total

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