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

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 2015, April 28. 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 were 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.

Credits: Reza Sheibani, Ehsan Nabovati, Mehdi Sheibani , Ameen Abu-Hanna, Alireza Heidari-Bakavoli ,Saeid Eslami

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