Publications by authors named "Abdulrhman Al Rowily"

Introduction: Direct oral anticoagulants (DOACs) are considered high risk medicines and are frequently associated with medication errors. The nature of incidents and associated outcomes of such incidents are poorly understood.

Areas Covered: Using a national patient safety reporting database, the National Reporting and Learning System (NRLS), this study aimed to report the contributory factors and outcomes including severe harm and deaths related to all safety incidents involving DOACs reported in England and Wales between 2017-2019.

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Background: Direct oral anticoagulants (DOACs) are considered high-risk medications and used to prevent thromboembolic events and stroke. This study aimed to examine patients' views and experiences of DOACs use and factors that can promote safety associated with DOACs.

Methods: In-depth interviews were conducted with adult patients who had been prescribed DOACs, identified and invited by local collaborators in three different tertiary care hospitals in Saudi Arabia.

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Background: Despite their effectiveness and ease of use, medication errors have been reported to be highly prevalent with direct-acting oral anticoagulants (DOAC).

Aim: The aim of this study was to explore views and experiences of pharmacists on contributory factors and mitigation strategies around medication errors in relation to DOAC.

Method: This study used a qualitative design.

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Background: Direct oral anticoagulants (DOACs) have become preferable for the management of thromboembolic events. Recent publications have however identified high volume of medication errors related to DOACs. There is limited literature on why and how such errors occur or happen in clinical practice.

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Purpose: This study aimed to estimate the prevalence, contributory factors, and severity of medication errors associated with direct acting oral anticoagulants (DOACs).

Methods: A systematic review and meta-analysis were undertaken by searching 11 databases including Medline, Embase, and CINHAL between January 2008 and September 2020. The pooled prevalence of errors and predictive intervals were estimated using random-effects models using Stata software.

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