Implementing evidence‐based anticoagulant prescribing: User‐centered design findings and recommendations

F. Jacob Seagull, Michael S. Lanham, Michelle Pomorski, Mollie Callahan,Elizabeth K. Jones,Geoffrey D. Barnes

Research and Practice in Thrombosis and Haemostasis(2022)

引用 2|浏览6
暂无评分
摘要
Background Direct oral anticoagulants (DOACs) are widely used medications with an unacceptably high rate of prescription errors and are a leading cause of adverse drug events. Clinical decision support, including medication alerts, can be an effective implementation strategy to reduce prescription errors, but quality is often inconsistent. User-centered design (UCD) approaches can improve the effectiveness of alerts. Objectives To design effective DOAC prescription alerts through UCD and develop a set of generalizable design recommendations Methods This study used an iterative UCD process with practicing clinicians. In three rapid iterative design and assessment stages, prototype alert designs were created and refined using a test electronic health record (EHR) environment and simulated patients. We identified key emergent themes across all user observations and interviews. The themes and final designs were used to derive a set of design guidelines. Results Our UCD sample comprised 13 prescribers, including advanced practice providers, physicians in training, primary care physicians, and cardiologists. The resulting alert designs embody our design recommendations, which include establishing intended indication, clarifying dosing by renal function, tailoring alert language in drug interactions, facilitating trust in alerts, and minimizing interaction overhead. Conclusions Through a robust UCD process, we have identified key recommendations for implementing medication alerts aimed at improving evidence-based DOAC prescribing. These recommendations may be applicable to the implementation of DOAC alerts in any EHR systems.
更多
查看译文
关键词
anticoagulants,clinical,decision support systems,electronic health records,prescriptions,user‐centered design
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要