A user-center designed anticoagulation shared decision-making tool for stroke prevention in atrial fibrillation

项目总结 房颤(房颤)是最常见的心律失常，预计到 2030年在美国。考虑到在这个人群中中风的风险增加了两到五倍，抗凝是 推荐大多数房颤患者使用。然而，指导方针是宽泛的，平衡了中风和 出血需要一种个性化的方法。抗凝血导致中风和出血的风险可能是 分别用CHA2DS2-VASC和HAS风险评估分数进行评估。这些风险 评估是有效的，但不区分临床结果，这是一个重大问题 鉴于中风的医疗并发症远远大于出血的医疗并发症。 房颤的ACC/AHA临床表现评估确定共同的抗凝治疗决策 作为一个质量指标。然而，这项措施没有解决执行方面的一个重要差距，即 缺乏价值澄清来证明中风和出血的风险。鉴于被广泛采用的 对于电子健康记录，迫切需要开发技术来促进价值澄清 房颤患者共同制定抗凝处方时的中风和出血风险。 拟议的项目将与患者和提供者合作，创建一个决策支持工具，以澄清 房颤患者抗凝的风险权衡，开发和实施共享决策支持应用程序 根据患者和提供者的反馈，确定新的决策支持工具是否具有价值 与标准通信相比，澄清有助于了解风险权衡。此外，这一点 提案将展示密歇根大学学习健康科学(LHS)知识的使用情况 网格(KGrid)，由支持大规模知识管理和管理的数字图书馆组成 和激活者，通过定制的决策支持将知识快速交付到实践中 给收件人的工具。 这些数据将对计划中的随机试验至关重要，该试验将测试新创建的共享 多中心电子健康档案实施中房颤抗凝结果的决策支持工具。 此外，这些数据将允许LHS KGrid作为可扩展和标准化的未来研究 共享决策和风险沟通的基础设施。

PROJECT SUMMARY Atrial fibrillation (AF) is the most common cardiac arrhythmia with a projected prevalence of 12.1 million by 2030 in the US. Given a two-to-five-fold increased risk of stroke in this population, anticoagulation is recommended for most AF patients. However, guidelines are broad and balancing the risks of stroke and bleeding require a personalized approach. The risk of stroke and bleeding from anticoagulation can be assessed with the CHA2DS2-VASc and HAS-BLED risk assessment scores, respectively. These risk assessments are valid, but do not distinguish between the clinical outcomes, which is a significant problem given that the medical complications of a stroke are far greater than the medical complications of a bleed. The ACC/AHA clinical performance measures for AF identify shared decision making for anticoagulant therapy as a quality metric. The measure does not, however, address an important gap in implementation, namely the lack of a value clarification to demonstrate the risks of stroke and bleeding. Given the widespread adoption of electronic health records, there is a critical need to develop technologies that facilitate value clarification of stroke and bleeding risk during shared decision making for anticoagulation prescribing in AF. The proposed project will work with patients and providers to create a decision support tool that clarifies the risk tradeoffs for anticoagulation in AF, develop and implement a shared decision-making support application based on the patient and provider feedback and determine if the new decision support tool with a value clarification facilitates knowledge of the risk tradeoffs compared to standard communication. In addition, this proposal will demonstrate the use of the University of Michigan Learning Health Sciences (LHS) Knowledge Grid (KGrid), which consists of a digital Library to support large-scale knowledge curation and management and an Activator to provide rapid delivery of knowledge into practice through a customized decision support tool to recipients. These data will be crucial for a planned randomized trial to test the effects of the newly created shared decision support tool on anticoagulation outcomes in AF in multicenter electronic health record implementation. In addition, these data will allow for future research of the LHS KGrid as a scalable and standardized infrastructure for shared decision making and risk communication.