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

项目摘要 心房颤动（AF）是最常见的心律失常，截至2010年， 2030年在美国。考虑到这一人群中风风险增加2 - 5倍，抗凝治疗是 推荐给大多数AF患者。然而，指南是广泛的，平衡了中风的风险， 出血需要个性化的方法。抗凝治疗引起中风和出血的风险可能是 分别用CHA 2DS 2-VASc和HAS-BLED风险评估评分进行评估。这些风险 评估是有效的，但不能区分临床结果，这是一个重要的问题 因为中风的医疗并发症远远大于出血的医疗并发症。 ACC/AHA AF临床性能指标确定了抗凝治疗的共同决策 作为质量指标。然而，这项措施并没有解决执行方面的一个重要差距，即： 缺乏证明卒中和出血风险的价值澄清。由于广泛采用 电子健康记录，迫切需要开发技术，促进价值澄清， 房颤抗凝治疗处方的共同决策过程中的卒中和出血风险。 拟议的项目将与患者和供应商合作，创建一个决策支持工具，澄清 AF抗凝治疗的风险权衡，开发并实施共享决策支持应用程序 基于患者和提供者的反馈，并确定新的决策支持工具是否具有 与标准通信相比，澄清有助于了解风险权衡。另外这款 该提案将展示密歇根大学学习健康科学（LHS）知识的使用 网格（KGrid），由数字图书馆组成，支持大规模的知识策展和管理 和一个通过定制的决策支持将知识快速交付到实践中的激活器 工具给收件人。 这些数据对于计划中的随机试验至关重要，以测试新创建的共享 多中心电子健康记录实施中房颤抗凝结局的决策支持工具。 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.