A Technology-Driven Intervention to Improve Early Detection and Management of Cognitive Impairment

项目摘要 到2050年，认知障碍(CI)的患病率预计将增加两倍，导致认知障碍的质量下降 生命，增加的医疗保健利用率，以及对已经紧张的初级保健系统的额外负担。 许多临床医生对CI缺乏评估、诊断和管理的信心，超过50%的CI患者 都没有诊断出来。为了解决这些重要问题，在该项目的第一阶段(R61)，我们开发了 使用完成的简要Mini-Cog屏幕的结果验证了名为MC-Plus的机器学习模型 定期在年度Medicare健康检查和电子健康记录(EHR)数据中识别患者 未来被诊断为CI的风险增加。我们还开发、验证和试行了CI临床决策支持 (CI-CDS)系统，让患者和临床医生就CI风险增加进行对话，并为临床医生提供 他们诊断和管理CI所需的信心和工具。MC-PLUS和CI-CDS系统都是 添加到现有的基于Web的CDS平台中，该平台具有高使用率和高初级保健临床医生 令人满意，并已与史诗EHR无缝集成。 我们目前正在开始第二阶段(R33)，这是一项大型务实试验，将30家初级保健诊所随机分配到 接受CI-CDS或常规护理(UC)。我们将评估CI诊断的变化和临床医生对 CI-CDS诊所与UC诊所提供者CI的诊断和管理。如果成功， CI-CDS系统将提高CI新诊断率，缩小现有社会人口 与UC相比，在CI-CDS的指数访问中MC-PLUS确定的CI风险升高的成年人的差异 诊所。 CI-CDS系统每年将在研究地点向200万名患者提供，有可能 通过建立在Epic EHR上的现有非商业化CDS平台更广泛地传播。然而， CI-CDS设计需要更新和现代化，从我们已建立的Epic EHR流水线升级到 确保其健壮性、可持续性、互操作性和可扩展性，以便向更大的社区传播。 建议的补助金旨在让我们的资讯科技、软件工程和 Epic EHR内部IT团队对CI-CDS架构进行现代化改造，以增强其可移植性、可扩展性和 通过以下步骤产生影响：a)将CI-CDS迁移到OpenShift平台；b)将其Epic EHR- 特定集成到基于快速医疗保健互操作性资源(FHIR)的应用程序编程 接口(API)；以及c)重新设计其患者数据提取和人工智能(AI)推理 我们的MC-plus模型正在从批处理模型到实时模型。这些活动将促进更广泛的 通过允许集成到多个不同的EHR来影响该工具。

Project Summary The prevalence of cognitive impairment (CI) is expected to triple by 2050, contributing to decreased quality of life, increased medical care utilization, and additional burden on an already stressed primary care system. Many clinicians lack confidence to assess, diagnose and manage CI, and more than 50% of patients with CI are undiagnosed. To address these important problems, in phase 1 (R61) of this project, we developed and validated a machine learning model called MC-PLUS using results from brief Mini-Cog screens completed routinely at Annual Medicare Wellness exams and electronic health record (EHR) data to identify patients at elevated risk of a future CI diagnosis. We also developed, validated, and piloted a CI clinical decision support (CI-CDS) system to engage patients and clinicians in conversation about elevated CI risk, and to give clinicians the confidence and tools they need to diagnose and manage CI. Both MC-PLUS and the CI-CDS system were added into an existing web-based CDS platform that has high use rates and high primary care clinician satisfaction and is already seamlessly integrated with the Epic EHR. We are currently beginning phase 2 (R33), a large pragmatic trial with 30 primary care clinics randomized to receive CI-CDS or usual care (UC). We will evaluate the change in CI diagnosis and clinician confidence in diagnosing and managing CI among providers in CI-CDS clinics compared to those in UC clinics. If successful, the CI-CDS system will improve rates of new CI diagnosis and narrow existing sociodemographic disparities for adults with elevated CI risk identified by MC-PLUS at index visits in CI-CDS compared to UC clinics. The CI-CDS system will be available to 2 million patients annually at the study sites with the potential to disseminate more broadly through the existing non-commercialized CDS platform built on Epic EHR. However, the CI-CDS design needs to be updated and modernized from our established legacy Epic EHR pipeline to ensure its robustness, sustainability, interoperability, and scalability for dissemination to the larger community. The proposed grant supplement aims to engage our IT (Information Technology), software engineering and internal Epic EHR IT teams to modernize the CI-CDS architecture to enhance its portability, scalability and impact through the following steps: a) migrating CI-CDS to the OpenShift platform; b) converting its Epic EHR- specific integration to Fast Healthcare Interoperability Resources (FHIR)-based application programming interfaces (APIs); and c) re-architecting its patient data extraction and artificial intelligence (AI) inference pipeline for our MC-PLUS model from batch-based to a real-time model. These activities will facilitate broader impact of the tool by allowing integration into many different EHRs.