DEVELOPMENT OF AN ELECTRONIC CARE PLAN FOR PERSONS WITH MULTIPLE CHRONIC CONDITIONS (E-CARE)

通过卫生与公众服务部以患者为中心的结果研究信托基金(PCOR TF)提供的资金，NIDDK与医疗保健研究与质量机构(AHRQ)合作开发和测试了一套可互操作的电子(E)护理规划工具试点套件，以促进在家庭、社区、诊所和研究环境中为患有多种慢性疾病(MCC)的人收集和共享关键的以患者为中心的数据，这些慢性疾病包括慢性肾脏疾病(CKD)、2型糖尿病(T2D)、心血管疾病(CVD)、慢性疼痛、和SARS-CoV-2感染的急性后遗症(PASC)。护理计划是多方面护理协调干预措施的重要组成部分，可减少死亡率和住院率，提高疾病管理和满意度。此外，积极的护理规划促进了以人为本，改善了结果，并降低了护理成本。开发基于标准化数据的护理计划-利用快速医疗互操作性资源(FHIR)和可替代医疗应用、可重用技术(SMART)(FHIR上的https://smarthealthit.org/))等标准-已被提出为使电子系统能够自动和动态地整合和共享数据元素的方法。这样的汇总数据不仅将提供可操作的信息，以确定和实现MCC患者的健康和健康目标，而且还将减少遗漏，提高用于务实研究的护理点数据的质量。NIDDK领导该项目的开发部分，而真实世界的测试则由AHRQ领导。

Through funding made available from the Department of Health and Human Services’ Patient-Centered Outcomes Research Trust Fund (PCOR TF), the NIDDK has partnered with the Agency for Healthcare Research and Quality (AHRQ) on the development and testing of a pilot suite of interoperable electronic (e-) care planning tools to facilitate aggregation and sharing of critical patient-centered data across home-, community-, clinic- and research-based settings for persons with multiple chronic conditions (MCC), including chronic kidney disease (CKD), type 2 diabetes mellitus (T2D), cardiovascular disease (CVD), chronic pain, and post-acute sequelae of SARS-CoV-2 infection (PASC). Care plans are a prominent part of multifaceted, care coordination interventions that reduce mortality and hospitalizations and improve disease management and satisfaction. In addition, proactive care planning promotes person-centeredness, improves outcomes, and reduces the cost of care. Development of care plans based on standardized data—leveraging standards such as Fast Healthcare Interoperability Resources (FHIR) and Substitutable Medical Apps, Reusable Technology (SMART) (https://smarthealthit.org/) on FHIR—has been proposed as a method for enabling electronic systems to pull together and share data elements automatically and dynamically. Such aggregated data would not only provide actionable information to identify and achieve health and wellness goals for individuals with MCC, but also would reduce missingness and improve quality of point-of-care data for use in pragmatic research. The NIDDK is leading the development component of the project, while real-world testing is being led by AHRQ.