Real-time symptom monitoring using ePROs to prevent adverse events during care transitions

使用 ePRO 进行实时症状监测，以预防护理过渡期间的不良事件

• 批准号: 10494143
• 负责人: Anuj K Dalal
• 金额: $ 39.98万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10494143
• 关键词: Real; time; symptom; monitoring; using

ABSTRACT Adverse events (AE) during care transitions range from 19-28% and may lead to readmissions, representing an ongoing threat to patient safety. Early identification and escalation of patient-reported symptoms to inpatient and ambulatory clinicians is critical, especially for patients with multiple chronic conditions (MCC). Clinically integrated digital health apps have the potential to more accurately predict post-discharge AEs and improve communication for patients, their caregivers, and the care team. Such tools can provide individualized risk assessments of AEs by systematically collecting relevant patient-reported outcomes (PROs) and leveraging standardized application programming interfaces (API) to combine them with electronic health record (EHR) data. While patient-reported outcomes (PROs) are increasingly used in ambulatory settings, their use for real- time symptom monitoring and escalation during transitions from the hospital is novel and potentially transformative–by both empowering patients to better understand their individualized risks of post-discharge AEs, and improving monitoring while transitioning out of the hospital. Our proposed intervention is grounded in evidence-based frameworks for care transitions, and scaling and spread of digital health tools. To inform our intervention, we propose developing and validating a predictive model of post-discharge AEs for hospitalized MCC patients using relevant PRO questionnaires and electronic health record (EHR) derived variables. We will then combine, adapt, extend, and refine our previously developed EHR-integrated hospital and ambulatory-focused digital health infrastructure to support MCC patients in real-time symptom monitoring using PROs when transitioning out of the hospital. Our intervention uses interoperable, data exchange standards and APIs to seamlessly integrate with existing vendor patient portal offerings, thereby addressing critical gaps and supporting the complete continuum of care. Our multidisciplinary team uses principles of user-centered design and agile software development to rapidly identify, design, develop, refine, and implement requirements from patients and clinicians. Our team will rigorously evaluate this intervention in a large-scale randomized controlled trial in which we compare our real-time symptom monitoring intervention to usual care for patients with MCCs transitioning out of the hospital. Finally, we will conduct a robust mixed methods evaluation to generate new knowledge and best practices for disseminating, implementing, and using this interoperable intervention at similar institutions with different EHR vendors.

摘要 护理过渡期间的不良事件（AE）范围为19-28%，可能导致再次入院， 对患者安全的持续威胁。早期识别患者报告的症状并将其上报给住院患者 和门诊医生是至关重要的，特别是对于患有多种慢性疾病（MCC）的患者。临床 集成的数字健康应用程序有可能更准确地预测出院后AE， 患者、其护理人员和护理团队的沟通。这些工具可以提供个性化的风险 通过系统收集相关患者报告结局（PRO）并利用 标准化应用程序编程接口（API），以便将其与电子健康记录（EHR）联合收割机结合起来 数据虽然患者报告结局（PRO）越来越多地用于门诊，但其用于真实的 在从医院过渡期间的时间症状监测和升级是新颖的， 变革性-通过使患者能够更好地了解他们出院后的个性化风险， 不良事件，并在出院时改善监测。我们提出的干预是基于 以证据为基础的护理过渡框架，以及数字健康工具的扩展和传播。地通知我们的 干预，我们建议开发和验证住院患者出院后AE的预测模型， MCC患者使用相关PRO问卷和电子健康记录（EHR）衍生变量。我们 然后将联合收割机结合，调整，扩展和完善我们以前开发的EHR综合医院， 以门诊为重点的数字卫生基础设施，支持MCC患者进行实时症状监测 在出院时使用专业人员。我们的干预使用可互操作的数据交换 标准和API与现有供应商患者门户产品无缝集成，从而解决 关键的差距和支持完整的连续护理。我们的多学科团队采用以下原则： 以用户为中心的设计和敏捷软件开发，以快速识别、设计、开发、改进和 满足患者和临床医生的要求。我们的团队将严格评估这种干预措施， 一项大规模随机对照试验，在该试验中，我们将我们的实时症状监测干预与 对出院的MCC患者进行常规护理。最后，我们将进行一个强大的混合 方法评价，以产生新的知识和最佳做法， 在拥有不同EHR供应商的类似机构中使用这种可互操作的干预。