Continuous Remote Patient Monitoring: Evaluation of the Heart Failure Cascade Soft Launch
Continuous Remote Patient Monitoring: Evaluation of the Heart Failure Cascade Soft Launch
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DOI：
10.1055/s-0041-1740480
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发表时间：
2021-10-01
影响因子：
2.9
通讯作者：
Shah, Nirav S.
中科院分区：
文献类型：
--
作者：
Chi, Wei Ning;Reamer, Courtney;Shah, Nirav S.
目的报告我们在心力衰竭(HF)患者出院后实施连续远程患者监测(CRPM)研究软启动的经验。从软启动中吸取的经验教训用于修改和微调工作流程和研究方案。方法这次软发射于2020年12月至2021年3月在北岸大学卫生系统的埃文斯顿医院进行。患者被提供了持续收集动态生理数据的非侵入性可穿戴生物传感器，以及收集患者报告结果的研究手机。这些生理数据通过机器学习算法进行分析，潜在地识别出心力衰竭患者的生理扰动。来自该算法的警报可以与其他患者状态数据级联，以通过结构化协议通知家庭健康护士(HHN)的管理。HHN每天审查监测平台。如果患者的状态符合特定标准，HHN会进行评估，并将患者病例上报给HF团队，以进一步指导早期干预。结果我们招募了5名患者参加软启动。四名参与者坚持学习活动。五名患者中有两名再次入院，一名患者因心力衰竭，一名患者因感染。观察到的沟通错误和协议差距被记录在协议修订中。研究团队采用了变革管理理论中的组织发展方法对研究方案进行了重新配置。结论我们试图通过将从可穿戴设备产生流数据的新技术与复杂的多提供商工作流程结合在一起，实现出院后护理的监测方面的自动化，使之成为一种新的协议，使用迭代的设计、实施和评估方法来监测出院后的心衰患者。CRPM具有结构化升级和远程监护协议，显示了将患者维持在他们的家庭环境中并减少与心衰相关的再入院的潜力。我们的结果表明，继续教育以吸引和增强使用先进技术的前线工人的能力，对于扩大这一方法是至关重要的。
Objective We report on our experience of deploying a continuous remote patient monitoring (CRPM) study soft launch with structured cascading and escalation pathways on heart failure (HF) patients post-discharge. The lessons learned from the soft launch are used to modify and fine-tune the workflow process and study protocol. Methods This soft launch was conducted at NorthShore University HealthSystem's Evanston Hospital from December 2020 to March 2021. Patients were provided with non-invasive wearable biosensors that continuously collect ambulatory physiological data, and a study phone that collects patient-reported outcomes. The physiological data are analyzed by machine learning algorithms, potentially identifying physiological perturbation in HF patients. Alerts from this algorithm may be cascaded with other patient status data to inform home health nurses' (HHNs') management via a structured protocol. HHNs review the monitoring platform daily. If the patient's status meets specific criteria, HHNs perform assessments and escalate patient cases to the HF team for further guidance on early intervention. Results We enrolled five patients into the soft launch. Four participants adhered to study activities. Two out of five patients were readmitted, one due to HF, one due to infection. Observed miscommunication and protocol gaps were noted for protocol amendment. The study team adopted an organizational development method from change management theory to reconfigure the study protocol. Conclusion We sought to automate the monitoring aspects of post-discharge care by aligning a new technology that generates streaming data from a wearable device with a complex, multi-provider workflow into a novel protocol using iterative design, implementation, and evaluation methods to monitor post-discharge HF patients. CRPM with structured escalation and telemonitoring protocol shows potential to maintain patients in their home environment and reduce HF-related readmissions. Our results suggest that further education to engage and empower frontline workers using advanced technology is essential to scale up the approach.