A Remote Patient Monitoring System With Feedback Mechanisms Using a Smartwatch: Concept, Implementation, and Evaluation Based on the activeDCM Randomized Controlled Trial.

IF 5.4 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES JMIR mHealth and uHealth Pub Date : 2024-11-22 DOI:10.2196/58441
Reto Wettstein, Farbod Sedaghat-Hamedani, Oliver Heinze, Ali Amr, Christoph Reich, Theresa Betz, Elham Kayvanpour, Angela Merzweiler, Christopher Büsch, Isabell Mohr, Birgit Friedmann-Bette, Norbert Frey, Martin Dugas, Benjamin Meder
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Abstract

Background: Technological advances allow for recording and sharing health-related data in a patient-centric way using smartphones and wearables. Secure sharing of such patient-generated data with physicians would enable close management of individual health trajectories, monitoring of risk factors, and asynchronous feedback. However, most remote patient monitoring (RPM) systems currently available are not fully integrated into hospital IT systems or lack a patient-centric design.

Objective: The objective of this study was to conceptualize and implement a user-friendly, reusable, interoperable, and secure RPM system incorporating asynchronous feedback mechanisms using a broadly available consumer wearable (Apple Watch). In addition, this study sought to evaluate factors influencing patient acceptance of such systems.

Methods: The RPM system requirements were established through focus group sessions. Subsequently, a system concept was designed and implemented using an iterative approach ensuring technical feasibility from the beginning. To assess clinical feasibility, the system was used as part of the activeDCM prospective randomized interventional study focusing on dilated cardiomyopathy. Each patient used the system for at least 12 months. The System Usability Scale was used to measure usability from a subjective patient perspective. In addition, an evaluation was conducted on the objective wearable interaction frequency as well as the completeness of transmitted data classified into sensor-based health data (SHD) and patient-reported outcome measures (PROMs). Descriptive statistics using box plots and bootstrapped multiple linear regression with 95% CIs were used for evaluation analyzing the influence of age, sex, device experience, and intervention group membership.

Results: The RPM system comprised 4 interoperable components: patient devices, a data server, a data viewer, and a notification service. The system was evaluated with 95 consecutive patients with dilated cardiomyopathy (28/95, 29% female; mean age 50, SD 12 y) who completed the activeDCM study protocol. The system's app achieved a mean System Usability Scale score of 78 (SD 17), which was most influenced by device experience. In total, 87% (83/95) of the patients could integrate the use of the app well or very well into their daily routine, and 71% (67/95) saw a benefit of the RPM system for management of their health condition. On average, patients interacted with the wearable on 61% (SD 26%) of days enrolled in the study. SHD were available on average for 78% (SD 23%) of days, and PROM data were available on 64% (SD 27%) of weeks enrolled in the study. Wearable interaction frequency, SHD, and PROM completeness were most influenced by intervention group membership.

Conclusions: Our results mark a first step toward integrating RPM systems based on a consumer wearable device for primary patient input into standardized clinical workflows. They can serve as a blueprint for creating a user-friendly, reusable, interoperable, and secure RPM system that can be integrated into patients' daily routines.

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使用智能手表的带有反馈机制的远程患者监护系统:基于 activeDCM 随机对照试验的概念、实施和评估。
背景:随着技术的进步,人们可以利用智能手机和可穿戴设备,以患者为中心记录和共享与健康相关的数据。与医生安全共享这些由患者生成的数据可实现对个人健康轨迹的密集管理、风险因素监测和异步反馈。然而,目前大多数远程患者监护(RPM)系统都没有完全集成到医院的 IT 系统中,或者缺乏以患者为中心的设计:目的:该研究旨在构思并实施一个用户友好、可重复使用、可互操作且安全的 RPM 系统,该系统结合了异步反馈机制,并使用了一种广泛可用的消费类可穿戴设备(Apple Watch)。此外,该研究还试图评估影响患者接受此类系统的因素:方法:通过焦点小组会议确定了 RPM 系统的要求。随后,采用迭代方法设计并实施了系统概念,从一开始就确保了技术可行性。为了评估临床可行性,该系统作为 activeDCM 前瞻性、随机、介入研究的一部分,主要针对扩张型心肌病 (DCM)。每位患者使用该系统至少 12 个月。系统可用性量表 (SUS) 被用来从患者的主观角度衡量可用性。此外,还对客观的可穿戴设备交互频率以及传输数据的完整性进行了评估,这些数据分为基于传感器的健康数据 (SHD) 和患者报告结果测量 (PROM)。评估中使用了方框图进行描述性统计,并使用带 95% 置信区间 (CI) 的自引导多元线性回归,分析了年龄、性别、设备使用经验和干预小组成员资格的影响:RPM 系统由四个互操作组件组成:患者设备、数据服务器、数据查看器和通知服务。该系统的评估对象是完成 activeDCM 研究方案的 95 名连续 DCM 患者(95 人中有 28 名女性,占 29%,年龄为 50±12 岁)。该系统的可穿戴/智能手机应用的平均 SUS 得分为 78±17,受设备使用经验的影响最大。95 位患者中有 83 位(87%)能将可穿戴应用(非常)很好地融入日常工作,95 位患者中有 67 位(70%)认为 RPM 系统有利于管理他们的健康状况。患者与可穿戴设备进行互动的天数平均为 61%±26%,即 396±39 天中的 239±99。平均有78%±23%的天数可获得SHD数据,有64%±27%的周数可获得PROM数据,分别相当于396±39天中的307±87天和56±5周中的35±15周。可穿戴设备交互频率、SHD和PROM完整性受干预小组成员资格的影响最大:我们的研究结果标志着将基于消费者可穿戴设备的 RPM 系统纳入标准化临床工作流程迈出了第一步。这些结果可作为创建用户友好、可重复使用、可互操作且安全的 RPM 系统的蓝图,该系统可融入患者的日常生活:临床试验:ClinicalTrials.gov-Identifier:NCT04359238。
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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
期刊最新文献
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