Process Evaluation of a Wireless Wearable Continuous Vital Signs Monitoring Intervention in 2 General Hospital Wards: Mixed Methods Study.

JMIR nursing Pub Date : 2023-05-04 DOI:10.2196/44061
Jobbe P L Leenen, Henriëtte J M Rasing, Cor J Kalkman, Lisette Schoonhoven, Gijsbert A Patijn
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引用次数: 2

Abstract

Background: Continuous monitoring of vital signs (CMVS) using wearable wireless sensors is increasingly available to patients in general wards and can improve outcomes and reduce nurse workload. To assess the potential impact of such systems, successful implementation is important. We developed a CMVS intervention and implementation strategy and evaluated its success in 2 general wards.

Objective: We aimed to assess and compare intervention fidelity in 2 wards (internal medicine and general surgery) of a large teaching hospital.

Methods: A mixed methods sequential explanatory design was used. After thorough training and preparation, CMVS was implemented-in parallel with the standard intermittent manual measurements-and executed for 6 months in each ward. Heart rate and respiratory rate were measured using a chest-worn wearable sensor, and vital sign trends were visualized on a digital platform. Trends were routinely assessed and reported each nursing shift without automated alarms. The primary outcome was intervention fidelity, defined as the proportion of written reports and related nurse activities in case of deviating trends comparing early (months 1-2), mid- (months 3-4), and late (months 5-6) implementation periods. Explanatory interviews with nurses were conducted.

Results: The implementation strategy was executed as planned. A total of 358 patients were included, resulting in 45,113 monitored hours during 6142 nurse shifts. In total, 10.3% (37/358) of the sensors were replaced prematurely because of technical failure. Mean intervention fidelity was 70.7% (SD 20.4%) and higher in the surgical ward (73.6%, SD 18.1% vs 64.1%, SD 23.7%; P<.001). Fidelity decreased over the implementation period in the internal medicine ward (76%, 57%, and 48% at early, mid-, and late implementation, respectively; P<.001) but not significantly in the surgical ward (76% at early implementation vs 74% at midimplementation [P=.56] vs 70.7% at late implementation [P=.07]). No nursing activities were needed based on vital sign trends for 68.7% (246/358) of the patients. In 174 reports of 31.3% (112/358) of the patients, observed deviating trends led to 101 additional bedside assessments of patients and 73 consultations by physicians. The main themes that emerged during interviews (n=21) included the relative priority of CMVS in nurse work, the importance of nursing assessment, the relatively limited perceived benefits for patient care, and experienced mediocre usability of the technology.

Conclusions: We successfully implemented a system for CMVS at scale in 2 hospital wards, but our results show that intervention fidelity decreased over time, more in the internal medicine ward than in the surgical ward. This decrease appeared to depend on multiple ward-specific factors. Nurses' perceptions regarding the value and benefits of the intervention varied. Implications for optimal implementation of CMVS include engaging nurses early, seamless integration into electronic health records, and sophisticated decision support tools for vital sign trend interpretation.

Abstract Image

2个综合医院病房无线可穿戴连续生命体征监测干预过程评价:混合方法研究
背景:使用可穿戴无线传感器持续监测生命体征(CMVS)越来越多地用于普通病房患者,可以改善预后并减少护士工作量。为了评估这些系统的潜在影响,成功的实施是很重要的。我们制定了CMVS干预和实施策略,并评估了其在2个普通病房的成功。目的:对某大型教学医院内科和普外科2个病区的干预保真度进行评价和比较。方法:采用混合方法序贯解释设计。经过全面的培训和准备,CMVS与标准的间歇人工测量并行实施,并在每个病房执行6个月。使用佩戴在胸前的可穿戴传感器测量心率和呼吸频率,并在数字平台上可视化生命体征趋势。在没有自动警报的情况下,定期评估和报告每个护理班次的趋势。主要结果是干预保真度,定义为在实施早期(1-2个月)、中期(3-4个月)和后期(5-6个月)出现偏离趋势的情况下,书面报告和相关护士活动的比例。对护士进行解释性访谈。结果:实施策略按计划执行。共纳入358名患者,在6142个护士班次中监测了45,113个小时。总共有10.3%(37/358)的传感器由于技术故障而过早更换。平均干预保真度为70.7% (SD 20.4%),外科病房更高(73.6%,SD 18.1% vs 64.1%, SD 23.7%;结论:我们成功地在2个医院病房大规模实施了CMVS系统,但我们的结果表明,干预的保真度随着时间的推移而下降,内科病房比外科病房更明显。这种下降似乎取决于多个病房特定因素。护士对干预的价值和益处的看法各不相同。优化CMVS实施的意义包括尽早让护士参与,无缝集成到电子健康记录中,以及用于生命体征趋势解释的复杂决策支持工具。
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CiteScore
5.20
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审稿时长
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