新的无线袜子监测系统降低了住院患者的跌倒率

New wireless sock monitoring system reduces fall rates among hospitalized patients

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Research led by nurses at The Ohio State University Wexner Medical Center found that a new wireless sock monitoring system reduced fall rates among "fall-risk" patients hospitalized at Ohio State's Brain and Spine Hospital. In fact, none of the patients who were on a fall-risk protocol fell while wearing the socks over 2,211.6 patient-days during the study.

The study evaluated the effectiveness of Palarum's PUP (Patient is Up) Smart Socks and findings are published online in the Journal of Nursing Care Quality.

Data was collected on 569 patients who were hospitalized in the major academic medical center's neurological and neurosurgical units during 13 months of the study period. These units specialize in stroke, orthopedics, neurosurgery, general neurology and epilepsy. Originally planned to enroll 2,500 patients, the study ended early because of the COVID-19 pandemic.

Patients can fall while they are hospitalized, and this can sometimes lead to injury or death. We know that existing fall prevention measures do not work consistently. During our study, we observed zero falls, which was a lower fall rate among the patients wearing these socks than the historical fall rate of 4 falls per 1,000 patient-days."

Tammy Moore, Senior Investigator, Associate Chief Nurse of Ohio State's Neurological Institute and Medical Surgical

During the study period, 5,010 safety events (alarms) were associated with the system. Eleven were reported to be false alarms, indicating 4,999 of the safety events (or 99.8%) were true patient stands, Moore said.

At admission to the hospital, patients' fall risk scores were assessed by nurses based on the hospital's assessment tool. All patients enrolled in the study were provided with the socks until discharge or removal from the fall risk protocol, and no other fall prevention system, such as chair or bed alarms or TeleSitter was used for these patients.

The safety system consists of the socks with built-in pressure sensors that detect when a patient is trying to stand up in combination with interrelated devices with sensors that exchange data over a wireless network. The system also includes an in-room tablet for each patient room, a local server, a monitoring device at the nurses' station and "Smart Badge" notification devices worn by the nurses, said Chris Baker, co-founder and vice-president for business development at Palarum.

When the socks detect an attempt to stand up, the system alerts the three nurses it finds closest to the alarming room through their badges. When a nurse with a badge then enters the patient's room, the alert is automatically deactivated. If none of those nurses enter the room within the first 60 seconds, the alarm escalates to the next three closest. If no one responds within 90 seconds, the system proceeds to an "all call" to all Smart Badges logged into the alarming unit, Baker said.

"Due to the rapidly aging population, the number of patients at higher risk of falling in hospitals is expected to increase substantially. About 30% of in-hospital falls are thought to be preventable, so it's imperative to determine better ways to keep our patients safe from falling while hospitalized," said study co-author Tina Bodine, a nurse navigator at Ohio State's Neurological Institute.

Fall prevention measures usually focus on patient education, increasing nurse awareness, or preventive measures such as installing bed and chair pressure sensors. In hospitals, bed and chair pressure sensors are very common because most falls occur when patients try to get out of bed to attempt to use the toilet. Despite their widespread use, other studies have shown that bed and chair pressure sensors do not prevent falls in hospitals.

"A major problem with bed and chair pressure sensors is that the high numbers of false alarms may cause 'alarm fatigue' that can contribute to delayed response," Bodine said. "With this system, no falls were detected, and only 0.2% of the alarms were false alarms. We also analyzed nurse response times that ranged from 1 second to nearly 10 minutes and found that the median nurse response time was 24 seconds."

Nurse response times to bed and chair pressure sensors have not been published, and researchers did not have historical response times for participating units.

"However, our staff believed that response times were improved compared with the use of bed and chair alarms, among others, because alarm notifications included room numbers, targeted the 3 closest clinical staff members, and notified nurses directly instead of indirectly through a nurse station," Moore said.

The research team also included collaborators with Ohio State's Center for Biostatistics and Wake Forest School of Medicine.

The sock monitoring system was made available for the study free of charge by Palarum LLC. The study authors declare they have no financial or any other relationship with the company.

全文翻译（仅供参考）

由俄亥俄州立大学韦克斯纳医学中心的护士领导的研究发现，一种新的无线袜子监测系统降低了在俄亥俄州立大学大脑和脊柱医院住院的“跌倒风险”患者的跌倒率。事实上，在研究期间，在 2,211.6 个患者日内穿着袜子的患者中，没有一个接受跌倒风险方案的患者跌倒。

该研究评估了 Palarum 的 PUP（Patient is Up）智能袜子的有效性，研究结果在线发表在《护理质量杂志》上。

在研究期间的 13 个月内，收集了 569 名在主要学术医疗中心的神经病学和神经外科病房住院的患者的数据。这些单位专门研究中风、骨科、神经外科、普通神经病学和癫痫。该研究最初计划招募 2,500 名患者，但由于 COVID-19 大流行而提前结束。

患者在住院期间可能会跌倒，这有时会导致受伤或死亡。我们知道现有的跌倒预防措施并不能始终如一地发挥作用。在我们的研究中，我们观察到零跌倒，即穿着这些袜子的患者的跌倒率低于每 1000 个患者日 4 次跌倒的历史跌倒率。”

Tammy Moore，高级研究员，俄亥俄州立大学神经病学研究所和内外科副主任护士

在研究期间，有 5,010 起安全事件（警报）与系统相关。据报道，有 11 起是误报，表明 4,999 起安全事件（或 99.8%）是真正的病人站，摩尔说。

入院时，护士根据医院的评估工具对患者的跌倒风险评分进行评估。在出院或从跌倒风险协议中移除之前，所有参加该研究的患者都获得了袜子，并且没有为这些患者使用其他跌倒预防系统，例如椅子或床警报器或 TeleSitter。

安全系统由带有内置压力传感器的袜子组成，这些传感器可以检测患者何时试图站起来，并结合相关设备以及通过无线网络交换数据的传感器。该系统还包括用于每个病房的室内平板电脑、本地服务器、护士站的监控设备和护士佩戴的“智能徽章”通知设备，Chris Baker 联合创始人兼副总裁说Palarum 的业务发展。

当袜子检测到有人试图站起来时，系统会通过他们的徽章提醒它发现离警报室最近的三名护士。当一名带徽章的护士进入患者房间时，警报会自动停用。如果这些护士在前 60 秒内没有人进入房间，警报会升级到下一个最近的三个。贝克说，如果在 90 秒内没有人响应，系统将继续对所有登录到警报单元的智能徽章进行“全部呼叫”。

“由于人口迅速老龄化，医院跌倒风险较高的患者数量预计将大幅增加。大约 30% 的院内跌倒被认为是可以预防的，因此必须确定更好的方法来留住我们的患者住院期间不会跌倒，”该研究的合著者、俄亥俄州立大学神经病学研究所的护士导航员 Tina Bodine 说。

跌倒预防措施通常侧重于患者教育、提高护士意识或安装床和椅子压力传感器等预防措施。在医院，床和椅子压力传感器非常常见，因为大多数跌倒发生在患者试图下床尝试使用厕所时。尽管它们被广泛使用，但其他研究表明，床和椅子压力传感器并不能防止医院跌倒。

“床和椅子压力传感器的一个主要问题是大量错误警报可能导致‘警报疲劳’，从而导致响应延迟，”博丁说。“有了这个系统，没有检测到跌倒，只有 0.2% 的警报是误报。我们还分析了从 1 秒到近 10 分钟不等的护士响应时间，发现护士响应时间的中位数为 24 秒。”

护士对床和椅子压力传感器的响应时间尚未公布，研究人员也没有参与单位的历史响应时间。

“但是，我们的工作人员认为，与使用床和椅子警报器等相比，响应时间有所提高，因为警报通知包括房间号，针对 3 位最近的临床工作人员，并直接通知护士而不是通过护士站间接通知”摩尔说。

该研究小组还包括与俄亥俄州立大学生物统计学中心和 维克森林医学院的合作者。

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