Using a Medical Intranet of Things System to Prevent Bed Falls in an Acute Care Hospital: A Pilot Study

Nurses' Perceptions of Telemonitoring Devices to Reduce Falls Among Hospitalized Patients: A Literature Review

PURPOSE

Technological advances have led to the adoption of telemonitoring devices for fall prevention. Multiple previous studies looked at the effectiveness of these devices. However, few studies looked at nursing staff perceptions of the technology. The current integrated literature review examined factors that influence nurses' and nursing staff's acceptance of telemonitoring technology for fall prevention.

METHOD

Three databases (CINAHL, Embase, and PubMed) were searched from January 2010 through September 2023. Study themes were analyzed, and study quality was appraised. Thirteen articles were identified and analyzed.

RESULTS

Nurses' perceptions included positive, negative, and mixed views of tele-monitoring technology. Key factors influencing staff perceptions of telemonitoring technology include the effectiveness of the technology at improving patient safety, its ease of use, and the degree to which staff felt supported by nursing leadership and hospital administration.

CONCLUSION

Findings demonstrate the importance of involving nurses in decisions regarding implementation of new technology. [Journal of Gerontological Nursing, 50(4), 6-10.].

Design and Implementation of an Inpatient Fall Risk Management Information System

BACKGROUND

Falls had been identified as one of the nursing-sensitive indicators for nursing care in hospitals. With technological progress, health information systems make it possible for health care professionals to manage patient care better. However, there is a dearth of research on health information systems used to manage inpatient falls.

OBJECTIVE

This study aimed to design and implement a novel hospital-based fall risk management information system (FRMIS) to prevent inpatient falls and improve nursing quality.

METHODS

This implementation was conducted at a large academic medical center in central China. We established a nurse-led multidisciplinary fall prevention team in January 2016. The hospital's fall risk management problems were summarized by interviewing fall-related stakeholders, observing fall prevention workflow and post-fall care process, and investigating patients' satisfaction. The FRMIS was developed using an iterative design process, involving collaboration among health care professionals, software developers, and system architects. We used process indicators and outcome indicators to evaluate the implementation effect.

RESULTS

The FRMIS includes a fall risk assessment platform, a fall risk warning platform, a fall preventive strategies platform, fall incident reporting, and a tracking improvement platform. Since the implementation of the FRMIS, the inpatient fall rate was significantly lower than that before implementation (P<.05). In addition, the percentage of major fall-related injuries was significantly lower than that before implementation. The implementation rate of fall-related process indicators and the reporting rate of high risk of falls were significantly different before and after system implementation (P<.05).

CONCLUSIONS

The FRMIS provides support to nursing staff in preventing falls among hospitalized patients while facilitating process control for nursing managers.

ROMI: A Real-Time Optical Digit Recognition Embedded System for Monitoring Patients in Intensive Care Units

With advances in the Internet of Things, patients in intensive care units are constantly monitored to expedite emergencies. Due to the COVID-19 pandemic, non-face-to-face monitoring has been required for the safety of patients and medical staff. A control center monitors the vital signs of patients in ICUs. However, some medical devices, such as ventilators and infusion pumps, operate in a standalone fashion without communication capabilities, requiring medical staff to check them manually. One promising solution is to use a robotic system with a camera. We propose a real-time optical digit recognition embedded system called ROMI. ROMI is a mobile robot that monitors patients by recognizing digits displayed on LCD screens of medical devices in real time. ROMI consists of three main functions for recognizing digits: digit localization, digit classification, and digit annotation. We developed ROMI by using Matlab Simulink, and the maximum digit recognition performance was 0.989 mAP on alexnet. The developed system was deployed on NVIDIA GPU embedded platforms: Jetson Nano, Jetson Xavier NX, and Jetson AGX Xavier. We also created a benchmark by evaluating the runtime performance by considering ten pre-trained CNN models and three NVIDIA GPU platforms. We expect that ROMI will support medical staff with non-face-to-face monitoring in ICUs, enabling more effective and prompt patient care.

Real-Time Internet of Medical Things System for Detecting Blood Leakage during Hemodialysis Using a Novel Multiple Concentric Ring Sensor

Venous needle dislodgement (VND) is a major healthcare safety concern in patients undergoing hemodialysis. Although VND is uncommon, it can be life-threatening. The main objective of this study was to implement a real-time multi-bed monitoring system for VND by combining a novel leakage-detection device and IoMT (Internet of Medical Things) technology. The core of the system, the Acusense IoMT platform, consisted of a novel leakage-detection patch comprised of multiple concentric rings to detect blood leakage and quantify the leaked volume. The performance of the leakage-detection system was evaluated on a prosthetic arm and clinical study. Patients with a high risk of blood leakage were recruited as candidates. The system was set up in a hospital, and the subjects were monitored for 2 months. During the pre-clinical simulation experiment, the system could detect blood leakage volumes from 0.3 to 0.9 mL. During the test of the IoMT system, the overall success rate of tests was 100%, with no lost data packets. A total of 701 dialysis sessions were analyzed, and the accuracy and sensitivity were 99.7% and 90.9%, respectively. Evaluation questionnaires showed that the use of the system after training changed attitudes and reduced worry of the nursing staff. Our results show the feasibility of using a novel detector combined with an IoMT system to automatically monitor multi-bed blood leakage. The innovative concentric-circle design could more precisely control the warning blood-leakage threshold in any direction to achieve clinical cost-effectiveness. The system reduced the load on medical staff and improved patient safety. In the future, it could also be applied to home hemodialysis for telemedicine during the era of COVID-19.

Internet of things in healthcare for patient safety: an empirical study

Introduction

This study evaluates the impact of an Internet of Things (IoT) intervention in a hospital unit and provides empirical evidence on the effects of smart technologies on patient safety (patient falls and hand hygiene compliance rate) and staff experiences.

Method

We have conducted a post-intervention analysis of hand hygiene (HH) compliance rate, and a pre-and post-intervention interrupted time-series (ITS) analysis of the patient falls rates. Lastly, we investigated staff experiences by conducting semi-structured open-ended interviews based on Roger’s Diffusion of Innovation Theory.

Results

The results showed that (i) there was no statistically significant change in the mean patient fall rates. ITS analysis revealed non-significant incremental changes in mean patient falls (− 0.14 falls/quarter/1000 patient-days). (ii) HH compliance rates were observed to increase in the first year then decrease in the second year for all staff types and room types. (iii) qualitative interviews with the nurses reported improvement in direct patient care time, and a reduced number of patient falls.

Conclusion

This study provides empirical evidence of some positive changes in the outcome variables of interest and the interviews with the staff of that unit reported similar results as well. Notably, our observations identified behavioral and environmental issues as being particularly important for ensuring success during an IoT innovation implementation within a hospital setting.

PUP® (Patient Is Up) Smart Sock Technology Prevents Falls Among Hospital Patients With High Fall Risk in a Clinical Trial and Observational Study

Hospital inpatient falls, especially of older adult patients, can result in injury and death and generate high costs. A new technology, PUP^® (Patient Is Up) Smart Socks, combines sensors and geolocation in socks with a wireless platform. To determine whether these socks prevent falls of patients with high fall risk, we performed a clinical trial at one hospital, and an observational study at two other hospitals. In the clinical trial, patients spent 1,694 patient-days wearing the socks, reducing falls from 4 to 0 per 1,000 patient-days (p < 0.01). In the observational study, patients spent 2,286 patient-days wearing the socks, reducing falls from 4 to 1.3 per 1,000 patient-days (p < 0.05). The new technology resulted in a significant reduction in fall rates among patients with high fall risk and may greatly reduce inpatient fall-related injury and death and their associated costs. [Journal of Gerontological Nursing, 47(10), 37-43.].

Effectiveness of an integrated three-mode bed exit alarm system in reducing inpatient falls within an acute care setting

AIM

To examine the effectiveness of an integrated three-mode bed exit alarm system in reducing inpatient falls within an acute care hospital setting in Singapore.

METHOD

A retrospective before-and-after study design was adopted.

RESULTS

Our results revealed that the use of bed exit alarms are associated with a reduction in falls incidence.

CONCLUSION

Bed exit alarm systems are associated with reduced fall incidence. Nonetheless, for an institution to benefit from the technology, there will be a need to take into account the effects of "alarm fatigue", ability of nurses to respond in time to alarms, and selection of right alarm mode/limits based on the patient's profile.

Preventing Falls in Hospitalized Patients: State of the Science

Falls in hospitalized patients are a pressing patient safety concern, but there is a limited body of evidence demonstrating the effectiveness of commonly used fall prevention interventions in hospitals. This article reviews common study designs and the evidence for various hospital fall prevention interventions. There is a need for more rigorous research on fall prevention in the hospital setting.

Laboratory Environment Monitoring: Implementation Experience and Field Study in a Tertiary General Hospital

Objectives

To successfully introduce an Internet of Things (IoT) system in the hospital environment, this study aimed to identify issues that should be considered while implementing an IoT based on a user demand survey and practical experiences in implementing IoT environment monitoring systems.

Methods

In a field test, two types of IoT monitoring systems (on-premises and cloud) were used in Department of Laboratory Medicine and tested for approximately 10 months from June 16, 2016 to April 30, 2017. Information was collected regarding the issues that arose during the implementation process.

Results

A total of five issues were identified: sensing and measuring, transmission method, power supply, sensor module shape, and accessibility.

Conclusions

It is expected that, with sufficient consideration of the various issues derived from this study, IoT monitoring systems can be applied to other areas, such as device interconnection, remote patient monitoring, and equipment/environmental monitoring.