Bed-exit alarm effectiveness

Alarm with care-a de-implementation strategy to reduce fall prevention alarm use in US hospitals: a study protocol for a hybrid 2 effectiveness-implementation trial

BACKGROUND

Fall prevention alarms are commonly used among US hospitals as a fall prevention strategy despite limited evidence of effectiveness. Further, fall prevention alarms are harmful to healthcare staff (e.g., alarm fatigue) and patients (e.g., sleep disturbance, mobility restriction). There is a need for research to develop and test strategies for reducing use of fall prevention alarms in US hospitals.

METHODS

To address this gap, we propose testing the effectiveness and implementation of Alarm with Care, a de-implementation strategy to reduce fall prevention alarm use using a stepped-wedge randomized controlled trial among 30 adult medical or medical surgical units from nonfederal US acute care hospitals. Guided by the Choosing Wisely De-Implementation Framework, we will (1) identify barriers to fall prevention alarm de-implementation and develop tailored de-implementation strategies for each unit and (2) compare the implementation and effectiveness of high- versus low-intensity coaching to support site-specific de-implementation of fall prevention alarms. We will evaluate effectiveness and implementation outcomes and examine the effect of multi-level (e.g., hospital, unit, and patient) factors on effectiveness and implementation. Rate of fall prevention alarm use is the primary outcome. Balancing measures will include fall rates and fall-related injuries. Implementation outcomes will include feasibility, acceptability, appropriateness, and fidelity.

DISCUSSION

Findings from this line of research could be used to support scale-up of fall prevention alarm de-implementation in other healthcare settings. Further, research generated from this proposal will advance the field of de-implementation science by determining the extent to which low-intensity coaching is an effective and feasible de-implementation strategy.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT06089239 . Date of registration: October 17, 2023.

Novel interventions significantly reduce falls with fractures: A meta-analysis and systematic review

INTRODUCTION

Worldwide, falls lead to possible complications such as prolonged hospitalization, prolonged bed rest, pressure injuries, fractures and mortality.

AIMS

The study aimed to evaluate the effectiveness of novel fall prevention strategies that utilized technology in preventing falls.

METHODS

The meta-analysis and systematic review was guided by the Cochrane guidelines for systematic reviews of interventions. The authors searched databases for specified keywords.

RESULTS

A total of 22 studies were included. Interventions included multi-modal fall prevention interventions, camera surveillance, motion sensors and bed/chair exit alarms. Video monitoring was equivocal in reducing fall rates. Exit alarms statistically significantly reduce falls between groups but not within groups. The interventions were not statistically significant in reducing falls with minor injuries but they were statistically significant in reducing falls with serious injuries including fractures.

CONCLUSION

A comprehensive fall prevention care plan, rather than one specific intervention, is necessary to prevent falls effectively.

Deriving Multiple-Layer Information from a Motion-Sensing Mattress for Precision Care

Bed is often the personal care unit in hospitals, nursing homes, and individuals' homes. Rich care-related information can be derived from the sensing data from bed. Patient fall is a significant issue in hospitals, many of which are related to getting in and/or out of bed. To prevent bed falls, a motion-sensing mattress was developed for bed-exit detection. A machine learning algorithm deployed on the chip in the control box of the mattress identified the in-bed postures based on the on/off pressure pattern of 30 sensing areas to capture the users' bed-exit intention. This study aimed to explore how sleep-related data derived from the on/off status of 30 sensing areas of this motion-sensing mattress can be used for multiple layers of precision care information, including wellbeing status on the dashboard and big data analysis for living pattern clustering. This study describes how multiple layers of personalized care-related information are further derived from the motion-sensing mattress, including real-time in-bed/off-bed status, daily records, sleep quality, prolonged pressure areas, and long-term living patterns. Twenty-four mattresses and the smart mattress care system (SMCS) were installed in a dementia nursing home in Taiwan for a field trial. Residents' on-bed/off-bed data were collected for 12 weeks from August to October 2021. The SMCS was developed to display care-related information via an integrated dashboard as well as sending reminders to caregivers when detecting events such as bed exits and changes in patients' sleep and living patterns. The ultimate goal is to support caregivers with precision care, reduce their care burden, and increase the quality of care. At the end of the field trial, we interviewed four caregivers for their subjective opinions about whether and how the SMCS helped their work. The caregivers' main responses included that the SMCS helped caregivers notice the abnormal situation for people with dementia, communicate with family members of the residents, confirm medication adjustments, and whether the standard care procedure was appropriately conducted. Future studies are suggested to focus on integrated care strategy recommendations based on users' personalized sleep-related data.

Dissonance Between Human Nurses And Technology: Understanding Nurses’ Experience Using Technology Beds With Monitoring Functions Within Clinical Nursing Practice

Aims:

Are nurses adapting to the mechanized nursing practice environment? Is it possible for nurses to collaborate with technology to provide care to patients? The aim of the study is to investigate what nurses feel about using technology in nursing practice.

Background:

Preventing patients from falling is one of the nursing tasks that can be helped by using technology, such as sensors. However, little is known about how nurses experience and feel the use of technological beds for monitoring functionality within clinical nursing practice. Especially it is indicated that alarm fatigue makes nurses and patients fatigued and induces a dissonance between nurses and technology.

Objective:

To clarify the experiences of nurses in clinical practice following the introduction of a bed with monitoring and fall prevention technology (technology bed).

Methods:

We interviewed 12 nurses working at a hospital about their nursing practice experiences with the technology bed.

Results:

The content of the interview was classified into three categories: ‘providing a safe environment’, ‘limitation of entry into machine care scenes’, and ‘nurses’ dilemmas’; with eight themes describing nursing practice: (1) strategies of fall prevention, (2) decrease in nurses’ burden, (3) not good at using technology (all tools must be easy to use), (4) inefficiency such as over-engineering, (5) patients feel annoyed by frequent visits from nurses, (6) limitations of utilization from a nursing perspective, (7) nurse resistance to equipment introduction and (8) ethical issues.

Conclusion:

Although technology beds could effectively prevent falls, many nurses face an ethical dilemma in using these beds. It would be important for nurses to recognize the role of technology, embrace it, and raise awareness of collaborating with technology to eliminate a dissonance between technology and nurses.

A Night-Time Monitoring System (eNightLog) to Prevent Elderly Wandering in Hostels: A Three-Month Field Study

Older people are increasingly dependent on others to support their daily activities due to geriatric symptoms such as dementia. Some of them stay in long-term care facilities. Elderly people with night wandering behaviour may lose their way, leading to a significant risk of injuries. The eNightLog system was developed to monitor the night-time bedside activities of older people in order to help them cope with this issue. It comprises a 3D time-of-flight near-infrared sensor and an ultra-wideband sensor for detecting human presence and to determine postures without a video camera. A threshold-based algorithm was developed to classify different activities, such as leaving the bed. The system is able to send alarm messages to caregivers if an elderly user performs undesirable activities. In this study, 17 sets of eNightLog systems were installed in an elderly hostel with 17 beds in 9 bedrooms. During the three-month field test, 26 older people with different periods of stay were included in the study. The accuracy, sensitivity and specificity of detecting non-assisted bed-leaving events was 99.8%, 100%, and 99.6%, respectively. There were only three false alarms out of 2762 bed-exiting events. Our results demonstrated that the eNightLog system is sufficiently accurate to be applied in the hostel environment. Machine learning with instance segmentation and online learning will enable the system to be used for widely different environments and people, with improvements to be made in future studies.

Night-Time Monitoring System (eNightLog) for Elderly Wandering Behavior

Wandering is a common behavioral disorder in the community-dwelling elderly. More than two-thirds of caregivers believe that wandering would cause falls. While physical restraint is a common measure to address wandering, it could trigger challenging behavior in approximately 80% of the elderly with dementia. This study aims to develop a virtual restraint using a night monitoring system (eNightLog) to provide a safe environment for the elderly and mitigate the caregiver burden. The eNightLog system consisted of remote sensors, including a near infra-red 3D time-of-flight sensor and ultrawideband sensors. An alarm system was controlled by customized software and algorithm based on the respiration rate and body posture of the elderly. The performance of the eNightLog system was evaluated in both single and double bed settings by comparing to that of a pressure mat and an infrared fence system, under simulated bed-exiting scenarios. The accuracy and precision for the three systems were 99.0%, 98.8%, 85.9% and 99.2%, 97.8%, 78.6%, respectively. With higher accuracy, precision, and a lower false alarm rate, eNightLog demonstrated its potential as an alternative to physical restraint to remedy the workload of the caregivers and the psychological impact of the elderly.

Technology Utilization in Fall Prevention

ABSTRACT

Falls, defined as unplanned descents to the floor with or without injury to an individual, remain to be one of the most challenging health conditions. Fall rate is a key quality metric of acute care hospitals, rehabilitation settings, and long-term care facilities. Fall prevention policies with proper implementation have been the focus of surveys by regulatory bodies, including The Joint Commission and the Centers for Medicare and Medicaid Services, for all healthcare settings. Since October 2008, the Centers for Medicare and Medicaid Services has stopped reimbursing hospitals for the costs related to patient falls, shifting the accountability for fall prevention to the healthcare providers. Research shows that almost one-third of falls can be prevented and extensive fall prevention interventions exist. Recently, technology-based applications have been introduced in healthcare to obtain superior patient care outcomes and experience via efficiency, access, and reliability. Several areas in fall prevention deploy technology, including predictive and prescriptive analytics using big data, video monitoring and alarm technology, wearable sensors, exergame and virtual reality, robotics in home environment assessment, and personal coaching. This review discusses an overview of these technology-based applications in various settings, focusing on the outcomes of fall reductions, cost, and other benefits.

Mobilisation alarm triggers, response times and utilisation before and after the introduction of policy for alarm reduction or elimination: A descriptive and comparative analysis

BACKGROUND

Mobilisation alarms are a falls prevention strategy used in hospitals to alert staff when an at risk patient is attempting to mobilise. Mobilisation alarms have an estimated annual cost of $AUD58MIL in Australia. There is growing evidence from randomised controlled trials indicating mobilisation alarms are unlikely to prevent falls.

AIM

The primary aim of this study was to describe the rate of mobilisation alarm false triggers and staff response time across different health services. The secondary aim was to compare pre to post mobilisation alarm utilisation following the introduction of policy to reduce or eliminate mobilisation alarms.

METHODS

This descriptive and comparative study was conducted through Monash Partners Falls Alliance across six health services in Melbourne, Australia. This study described true and false alarm triggers and trigger response times across three health services and usual care mobilisation alarm utilisation across six health services; and then compared alarm utilisation across two health services following the introduction of policy to reduce (<2.5%) or eliminate (0.0%) mobilisation alarms in the acute and rehabilitation settings.

RESULTS

The most frequent observation was a false alarm (n = 74, 52%), followed by a true alarm (n = 67, 47%) and no alarm (n = 3, 2%). Time to respond to the true and false alarms was an average of 37 seconds (SD 92) and this included 61 occasions of 0 seconds as a member of staff was present when the alarm triggered. If the 61 occasions of staff being present when the alarm triggered were removed, the average time to respond was 65 seconds (SD114). Usual care mobilisation alarm utilisation in acute was 7% (n = 171/2,338) and in rehabilitation was 11% (n = 286/2,623). Introducing policy for reduced and eliminated mobilisation alarm conditions was successful with a reduced utilisation rate of 1.8% (n = 11/609) and an eliminated utilisation rate of 0.0% (n = 0/521).

CONCLUSION

Half of mobilisation alarm triggers are false and when alarms trigger without staff present, staff take about a minute to respond. While usual care has one in fourteen patients in acute and one in nine patients in rehabilitation using a mobilisation alarm, it is possible to introduce policy which will change practice to reduce or eliminate the use of mobilisation alarms, providing evidence of feasibility for future disinvestment effectiveness studies that it is feasible to disinvest in the alarms.

A Data-Driven Human Activity Classification Method for an Intelligent Hospital Bed

Bedridden patients always need more attention in order to prevent unexpected falling, bedsores and other dangerous situations in daily care. This work proposes a data-driven classification method to recognize different bed-related human activities including exiting the bed, turning over, stretching out for something on the bedside table, sitting up and lying down by analyzing the real-time signals that are acquired from four load cells installed around the hospital bed. Considering the dynamic characteristics of the signals, dynamic principal component analysis (DPCA), here serving as a pre-processing step, is firstly utilized to extract both static and dynamic relations from the variables. Then the final statistical model for each class is established by Gaussian mixture model (GMM) with Figueiredo-Jain algorithm that can optimally select the number of components. An alarm will be triggered when a noteworthy action is detected. The proposed method has achieved superior performance using the experimental data from 10 adult volunteers. The results move a step forward towards the design of an intelligent hospital bed for practical applications.

Semi-Automatic Calibration Method for a Bed-Monitoring System Using Infrared Image Depth Sensors

With the aging of society, the number of fall accidents has increased in hospitals and care facilities, and some accidents have happened around beds. To help prevent accidents, mats and clip sensors have been used in these facilities but they can be invasive, and their purpose may be misinterpreted. In recent years, research has been conducted using an infrared-image depth sensor as a bed-monitoring system for detecting a patient getting up, exiting the bed, and/or falling; however, some manual calibration was required initially to set up the sensor in each instance. We propose a bed-monitoring system that retains the infrared-image depth sensors but uses semi-automatic rather than manual calibration in each situation where it is applied. Our automated methods robustly calculate the bed region, surrounding floor, sensor location, and attitude, and can recognize the spatial position of the patient even when the sensor is attached but unconstrained. Also, we propose a means to reconfigure the spatial position considering occlusion by parts of the bed and also accounting for the gravity center of the patient’s body. Experimental results of multi-view calibration and motion simulation showed that our methods were effective for recognition of the spatial position of the patient.

A systematic review of electronic assistive technology within supporting living environments for people with dementia

Health and social care provision needs to change in order to meet the needs of an increase in the number of people living with dementia. Environmental design, technology and assistive devices have the potential to complement care, help address some of the challenges presented by this growing need and impact on the lived experience of this vulnerable population. This systematic review was undertaken to identify the research on the use of electronic assistive technology within long-term residential care settings. A total of 3229 papers published from the inception of each of the databases up until May 2016 were retrieved from searches in four major databases. Sixty-one were identified to be included in the review. The inclusion criteria were: original peer reviewed journals; an electronic assistive technology intervention; with residents or tenants living with dementia or their family or paid caregivers; in supported living environments or residential care. The data extracted from the included studies focused on the methodology, technology, outcomes and the role of people living with dementia within the research. Overall, an extensive variety of technical interventions were found, with a broad range of methodological heterogeneity to explore their effect. Additionally, wide-spanning outcomes to support the potential of technology solutions and the challenges presented by such intervention were found.

An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment

The lack of healthcare staff and increasing proportions of elderly population is alarming. The traditional means to look after elderly has resulted in 255,000 reported falls (only within UK). This not only resulted in extensive aftercare needs and surgeries (summing up to £4.4 billion) but also in added suffering and increased mortality. In such circumstances, the technology can greatly assist by offering automated solutions for the problem at hand. The proposed work offers an Internet of things (IoT) based patient bed-exit monitoring system in clinical settings, capable of generating a timely response to alert the healthcare workers and elderly by analyzing the wireless data streams, acquired through wearable sensors. This work analyzes two different datasets obtained from divergent families of sensing technologies, i.e., smartphone-based accelerometer and radio frequency identification (RFID) based accelerometer. The findings of the proposed system show good efficacy in monitoring the bed-exit and discriminate other ambulating activities. Furthermore, the proposed work manages to keep the average end-to-end system delay (i.e., communications of sensed data to Data Sink (DS)/Control Center (CC) + machine-based feature extraction and class identification + feedback communications to a relevant healthcare worker/elderly) below 1 10 th of a second.

Alarming and/or Alerting Device Effectiveness in Reducing Falls in Long-Term Care (LTC) Facilities? A Systematic Review

Perceptions against the use of alarming devices persist in long-term care environments as they are seen as annoying, costly, and a waste of time to the staff involved. Ascertaining whether these perceptions are true or false via the literature was a focus of this study. Proper information to educate staff and to work past these perceptions can be a positive effector for resident safety. Many facilitators for the use of alarming devices were found, as well as many barriers to their use as well. New technology is changing the perceptions regarding these types of devices as time passes. Education is a key component for staff, residents, and families. There are “traditional” issues with the use of alarms such as alarm fatigue by caregivers, high costs of implementation, and issues with proper implementation of alarms. Alarms are perceived as intrusive and the noise from them can be a potential cause of falls. However, alarming devices can be a key intervention in the safety of those residents who are prone to falls. This requires proper implementation and education for all parties involved, and proper oversight surrounding use of the devices.

INBED: A Highly Specialized System for Bed-Exit-Detection and Fall Prevention on a Geriatric Ward

OBJECTIVE

In geriatric institutions, the risk of falling of patients is very high and frequently leads to fractures of the femoral neck, which can result in serious consequences and medical costs. With regard to the current numbers of elderly people, the need for smart solutions for the prevention of falls in clinical environments as well as in everyday life has been evolving.

METHODS

Hence, in this paper, we present the Inexpensive Node for bed-exit Detection (INBED), a comprehensive, favourable signaling system for bed-exit detection and fall prevention, to support the clinical efforts in terms of fall reduction. The tough requirements for such a system in clinical environments were gathered in close cooperation with geriatricians.

RESULTS

The conceptional efforts led to a multi-component system with a core wearable device, attached to the patients, to detect several types of movements such as rising, restlessness and-in the worst case-falling. Occurring events are forwarded to the nursing staff immediately by using a modular, self-organizing and dependable wireless infrastructure. Both, the hardware and software of the entire INBED system as well as the particular design process are discussed in detail. Moreover, a trail test of the system is presented.

CONCLUSIONS

The INBED system can help to relieve the nursing staff significantly while the personal freedom of movement and the privacy of patients is increased compared to similar systems.

A battery-less and wireless wearable sensor system for identifying bed and chair exits in a pilot trial in hospitalized older people

Falls in hospitals are common, therefore strategies to minimize the impact of these events in older patients and needs to be examined. In this pilot study, we investigate a movement monitoring sensor system for identifying bed and chair exits using a wireless wearable sensor worn by hospitalized older patients. We developed a movement monitoring sensor system that recognizes bed and chair exits. The system consists of a machine learning based activity classifier and a bed and chair exit recognition process based on an activity score function. Twenty-six patients, aged 71 to 93 years old, hospitalized in the Geriatric Evaluation and Management Unit participated in the supervised trials. They wore over their attire a battery-less, lightweight and wireless sensor and performed scripted activities such as getting off the bed and chair. We investigated the system performance in recognizing bed and chair exits in hospital rooms where RFID antennas and readers were in place. The system’s acceptability was measured using two surveys with 0–10 likert scales. The first survey measured the change in user perception of the system before and after a trial; the second survey, conducted only at the end of each trial, measured user acceptance of the system based on a multifactor sensor acceptance model. The performance of the system indicated an overall recall of 81.4%, precision of 66.8% and F-score of 72.4% for joint bed and chair exit recognition. Patients demonstrated improved perception of the system after use with overall score change from 7.8 to 9.0 and high acceptance of the system with score ≥ 6.7 for all acceptance factors. The present pilot study suggests the use of wireless wearable sensors is feasible for detecting bed and chair exits in a hospital environment.

Traumatic Facial Injuries Among Elderly Nursing Home Residents: Never Event or Frequent Occurrence?

Importance

As the nursing home population continues to increase, an understanding of preventable injuries becomes exceedingly important. Although other fall-related injuries have been characterized, little attention has been dedicated to facial trauma.

Objectives

To estimate the incidence of facial trauma among nursing home residents and detail mechanisms of injury, injury characteristics, and patient demographic data.

Design, Setting, and Participants

The National Electronic Injury Surveillance System was used to calculate a weighted national incidence of facial trauma among individuals older than 60 years from a nationally representative collection of emergency departments from January 1, 2011, through December 31, 2015. Entries were screened for nursing home residents, and diagnosis, anatomical site, demographic data, and mechanism of injury were analyzed.

Results

There were 109 795 nursing home residents (median age, 84.1 years; interquartile range, 79-89 years; 71 466 women [65.1%]) who required emergency department care for facial trauma. Women sustained a greater proportion of injuries with increasing age. The most common injuries were lacerations (48 679 [44.3%]), other soft-tissue injuries (45 911 [41.8%]; avulsions, contusions, and hematomas), and fractures (13 814 [12.6%]). Nasal (9331 [67.5%]) and orbital (1144 [8.3%]) fractures were the most common sites. The most common injury causes were direct contact with structural housing elements or fixed items (62 604 [57.0%]) and transfer to and from bed (24 870 [22.6%]).

Conclusions and Relevance

Despite falls being considered a Centers for Medicare & Medicaid Services preventable never event in hospitals, our analysis in the nursing home setting found more than 100 000 facial injuries during 5 years, suggesting these underappreciated injuries contribute substantially to health care expenditures. Although structural elements facilitated the greatest number of falls, transfer to and from bed remains a significant mechanism, suggesting an area for intervention.

Effectiveness of an Ambient Intelligent Geriatric Management system (AmbIGeM) to prevent falls in older people in hospitals: protocol for the AmbIGeM stepped wedge pragmatic trial

Background

Although current best practice recommendations contribute to falls prevention in hospital, falls and injury rates remain high. There is a need to explore new interventions to reduce falls rates, especially in geriatric and general medical wards where older patients and those with cognitive impairment are managed.

Design and methods

A three-cluster stepped wedge pragmatic trial, with an embedded qualitative process, of the Ambient Intelligent Geriatric Management (AmbIGeM) system (wearable sensor device to alert staff of patients undertaking at-risk activities), for preventing falls in older patients compared with standard care. The trial will occur on three acute/subacute wards in two hospitals in Adelaide and Perth, Australia.

Participants

Patients aged >65 years admitted to study wards. A waiver (Perth) and opt-out of consent (Adelaide) was obtained for this study. Patients requiring palliative care will be excluded.

Outcomes

The primary outcome is falls rate; secondary outcome measures are: (1) proportion of participants falling; (2) rate of injurious inpatient falls/1000 participant bed-days; (3) acceptability and safety of the interventions from patients and clinical staff perspectives; and (4) hospital costs, mortality and use of residential care to 3 months postdischarge.

Discussion

This study investigates a novel technological approach to preventing falls in hospitalised older people. We hypothesise that the AmbIGeM intervention will reduce falls and injury rates, with an economic benefit attributable to the intervention. If successful, the AmbIGeM system will be a useful addition to falls prevention in hospital wards with high proportions of older people and people with cognitive impairment.

Trial registration number

Australian and New Zealand Clinical Trial Registry: ACTRN 12617000981325; Pre-results.

Recognizing Bedside Events Using Thermal and Ultrasonic Readings

Falls in homes of the elderly, in residential care facilities and in hospitals commonly occur in close proximity to the bed. Most approaches for recognizing falls use cameras, which challenge privacy, or sensor devices attached to the bed or the body to recognize bedside events and bedside falls. We use data collected from a ceiling mounted 80 × 60 thermal array combined with an ultrasonic sensor device. This approach makes it possible to monitor activity while preserving privacy in a non-intrusive manner. We evaluate three different approaches towards recognizing location and posture of an individual. Bedside events are recognized using a 10-second floating image rule/filter-based approach, recognizing bedside falls with 98.62% accuracy. Bed-entry and exit events are recognized with 98.66% and 96.73% accuracy, respectively.

The Effectiveness of a Wireless Modular Bed Absence Sensor Device for Fall Prevention among Older Inpatients

Background

Falls and fall-related injuries are increasingly serious issues among elderly inpatients due to population aging. The bed-exit alarm has only previously been evaluated in a handful of studies with mixed results. Therefore, we evaluated the effectiveness of a modular bed absence sensor device (M-BAS) in detecting bed exits among older inpatients in a middle income nation in East Asia.

Methods

Patients aged ≥65 years on an acute geriatric ward who were able to mobilize with or without walking aids and physical assistance were recruited to the study. The total number of alarms and the numbers of true and false alarms were recorded by ward nurses. The M-BAS device is placed across the mattress of all consenting participants. Nurses’ workload was assessed using the National Aeronautics and Space Administration-Task Load Index (NASA-TLX) score, while nurses’ perceptions were surveyed.

Results

The sensitivity of the M-BAS was 100% with a positive predictive value of 68% and a nuisance alarm rate of 31%. There was a significant reduction in total NASA-TLX workload score (mean difference = 14.34 ± 13.96 SD, p < 0.001) at the end of the intervention period. 83% of the nurses found the device useful for falls prevention, 97% found it user friendly, and 87% would use it in future.

Conclusion

The M-BAS was able to accurately detect bed absence episodes among geriatric inpatients and alert nurses accordingly. The use of the device significantly reduced the total workload score, while the acceptability of the device was high among our nurses. A larger, cluster randomized study to measure actual falls outcome associated with the use of the device is now indicated.

US and Dutch nurse experiences with fall prevention technology within nursing home environment and workflow: A qualitative study

Falls remain a major geriatric problem, and the search for new solutions continues. We investigated how existing fall prevention technology was experienced within nursing home nurses' environment and workflow. Our NIH-funded study in an American nursing home was followed by a cultural learning exchange with a Dutch nursing home. We constructed two case reports from interview and observational data and compared the magnitude of falls, safety cultures, and technology characteristics and effectiveness. Falls were a high-magnitude problem at the US site, with a collectively vigilant safety culture attending to non-directional audible alarms; falls were a low-magnitude problem at the NL site which employed customizable, infrared sensors that directed text alerts to assigned staff members' mobile devices in patient-centered care culture. Across cases, 1) a coordinated communication system was essential in facilitating effective fall prevention alert response, and 2) nursing home safety culture is tightly associated with the chosen technological system.

Effectiveness of a Batteryless and Wireless Wearable Sensor System for Identifying Bed and Chair Exits in Healthy Older People

Aging populations are increasing worldwide and strategies to minimize the impact of falls on older people need to be examined. Falls in hospitals are common and current hospital technological implementations use localized sensors on beds and chairs to alert caregivers of unsupervised patient ambulations; however, such systems have high false alarm rates. We investigate the recognition of bed and chair exits in real-time using a wireless wearable sensor worn by healthy older volunteers. Fourteen healthy older participants joined in supervised trials. They wore a batteryless, lightweight and wireless sensor over their attire and performed a set of broadly scripted activities. We developed a movement monitoring approach for the recognition of bed and chair exits based on a machine learning activity predictor. We investigated the effectiveness of our approach in generating bed and chair exit alerts in two possible clinical deployments (Room 1 and Room 2). The system obtained recall results above 93% (Room 2) and 94% (Room 1) for bed and chair exits, respectively. Precision was >78% and 67%, respectively, while F-score was >84% and 77% for bed and chair exits, respectively. This system has potential for real-time monitoring but further research in the final target population of older people is necessary.

Feasibility, acceptability, and effectiveness of an electronic sensor bed/chair alarm in reducing falls in patients with cognitive impairment in a subacute ward

Falls from bed are common in subacute hospital settings, particularly for patients with cognitive impairment. This repeated measures, single cohort study in 1 subacute ward evaluated effectiveness of an electronic sensor alarm in reducing falls in patients (n = 34) with cognitive impairment. Nursing staff feedback (focus group, survey) was used to determine electronic sensor alarm feasibility. The electronic alarm system was found to be a feasible, effective, and acceptable fall prevention strategy for patients with cognitive impairment.

Detection of patient's bed statuses in 3D using a Microsoft Kinect

Patients spend the vast majority of their hospital stay in an unmonitored bed where various mobility factors can impact patient safety and quality. Specifically, bed positioning and a patient's related mobility in that bed can have a profound impact on risks such as pneumonias, blood clots, bed ulcers and falls. This issue has been exacerbated as the nurse-per-bed (NPB) ratio has decreased in recent years. To help assess these risks, it is critical to monitor a hospital bed's positional status (BPS). Two bed positional statuses, bed height (BH) and bed chair angle (BCA), are of critical interests for bed monitoring. In this paper, we develop a bed positional status detection system using a single Microsoft Kinect. Experimental results show that we are able to achieve 94.5% and 93.0% overall accuracy of the estimated BCA and BH in a simulated patient's room environment.

Development and pilot study of a bed-exit alarm based on a body-worn accelerometer

BACKGROUND

Falls are a major problem in hospitals and nursing homes. The consequences of falls can be severe, both for the individual and for the caring institution.

OBJECTIVE

The aim of the work presented here is to reduce the number of falls on a geriatric ward by monitoring patients more closely. To achieve this goal, a bed-exit alarm that reliably detects an attempt to get up has been constructed.

MATERIALS AND METHODS

A requirements analysis revealed the nurses' and physicians' needs and preferences. Based on the gathered information, an incremental design process generated different prototypes. These were tested for the reliability of their ability to detect attempts to get up in both laboratory settings and with geriatric patients. Based on the result of these tests, a scalable technical solution has been developed and proven its reliability in a 1-year, randomized controlled pilot clinical trial on a geriatric ward.

RESULTS

The developed system is unobtrusive and easy to deploy. It has been tested in laboratory settings, usability tests and a 1-year randomized clinical trial with 98 patients. This paper focuses on the technical development of the system. We present different prototypes, the experiments and the pilot study used to evaluate their performance. Last but not least, we discuss the lessons learned so far.

CONCLUSION

The developed bed-exit alarm is able to reliably detect patients' attempts to get up. The results of the clinical trial show that the system is able to reduce the number of falls on a geriatric ward. Next steps are the design of a specialized sensor node that is easier to use and can be applied on an even larger scale due to its reduced cost. A multicenter trial with a larger number of patients is required to confirm the results of this pilot study.

Low cost and batteryless sensor-enabled radio frequency identification tag based approaches to identify patient bed entry and exit posture transitions

INTRODUCTION

Falls in hospitals and residential care facilities commonly occur near the bed. The aim of this study was to investigate the accuracy of a continuously wearable, batteryless, low power and low cost monitoring device (Wearable Wireless Identification and Sensing Platform) with a single kinematic sensor capable of real-time monitoring to automatically detect bed entry and exit events.

MATERIALS AND METHODS

Three dimensional acceleration readings and the strength of the transmitted signal from the WISP was interpreted to identify bed exit events and sensitivity, specificity and Receiving Operator Curves (ROC) were determined.

RESULTS

The sensor located over sternum method performed best with sensitivity and specificity values of 92.8% and 97.5% respectively for detecting bed entry and values of 90.4% and 93.80% respectively for bed exit. On the other hand, the sensor-on-mattress algorithm achieved sensitivity and specificity values of 84.2% and 97.4% respectively for bed entry and 79% and 97.4% for bed exit detection.

CONCLUSION

The WISP located over the sternum method is the preferred method to detect bed entry and exit. However, further work in frail older people is required to confirm the performance of this method.

Quality improvement in nursing homes: testing of an alarm elimination program

Falls are the most common cause of injury deaths and nonfatal injuries in older adults. In an effort to detect a resident's movement, many nursing homes use bed or chair alarms to alert staff that the resident may get up and possibly fall. However, there is little evidence that bed or chair alarms prevent falls, and mounting evidence that alarms can impede the functional status and negatively impact feelings of dignity among older adults in nursing homes. The purpose of this article was to describe the development and pilot testing of an alarm elimination program for nursing homes. A program aimed at decreasing or eliminating the use of alarms may enhance quality of life of older adults in nursing homes.

Effects of an intervention to increase bed alarm use to prevent falls in hospitalized patients: a cluster randomized trial

BACKGROUND

Bed alarm systems intended to prevent hospital falls have not been formally evaluated.

OBJECTIVE

To investigate whether an intervention aimed at increasing bed alarm use decreases hospital falls and related events.

DESIGN

Pair-matched, cluster randomized trial over 18 months. Nursing units were allocated by computer-generated randomization on the basis of baseline fall rates. Patients and outcome assessors were blinded to unit assignment; outcome assessors may have become unblinded. (ClinicalTrials.gov registration number: NCT00183053)

SETTING

16 nursing units in an urban community hospital.

PATIENTS

27 672 inpatients in general medical, surgical, and specialty units.

INTERVENTION

Education, training, and technical support to promote use of a standard bed alarm system (intervention units); bed alarms available but not formally promoted or supported (control units).

MEASUREMENTS

Pre-post difference in change in falls per 1000 patient-days (primary end point); number of patients who fell, fall-related injuries, and number of patients restrained (secondary end points).

RESULTS

Prevalence of alarm use was 64.41 days per 1000 patient-days on intervention units and 1.79 days per 1000 patient-days on control units (P = 0.004). There was no difference in change in fall rates per 1000 patient-days (risk ratio, 1.09 [95% CI, 0.85 to 1.53]; difference, 0.41 [CI, -1.05 to 2.47], which corresponds to a greater difference in falls in control vs. intervention units) or in the number of patients who fell, injurious fall rates, or the number of patients physically restrained on intervention units compared with control units.

LIMITATION

The study was conducted at a single site and was slightly underpowered compared with the initial design.

CONCLUSION

An intervention designed to increase bed alarm use in an urban hospital increased alarm use but had no statistically or clinically significant effect on fall-related events or physical restraint use.

PRIMARY FUNDING SOURCE

National Institute on Aging.

How feasible was a bed-height alert system?

This qualitative and descriptive study examined the feasibility of a bed-height alert system as a fall-prevention strategy. The alpha prototype was developed to measure and record bed height, and to remind staff to keep patient beds in the lowest position. This pilot project was conducted in a 52-bed adult acute surgical inpatient care unit of a Michigan community hospital. Qualitative and quantitative information was gathered during semistructured interviews of nursing staff (18 RNs and 13 PCAs; January-April 2011). Descriptive content analysis and descriptive analyses were performed. The overall response rate was 44.9%. The mean values of the feasibility questions are all favorable. Staff's comments also support the view that the alert system would promote patient safety and prevent falls. In short, this system was found to be somewhat useful, feasible, appropriate, and accurate. It has the potential to promote patient safety and prevent bed-associated injurious falls in inpatient care settings.

Interventions designed to prevent healthcare bed-related injuries in patients

BACKGROUND

Every patient in residential healthcare has a bed. Falling out of bed is associated with preventable patient harm. Various interventions to prevent injury are available. Bed rails are the most common intervention designed to prevent patients falling out of bed; however, their effectiveness is uncertain and bed rail entrapment can also result in injuries.

OBJECTIVES

To assess the effectiveness of interventions designed to prevent patient injuries and falls from their beds.

SEARCH METHODS

We searched the Cochrane Injuries Group Specialised Register, Cochrane Central Register of Controlled Trials 2010, Issue 2 (The Cochrane Library), MEDLINE (Ovid), EMBASE (Ovid), CINAHL (EBSCO), ISOI Web of Science and Web-based trials registers (all to December 2010) as well as reference lists.

SELECTION CRITERIA

Randomised controlled trials of interventions designed to prevent patient injuries from their beds which were conducted in hospitals, nursing care facilities or rehabilitation units were eligible for inclusion.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed the risk of bias and extracted data from the included studies. Authors contacted investigators to obtain missing information.

MAIN RESULTS

Two studies met the inclusion criteria, involving a total of 22,106 participants. One study tested low height beds and the other tested bed exit alarms. Both studies used standard care for their control group and both studies were conducted in hospitals. No study investigating bed rails met the inclusion criteria. Due to the clinical heterogeneity of the interventions in the included studies pooling of data and meta-analysis was inappropriate, and so the results of the studies are described.A single cluster randomised trial of low height beds in 18 hospital wards, including 22,036 participants, found no significant reduction in the frequency of patient injuries due to their beds (there were no injuries in either group), patient falls in the bedroom (rate ratio 0.69, 95% CI 0.35 to 1.34), all falls (rate ratio 1.26, 95% CI 0.83 to 1.90) or patient injuries due to all falls (rate ratio 1.35, 95% CI 0.68 to 2.68).One randomised controlled trial of bed exit alarms in one hospital geriatric ward, involving 70 participants, found no significant reduction in the frequency of patient injuries due to their beds (there were no injuries in either group), patient falls out of bed (rate ratio 0.25, 95% CI 0.03 to 2.24), all falls (rate ratio 0.42, 95% CI 0.15 to 1.18) or patient injuries due to all falls (no injuries in either group).

AUTHORS' CONCLUSIONS

The effectiveness of interventions designed to prevent patient injuries from their beds (including bed rails, low height beds and bed exit alarms) remains uncertain. The available evidence shows no significant increase or decrease in the rate of injuries with the use of low height beds and bed exit alarms. Limitations of the two included studies include lack of blinding and insufficient power. No randomised controlled trials of bed rails were identified. Future reports should fully describe the standard care received by the control group.

Elimination of position-change alarms in an Alzheimer's and dementia long-term care facility

In a long-term care facility, whose residents have been diagnosed with Alzheimer's disease or dementia, falls are a particularly prominent issue. Technology in health care has continued to evolve and play a larger role in how we care for our patients, even in preventing falls. However, overreliance on these types of technologies may have detrimental effects. In our facility, it was felt that staff reliance on position-change alarms was inappropriate due to the high rate of false alarms associated with these devices. We took a tiered approach to removing position-change alarms from our facility, monitoring the fall incidence rate for a period before, during, and after the elimination of these alarms. After discontinuing their use, we found a decrease in the rate of falls, and a decrease in the percentage of our residents who fell. Staff has easily adapted and reports a calmer, more pleasant environment.

Interventions designed to prevent healthcare bed-related injuries in patients

BACKGROUND

Every patient in residential healthcare has a bed. Falling out of bed is associated with preventable patient harm. Various interventions to prevent injury are available. Bed rails are the most common intervention designed to prevent patients falling out of bed; however, their effectiveness is uncertain and bed rail entrapment can also result in injuries.

OBJECTIVES

To assess the effectiveness of interventions designed to prevent patient injuries and falls from their beds.

SEARCH METHODS

We searched the Cochrane Injuries Group Specialised Register, Cochrane Central Register of Controlled Trials 2010, Issue 2 (The Cochrane Library), MEDLINE (Ovid), EMBASE (Ovid), CINAHL (EBSCO), ISOI Web of Science and Web-based trials registers (all to December 2010) as well as reference lists.

SELECTION CRITERIA

Randomised controlled trials of interventions designed to prevent patient injuries from their beds which were conducted in hospitals, nursing care facilities or rehabilitation units were eligible for inclusion.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed the risk of bias and extracted data from the included studies. Authors contacted investigators to obtain missing information.

MAIN RESULTS

Two studies met the inclusion criteria, involving a total of 22,106 participants. One study tested low height beds and the other tested bed exit alarms. Both studies used standard care for their control group and both studies were conducted in hospitals. No study investigating bed rails met the inclusion criteria. Due to the clinical heterogeneity of the interventions in the included studies pooling of data and meta-analysis was inappropriate, and so the results of the studies are described.A single cluster randomised trial of low height beds in 18 hospital wards, including 22,036 participants, found no significant reduction in the frequency of patient injuries due to their beds (there were no injuries in either group), patient falls in the bedroom (rate ratio 0.69, 95% CI 0.35 to 1.34), all falls (rate ratio 1.26, 95% CI 0.83 to 1.90) or patient injuries due to all falls (rate ratio 1.35, 95% CI 0.68 to 2.68).One randomised controlled trial of bed exit alarms in one hospital geriatric ward, involving 70 participants, found no significant reduction in the frequency of patient injuries due to their beds (there were no injuries in either group), patient falls out of bed (rate ratio 0.25, 95% CI 0.03 to 2.24), all falls (rate ratio 0.42, 95% CI 0.15 to 1.18) or patient injuries due to all falls (no injuries in either group).

AUTHORS' CONCLUSIONS

The effectiveness of interventions designed to prevent patient injuries from their beds (including bed rails, low height beds and bed exit alarms) remains uncertain. The available evidence shows no significant increase or decrease in the rate of injuries with the use of low height beds and bed exit alarms. Limitations of the two included studies include lack of blinding and insufficient power. No randomised controlled trials of bed rails were identified. Future reports should fully describe the standard care received by the control group.