Alarm Fatigue Research Articles

Preemptive listening: a roundtable discussion about sirens

ABSTRACT Nested within the crisis of our attention economy, the siren is undergoing a profound transformation, prompted by our ongoing alarm fatigue and noise pollution, as well as the near-obsolescence and inefficiency of public sound system broadcasts. Employing an interdisciplinary approach from specialists in the field of sound studies, behavioural psychology, policy advisors and creative practitioners, this roundtable article aims to unpack the critical potential of reimagining sirens, extending physically beyond ear-centred listening, conceptually beyond immediate timeframes, and opening up to new collaborative methodologies across academia, industry, artistic networks and more, to tackle today’s urgent need to recalibrate emergency signals for the immediate and the distant future.

Attention Among Health Care Professionals : A Scoping Review.

The concept of attention can provide insight into the needs of clinicians and how health systems design can impact patient care quality and medical errors. To conduct a scoping review to 1) identify and characterize literature relevant to clinician attention; 2) compile metrics used to measure attention; and 3) create a framework of key concepts. Cumulated Index to Nursing and Allied Health Literature (CINAHL), Medline (PubMed), and Embase (Ovid) from 2001 to 26 February 2024. English-language studies addressing health care worker attention in patient care. At least dual review and data abstraction. Article information, health care professional studied, practice environment, study design and intent, factor type related to attention, and metrics of attention used. Of 6448 screened articles, 585 met inclusion criteria. Most studies were descriptive (n = 469) versus investigational (n = 116). More studies focused on barriers to attention (n = 387; 342 descriptive and 45 investigational) versus facilitators to improving attention (n = 198; 112 descriptive and 86 investigational). We developed a framework, grouping studies into 6 categories: 1) definitions of attention, 2) the clinical environment and its effect on attention, 3) personal factors affecting attention, 4) relationships between interventions or factors that affect attention and patient outcomes, 5) the effect of clinical alarms and alarm fatigue on attention, and 6) health information technology's effect on attention. Eighty-two metrics were used to measure attention. Does not synthesize answers to specific questions. Quality of studies was not assessed. This overview may be a resource for researchers, quality improvement experts, and health system leaders to improve clinical environments. Future systematic reviews may synthesize evidence on metrics to measure attention and on the effectiveness of barriers or facilitators related to attention. None.

238 The effectiveness of alarm management bundle in reducing alarm fatigue and burnout among nurses

238 The effectiveness of alarm management bundle in reducing alarm fatigue and burnout among nurses

Machine learning model with output correction: Towards reliable bradycardia detection in neonates

Bradycardia is a commonly occurring condition in premature infants, often causing serious consequences and cardiovascular complications. Reliable and accurate detection of bradycardia events is pivotal for timely intervention and effective treatment. Excessive false alarms pose a critical problem in bradycardia event detection, eroding trust in machine learning (ML)-based clinical decision support tools designed for such detection. This could result in disregarding the algorithm’s accurate recommendations and disrupting workflows, potentially compromising the quality of patient care. This article introduces an ML-based approach incorporating an output correction element, designed to minimise false alarms. The approach has been applied to bradycardia detection in preterm infants. We applied five ML-based autoencoder techniques, using recurrent neural network (RNN), long-short-term memory (LSTM), gated recurrent unit (GRU), 1D convolutional neural network (1D CNN), and a combination of 1D CNN and LSTM. The analysis is performed on ∼440 hours of real-time preterm infant data. The proposed approach achieved 0.978, 0.73, 0.992, 0.671 and 0.007 in AUC-ROC, AUC-PRC, recall, F1 score, and false positive rate (FPR) respectively and a false alarms reduction of 36% when compared with methods without the correction approach. This study underscores the imperative of cultivating solutions that alleviate alarm fatigue and encourage active engagement among healthcare professionals.

Sacred breath: Ohio nurses respond to COVID-19

In the fall of 2021, the Wick Poetry Center, a recognized international leader in creative writing interventions, launched the website Sacred Breath: Voices of Ohio Nurses in Response to COVID-19 (sacredbreathproject.com) with funding from the Ohio Nurses Foundation. The purpose of the website was to offer Ohio nurses an accessible platform to reflect on their personal and professional lived experiences as caregivers during an historic time of pandemic, sacrifice, uncertainty, and scarcity, and to share their voice with others. What resulted was 204 submissions over a three-month period with participant responses touching on widespread sentiments including grief, fatigue, anger, and resilience. It was from the gap in the current literature on pandemic narratives that the researchers of this study began a basic qualitative thematic analysis of the Sacred Breath project website (SBP) responses to gain a better understanding of how nurses, nurse educators, and nursing students made sense of and gave voice to their personal and professional lived experiences during the ongoing COVID-19 pandemic.While stories of nursing during the Covid-19 pandemic have been widely available and disseminated by popular media, academic studies have been slower to utilize qualitative and experimental methods to specifically address pandemic narratives and the resulting discourses by nurses working in and around clinical settings. The Wick Poetry Center at Kent State University has spent nearly forty years working in the community to address urgent social needs using expressive writing methods that are often overlooked by traditional social and arts outreach. The Wick Poetry Center engaged local academic networks and community health partners to invite nurses, nursing students, and nurse educators the Sacred Breath Project By evaluating responses to the intervention website, this qualitative study is aimed to fill this gap in the current literature as well as begin to understand how nurses made sense of their work lives during the ongoing Covid-19 pandemic.What does this paper contribute to the wider global clinical community?What is already known:•The COVID-19 pandemic resulted in substantial increases of alarm fatigue, moral distress, and dysfunctional coping mechanisms among clinical nurses.•Art interventions positively impact mental health conditions in nurses.What this paper adds:•This review of the Sacred Breath thematic analysis broadens the understanding of how nurses made sense of their work lives during the Covid-19 pandemic.•This review creates a new discourse about the nursing profession in times of crisis—one cocreated by practitioners, educators, students, and creative intervention participants.

Contributors to fatigue among nurses working in critical care units: A qualitative study.

Fatigue is a growing concern among nurses who provide care to unstable and critically ill patients in critical care wards. It has various negative consequences for both nurses and patients. To explore and describe contributors to fatigue among nurses working in critical care units. A qualitative content analysis. Participants were 21 nurses chosen using purposeful sampling. They were working in different critical care units at different hospitals in nine urban areas of Iran. Semi-structured interviews were used to collect data, and conventional content analysis was used to develop categories and subcategories. The analysis of data on the nurses' perspectives and experiences led to developing nine categories as contributors to fatigue: 'compassion fatigue', 'extensive network of interactions', 'sound and alarm fatigue', 'psychological tensions', 'managerial and organizational tensions', 'lack of motivation and incentives', 'individual characteristics of nurses', 'physical and mental pressure', and requirements of special care and situational complexity'. Understanding the factors that influence the experience of fatigue among nurses working in critical care units is essential for maintaining a reliable and high-quality health care environment within health care facilities. The experience of fatigue by critical care nurses can increase the possibility of practice errors, reduce patient safety and quality of care, and enhance staff burnout and turnover. Proactive policies should be formulated to assess nurses' fatigue levels and implement strategies for effective fatigue management. This approach aims to enhance both patient safety and job satisfaction in the workplace.

Identifying the deficiencies of currently available CGM to improve uptake and benefit.

The use of diabetes technologies is increasing worldwide, with health systems facilitating improved access to devices. Continuous glucose monitoring is a complex intervention that provides information on glucose concentration, rate and direction of change, historical data and alerts and alarms for extremes of glucose. These data do not themselves change glycaemia and require translation to a meaningful action for impact. It is, therefore, crucial that such systems advance to better meet the needs of individuals using them. Narrative review of the use of, engagement with, limitations and unmet needs of continuous glucose monitoring systems. CGM devices have made a significant contribution to the self-management of diabetes; however, challenges with access and user experience persist, with multiple limitations to uptake and benefit. These limitations include physical size and implementation, with associated stigma, alarm fatigue, sleep disturbance and the challenge of addressing large volumes of real-time data. Greater personalisation throughout the continuous glucose monitoring journey, with a focus on usability, may improve the benefits derived from the device and reduce the burden of self-management. Healthcare professionals may have unconscious biases that affect the provision of continuous glucose monitors due to deprivation, education, age, ethnicity and other characteristics. Continuous glucose monitoring exerts a dose-dependent response; the more it is used, the more effective it is. For optimal use, continuous glucose monitors must not just reduce the burden of management in one dimension but facilitate net improvement in all domains of self-management for all users.

Alarm Configuration in Intensive Care Units of a Corporate Hospital

In intensive care units (ICUs), inappropriate alarm configuration practices pose significant challenges to patient safety and healthcare providers. The current practices lack standardized guidelines, resulting in excessive alarms and alarm fatigue, where healthcare providers become desensitized and may miss critical events. The absence of standardized protocols and ineffective alarm prioritization exacerbate the problem. The present study aims to understand the various alarm configuration practices in the Intensive Care Unit and to proactively evaluate the limitations of clinical alarm systems management. It focused on identifying reasons for the occurrence of nuisance and false alarms, factoring in the proportion of these unnecessary alarms, and chalking out measures to reduce these false and nuisance alarms. After months of ICU observation, Alarm desensitization, and Alarm fatigue came out to be eminent issues in the functioning of an Intensive Care Unit. The clamor of alarms has been demonstrated to hinder patient recovery, lengthen stays, have a poor impact on patient satisfaction, and cause patient anxiety, sleep difficulties, delirium, elevated blood pressure and heart rates, and immune system deterioration. Therefore, fewer alerts and a simpler alarm configuration procedure can aid in better patient outcomes. The response to all alarms is imperative but false and nuisance alarms make it challenging for the nurses to differentiate and respond to genuine alarms. The study focused on identifying reasons for the occurrence of nuisance and false alarms, factoring in the proportion of these unnecessary alarms, and chalking out measures to reduce these false and nuisance alarms. This included a checklist to monitor the alarms in ICUs on a daily basis for various equipment including cardiac monitors, ventilators, dialysis machines, syringe pumps, and infusion pumps. These were monitored for around 5 hours a day and the analysis revealed most of the equipment especially cardiac monitors giving out false and nuisance alarms. A pre-assessment questionnaire was made to assess the knowledge and perception regarding clinical alarms for nurses. The analysis revealed that 40% of nurses could not differentiate between false and nuisance alarms.

Alarm fatigue and perceived stress among critical care nurses in the intensive care units: Palestinian perspectives

ObjectiveThe frequency of alarms generated by monitors and other electro-medical devices is undeniably valuable but can simultaneously escalate the workload for healthcare professionals, potentially subjecting intensive care unit nurses to alarm fatigue. The aim of this study is to investigate alarm fatigue and stress levels among critical care nursing personnel. Additionally, the study aims to assess predictors for both alarm fatigue and perceived stress.Methodology: A descriptive cross-sectional study recruited 187 Intensive Care Unit (ICU) nurses from hospitals located in the northern and central regions of the West Bank, Palestine. Data were gathered through online surveys due to logistic concerns using the Alarm Fatigue Scale and the Perceived Stress Scale. The research was conducted between November 2023 and January 2024.ResultsThe mean overall alarm fatigue score was 23.36 (SD = 5.57) out of 44. The study showed that 62.6% of the participating ICU nurses experience average to high degree of alarm fatigue, while 69.5% experience average to high levels of perceived stress. A significant positive Pearson correlation was found between stress and alarm fatigue (0.40, P < 0.01). Important predictors of alarm fatigue include perceived stress, nurse-to-patient ratio, gender, and years of experience, while important predictors of perceived stress include alarm fatigue, type of working shift and hospital unit.ConclusionAlarm fatigue can compromise the timely intervention required to prevent adverse outcomes by causing delayed responses or missed critical alarm, which can have major ramifications for patient safety. Addressing stress is crucial for mitigating alarm fatigue and fostering a supportive work environment to ensure optimal patient care. Consequently, exploring strategies to alleviate the negative impacts of alarm fatigue on critical care nurses’ stress merits further investigation in future research studies.

A machine learning algorithm for detecting abnormal patterns in continuous capnography and pulse oximetry monitoring

Continuous capnography monitors patient ventilation but can be susceptible to artifact, resulting in alarm fatigue. Development of smart algorithms may facilitate accurate detection of abnormal ventilation, allowing intervention before patient deterioration. The objective of this analysis was to use machine learning (ML) to classify combined waveforms of continuous capnography and pulse oximetry as normal or abnormal. We used data collected during the observational, prospective PRODIGY trial, in which patients receiving parenteral opioids underwent continuous capnography and pulse oximetry monitoring while on the general care floor [1]. Abnormal ventilation segments in the data stream were reviewed by nine experts and inter-rater agreement was assessed. Abnormal segments were defined as the time series 60s before and 30s after an abnormal pattern was detected. Normal segments (90s continuous monitoring) were randomly sampled and filtered to discard sequences with missing values. Five ML models were trained on extracted features and optimized towards an Fβ score with β = 2. The results show a high inter-rater agreement (> 87%), allowing 7,858 sequences (2,944 abnormal) to be used for model development. Data were divided into 80% training and 20% test sequences. The XGBoost model had the highest Fβ score of 0.94 (with β = 2), showcasing an impressive recall of 0.98 against a precision of 0.83. This study presents a promising advancement in respiratory monitoring, focusing on reducing false alarms and enhancing accuracy of alarm systems. Our algorithm reliably distinguishes normal from abnormal waveforms. More research is needed to define patterns to distinguish abnormal ventilation from artifacts.

Pro-Con Debate: Universal Versus Selective Continuous Monitoring of Postoperative Patients.

In this Pro-Con commentary article, we discuss use of continuous physiologic monitoring for clinical deterioration, specifically respiratory depression in the postoperative population. The Pro position advocates for 24/7 continuous surveillance monitoring of all patients starting in the postanesthesia care unit until discharge from the hospital. The strongest arguments for universal monitoring relate to inadequate assessment and algorithms for patient risk. We argue that the need for hospitalization in and of itself is a sufficient predictor of an individual's risk for unexpected respiratory deterioration. In addition, general care units carry the added risk that even the most severe respiratory events will not be recognized in a timely fashion, largely due to higher patient to nurse staffing ratios and limited intermittent vital signs assessments (e.g., every 4 hours). Continuous monitoring configured properly using a "surveillance model" can adequately detect patients' respiratory deterioration while minimizing alarm fatigue and the costs of the surveillance systems. The Con position advocates for a mixed approach of time-limited continuous pulse oximetry monitoring for all patients receiving opioids, with additional remote pulse oximetry monitoring for patients identified as having a high risk of respiratory depression. Alarm fatigue, clinical resource limitations, and cost are the strongest arguments for selective monitoring, which is a more targeted approach. The proponents of the con position acknowledge that postoperative respiratory monitoring is certainly indicated for all patients, but not all patients need the same level of monitoring. The analysis and discussion of each point of view describes who, when, where, and how continuous monitoring should be implemented. Consideration of various system-level factors are addressed, including clinical resource availability, alarm design, system costs, patient and staff acceptance, risk-assessment algorithms, and respiratory event detection. Literature is reviewed, findings are described, and recommendations for design of monitoring systems and implementation of monitoring are described for the pro and con positions.

Adaptation and validation of the Turkish version of the alarm fatigue assessment questionnaire

ObjectiveAlarm fatigue may endanger the safety of patients by negatively affecting nurses' concentration and ability to provide effective care. Identifying alarm fatigue and taking appropriate measures are critical in preventing medical errors and for nurses to work with high motivation. This study aimed to test the psychometric properties of the Turkish version of the 23-item Alarm Fatigue Assessment Questionnaire (AFAQ). MethodThe study was conducted between February 2022 and April 2022 and included nurses with at least one year of clinical or intensive care experience. The data were collected via a web-based questionnaire. During the adaptation of AFAQ, language, content, and construct validity were evaluated; reliability was examined by internal consistency analysis. ResultsThe item and scale content validity index of AFAQ were found to be high (>0.80). The Kaiser–Meyer–Olkin measure of sampling adequacy indicated an adequate sampling (0.85); Bartlett's test of sphericity χ2 was 1935.074, p<0.001. Exploratory factor analysis (EFA) showed that the 21-item scale had a five-factor structure, explaining 51.606% of the total variance, and the factor loadings of the items were >0.30 (0.422−0.803). Confirmatory factor analysis (CFA) showed that the five-factor model had a good fit index (χ2/df=1.855, SRMR=0.039, RMSEA=0.048, CFI=0.915, and TLI=0.908) and appropriate factor loadings (>0.30). The internal consistency of AFAQ (Cronbach's alpha coefficient) was 0.85, and the corrected item-total correlations were between 0.32−0.55. ConclusionThe results indicated that the Turkish version of the Alarm Fatigue Assessment Questionnaire was sufficiently valid and reliable to measure alarm fatigue in nurses.

Critical Care Alarm Fatigue and Monitor Customization: Alarm Frequencies and Context Factors.

Alarm fatigue among nurses working in the intensive care unit has garnered considerable attention as a national patient safety priority. A viable solution for reducing the frequency of alarms and unnecessary noise is intensive care unit alarm monitor customization. A 24-bed cardiovascular and thoracic surgery intensive care unit in a large academic medical center identified a high rate of alarms and associated noise as a problem contributing to nurse alarm fatigue. An alarm monitor quality improvement project used both alarm frequency and nurse surveys before and after implementation to determine the effectiveness of interventions. Multimodal interventions included nurse training sessions, informational flyers, organizational policies, and an alarm monitor training video. Unexpected results inspired an extensive investigation and secondary analysis, which included examining the data-capturing capabilities of the alarm monitors and the impact of context factors. Alarm frequencies unexpectedly increased after the intervention. The software data-capturing features of the alarm monitors for determining frequency did not accurately measure nurse interactions with monitors. Measured increases in patient census, nurse staffing, and data input from medical devices from before to after the intervention substantially affected project results. Alarm frequencies proved an unreliable measure of nurse skills and practices in alarm customization. Documented changes in context factors provided strong anecdotal evidence of changed circumstances that clarified project results and underscored the critical importance of contemporaneous collection of context data. Designs and methods used in quality improvement projects must include reliable outcome measures to achieve meaningful results.

Clinical decision support tools useful for identifying sepsis risk.

Evaluate the effectiveness of the clinical decision support tools (CDSTs), POC Advisor (POCA), and Modified Early Warning System (MEWS) in identifying sepsis risk and influencing time to treatment for inpatients, comparing their respective alert mechanisms. This study was conducted at two academic university medical center hospitals. Data from adult inpatients in medical-surgical and telemetry units were analyzed from January 1, 2020, to December 31, 2020. Criteria included sepsis-related ICD-10 codes, antibiotic administration, and ordered sepsis labs. Subsequent statistical analyses utilized Fisher's exact test and Wilcoxon Rank Sum test, focusing on mortality differences by age, sex, and race/ethnicity. Among 744 patients, 143 sepsis events were identified, with 83% already receiving treatment upon CDST alert. Group 1 (POCA alert) showed reduced response time compared with MEWS, while Group 3 (MEWS) experienced longer time to treatment. Group 4 included sepsis events missed by both systems. Mortality differences were not significant among the groups. While CDSTs play a role, nursing assessment and clinical judgment are crucial. This study recognized the potential for alarm fatigue due to a high number of CDST-driven alerts, while emphasizing the importance of a collaborative approach for prompt sepsis treatment and potential reduction in sepsis-related mortality.

Human-artificial intelligence interaction in gastrointestinal endoscopy.

The number and variety of applications of artificial intelligence (AI) in gastrointestinal (GI) endoscopy is growing rapidly. New technologies based on machine learning (ML) and convolutional neural networks (CNNs) are at various stages of development and deployment to assist patients and endoscopists in preparing for endoscopic procedures, in detection, diagnosis and classification of pathology during endoscopy and in confirmation of key performance indicators. Platforms based on ML and CNNs require regulatory approval as medical devices. Interactions between humans and the technologies we use are complex and are influenced by design, behavioural and psychological elements. Due to the substantial differences between AI and prior technologies, important differences may be expected in how we interact with advice from AI technologies. Human-AI interaction (HAII) may be optimised by developing AI algorithms to minimise false positives and designing platform interfaces to maximise usability. Human factors influencing HAII may include automation bias, alarm fatigue, algorithm aversion, learning effect and deskilling. Each of these areas merits further study in the specific setting of AI applications in GI endoscopy and professional societies should engage to ensure that sufficient emphasis is placed on human-centred design in development of new AI technologies.

Musical timbre with varied amplitude envelope improves efficacy in auditory alarms

Current alarm standards used in safety critical environments (e.g., medical alarms used in hospitals) suffer from a myriad of complications with detectability, annoyance, and alarm fatigue affecting the wellbeing of patients and staff. To a large extent, these are based on the same simplistic, temporally invariant tones. Here we explore how insights from the acoustic properties of the musical triangle can aid in detection, reducing overall levels hence reducing annoyance ratings. Two tones are used, (1) a standard tone similar to those used in current medical devices, and (2) a tone synthesized based on the spectral-temporal structure of a concert triangle. We conducted a detection experiment where participants indicated if the auditory stimulus is heard when presented a range of signal-to-noise (SNR) ratios and a two-alternative force choice task to measure annoyance ratings. Although reductions in SNRs reduced detectability for the standard tone, similar deductions had no meaningful effect on detectability of tones modeled off the musical triangle. Crucially, we identified a number of triangle inspired tones which are both less annoying and more detectable than standard tones. This suggests that these more complex sounds can reduce annoyance without harming detection, offering useful insight to medical device sound design.

Improving Safety Culture by Establishing Alarm Fatigue Performance in The Adult Intensive Care Unit, Dammam Hospital

Alarm fatigue is becoming a more significant global public health issue that compromises patient safety. Alarm fatigue is especially common among critical care nurses, who are the frontline healthcare providers that provide patients with the most direct care and round-the-clock patient monitoring. An excessive number of alerts, together with erroneous and ineffective alerts, can cause alarm fatigue and negatively impact the psychological well-being of nurses and patients during their recovery process. To find a way to lower the number of false alarms and assess the effectiveness of the measures put in place, a quantitative, descriptive cross-sectional approach was employed. In the adult ICU at NGHA Dammam, this pilot project was carried out from June 2019 to November 2020. In order to identify true alarms and false alarms, the Central Monitor Nurse Daily Checklist was utilized as a data collection tool in conjunction with education training and departmental policies and procedures. There are about 820 alerts per patient each day, including 104 telemetry and 716 bedside alarms. Three months into the project, the project's top alarm measurement was 1503 alarms per patient per day. The project has shown a constant trend in alarm declinations after this peak, largely as a result of project improvement activities. The lowest recorded alarm count in November 2020 was 226 alerts, a 72% decrease from the initial 820 alarms. Nonetheless, the declining trend over the previous three months showed a 22%, 42%, and 48% drop in the overall number of alarms. This study found that alarm fatigue, which is influenced by a number of variables, including safety culture practices, was more common among critical care nurses working in the Intensive Care Unit at NGHA Dammam. Overall, during the first two months of its deployment, this study effectively met its aim and had a considerable impact on the reduction of "false alarms". The results of this study, taken together with improved psychological health for nurses and the provision of a therapeutic environment for patients, offer crucial direction for future intervention programs aimed at reducing alarm fatigue among critical care nurses. Future studies should concentrate on the traits of adherence and management, as well as the obstacles that prevent ICU staff from continuing to implement interventions and false alarm reduction strategies.

Experiences, barriers and expectations regarding current patient monitoring systems among ICU nurses in a University Hospital in Lebanon: a qualitative study.

The aim of the study is to assess the experiences, barriers, and expectations regarding current patient monitoring systems among intensive care unit nurses at one university hospital. A qualitative exploratory study approach was adopted to test the research questions. Intensive care unit personnel placed a high value on practical criteria such as user friendliness and visualization while assessing the present monitoring system. Poor alarm handling was recognized as possible patient safety hazards. The necessity of high accessibility was highlighted once again for a prospective system; wireless, noninvasive, and interoperability of monitoring devices were requested; and smart phones for distant patient monitoring and alert management improvement were required. Core comments from ICU personnel are included in this qualitative research on patient monitoring. All national healthcare involved parties must focus more on user-derived insights to ensure a speedy and effective introduction of digital health technologies in the ICU. The findings from the alarm control or mobile device studies might be utilized to train ICU personnel to use new technology, minimize alarm fatigue, increase medical device accessibility, and develop interoperability standards in critical care practice.

Performance comparison of 6 in-hospital patient monitoring systems in the detection and alarm of ventricular cardiac arrhythmias

BackgroundPatient monitoring devices are critical in alerting potential cardiac arrhythmias during hospitalization; however, there are concerns of alarm fatigue due to high false alarm rates. ObjectiveTo evaluate sensitivity and false alarm rate of hospital-based continuous electrocardiographic (ECG) monitoring technologies. MethodsSix commonly-used multiparameter bedside monitoring systems available in the United States were evaluated: B125M (GE HealthCare), ePM10 and iPM12 (Mindray), Efficia and IntelliVue (Philips), and Life Scope (Nihon Kohden). Sensitivity was tested using ECG recordings containing 57 true ventricular tachycardia (VT) events. False positive rate testing used 205 patient-hours of ECG recordings containing no cardiac arrhythmias. Signals from ECG recordings were fed to devices simultaneously; high-severity arrhythmia alarms were tracked. Sensitivity to true VT events and false positive rates were determined. Differences were assessed using Fisher’s exact tests (sensitivity) and Z-tests (false positive rates). ResultsB125M raised 56 total alarms for 57 annotated VT events and had the highest sensitivity (98%, P<0.05), followed by iPM12 (84%), Life Scope (81%), Efficia (79%), ePM10 (77%), and IntelliVue (75%). B125M raised 20 false alarms, significantly lower (P<0.0001) than iPM12 (284), Life Scope (292), IntelliVue (304), ePM10 (324), and Efficia (493). The most common false alarm was VT, followed by non-sustained VT. ConclusionWe found significant performance differences among multiparameter bedside ECG monitoring systems using previously-collected recordings. B125M had the highest sensitivity in detecting true VT events and lowest false alarm rate. These results can assist in minimizing alarm fatigue and optimizing patient safety by careful selection of in-hospital continuous monitoring technology.

Levels and Factors of Nurses' Alarm Fatigue in Critical Care Settings in Saudi Arabia: A Multicenter Cross-Sectional Study.

A continuous and high frequency of alarms from monitoring and treatment devices can lead to nurses' sensory exhaustion and alarm fatigue in critical care settings. The purpose of this study was to evaluate the level of alarm fatigue and determine the relationship between nurses' sociodemographic and work-related factors and the level of alarm fatigue in critical care settings in Hail City, Saudi Arabia. Between May and July 2023, 298 nurses who worked in the emergency, intensive care, and critical care units of all the public hospitals in Hail City participated in a cross-sectional survey. Sociodemographic and work-related sheet and the Nurses' Alarm Fatigue Questionnaire were used to collect data. The total mean score of alarm fatigue was 26.38±8.30 out of 44. The highest score was observed for the item "I pay more attention to the alarms in certain", while the lowest score were observed for the items "I turn off the alarms at the beginning of every shift" with mean scores of 2.51 and 1.61, respectively. Nurses who were males, older than 30 years and Saudi citizens had significantly higher mean scores of alarm fatigue than their counterparts. In addition, significantly higher mean scores of alarm fatigue were noticed for nurses experienced for 10 years or more and who had regular morning shifts. Multiple linear regression showed that male (p=0.014), age (p=0.012), and Saudi nationality (p <0.029) were the independent factors affecting the level of fatigue alarm among nurses. Nurses working in critical care settings at hospitals in Hail city are exposed to average levels of alarm fatigue, which can be influenced by sex, age, nationality, and experience of nurses. Therefore, it is imperative to manage alarm fatigue in critical care units by considering work-related and personality-related factors to ensure patient safety.