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Background and Aims: Dwell time is a critical component of automated peritoneal dialysis (APD) prescription, the stage at which transmembrane mass and fluid transfer occur. Loss of prescribed dwell time (LDT) can negatively influence the efficiency of APD. We investigated the incidence of LDT and related causes using APD in the acute care setting at a tertiary care center., Methods: Retrospective analysis was conducted of all inpatients receiving APD treatments from 1 December 2021 to 1 June 2023. Patient demographics, comorbidities, laboratory, and treatment data were extracted from electronic medical records and a propriety database., Results: N  = 235 cycler treatments completed by 32 patients were included for analysis. The total LDT per treatment exceeding 30 minutes and 60 minutes occurred in 27% and 20% of all treatments. LDT of more than 10 minutes per each cycle exchange occurred in 26%. Session disruptions were caused by slow out-flow (55%), inadequate drain volumes (32%), patient line occlusions (20%), and priming errors (23%). The slow flow alarm requiring user intervention was reported to occur in about one-third of all treatments (31%)., Conclusion: There was significant LDT and inadequate drain volume seen in about one-quarter and one-third of all inpatient APD treatments respectively. This can impact solute clearance and ultrafiltration.  Slow flow alarms were the most prevalent and the leading cause of LDT followed by inadequate drain volume. Future studies are required to investigate measures to reduce slow drain and improve drain volume in the hospital setting.   .

Background: Alarms pervade the hospital environment, often increasing nurses' workload. Hospital nurses are experiencing burnout at unprecedented rates., Puropse: This study examined the association between nurses' experience of alarms and burnout., Methods: Survey data from U.S. nurses (n = 2,131) were analyzed., Findings: Nurses who frequently/occasionally experienced overwhelm from alarms had 2.47 (95% CI [1.93, 3.16]) greater odds of high burnout than those who rarely/never experienced alarm overwhelm; those who frequently/occasionally had to delay alarm response had 2.13 [1.67, 2.70] greater odds of high burnout than those who rarely/never did; and those who frequently/occasionally encountered situations where no one responded to an urgent alarm had 2.5 [2.07, 3.03] greater odds of high burnout than those who rarely/never encountered such situations. The associations remained largely unchanged after adjusting for hospital characteristics, nurse practice environment, and nurse staffing., Conclusion: Although this study was cross-sectional, the potential impact of alarms on nurses' well-being is an important consideration as technology advances., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: The Charité Alarm Fatigue Questionnaire (CAFQa) is a 9-item questionnaire that aims to standardize how alarm fatigue in nurses and physicians is measured. We previously hypothesized that it has 2 correlated scales, one on the psychosomatic effects of alarm fatigue and the other on staff's coping strategies in working with alarms., Objective: We aimed to validate the hypothesized structure of the CAFQa and thus underpin the instrument's construct validity., Methods: We conducted 2 independent studies with nurses and physicians from intensive care units in Germany (study 1: n=265; study 2: n=1212). Responses to the questionnaire were analyzed using confirmatory factor analysis with the unweighted least-squares algorithm based on polychoric covariances. Convergent validity was assessed by participants' estimation of their own alarm fatigue and exposure to false alarms as a percentage., Results: In both studies, the χ2 test reached statistical significance (study 1: χ226=44.9; P=.01; study 2: χ226=92.4; P<.001). Other fit indices suggested a good model fit (in both studies: root mean square error of approximation <0.05, standardized root mean squared residual <0.08, relative noncentrality index >0.95, Tucker-Lewis index >0.95, and comparative fit index >0.995). Participants' mean scores correlated moderately with self-reported alarm fatigue (study 1: r=0.45; study 2: r=0.53) and weakly with self-perceived exposure to false alarms (study 1: r=0.3; study 2: r=0.33)., Conclusions: The questionnaire measures the construct of alarm fatigue as proposed in our previous study. Researchers and clinicians can rely on the CAFQa to measure the alarm fatigue of nurses and physicians., (© Maximilian Markus Wunderlich, Henning Krampe, Kristina Fuest, Dominik Leicht, Moriz Benedikt Probst, Julian Runge, Sebastian Schmid, Claudia Spies, Björn Weiß, Felix Balzer, Akira-Sebastian Poncette, CAFQa Study Group Germany. Originally published in JMIR Human Factors (https://humanfactors.jmir.org).)

Background and Objectives: Alarms at hospitals are frequent and can lead to alarm fatigue posing patient safety risks. We aimed to describe alarm burden over a 1-year period and explored variations in alarm rates stratified by unit type, alarm source, and cause., Methods: A retrospective study of inpatient alarm and patient census data at 1 children's hospital from January 1, 2019, to December 31, 2019, including 8 inpatient units: 6 medical/surgical unit (MSU), 1 PICU, and 1 NICU. Rates of alarms per patient day (appd) were calculated overall and by unit type, alarm source, and cause. Poisson regression was used for comparisons., Results: There were 7 934 997 alarms over 84 077 patient days (94.4 appd). Significant differences in alarm rates existed across inpatient unit types (MSU 81.3 appd, PICU 90.7, NICU 117.5). Pulse oximetry (POx) probes were the alarm source with highest rate, followed by cardiorespiratory leads (54.4 appd versus 31). PICU had lowest rate of POx alarms (33.3 appd, MSU 37.6, NICU 92.6), whereas NICU had lowest rate of cardiorespiratory lead alarms (16.2 appd, MSU 40.1, PICU 31.4). Alarms stratified by cause displayed variation across unit types where "low oxygen saturation" had the highest overall rate, followed by "technical" alarms (43.4 appp versus 16.3). ICUs had higher rates of low oxygenation saturation alarms, but lower rates of technical alarms than MSUs., Conclusions: Clinical alarms are frequent and vary across unit types, sources, and causes. Unit-level alarm rates and frequent alarm sources (eg, POx) should be considered when implementing alarm reduction strategies., (Copyright © 2024 by the American Academy of Pediatrics.)

Background: Alarms are crucial in informing Healthcare Workers (HCWs) about critical patient needs, but unmanaged frequency and noise of alarms can de-sensitize medical staff and compromise patient safety. Alarm fatigue is identified as the major cause of the clinical alarm management problem. It occurs when the medical staff is overwhelmed by the number of clinical alarms., Methods: The survey was conducted online using Google's form-making tools from June to July 2023. There were three parts to the survey used in the study: a socio-demographic metric, the Alarm Fatigue Assessment Questionnaire (AFAQ), and The Pittsburgh Sleep Quality Index (PSQI). A significance level of 0.05 was used in the analysis., Results: The survey included 756 medical professionals from three European countries (Slovakia, the Czech Republic and Poland). The participants in the study were 42 years old on average, and they had 12 years of work experience. 603 out of 756 survey participants had poor sleep quality, 147 had good sleep quality, and 6 did not provide an answer. This study analyzed the alarm fatigue levels of respondents in every country. In the Czech Republic, Poland and Slovakia, a statistically significant association ( p = 0.039, p = 0.001, p < 0.001) was found between alarm fatigue and sleep quality in medical staff., Conclusion: Based on our study, alarm fatigue and sleep quality of HCWs are correlated. Therefore, alarm fatigue and sleep hygiene should be monitored., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Rypicz, Witczak, Šupínová, Salehi and Jarabicová.)

Objectives:  To understand the status quo and related influencing factors of machine alarm fatigue of hemodialysis nurses in tertiary hospitals in Liaoning Province., Methods:  This cross-sectional study employed convenience sampling to select 460 nurses from 29 tertiary hospitals in Liaoning Province, who are involved in hemodialysis care. Surveys were conducted using the General Information Questionnaire, Alarm Fatigue Scale, National Aeronautics and Space Administration Task Load Index, and Maslach Burnout Inventory Scale., Results:  The overall machine alarm fatigue score for 460 hemodialysis nurses from 29 tertiary hospitals in Liaoning Province was 17.04 ± 3.21, indicating a moderate level. The multiple linear regression analysis shows that years of experience in hemodialysis nursing, the number of patients managed per shift, whether specialized nursing training has been received, self-reported health status, emotional exhaustion, and workload have statistically significant associations with alarm fatigue among hemodialysis nurses ( p  < 0.05). Among them, the years of experience in hemodialysis nursing are negatively correlated with alarm fatigue among hemodialysis nurses, whereas the number of patients managed per shift and workload are positively correlated with alarm fatigue among hemodialysis nurses., Conclusion:  This study indicates that certain demographic factors, workload, and occupational burnout are associated with machine alarm fatigue among hemodialysis nurses. Therefore, hemodialysis-related managers should establish a Machine Alarm Management System, implement Personalized Thresholds and Delayed Alarms, ensure reasonable staffing arrangements, improve compassion fatigue, and enhance anticipatory care. Our findings have implications for improving the health and well-being of hemodialysis nurses, providing a conducive environment for professional training in hemodialysis, and ultimately addressing the current situation of machine alarm fatigue among hemodialysis nurses., Competing Interests: None declared., (Thieme. All rights reserved.)

Background: As one of the most essential technical components of the intensive care unit (ICU), continuous monitoring of patients' vital parameters has significantly improved patient safety by alerting staff through an alarm when a parameter deviates from the normal range. However, the vast number of alarms regularly overwhelms staff and may induce alarm fatigue, a condition recently exacerbated by COVID-19 and potentially endangering patients., Objective: This study focused on providing a complete and repeatable analysis of the alarm data of an ICU's patient monitoring system. We aimed to develop do-it-yourself (DIY) instructions for technically versed ICU staff to analyze their monitoring data themselves, which is an essential element for developing efficient and effective alarm optimization strategies., Methods: This observational study was conducted using alarm log data extracted from the patient monitoring system of a 21-bed surgical ICU in 2019. DIY instructions were iteratively developed in informal interdisciplinary team meetings. The data analysis was grounded in a framework consisting of 5 dimensions, each with specific metrics: alarm load (eg, alarms per bed per day, alarm flood conditions, alarm per device and per criticality), avoidable alarms, (eg, the number of technical alarms), responsiveness and alarm handling (eg alarm duration), sensing (eg, usage of the alarm pause function), and exposure (eg, alarms per room type). Results were visualized using the R package ggplot2 to provide detailed insights into the ICU's alarm situation., Results: We developed 6 DIY instructions that should be followed iteratively step by step. Alarm load metrics should be (re)defined before alarm log data are collected and analyzed. Intuitive visualizations of the alarm metrics should be created next and presented to staff in order to help identify patterns in the alarm data for designing and implementing effective alarm management interventions. We provide the script we used for the data preparation and an R-Markdown file to create comprehensive alarm reports. The alarm load in the respective ICU was quantified by 152.5 (SD 42.2) alarms per bed per day on average and alarm flood conditions with, on average, 69.55 (SD 31.12) per day that both occurred mostly in the morning shifts. Most alarms were issued by the ventilator, invasive blood pressure device, and electrocardiogram (ie, high and low blood pressure, high respiratory rate, low heart rate). The exposure to alarms per bed per day was higher in single rooms (26%, mean 172.9/137.2 alarms per day per bed)., Conclusions: Analyzing ICU alarm log data provides valuable insights into the current alarm situation. Our results call for alarm management interventions that effectively reduce the number of alarms in order to ensure patient safety and ICU staff's work satisfaction. We hope our DIY instructions encourage others to follow suit in analyzing and publishing their ICU alarm data., (©Akira-Sebastian Poncette, Maximilian Markus Wunderlich, Claudia Spies, Patrick Heeren, Gerald Vorderwülbecke, Eduardo Salgado, Marc Kastrup, Markus A Feufel, Felix Balzer. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.05.2021.)

Background: In conditions of intensive therapy, where the patients treated are in a critical condition, alarms are omnipresent. Nurses, as they spend most of their time with patients, monitoring their condition 24 h, are particularly exposed to so-called alarm fatigue. The purpose of this study is to review the literature available on the perception of clinical alarms by nursing personnel and its impact on work in the ICU environment., Methods: A systematic review of the literature was carried out according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol. The content of electronic databases was searched through, i.e., PubMed, OVID, EBSCO, ProQuest Nursery, and Cochrane Library. The keywords used in the search included: "intensive care unit," "nurse," "alarm fatigue," "workload," and "clinical alarm." The review also covered studies carried out among nurses employed at an adult intensive care unit. Finally, seven publications were taken into consideration. Data were analyzed both descriptively and quantitatively, calculating a weighted average for specific synthetized data., Results: In the analyzed studies, 389 nurses were tested, working in different intensive care units. Two studies were based on a quality model, while the other five described the problem of alarms in terms of quantity, based on the HTF (Healthcare Technology Foundation) questionnaire. Intensive care nurses think that alarms are burdensome and too frequent, interfering with caring for patients and causing reduced trust in alarm systems. They feel overburdened with an excessive amount of duties and a continuous wave of alarms. Having to operate modern equipment, which is becoming more and more advanced, takes time that nurses would prefer to dedicate to their patients. There is no clear system for managing the alarms of monitoring devices., Conclusion: Alarm fatigue may have serious consequences, both for patients and for nursing personnel. It is necessary to introduce a strategy of alarm management and for measuring the alarm fatigue level.

Purpose: The purpose of this study was to compare the effectiveness of bell-and-pad alarm therapy to body-worn alarm therapy for the management of monosymptomatic enuresis in children 6 to 16 years of age., Design: A prospective, randomized, adaptive clinical control trial., Subjects and Setting: The sample comprised 86 children who attended a continence clinic for treatment of monosymptomatic enuresis and met the criteria for enuresis alarm therapy as per International Children's Continence Society (ICCS) guidelines. Subjects were randomly allocated to an experimental group (body-worn alarm, n = 41) or a control group (bell-and-pad alarm, n = 45). The study setting was a single-site specialist continence service in regional Victoria, Australia. Treatment was administered in the child's home., Methods: Alarm therapy was administered by the child and/or parent for an initial period of 8 weeks at which time the child underwent a review with the continence nurse specialist. If the child had achieved 14 consecutive dry nights, the therapy was deemed successful and ceased. Children who had not become dry continued therapy for a further 8 weeks up to a maximum of 16 weeks, with a final review was instituted. Each child kept a diary for the duration of alarm therapy to report on frequency of wet/dry nights, times of alarm, response to alarm, and response to sensation to void (without alarm). The 2 types of alarm devices were compared with respect to categorical variables using dichotomous cross-tabulations and χ tests of independence based on the most positive outcome versus the other outcomes., Results: Dryness in accordance with the criteria outlined by the ICCS guidelines was achieved in 18 children (43.9%) in the body-worn alarm group versus 29 children (64.4%) in the routine (bell-and-pad) group (P = .056). The bell-and-pad alarm performed better on 7 out of the 9 indicators, including the primary outcome measure of the child attained dryness for 14 nights or more, nightly alarm use, alarm woke child, alarm woke parent (P = .022), false (positive) alarms (P = .039), child turned alarm off and went back to sleep (P = .003), and child was compliant with alarm use. The body-worn device produced higher proportions of the most positive outcomes for 2 of the 9 indicators: relapse (P = .076) and false (negative) nonalarms (P = .066)., Conclusions: Study findings suggests that the bell-and-pad alarm is preferable to the body-worn alarm. Additional research is recommended using other body-worn alarm devices across a larger population in order to establish the more definitive findings needed for clinical decision-making.

Objective: The present study aimed to determine the types of monitor alarms and nurses' responses to them in an adult intensive care unit., Design and Methods: This was an observational descriptive research study conducted in the adult intensive care unit of a university hospital in the Mediterranean region of Turkey. The nonparticipant observation method was used. Data were collected by two observers using a semi-structured observation form developed according to literature., Results: Between August 2016 and January 2017, 13 registered nurses were observed for 328 hours. There were 1781 alarms, which included alarms for blood pressure (37.6%), respiration and oxygen saturation (35.3%) and heart rate and arrhythmia (27.1%). Nurses responded to approximately half (46.9%) of the alarms that required a response. Responses to alarms included silencing them, responding to the patient's clinical condition and solving contact and transmission problems., Conclusion: In the present study, according to response requirement, the division of the alarms was different. The number of alarms that do not reflect the clinical status of the patient was high. It was found that as the false alarm rate increased, the response rate of nurses to these alarms decreased., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Bed and chair alarms are widely used in hospitals, despite lack of effectiveness and unintended negative consequences. In this cross-sectional, observational study, we examined alarm prevalence and contributions of patient- and unit-level factors to alarm use on 59 acute care nursing units in 57 US hospitals participating in the National Database of Nursing Quality Indicators®. Nursing unit staff reported data on patient-level fall risk and fall prevention measures for 1,489 patients. Patient-level propensity scores for alarm use were estimated using logistic regression. Expected alarm use on each unit, defined as the mean patient propensity-for-alarm score, was compared with the observed rate of alarm use. Over one-third of patients assessed had an alarm in the "on" position. Patient characteristics associated with higher odds of alarm use included recent fall, need for ambulation assistance, poor mobility judgment, and altered mental status. Observed rates of unit alarm use ranged from 0% to 100% (median 33%, 10th percentile 5%, 90th percentile 67%). Expected alarm use varied less (median 31%, 10th percentile 27%, and 90th percentile 45%). Only 29% of variability in observed alarm use was accounted for by expected alarm use. Unit assignment was a stronger predictor of alarm use than patient-level fall risk variables. Alarm use is common, varies widely across hospitals, and cannot be fully explained by patient fall risk factors; alarm use is driven largely by unit practices. Alarms are used too frequently and too indiscriminately, and guidance is needed for optimizing alarm use to reduce noise and encourage mobility in appropriate patients., (© 2020 Wiley Periodicals LLC.)

Objectives: to estimate the magnitude of the Nursing Activities Score effect on multiparametric monitor alarm response and staff response time., Methods: an observational, cross-sectional study outlined as an open cohort, performed in an Adult General Intensive Care Unit. The time taken for alarms triggered by the multi-parameter monitors was timed and characterized as attended or not., Results: the study obtained a total of 254 alarms triggered from the multiparameter monitors of 63 patients. The mean number of alarms triggered was 4.5 alarms per period/observation and 1.5 alarms/hour. The study showed that the Nursing Activities Score is associated with an additional probability of 4% (p < 0.05) of an alarm being met, for each additional point in the scale, and reduction in team response time., Conclusion: it has been verified that Nursing Activities Score has a direct relationship with the attendance and with the response time to the alarms triggered.

Study Objective: Monitor alarms are prevalent in the ED. Continuous electronic monitoring of patients' vital signs may alert staff to physiologic decompensation. However, repeated false alarms may lead to desensitization of staff to alarms. Mitigating this could involve prioritizing the most clinically-important alarms. There are, however, little data on which ED monitor alarms are clinical meaningful. We evaluated whether and which ED monitor alarms led to observable changes in patients' ED care., Methods: This prospective, observational study was conducted in an urban, academic ED. An ED physician completed 53 h of observation, recording patient characteristics, alarm type, staff response, whether the alarm was likely real or false, and whether it changed clinical management. The primary outcome was whether the alarm led to an observable change in patient management. Secondary outcomes included the type of alarms and staff responses to alarms., Results: There were 1049 alarms associated with 146 patients, for a median of 18 alarms per hour of observation. The median number of alarms per patient was 4 (interquartile range 2-8). Alarms changed clinical management in 8 out of 1049 observed alarms (0.8%, 95% CI, 0.3%, 1.3%) in 5 out of the 146 patients (3%, 95% CI, 0.2%, 5.8%). Staff did not observably respond to most alarms (63%)., Conclusion: Most ED monitor alarms did not observably affect patient care. Efforts at improving the clinical significance of alarms could focus on widening alarm thresholds, customizing alarms parameters for patients' clinical status, and on utilizing monitoring more selectively., Competing Interests: Declaration of Competing Interest None., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Hourly rounding by nursing staff helps to proactively manage patient needs and minimize the number of unscheduled calls from patients. The focus of this study was to determine if an increased emphasis on hourly rounding had an effect on call bell usage on an oncology unit. Patient call bell usage requests, such as asking for water or repositioning, and the total number of all alarms, such as bed exit alarms and lavatory assist alarms, decreased. Subsequent patient satisfaction surveys showed an increase in patient perception of how quickly help was received.

Studies reveal that the false alarm rate (FAR) demonstrated by intensive care unit (ICU) vital signs monitors ranges from 0.72 to 0.99. We applied machine learning (ML) to ICU multi-sensor information to imitate a medical specialist in diagnosing patient condition. We hypothesized that applying this data-driven approach to medical monitors will help reduce the FAR even when data from sensors are missing. An expert-based rules algorithm identified and tagged in our dataset seven clinical alarm scenarios. We compared a random forest (RF) ML model trained using the tagged data, where parameters (e.g., heart rate or blood pressure) were (deliberately) removed, in detecting ICU signals with the full expert-based rules (FER), our ground truth, and partial expert-based rules (PER), missing these parameters. When all alarm scenarios were examined, RF and FER were almost identical. However, in the absence of one to three parameters, RF maintained its values of the Youden index (0.94-0.97) and positive predictive value (PPV) (0.98-0.99), whereas PER lost its value (0.54-0.8 and 0.76-0.88, respectively). While the FAR for PER with missing parameters was 0.17-0.39, it was only 0.01-0.02 for RF. When scenarios were examined separately, RF showed clear superiority in almost all combinations of scenarios and numbers of missing parameters. When sensor data are missing, specialist performance worsens with the number of missing parameters, whereas the RF model attains high accuracy and low FAR due to its ability to fuse information from available sensors, compensating for missing parameters.

Background: The prevalence of nuisance (technical) alarms is the leading cause of alarm fatigue resulting in decreased awareness and a reduction in effective care. The Joint Commission identified in their National Patient Safety goals alarm fatigue as a major safety issue. The introduction of noninvasive respiratory volume monitoring (RVM) has implications for effective perioperative respiratory status management. We evaluated this within the Kaiser Permanente health system., Methods: This observational study was conducted at 4 hospitals in the Kaiser Permanente system. Standard data from RVM, pulse oximetry, and capnography were collected postoperatively in the post-anesthesia care unit (PACU) and/or on the general hospital floor. Device-specific alarm types, rates, and respective actions were recorded and analyzed by non-study staff., Results: RVM was applied to 247 subjects (143 females, body mass index 32.3 ± 8.7 kg/m 2 , age 60.9 ± 13.9 y) providing 2,321 h. RVM alarms occurred 605 times (0.25 alarms/h); 64% were actionable and addressed, 17% were not addressed, 13% were self-resolved, and only 6% were nuisance. In a subgroup, RVM completed all 127 h of monitoring, whereas oximetry with capnography only completed 51 h with 12.9 alarms/h (73% nuisance). The overall RVM alarm rate was significantly lower than with either pulse oximeters or capnography monitors. We saw a nearly 1,000-fold reduction in nuisance alarms compared to capnography and a 20-50-fold reduction in nuisance alarms compared to pulse oximetry., Conclusions: Our study indicates that alarm fatigue due to nuisance alarms continues to be a clinical challenge in perioperative settings. Among the 3 common technologies for respiratory function monitoring, RVM had the lowest rate of overall technical alarms and the highest rate of compliance. Furthermore, with early interventions, none of the subjects monitored with RVM suffered any negative outcomes., (Copyright © 2020 by Daedalus Enterprises.)

Background: Nonactionable alarms comprise over 70% of alarms and contribute a threat to patient safety. Few studies have reported approaches to translate and sustain these interventions in clinical settings., Purpose: This study tested whether an interprofessional team-based approach can translate and implement effective alarm reduction interventions in the adult intensive care unit., Methods: The study was a prospective, cohort, pre- and postdesign with repeated measures at baseline (preintervention) and post-phase I and II intervention periods. The settings for the most prevalent nonactionable arrhythmia and bedside parameter alarms were adjusted during phases I and II, respectively., Results: The number of total alarms was reduced by 40% over a 14-day period after both intervention phases were implemented. The most prevalent nonactionable parameter alarms decreased by 47% and arrhythmia alarms decreased by 46%., Conclusions: It is feasible to translate and sustain system-level alarm management interventions addressing alarm fatigue using an interprofessional team-based approach.

Background: Patients with both true and false arrhythmia alarms pose a challenge because true alarms might be buried among a large number of false alarms, leading to missed true events., Objective: To determine (1) the frequency of patients with both true and false arrhythmia alarms; (2) patient, clinical, and electrocardiographic characteristics associated with both true and false alarms; and (3) the frequency and types of true and false arrhythmia alarms., Methods: This was a secondary analysis using data from an alarm study conducted at a tertiary academic medical center., Results: Of 461 intensive care unit patients, 211 (46%) had no arrhythmia alarms, 12 (3%) had only true alarms, 167 (36%) had only false alarms, and 71 (15%) had both true and false alarms. Ventricular pacemaker, altered mental status, mechanical ventilation, and cardiac intensive care unit admission were present more often in patients with both true and false alarms than among other patients (P < .001). Intensive care unit stays were longer in patients with only false alarms (mean [SD], 106 [162] hours) and those with both true and false alarms (mean [SD], 208 [333] hours) than in other patients. Accelerated ventricular rhythm was the most common alarm type (37%)., Conclusions: An awareness of factors associated with arrhythmia alarms might aid in developing solutions to decrease alarm fatigue. To improve detection of true alarms, further research is needed to build and test electrocardiographic algorithms that adjust for clinical and electrocardiographic characteristics associated with false alarms., (©2020 American Association of Critical-Care Nurses.)

Introduction: Clinical alarms promote patient safety by alerting clinicians when there is an indication or change in a condition requiring a response. An excessive volume of alarm fires, however, contributes to sensory overload and desensitization, referred to as alarm fatigue, which has significant implications when alarms are missed. This evidence-based, practice project aimed to implement and evaluate a program that reduces the number of clinically nonactionable, physiologic alarms in an emergency department. Although alarm fatigue is an important negative consequence, the focus of this project is not on alarm fatigue but on measures to reduce the volume of clinically nonactionable alarms that lead to alarm fatigue. The Iowa Model was used as a conceptual framework., Methods: This project involved adjusting default alarm settings and implementing an education plan on the safe use of alarms. The sample population included all patients on physiologic monitors at an emergency department. Retrospective data were collected, and regression discontinuity design was applied to compare the rate of alarm fires triggered by the physiologic monitor between pre- and postimplementation of an alarm protocol., Results: A significant change in the rate of alarm fires occurred with an estimated reduction of 14.96 (P = 0.003). There were no reports of adverse outcomes such as a delay in responding to a change in patient condition or delay leading to cardiopulmonary arrest., Discussion: A reduction in nonactionable, physiologic alarms was attained after implementing multimodal strategies inclusive of adjusting default settings, staff education on managing alarms, and emphasis on staff accountability., (Copyright © 2019 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.)

Background: Hospitalized children generate up to 152 alarms per patient per day outside of the intensive care unit. In that setting, as few as 1% of alarms are clinically important. How nurses make decisions about responding to alarms, given an alarm's low specificity for detecting clinical deterioration, remains unclear., Objective: Our objective was to describe how bedside nurses think about and act upon monitor alarms for hospitalized children., Design, Setting, Participants: This was a qualitative study that involved the direct observation of nurses working on a general pediatric unit at a large children's hospital., Measurements: We used a structured tool that included predetermined categories to assess nurse responses to monitor alarms. Data on alarm frequency and type were pulled from bedside monitors., Results: We conducted 61.3 patient-hours of observation with nine nurses, in which we documented 207 nurse responses to patient alarms. For 67% of alarms heard outside of the room, the nurse decided not to respond without further assessment. Nurses most commonly cited reassuring clinical context (eg, medical team in room), as the rationale for alarm nonresponse. The nurse deemed clinical intervention necessary in only 14 (7%) of the observed responses., Conclusion: Nurses rely on clinical and contextual details to determine how to respond to alarms. Few of the alarm responses in our study resulted in a clinical intervention. These findings suggest that multiple system-level and educational interventions may be necessary to improve the efficacy and safety of continuous monitoring.

Introduction: Acute kidney injury (AKI) is common among hospitalised patients and under-recognised by providers and yet carries a significant risk of morbidity and mortality. Electronic alerts for AKI have become more common despite a lack of strong evidence of their benefits. We designed a multicentre, randomised, controlled trial to evaluate the effectiveness of AKI alerts. Our aim is to highlight several challenges faced in the design of this trial, which uses electronic screening, enrolment, randomisation, intervention and data collection., Methods and Analysis: The design and implementation of an electronic alert system for AKI was a reiterative process involving several challenges and limitations set by the confines of the electronic medical record system. The trial will electronically identify and randomise 6030 adults with AKI at six hospitals over a 1.5-2 year period to usual care versus an electronic alert containing an AKI-specific order set. Our primary outcome will be a composite of AKI progression, inpatient dialysis and inpatient death within 14 days of randomisation. During a 1-month pilot in the medical intensive care unit of Yale New Haven Hospital, we have demonstrated feasibility of automating enrolment and data collection. Feedback from providers exposed to the alerts was used to continually improve alert clarity, user friendliness and alert specificity through refined inclusion and exclusion criteria., Ethics and Dissemination: This study has been approved by the appropriate ethics committees for each of our study sites. Our study qualified for a waiver of informed consent as it presents no more than minimal risk and cannot be feasibly conducted in the absence of a waiver. We are committed to open dissemination of our data through clinicaltrials.gov and submission of results to the NIH data sharing repository. Results of our trial will be submitted for publication in a peer-reviewed journal., Trial Registration Number: NCT02753751; Pre-results., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Excessive electrocardiographic alarms contribute to "alarm fatigue," which can lead to patient harm. In a prior study, one-third of audible electrocardiographic alarms were for accelerated ventricular rhythm (AVR), and most of these alarms were false. It is uncertain whether true AVR alarms are clinically relevant., Objectives: To determine from bedside electrocardiographic monitoring data (1) how often true AVR alarms are acknowledged by clinicians, (2) whether such alarms are actionable, and (3) whether such alarms are associated with adverse outcomes ("code blue," death)., Methods: Secondary analysis using data from a study conducted in an academic medical center involving 5 adult intensive care units with 77 beds. Electronic health records of 23 patients with 223 true alarms for AVR were examined., Results: The mean age of the patients was 62.9 years, and 61% were white and male. All 223 of the true alarms were configured at the warning level (ie, 2 continuous beeps), and 215 (96.4%) lasted less than 30 seconds. Only 1 alarm was acknowledged in the electronic health record. None of the alarms were clinically actionable or led to a code blue or death., Conclusions: True AVR alarms may contribute to alarm fatigue. Hospitals should reevaluate the need for close monitoring of AVR and consider configuring this alarm to an inaudible message setting to reduce the risk of patient harm due to alarm fatigue. Prospective studies involving larger patient samples and varied monitors are warranted., (© 2019 American Association of Critical-Care Nurses.)

Alarm fatigue is the most common contributing factor in alarm-related sentinel events. Researchers have demonstrated a 35% overuse of telemetry, a key factor in alarm fatigue. This project evaluates practice patterns for the ordering and discontinuation of telemetry on medical-surgical units. Practice patterns were reviewed to determine if they aligned with the American Heart Association evidence-based practice guidelines for telemetry monitoring and whether the order indication was congruent with the patient's clinical status. Nurse's attitudes and practices related to alarm safety were evaluated., (Copyright © 2018 Elsevier Inc. All rights reserved.)

To address inconsistencies in the recognition and management of acute kidney injury (AKI), an electronic-alert (e-alert) system was implemented by NHS England in 2015. This study aimed to describe its impact within acute medicine in the West Midlands. All admissions to included acute medical units were screened for AKI in two phases, before and after the e-alert was introduced. Data describing recognition and management of patients with AKI were collected. In the 10 units that participated in both phases, recognition of AKI by clinicians significantly improved from 67.9% in 2015 to 76.1% in 2016 (p=0.04). Further analysis of the data found that the presence of an e-alert had a limited effect on recognition and management, suggesting it was not the primary cause of the improvements. Multiple avenues of research have been recommended to clarify the impact of the e-alert system and to improve deficiencies in management that were identified in the data., (© Royal College of Physicians 2019. All rights reserved.)

Introduction: Although the effectiveness of domiciliary monitoring (telehealth) to improve outcomes in chronic obstructive pulmonary disease (COPD) is controversial, it is being used in the National Health Service (NHS)., Aim: To explore the use of teleheath for COPD across England and Wales, to assess the perceptions of clinicians employing telehealth in COPD and to summarise the techniques that have been used by healthcare providers to personalise alarm limits for patients with COPD enrolled in telehealth programmes., Methods: A cross-sectional survey consisting of 14 questions was sent to 230 COPD community services in England and Wales. Questions were designed to cover five aspects of telehealth in COPD: purpose of use, equipment type, clinician perceptions, variables monitored and personalisation of alarm limits., Results: 65 participants completed the survey from 52 different NHS Trusts. 46% of Trusts had used telehealth for COPD, and currently, 31% still provided telehealth services to patients with COPD. Telehealth is most commonly used for baseline monitoring and to allow early detection of exacerbations, with 54% believing it to be effective. The three most commonly monitored variables were oxygen saturation, heart rate and breathlessness. A variety of methods were used to set alarm limits with the majority of respondents believing that at least 40% of alarms were false., Conclusion: Around one-third of responded community COPD services are using telehealth, believing it to be effective without robust evidence, with a variety of variables monitored, a variety of hardware and varying techniques to set alarm limits with high false alarm frequencies., Competing Interests: Competing interests: None declared.

Reduction of clinical alarms is a priority due to alarm fatigue and the high incidence of nonactionable alarms, especially those generated from physiological monitors. However, research on infusion pump alarm types and frequencies is limited. The purpose of this study was to establish a baseline for infusion pump alarm frequencies and duration in the hospital setting. Frequency and duration of alarms across 29 hospitals using 11,410 infusion pumps revealed 987,240 alarms associated with 568,164 infusions during a consecutive 60-day period. Pump alarms accounted for only 0.8% of infusion time, with an average of 1.74 alarms per delivery and 0.18 alarms per hour. Average alarm duration was 0:02:38 (h:min:s), with 60% of alarms being addressed within 0:01:08. The most frequent alarms were keep vein open (33.77%), hold expired (27.18%), and downstream occlusion (22.94%). The medical/surgical and intensive care unit (ICU) care areas had the highest number of alarms (41.66% and 39.70% of total alarms, respectively), but pediatrics/neonatal ICU had the highest frequency of alarms per delivery (4.91). Intravenous fluids accounted for 47.16% of total alarms, with an average of 3.03 alarms per delivery, whereas parenteral nutrition and propofol had 6.77 and 6.74 average alarms per delivery, respectively. A higher average number of alarms per delivery occurred on Saturdays (1.74) and Sundays (1.73) compared with weekdays. Infusion pump alarm data collected and analyzed were sufficient to establish a reasonable baseline of infusion pump alarm types and relative frequencies for the device.

Unrecognized changes in patients' vital signs can result in preventable deaths in hospitalized patients. Few publications or studies instituting routine patient monitoring have described implementation and the setting of alarm parameters for vital signs. We wanted to determine if continuous multi-parameter patient monitoring can be accomplished with an alarm rate that is acceptable to hospital floor nurses and to compare the rate of patient deterioration events to those observed with routine vital sign monitoring. We conducted a prospective, observational, 5-month pilot study in a 26-bed adult, neurological/neurosurgical unit (non-ICU) in an academic medical center. A patient surveillance system employing a wireless body-worn vital signs monitor with automated nursing notification of alarms via smartphones was used to gather data. Data collected included: alarm rates, rapid response team (RRT) calls, intensive care unit (ICU) transfers, and unplanned deaths before and during the pilot study. Average alarm rate for all alarms (SpO 2 , HR, RR, NIBP) was 2.3 alarms/patient/day. The RRT call rate was significantly reduced (p < 0.05) from 189 to 158 per 1000 discharges. ICU transfers per 1000 discharges were insignificantly reduced from 53 to 40 compared to the previous 5-month period in the same unit. Similar measures of comparison units did not change over the same period. Although unplanned patient deaths in the study unit were also reduced during the intervention period, this was not statistically significant. Continual, multi-parameter vital signs monitoring can be customized to reduce a high alarm rates, and may reduce rapid response team calls.

Background: Monitor alarms occur frequently but rarely warrant intervention., Objective: This study aimed to determine if a safety huddle-based intervention reduces unit-level alarm rates or alarm rates of individual patients whose alarms are discussed, as well as evaluate implementation outcomes., Design: Unit-level, cluster randomized, hybrid effectiveness-implementation trial with a secondary patient-level analysis., Setting: Children's hospital., Patients: Unit-level: all patients hospitalized on 4 control (n = 4177) and 4 intervention (n = 7131) units between June 15, 2015 and May 8, 2016. Patient-level: 425 patients on randomly selected dates postimplementation., Intervention: Structured safety huddle review of alarm data from the patients on each unit with the most alarms, with a discussion of ways to reduce alarms., Measurements: Unit-level: change in unit-level alarm rates between baseline and postimplementation periods in intervention versus control units. Patient-level: change in individual patients' alarm rates between the 24 hours leading up to huddles and the 24 hours after huddles in patients who were discussed versus not discussed in huddles., Results: Alarm data informed 580 huddle discussions. In unit-level analysis, intervention units had 2 fewer alarms/patient-day (95% CI: 7 fewer to 6 more, P = .50) compared with control units. In patient-level analysis, patients discussed in huddles had 97 fewer alarms/patientday (95% CI: 52-138 fewer, P < .001) in the posthuddle period compared with patients not discussed in huddles. Implementation outcome analysis revealed a low intervention dose of 0.85 patients/unit/day., Conclusions: Safety huddle-based alarm discussions did not influence unit-level alarm rates due to low intervention dose but were effective in reducing alarms for individual children., (© 2018 Society of Hospital Medicine)

Background: Customizing monitor alarm settings to individual patients can reduce alarm fatigue in intensive care units (ICUs), but has not been widely studied., Objectives: To understand ICU nurses' approaches to customization of electrocardiographic (ECG) monitor alarms., Methods: A convergent mixed methods study was conducted in 3 ICUs in 1 hospital. Data on the type and frequency of ECG alarm customization were collected from patient monitors (n=298). Nurses' customization clinical reasoning was explored through semi-structured interviews (n=27)., Results: Of the 298 patients, 58.7% had ≥1 alarm(s) customized. Heart rate limits, irregular heart rate, and atrial fibrillation were the most commonly customized alarms. Interviews revealed that customization practices varied widely and were influenced by factors including clinical expertise, lack of customization education, and negative experiences., Conclusion: Alarm customization is nuanced and requires adequate support to develop safe and effective practices. The challenges identified can inform development of strategies to improve alarm customization., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: To characterize the rate of monitoring alarms by alarm priority, signal type, and developmental age in a Level-IIIB Neonatal Intensive Care Unit (NICU) population., Study Design: Retrospective analysis of 2,294,687 alarm messages from Philips monitors in a convenience sample of 917 NICU patients, covering 12,001 patient-days. We stratified alarm rates by alarm priority, signal type, postmenstrual age (PMA) and birth weight (BW), and reviewed and adjudicated over 21,000 critical alarms., Results: Of all alarms, 3.6% were critical alarms, 55.0% were advisory alarms, and 41.4% were device alerts. Over 60% of alarms related to oxygenation monitoring. The average alarm rate (±SEM) was 177.1 ± 4.9 [median: 135.9; IQR: 89.2-213.3] alarms/patient-day; the medians varied significantly with PMA and BW (p < 0.001) in U-shaped patterns, with higher rates at lower and higher PMA and BW. Based on waveform reviews, over 99% of critical arrhythmia alarms were deemed technically false., Conclusions: The alarm burden in this NICU population is very significant; the average alarm rate significantly underrepresents alarm rates at low and high PMA and BW. Virtually all critical arrhythmia alarms were artifactual.

Purpose: To investigate the application value of "electronic alerts" ("e-alerts") for acute kidney injury (AKI) among high-risk wards of hospitals., Methods: A prospective, randomized, controlled study was conducted. We developed an e-alert system for AKI and ran the system in intensive care units and divisions focusing on cardiovascular disease. The e-alert system diagnosed AKI automatically based on serum creatinine levels. Patients were assigned randomly to an e-alert group (467 patients) or non-e-alert group (408 patients). Only the e-alert group could receive pop-up messages., Results: The sensitivity, specificity, Youden Index and accuracy of the AKI e-alert system were 99.8, 97.7, 97.5 and 98.1%, respectively. The prevalence of the diagnosis for AKI and expanded-AKI (AKI or multiple-organ failure) in the e-alert group was higher than that in the non-e-alert group (AKI 7.9 and 2.7%, P = 0.001; expanded-AKI 16.3 and 6.1%, P < 0.001). The prevalence of nephrology consultation in the e-alert group was higher than that in the non-e-alert group (9.0 and 3.7%, P = 0.001). There was no significant difference in the prevalence dialysis, rehabilitation of renal function or death in the two groups., Conclusion: The e-alert system described here was a reliable tool to make an accurate diagnosis of AKI.

Objective: To investigate the frequency and cause of neonatal ventilator alarms. Neonatal ventilators frequently alarm and also disturb babies, parents and nurses. If frequent they may cause alarm fatigue and be ignored. The number, frequency and details of neonatal ventilator alarms are unreported., Methods: We developed programs for retrieving and analysing ventilator data each second on alarms and ventilation parameters from 46 babies ventilated with Dräger Babylog VN500 ventilators using various modes., Results: A mean of 60 hours was recorded per baby. Over 116 days, 27 751 alarms occurred. On average, that was 603 per baby and 10 per hour. Median (IQR) alarm duration was 10 (4-21) s. Type, frequency and duration varied between infants. Some babies had >10% of their time with alarms. Eight alarm types caused ~99% of all alarms. Three alarms, 'MV high limit' and 'respiratory rate >high limit', caused 46.6%, often due to inappropriate settings. 49.9% were due to a low expired tidal volume during volume guarantee ventilation, often due to the maximum pressure being set too low. 26 106 (94.1%) of all alarms lasted <1 min. However, 86 alarms lasted >10 min and 16 alarms >1 hour. Similar alarms were frequently clustered, sometimes >100/hour., Conclusions: Frequent ventilator alarms are caused by physiological variability in the respiratory rate or minute volume, inappropriate alarm limits or too low maximum peak inflating pressure during volume-targeted ventilation. While most alarms were very short, sometimes alarms were ignored by neonatal intensive care unit staff for long periods., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Objectives: To determine differences in alarm pressure between two otherwise comparable neonatal intensive care units (NICUs) differing in architectural layout-one of a single-family room (SFR) design and the other of an open bay area (OBA) design., Design: Retrospective audit of more than 2000 patient days from each NICU cataloguing the differences in the number and duration of alarms for critical and alerting alarms, as well as the interaction of clinicians with the patient monitor., Setting: Two level 3 NICUs., Results: A total of more than 150 000 critical and 1.2 million alerting alarms were acquired from the two NICUs. The number of audible alarms and the associated noise pollution varied considerably with the OBA NICU generating 44% more alarms per infant per day even though the SFR NICU generated 2.5 as many critical desaturation alarms per infant per day., Conclusion: Differences in the architectural layout of NICUs and the consequent differences in delays, thresholds and distribution systems for alarms are associated with differences in alarm pressure., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Alarm fatigue has been linked to patient morbidity and mortality in hospitals due to delayed or absent responses to monitor alarms. We sought to describe alarm rates at 5 freestanding children's hospitals during a single day and the types of alarms and proportions of patients monitored by using a point-prevalence, cross-sectional study design. We collected audible alarms on all inpatient units and calculated overall alarm rates and rates by alarm type per monitored patient per day. We found a total of 147,213 alarms during the study period, with 3-fold variation in alarm rates across hospitals among similar unit types. Across hospitals, onequarter of monitored beds were responsible for 71%, 61%, and 63% of alarms in medical-surgical, neonatal intensive care, and pediatric intensive care units, respectively. Future work focused on addressing nonactionable alarms in patients with the highest alarm counts may decrease alarm rates., (© 2018 Society of Hospital Medicine.)

In this focus group study, we identified issues associated with sensory overload from medical technology alarms/alerts for intensive care unit nurses. Participants indicated that alarms from cardiopulmonary monitors, ventilators, and intravenous pumps contributed the most to sensory overload and, yet, these alarms were also deemed the most helpful. Alerts/alarms from electronic health records and medication dispensing systems were rated low in contributing to sensory overload, as well as being the least helpful. Specific device/technology barriers, related to device alerts/alarms, are detailed. Future user-centered and integrated improvements in alarm systems associated with medical devices in the intensive care unit are needed., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: To investigate the effect of different pulse oximetry (SpO 2 ) target range settings during automated fraction of inspired oxygen control (A-FiO 2 ) on time spent within a clinically set SpO 2 alarm range in oxygen-dependent infants on noninvasive respiratory support., Study Design: Forty-one preterm infants (gestational age [median] 26 weeks, age [median] 21 days) on FiO 2  >0.21 receiving noninvasive respiratory support were subjected to A-FiO 2 using 3 SpO 2 target ranges (86%-94%, 88%-92%, or 89%-91%) in random order for 24 hours each. Before switching to the next target range, SpO 2 was manually controlled for 24 hours (washout period). The primary outcome was the time spent within the clinically set alarm limits of 86%-94%., Results: The percent time within the 86%-94% SpO 2 alarm range was similar for all 3 A-FiO 2 target ranges (74%). Time spent in hyperoxemia was not significantly different between target ranges. However, the time spent in severe hypoxemia (SpO 2  <80%) was significantly reduced during the narrowed target ranges of A-FiO 2 (88%-92%; 1.9%, 89%-91%; 1.7%) compared with the wide target range (86%-94%; 3.4%, P < .001). There were no differences between the 88%-92% and 89-91% target range., Conclusions: Narrowing the target range of A-FiO 2 to the desired median ±2% is effective in reducing the time spent in hypoxemia, without increasing the risk of hyperoxemia., Trial Registration: www.trialregister.nl: NTR4368., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Despite significant advances in type 1 diabetes (T1D) management, achieving targeted glycemic control in pediatric patients remains a struggle. Continuous glucose monitoring (CGM) with remote access holds the promise to address this challenge by allowing caregivers to monitor glucose, even when the child is not directly under their supervision., Objective: To explore real-time and remote CGM practices in homes and schools, including caregiver expectations regarding this technology., Subjects: Parents and daytime caregivers., Methods: Respondents answered an anonymous survey assessing characteristics of CGM use. Cross-sectional data were collected and analyzed using quantitative and qualitative methods., Results: Thirty-three parents and 17 daytime caregivers responded. Threshold alerts (alerts when patients reached certain pre-set high or low limits) were used most frequently, followed by rate of change alerts. Most parents and daytime caregivers responded to low- and high-threshold CGM alerts by confirming with a glucose meter prior to treatment; while about one-third endorsed treating lows without a confirmatory test. Most parents expected their child's daytime caregiver to respond to CGM alerts and daytime caregivers felt the parent's expectations of them were reasonable. All parents and most caregivers reported decreased overall worry/stress. Parents felt positive about CGM use and daytime caregivers felt comfortable with CGM., Conclusion: The positive and collaborative management reported by parents and daytime caregivers sets the stage for CGM to play an important role in the management of children with T1D both in the home and in the school settings., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Alarm fatigue, a condition in which clinical staff become desensitized to alarms due to the high frequency of unnecessary alarms, is a major patient safety concern. Alarm fatigue is particularly prevalent in the pediatric setting, due to the high level of variation in vital signs with patient age. Existing studies have shown that the current default pediatric vital sign alarm thresholds are inappropriate, and lead to a larger than necessary alarm load. This study leverages a large database containing over 190 patient-years of heart rate data to accurately identify the 1st and 99th percentiles of an individual's heart rate on their first day of vital sign monitoring. These percentiles are then used as personalized vital sign thresholds, which are evaluated by comparing to non-default alarm thresholds used in practice, and by using the presence of major clinical events to infer alarm labels. Using the proposed personalized thresholds would decrease low and high heart rate alarms by up to 50% and 44% respectively, while maintaining sensitivity of 62% and increasing specificity to 49%. The proposed personalized vital sign alarm thresholds will reduce alarm fatigue, thus contributing to improved patient outcomes, shorter hospital stays, and reduced hospital costs.

Background: Several electronic alert systems for acute kidney injury (AKI) have been introduced. However, their clinical benefits require further investigation., Study Design: Before-and-after quality improvement study., Setting & Participants: A tertiary teaching hospital in Korea, which adopted an AKI alert system on June 1, 2014. Before and after launch of the alert system, 1,884 and 1,309 patients with AKI were included in the usual-care and alert groups, respectively., Quality Improvement Plan: Implementation of an AKI alert system through which clinicians could generate automated consultations to the nephrology division for all hospitalized patients., Outcomes: Primary outcomes included overlooked AKI events, defined as not measuring the follow-up creatinine value, and the consultation pattern of clinicians. Secondary outcomes were severe AKI events; AKI recovery, defined based on the creatinine-based criterion; and patient mortality., Measurements: ORs for events of overlooked AKI, early consultation, and severe AKI were calculated with logistic regression. AKI recovery rate and patient mortality were assessed using Cox regression., Results: After introduction of the alert system, the odds of overlooked AKI events were significantly lower (adjusted OR, 0.40; 95% CI, 0.30-0.52), and the odds of an early consultation with a nephrologist were greater (adjusted OR, 6.13; 95% CI, 4.80-7.82). The odds of a severe AKI event was reduced after implementation of the alerts (adjusted OR, 0.75; 95% CI, 0.64-0.89). Furthermore, the likelihood of AKI recovery was improved in the alert group (adjusted HR, 1.70; 95% CI, 1.53-1.88). Mortality was not affected by the AKI alert system (adjusted HR, 1.07; 95% CI, 0.68-1.68)., Limitations: Possible unreported differences between the alert and usual-care groups., Conclusions: Implementation of the AKI alert system was associated with beneficial effects in terms of an improved rate of recovery from AKI. Therefore, widespread adoption of such systems could be considered in general hospitals., (Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Background: Physiologic monitors generate high rates of alarms in the pediatric intensive care unit (PICU), yet few are actionable., Objective: To determine the association between a huddle-based intervention focused on reducing unnecessary alarms and the change in individual patients' alarm rates in the 24 hours after huddles., Design: Quasi-experimental study with concurrent and historical controls., Setting: A 55-bed PICU., Participants: Three hundred low-acuity patients with more than 40 alarms during the 4 hours preceding a safety huddle in the PICU between April 1, 2015, and October 31, 2015., Intervention: Structured safety huddle review and discussion of alarm causes and possible monitor parameter adjustments to reduce unnecessary alarms., Main Measurements: Rate of priority alarms per 24 hours occurring for intervention patients as compared with concurrent and historical controls. Balancing measures included unexpected changes in patient acuity and code blue events., Results: Clinicians adjusted alarm parameters in the 5 hours following the huddles in 42% of intervention patients compared with 24% of control patients (𝑃 = .002). The estimate of the effect of the intervention adjusted for age and sex compared with concurrent controls was a reduction of 116 priority alarms (95% confidence interval, 37-194) per 24 hours (𝑃 = .004). There were no unexpected changes in patient acuity or code blue events related to the intervention., Conclusions: Integrating a data-driven monitor alarm discussion into safety huddles was a safe and effective approach to reducing alarms in low-acuity, highalarm PICU patients., (© 2017 Society of Hospital Medicine)

Objective: Our previous studies have shown that "code blue" events can be predicted by SuperAlarm patterns that are multivariate combinations of monitor alarms and laboratory test results cooccurring frequently preceding the events but rarely among control patients. Deploying these patterns to the monitor data streams can generate SuperAlarm sequences. The objective of this study is to test the hypothesis that SuperAlarm sequences may contain more predictive sequential patterns than monitor alarms sequences., Methods: Monitor alarms and laboratory test results are extracted from a total of 254 adult coded and 2213 control patients. The training dataset is composed of subsequences that are sampled from complete sequences and then further represented as fixed-dimensional vectors by the term frequency inverse document frequency method. The information gain technique and weighted support vector machine are adopted to select the most relevant features and train a classifier to differentiate sequences between coded patients and control patients. Performances are assessed based on an independent dataset using three metrics: sensitivity of lead time (Sen L @T), alarm frequency reduction rate (AFRR), and work-up to detection ratio (WDR)., Results: The performance of 12-h-long sequences of SuperAlarm can yield a Sen L @2 of 93.33%, an AFRR of 87.28%, and a WDR of 3.01. At an AFRR = 87.28%, Sen L @2 for raw alarm sequences and discretized alarm sequences are 73.33% and 70.19%, respectively. At a WDR = 3.01, Sen L @2 are 49.88% and 43.33%., Conclusion and Significance: The results demonstrate that SuperAlarm sequences indeed outperform monitor alarm sequences and suggest that one can focus on sequential patterns from SuperAlarm sequences to develop more precise patient monitoring solutions.

Objectives: To evaluate how often and why providers overrode drug allergy alerts in both the inpatient and outpatient settings., Design: A cross-sectional observational study of drug allergy alerts generated over a 3-year period between 1 January 2009 and 31 December 2011., Setting: A 793-bed tertiary care teaching affiliate of Harvard Medical School and 36 primary care practices., Participants: Drug allergy alerts were displayed for a total of 29 420 patients across both settings., Main Outcome Measures: Proportion of drug allergy alerts displayed and overridden, proportion of appropriate overrides, proportion of overrides in each medication class, different reasons for overriding and types of reactions overridden., Results: A total of 158 023 drug allergy alerts were displayed, 131 615 (83%) in the inpatient setting and 26 408 (17%) in the outpatient setting; 128 157 (81%) of which were overridden. A random sample of inpatient (n=200, 0.19%) and outpatient (n=50, 0.25%) alert overrides were screened for appropriateness, with >96% considered appropriate. Alerts for some drug classes, such as 'non-antibiotic sulfonamides', were overridden for >81% of prescriptions in both settings. The most common override reason was patient has taken previously without allergic reaction . In the inpatient setting alone, 70.9% of alerts that warned against the risk of anaphylaxis were overridden., Conclusions: The information contained in patients' drug allergy lists needs to be regularly updated. Most of the drug allergy alerts were overridden, with the majority of alert overrides in the subsample considered appropriate. Some of the rules for these alerts should be carefully reviewed and modified, or removed. Further research is needed to understand providers' overriding of alerts that warned against the risk of 'anaphylaxis', which are more concerning with respect to patient safety., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Background: Acute kidney injury (AKI) often takes a complicated course if diagnosed late and undertreated. Electronic alerts that provide an early warning of AKI are intended to support treating physicians in making the diagnosis of AKI and treating it appropriately. The available evidence on the effects of such alert systems is inconsistent., Methods: We employed the PRISMA recommendations for systematic literature reviews to identify relevant articles in the PubMed, Scopus, and Web of Science databases. All of the studies that were retrieved were independently assessed by two of the authors with respect to the methods of computer-assisted electronic alert systems and their effects on process indicators and clinical endpoints., Results: 16 studies with a total of 32 842 patients were identified. 8.5% of admitted patients had community-acquired or hospital-acquired AKI, with an in-hospital mortality of 22.8%. Fifteen electronic alert systems were in use throughout the participating hospitals. In 13 of 15 studies, alarm activation was accompanied by concrete treatment recommendations. A randomized controlled trial in which no such recommendations were given did not reveal any benefit of the alert system for the patients. In controlled but non-randomized trials, however, the provision of concrete treatment recommendations when the alert was activated led to more frequent implementation of diagnostic or therapeutic measures, less loss of renal function, lower in-hospital mortality, and lower mortality after discharge compared to control groups without an electronic alert for AKI., Conclusion: Non-randomized controlled trials of electronic alerts for AKI that were coupled with treatment recommendations have yielded evidence of improved care processes and treatment outcomes for patients with AKI. This review is limited by the low number of randomized trials and the wide variety of endpoints used in the studies that were evaluated.

The purpose of this article is to describe the impact of an evidence-based alarm management strategy on patient safety. An alarm management program reduced alarms up to 30%. Evaluation of patients on continuous cardiac monitoring showed a 3.5% decrease in census. This alarm management strategy has the potential to save $136 500 and 841 hours of registered nurses' time per year. No patient harm occurred during the 2-year project.

Background: The goal of intraoperative neurophysiologic monitoring (IONM) is to minimize neurologic injury during surgery, yet patients still emerge with postoperative deficits. Few studies focus on outcomes relative to IONM alarms and interventions in this population. The authors sought to analyze the influence of IONM alarms with and without surgical intervention on patient outcome in spinal surgical patients who suffered immediate postoperative neurologic deficits., Methods: Of 62,038 spinal surgeries with multimodality IONM, 90 patients with new or worsened postoperative neurologic deficits and whose outcomes were reported immediate to the surgery and at discharge were analyzed. Outcomes at discharge were compared for surgeries in which an IONM alarm versus no alarm occurred. Outcomes where surgical intervention was performed versus not performed were also compared., Results: By discharge, 48 (53.3%) of 90 patients had complete or partial recovery of their postoperative deficit. Patients with IONM alarms and surgical interventions had an 80% (39/49) recovery rate overall versus only 26% (7/27) recovery rate of patients with IONM alarms but no interventions, and only 14% (2/14) of patients without IONM alarms and without interventions (P < 0.001)., Conclusions: These data showed significantly more patients recovered by the time of discharge when a surgical intervention was precipitated by an IONM alarm versus when it was not. The authors conclude that surgical interventions based on IONM alarms do improve patient outcomes despite immediate postoperative deficit.

Background: Medtronic implantable cardioverter defibrillators (ICDs; Medtronic Inc., Mounds View, MN, USA) are equipped with Patient Alert™, a feature in which the ICD generator emits a series of audible tones to notify patients of possible system malfunction. A prior study of this issue revealed that only 50% of patients with older Medtronic devices were able to hear alerts. More recently, Medtronic has incorporated modifications to the alert. Therefore, we studied how frequently alert tones emitted by the current generation of Medtronic ICDs are audible by patients., Methods: A series of patients were evaluated in an outpatient ICD clinic. Alert tones were demonstrated using a device programmer in a quiet room and in the presence of low-level background noise. Patients reported whether they heard the tones, and they completed questionnaires regarding the tones., Results: The total sample size was 100 patients, 81 male, who ranged from 29 years to 94 years of age (mean age 72.1 ± 11.8). Among the study subjects, 46% were older than 75 years, 41% were between 55 years and 75 years, and 13% were younger than 55 years. In the absence of background noise, 94% of patients were able to hear both alerts, 1% heard only one alert, and 5% heard neither. In the presence of background noise, 88% of patients heard both the alerts, 7% heard only one alert, and 5% heard neither alerts., Conclusions: Our results demonstrate that alert tones in recent generation Medtronic ICDs have improved audibility, compared to prior published data, among a large outpatient ICD population., (© 2016 Wiley Periodicals, Inc.)

Background: We tested the hypothesis that an electronic alert for a "double low" of mean arterial pressure less than 75 mmHg and a bispectral index less than 45 reduces the primary outcome of 90-day mortality., Methods: Adults having noncardiac surgery were randomized to receive either intraoperative alerts for double-low events or no alerts. Anesthesiologists were not blinded and not required to alter care based upon the alerts. The primary outcome was all-cause 90-day mortality., Results: Patients (20,239) were randomized over 33 months, and 19,092 were analyzed. After adjusting for age, comorbidities, and perioperative factors, patients with more than 60 min of cumulative double-low time were twice as likely to die (hazard ratio, 1.99; 95% CI, 1.2 to 3.2; P = 0.005). The median number of double-low minutes (quartiles) was only slightly lower in the alert arm: 10 (2 to 30) versus 12 (2 to 34) min. Ninety-day mortality was 135 (1.4%) in the alert arm and 123 (1.3%) in the control arm. The difference in percent mortality was 0.18% (99% CI, -0.25 to 0.61)., Conclusions: Ninety-day mortality was not significantly lower in patients cared for by anesthesiologists who received automated alerts to double-low states. Prolonged cumulative double-low conditions were strongly associated with mortality.

Background: The Joint Commission's 2014 National Patient Safety Goals required hospitals to evaluate alarm safety in 2014-2015 and implement alarm safety policies., Objective: The aim of this study was to assess common alarm management safety factors in our 187-bed community hospital., Methods: Two weeks' worth of IV pump report data was evaluated to characterize 33 IV pump alarm types. Hospital and IV pump noise was measured, and an alarm management nurse survey was conducted., Results: There were 8731 total IV pump alarms/alerts (24-hour mean, 623.6) across 6 units. The 2-minute idle alarm accounted for 32.4% of all total IV alarms/alerts, suggestive of high levels of nurse multitasking and nurse work interruptions. IV pump volumes contributed to overall hospital noise. Survey data identified patient units and alarm safety practices needing additional support., Conclusions: Characterization of IV pump alarms/alerts is an emerging area of scientific inquiry. Findings indicate the need for organizations to evaluate alarm burden and alarm management safety practices to reduce alarm fatigue risks.