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      Patient characteristics associated with false arrhythmia alarms in intensive care

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          A high rate of false arrhythmia alarms in the intensive care unit (ICU) leads to alarm fatigue, the condition of desensitization and potentially inappropriate silencing of alarms due to frequent invalid and nonactionable alarms, often referred to as false alarms.


          The aim of this study was to identify patient characteristics, such as gender, age, body mass index, and diagnosis associated with frequent false arrhythmia alarms in the ICU.


          This descriptive, observational study prospectively enrolled patients who were consecutively admitted to one of five adult ICUs (77 beds) at an urban medical center over a period of 31 days in 2013. All monitor alarms and continuous waveforms were stored on a secure server. Nurse scientists with expertise in cardiac monitoring used a standardized protocol to annotate six clinically important types of arrhythmia alarms (asystole, pause, ventricular fibrillation, ventricular tachycardia, accelerated ventricular rhythm, and ventricular bradycardia) as true or false. Total monitoring time for each patient was measured, and the number of false alarms per hour was calculated for these six alarm types. Medical records were examined to acquire data on patient characteristics.


          A total of 461 unique patients (mean age =60±17 years) were enrolled, generating a total of 2,558,760 alarms, including all levels of arrhythmia, parameter, and technical alarms. There were 48,404 hours of patient monitoring time, and an average overall alarm rate of 52 alarms/hour. Investigators annotated 12,671 arrhythmia alarms; 11,345 (89.5%) were determined to be false. Two hundred and fifty patients (54%) generated at least one of the six annotated alarm types. Two patients generated 6,940 arrhythmia alarms (55%). The number of false alarms per monitored hour for patients’ annotated arrhythmia alarms ranged from 0.0 to 7.7, and the duration of these false alarms per hour ranged from 0.0 to 158.8 seconds. Patient characteristics were compared in relation to 1) the number and 2) the duration of false arrhythmia alarms per 24-hour period, using nonparametric statistics to minimize the influence of outliers. Among the significant associations were the following: age ≥60 years ( P=0.013; P=0.034), confused mental status ( P<0.001 for both comparisons), cardiovascular diagnoses ( P<0.001 for both comparisons), electrocardiographic (ECG) features, such as wide ECG waveforms that correspond to ventricular depolarization known as QRS complex due to bundle branch block (BBB) ( P=0.003; P=0.004) or ventricular paced rhythm ( P=0.002 for both comparisons), respiratory diagnoses ( P=0.004 for both comparisons), and support with mechanical ventilation, including those with primary diagnoses other than respiratory ones ( P<0.001 for both comparisons).


          Patients likely to trigger a higher number of false arrhythmia alarms may be those with older age, confusion, cardiovascular diagnoses, and ECG features that indicate BBB or ventricular pacing, respiratory diagnoses, and mechanical ventilatory support. Algorithm improvements could focus on better noise reduction (eg, motion artifact with confused state) and distinguishing BBB and paced rhythms from ventricular arrhythmias. Increasing awareness of patient conditions that apparently trigger a higher rate of false arrhythmia alarms may be useful for reducing unnecessary noise and improving alarm management.

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          Most cited references 26

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          Gorillas in our midst: sustained inattentional blindness for dynamic events.

          With each eye fixation, we experience a richly detailed visual world. Yet recent work on visual integration and change direction reveals that we are surprisingly unaware of the details of our environment from one view to the next: we often do not detect large changes to objects and scenes ('change blindness'). Furthermore, without attention, we may not even perceive objects ('inattentional blindness'). Taken together, these findings suggest that we perceive and remember only those objects and details that receive focused attention. In this paper, we briefly review and discuss evidence for these cognitive forms of 'blindness'. We then present a new study that builds on classic studies of divided visual attention to examine inattentional blindness for complex objects and events in dynamic scenes. Our results suggest that the likelihood of noticing an unexpected object depends on the similarity of that object to other objects in the display and on how difficult the priming monitoring task is. Interestingly, spatial proximity of the critical unattended object to attended locations does not appear to affect detection, suggesting that observers attend to objects and events, not spatial positions. We discuss the implications of these results for visual representations and awareness of our visual environment.
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            Monitor alarm fatigue: an integrative review.

             Maria Cvach (2016)
            Alarm fatigue is a national problem and the number one medical device technology hazard in 2012. The problem of alarm desensitization is multifaceted and related to a high false alarm rate, poor positive predictive value, lack of alarm standardization, and the number of alarming medical devices in hospitals today. This integrative review synthesizes research and non-research findings published between 1/1/2000 and 10/1/2011 using The Johns Hopkins Nursing Evidence-Based Practice model. Seventy-two articles were included. Research evidence was organized into five main themes: excessive alarms and effects on staff; nurse's response to alarms; alarm sounds and audibility; technology to reduce false alarms; and alarm notification systems. Non-research evidence was divided into two main themes: strategies to reduce alarm desensitization, and alarm priority and notification systems. Evidence-based practice recommendations and gaps in research are summarized.
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              Monitor alarm fatigue: standardizing use of physiological monitors and decreasing nuisance alarms.

              Reliance on physiological monitors to continuously "watch" patients and to alert the nurse when a serious rhythm problem occurs is standard practice on monitored units. Alarms are intended to alert clinicians to deviations from a predetermined "normal" status. However, alarm fatigue may occur when the sheer number of monitor alarms overwhelms clinicians, possibly leading to alarms being disabled, silenced, or ignored. Excessive numbers of monitor alarms and fear that nurses have become desensitized to these alarms was the impetus for a unit-based quality improvement project. Small tests of change to improve alarm management were conducted on a medical progressive care unit. The types and frequency of monitor alarms in the unit were assessed. Nurses were trained to individualize patients' alarm parameter limits and levels. Monitor software was modified to promote audibility of critical alarms. Critical monitor alarms were reduced 43% from baseline data. The reduction of alarms could be attributed to adjustment of monitor alarm defaults, careful assessment and customization of monitor alarm parameter limits and levels, and implementation of an interdisciplinary monitor policy. Although alarms are important and sometimes life-saving, they can compromise patients' safety if ignored. This unit-based quality improvement initiative was beneficial as a starting point for revamping alarm management throughout the institution.

                Author and article information

                Ther Clin Risk Manag
                Ther Clin Risk Manag
                Therapeutics and Clinical Risk Management
                Therapeutics and Clinical Risk Management
                Dove Medical Press
                19 April 2017
                : 13
                : 499-513
                [1 ]Department of Nursing, School of Health and Natural Sciences, Dominican University of California, San Rafael
                [2 ]Department of Physiological Nursing, School of Nursing, University of California, San Francisco, CA
                [3 ]School of Nursing
                [4 ]Department of Emergency Medicine, School of Medicine, University of North Carolina at Chapel Hill, NC
                [5 ]Intensive Care Unit, The Neuroscience Center, Sutter Eden Medical Center, Castro Valley
                [6 ]Hu Research Laboratory, Department of Physiological Nursing, School of Nursing, University of California, San Francisco
                [7 ]ECG Monitoring Research Lab, Department of Physiological Nursing, School of Nursing
                [8 ]Physiological Nursing and Neurological Surgery, Affiliate Faculty of Institute for Computational Health Sciences Core Faculty UCB/UCSF Joint Bio-Engineering Graduate Program, University of California, San Francisco, CA, USA
                Author notes
                Correspondence: Patricia R Harris, Dominican University of California, School of Health and Natural Sciences, Department of Nursing, 50 Acacia Avenue, San Rafael, CA 94901, USA, Tel +1 415 458 3797, Email patricia.harris@ 123456dominican.edu
                © 2017 Harris et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Original Research


                alarm fatigue, electrocardiography, patient safety


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