Reduce Alarm Fatigue Research Articles

Reducing alarm fatigue: exploring decision structures, risks, and design

Automated patient monitoring systems suer from several design problems. Among them, alarm fatigue is one of the most critical issues, as evidenced by the Sentinel Event Alert that The Joint Commission – the U.S. hospital-accrediting body – recently issued. In this study, we explore fast-and-frugal heuristics that may be used to prioritize patient alarms, while continuing to monitor patient physiological state. By using a combination of human factors methodologies and the theory of Distributed Cognition (DCog), we studied alarm fatigue and its relationship to the underlying hospital systems. We identified three specific factors that we envision to be helpful for clinical personnel: ventilator presence, number of intravenous drips, and number of medications. We discuss their application in daily hospital operation. We also address cost-benefit considerations and possible monitor designs.

A multidisciplinary approach to reducing alarm fatigue and cost through appropriate use of cardiac telemetry

BackgroundAlarm fatigue (AF) is a distressing factor for staff and patients in the hospital. Using cardiac telemetry (CT) without clinical indications can create unnecessary alarms, and increase AF and cost...

Drawing Up a New Game Plan to Reduce Alarm Fatigue.

Drawing Up a New Game Plan to Reduce Alarm Fatigue.

A Community Hospital's Evaluation of Alarm Management Safety Factors.

The Joint Commission's 2014 National Patient Safety Goals required hospitals to evaluate alarm safety in 2014-2015 and implement alarm safety policies. The aim of this study was to assess common alarm management safety factors in our 187-bed community hospital. 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. 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. 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.

Data-Driven Implementation of Alarm Reduction Interventions in a Cardiovascular Surgical ICU

Alarm fatigue in the ICU setting has been well documented in the literature. The ICU's high-intensity environment requires staff's vigilant attention, and distraction from false and non-actionable alarms pulls staff away from important tasks, creates dissatisfaction, and is a potential patient safety risk if alarms are missed or ignored. This project was intended to improve patient safety by optimizing alarm systems in a cardiovascular surgical intensive care unit (CVSICU). Specific aims were to examine nurses' attitudes toward clinical alarm signals, assess nurses' ability to discriminate audible alarm signals, and implement a bundled set of best practices for monitor alarm reduction without undermining patient safety. CVSICU nurses completed an alarm perception survey and participated in alarm discriminability testing. Nurse survey data and baseline monitor alarm data were used to select targeted alarm reduction interventions, which were progressively phased in. Monitor alarm data and cardiorespiratory event data were trended over one year. Five of the most frequent CVSICU monitor alarm types-pulse oximetry, heart rate, systolic and diastolic blood pressure, pulse oximetry sensor, and ventricular tachycardia > 2-were targeted. After implementation, there was a 61% reduction in average alarms per monitored bed and a downward trend in cardiorespiratory events. To reduce alarm fatigue it is important to decrease alarm burden through targeted interventions. Methods to reduce non-actionable alarms include adding short delays to allow alarm self-correction, adjusting default alarm threshold limits, providing alarm notification through a secondary device, and teaching staff to optimize alarm settings for individual patients.

Evidence-Based Cardiac Monitoring in Surgical Patients: Reducing Alarm Fatigue and Improving Resource Allocation

Evidence-Based Cardiac Monitoring in Surgical Patients: Reducing Alarm Fatigue and Improving Resource Allocation

Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data.

The use of machine-learning algorithms to classify alerts as real or artifacts in online noninvasive vital sign data streams to reduce alarm fatigue and missed true instability. Observational cohort study. Twenty-four-bed trauma step-down unit. Two thousand one hundred fifty-three patients. Noninvasive vital sign monitoring data (heart rate, respiratory rate, peripheral oximetry) recorded on all admissions at 1/20 Hz, and noninvasive blood pressure less frequently, and partitioned data into training/validation (294 admissions; 22,980 monitoring hours) and test sets (2,057 admissions; 156,177 monitoring hours). Alerts were vital sign deviations beyond stability thresholds. A four-member expert committee annotated a subset of alerts (576 in training/validation set, 397 in test set) as real or artifact selected by active learning, upon which we trained machine-learning algorithms. The best model was evaluated on test set alerts to enact online alert classification over time. The Random Forest model discriminated between real and artifact as the alerts evolved online in the test set with area under the curve performance of 0.79 (95% CI, 0.67-0.93) for peripheral oximetry at the instant the vital sign first crossed threshold and increased to 0.87 (95% CI, 0.71-0.95) at 3 minutes into the alerting period. Blood pressure area under the curve started at 0.77 (95% CI, 0.64-0.95) and increased to 0.87 (95% CI, 0.71-0.98), whereas respiratory rate area under the curve started at 0.85 (95% CI, 0.77-0.95) and increased to 0.97 (95% CI, 0.94-1.00). Heart rate alerts were too few for model development. Machine-learning models can discern clinically relevant peripheral oximetry, blood pressure, and respiratory rate alerts from artifacts in an online monitoring dataset (area under the curve > 0.87).

Retrospective analysis of pulse oximeter alarm settings in an intensive care unit patient population

BackgroundThe cacophony of alerts and alarms in a hospital produced by medical devices results in alarm fatigue. The pulse oximeter is one of the most common sources of alarms. One of the ways to reduce alarm rates is to adjust alarm settings at the bedside. This study is aimed to retrospectively examine individual pulse oximeter alarm settings on alarm rates and inter- and intra- patient variability.MethodsNine hundred sixty-two previously collected intensive care unit (ICU) patient records were obtained from the Multiparameter Intelligent Monitoring in Intensive Care II Database (Beth Israel Deaconess Medical Center, Boston, MA). Inclusion criteria included patient records that contained SpO2 trend data sampled at 1 Hz for at least 1 h and a matching clinical record. SpO2 alarm rates were simulated by applying a range of thresholds (84, 86, 88, and 90 %) and delay times (10 to 60 s) to the SpO2 data. Patient records with at least 12 h of SpO2 data were examined for the variability in alarm rate over time.ResultsDecreasing SpO2 thresholds and increasing delay times resulted in decreased alarm rates. A limited number of patient records accounted for most alarms, and this number increased as alarm settings loosened (the top 10 % of patient records were responsible for 57.4 % of all alarms at an SpO2 threshold of 90 % and 15 s delay and 81.6 % at an SpO2 threshold of 84 % and 45 s delay). Alarm rates were not consistent over time for individual patients with periods of high and low alarms for all alarm settings.ConclusionPulse oximeter SpO2 alarm rates are variable between patients and over time, and the alarm rate and the extent of inter- and intra-patient variability can be affected by the alarm settings. Personalized alarm settings for a patient’s current status may help to reduce alarm fatigue for nurses.Electronic supplementary materialThe online version of this article (doi:10.1186/s12912-016-0149-3) contains supplementary material, which is available to authorized users.

Human Factors and Health-Care Professionals Collaboration to Reduce Alarm Fatigue in ICU Settings at a Large Academic Medical Center

Key stakeholders across healthcare’s complex socio-technical environment have been called by the Joint Commission to take part in the shared responsibility to improve alarm safety. This project demonstrated the value added from applying Human Factors principles to a process supporting the safety of patients and the work of health-care providers by reducing the non-actionable alarms in 4 in-patient care units. An Alarm Safety Quality Improvement project is described with specific objectives, methods and results. Results from this project demonstrated an iterative process which provided data and empowerment to the team. The data provided the unit leaders new actionable information and targeted intervention planning with associated meaningful measurements. The process has empowered units to tackle alarm fatigue with the necessary knowledge, tools, and support. The four in-patient care units that have completed this process saw a combined average weekly decrease of 14,000 alarms.

Pattern discovery in critical alarms originating from neonates under intensive care

Patient monitoring generates a large number of alarms, the vast majority of which are false. Excessive non-actionable medical alarms lead to alarm fatigue, a well-recognized patient safety issue. While multiple approaches to reduce alarm fatigue have been explored, patterns in alarming and inter-alarm relationships, as they manifest in the clinical workspace, are largely a black-box and hamper research efforts towards reducing alarms. The aim of this study is to detect opportunities to safely reduce alarm pressure, by developing techniques to identify, capture and visualize patterns in alarms.Nearly 500 000 critical medical alarms were acquired from a neonatal intensive care unit over a 20 month period. Heuristic techniques were developed to extract the inter-alarm relationships. These included identifying the presence of alarm clusters, patterns of transition from one alarm category to another, temporal associations amongst alarms and determination of prevalent sequences in which alarms manifest.Desaturation, bradycardia and apnea constituted 86% of all alarms and demonstrated distinctive periodic increases in the number of alarms that were synchronized with nursing care and enteral feeding. By inhibiting further alarms of a category for a short duration of time (30 s/60 s), non-actionable physiological alarms could be reduced by 20%. The patterns of transition from one alarm category to another and the time duration between such transitions revealed the presence of close temporal associations and multiparametric derangement. Examination of the prevalent alarm sequences reveals that while many sequences comprised of multiple alarms, nearly 65% of the sequences were isolated instances of alarms and are potentially irreducible.Patterns in alarming, as they manifest in the clinical workspace were identified and visualized. This information can be exploited to investigate strategies for reducing alarms.

Reduction of clinically irrelevant alarms in patient monitoring by adaptive time delays.

The problem of high rates of false alarms in patient monitoring in anesthesiology and intensive care medicine is well known but remains unsolved. False alarms desensitize the medical staff, leading to ignored true alarms and reduced quality of patient care. A database of intra-operative monitoring data was analyzed to find characteristic alarm patterns. The original data were re-evaluated to find relevant events and to rate the severity of these events. Based on this analysis an adaptive time delay was developed that individually delays the alarms depending on the grade of threshold deviation. The conventional threshold algorithm led to 4893 alarms. 3515 (71.84%) of these alarms were annotated as clinically irrelevant. In total 81.0% of all clinically irrelevant alarms were caused by only mild and/or brief threshold violations. We implemented the new algorithm for selected parameters. These parameters equipped with adaptive validation delays led to 1729 alarms. 931 (53.85%) alarms were annotated as clinically irrelevant. 632 alarms indicated the 645 clinically relevant events. The positive predictive value of occurring alarms improved from 28.16% (conventional algorithm) to 46.15% (new algorithm). 13 events were missed. The false positive alarm reduction rate of the algorithm ranged from 33 to 86.75%. The overall reduction was 73.51%. The implementation of this algorithm may be able to suppress a large percentage of false alarms. The effect of this approach has not been demonstrated but shows promise for reducing alarm fatigue. Its safety needs to be proven in a prospective study.

Multi-parameter vital sign database to assist in alarm optimization for general care units.

Continual vital sign assessment on the general care, medical-surgical floor is expected to provide early indication of patient deterioration and increase the effectiveness of rapid response teams. However, there is concern that continual, multi-parameter vital sign monitoring will produce alarm fatigue. The objective of this study was the development of a methodology to help care teams optimize alarm settings. An on-body wireless monitoring system was used to continually assess heart rate, respiratory rate, SpO2 and noninvasive blood pressure in the general ward of ten hospitals between April 1, 2014 and January 19, 2015. These data, 94,575 h for 3430 patients are contained in a large database, accessible with cloud computing tools. Simulation scenarios assessed the total alarm rate as a function of threshold and annunciation delay (s). The total alarm rate of ten alarms/patient/day predicted from the cloud-hosted database was the same as the total alarm rate for a 10 day evaluation (1550 h for 36 patients) in an independent hospital. Plots of vital sign distributions in the cloud-hosted database were similar to other large databases published by different authors. The cloud-hosted database can be used to run simulations for various alarm thresholds and annunciation delays to predict the total alarm burden experienced by nursing staff. This methodology might, in the future, be used to help reduce alarm fatigue without sacrificing the ability to continually monitor all vital signs.Electronic supplementary materialThe online version of this article (doi:10.1007/s10877-015-9790-8) contains supplementary material, which is available to authorized users.

Insights into the problem of alarm fatigue with physiologic monitor devices: a comprehensive observational study of consecutive intensive care unit patients.

PurposePhysiologic monitors are plagued with alarms that create a cacophony of sounds and visual alerts causing “alarm fatigue” which creates an unsafe patient environment because a life-threatening event may be missed in this milieu of sensory overload. Using a state-of-the-art technology acquisition infrastructure, all monitor data including 7 ECG leads, all pressure, SpO2, and respiration waveforms as well as user settings and alarms were stored on 461 adults treated in intensive care units. Using a well-defined alarm annotation protocol, nurse scientists with 95% inter-rater reliability annotated 12,671 arrhythmia alarms.ResultsA total of 2,558,760 unique alarms occurred in the 31-day study period: arrhythmia, 1,154,201; parameter, 612,927; technical, 791,632. There were 381,560 audible alarms for an audible alarm burden of 187/bed/day. 88.8% of the 12,671 annotated arrhythmia alarms were false positives. Conditions causing excessive alarms included inappropriate alarm settings, persistent atrial fibrillation, and non-actionable events such as PVC's and brief spikes in ST segments. Low amplitude QRS complexes in some, but not all available ECG leads caused undercounting and false arrhythmia alarms. Wide QRS complexes due to bundle branch block or ventricular pacemaker rhythm caused false alarms. 93% of the 168 true ventricular tachycardia alarms were not sustained long enough to warrant treatment.DiscussionThe excessive number of physiologic monitor alarms is a complex interplay of inappropriate user settings, patient conditions, and algorithm deficiencies. Device solutions should focus on use of all available ECG leads to identify non-artifact leads and leads with adequate QRS amplitude. Devices should provide prompts to aide in more appropriate tailoring of alarm settings to individual patients. Atrial fibrillation alarms should be limited to new onset and termination of the arrhythmia and delays for ST-segment and other parameter alarms should be configurable. Because computer devices are more reliable than humans, an opportunity exists to improve physiologic monitoring and reduce alarm fatigue.

What's that sound? Managing alarm fatigue

What's that sound? Managing alarm fatigue

The Roundup

The Roundup

Medical audible alarms: a review.

This paper summarizes much of the research that is applicable to the design of auditory alarms in a medical context. It also summarizes research that demonstrates that false alarm rates are unacceptably high, meaning that the proper application of auditory alarm design principles are compromised. Designers, users, and manufacturers of medical information and monitoring systems that indicate when medical or other parameters are exceeded and that are indicated by an auditory signal or signals. The emergence of alarms as a 'hot topic'; an outline of the issues and design principles, including IEC 60601-1-8; the high incidence of false alarms and its impact on alarm design and alarm fatigue; approaches to reducing alarm fatigue; alarm philosophy explained; urgency in audible alarms; different classes of sound as alarms; heterogeneity in alarm set design; problems with IEC 60601-1-8 and ways of approaching this design problem.