Stop the Noise: A Quality Improvement Project to Decrease Electrocardiographic Nuisance Alarms

Hospital-Based Electrocardiographic Monitoring: The Good, the Not So Good, and Untapped Potential

Continuous electrocardiographic (ECG) monitoring was first introduced into hospitals in the 1960s, initially into critical care, as bedside monitors, and eventually into step-down units with telemetry capabilities. Although the initial use was rather simplistic (ie, heart rate and rhythm assessment), the capabilities of these devices and associated physiologic (vital sign) monitors have expanded considerably. Current bedside monitors now include sophisticated ECG software designed to identify myocardial ischemia (ie, ST-segment monitoring), QT-interval prolongation, and a myriad of other cardiac arrhythmia types. Physiologic monitoring has had similar advances from noninvasive assessment of core vital signs (blood pressure, respiratory rate, oxygen saturation) to invasive monitoring including arterial blood pressure, temperature, central venous pressure, intracranial pressure, carbon dioxide, and many others. The benefit of these monitoring devices is that continuous and real-time information is displayed and can be configured to alarm to alert nurses to a change in a patient's condition. I think it is fair to say that critical and high-acuity care nurses see these devices as having a positive impact in patient care. However, this enthusiasm has been somewhat dampened in the past decade by research highlighting the shortcomings and unanticipated consequences of these devices, namely alarm and alert fatigue. In this article, which is associated with the American Association of Critical-Care Nurses' Distinguished Research Lecture, I describe my 36-year journey from a clinical nurse to nurse scientist and the trajectory of my program of research focused primarily on ECG and physiologic monitoring. Specifically, I discuss the good, the not so good, and the untapped potential of these monitoring systems in clinical care. I also describe my experiences with community-based research in patients with acute coronary syndrome and/or heart failure.

The effect of interventions made in intensive care units to reduce alarms: A systematic review and meta-analysis study

OBJECTIVES

This study examines the effects of the interventions in alarm management in intensive care units on reducing alarms on the basis of current evidence.

METHODOLOGY

This systematic review and meta-analysis study was conducted between January 1, 2010 and October 31, 2021 by searching 16 databases through an independent search by three researchers. The acronym of PICOS was used and the keywords as well as inclusion/exclusion criteria were determined. The Joanna Briggs Institute meta-Analysis of Statistics Assessment and Review Instruments (JBI-MAStARI) were used to assess methodological quality. Professional meta-analysis Software (ProMeta 3) statistical software package was used for data analysis. The study is preregistered on PROSPERO (CRD42021286770).

SETTING

Intensive care units.

RESULTS

The systematic review included 25 studies, whereas the meta-analysis included 15. According to the heterogeneity test in the study, alarm-reducing interventions yielded a heterogeneous distribution. The overall effect size value of all studies, which was found using the random-effects model, was determined to be -0.03 [95 % confidence interval (CI)], a value between -0.16 and 0.10 CI. Based on the results, individual studies showed that the strategies suggesting to ensure alarm safety were effective in reducing the number of alarms; the combined results of the studies in this meta-analysis showed that the interventions made to reduce alarms had too little effect.

CONCLUSION

This study showed that the interventions have a very weak effect size on reducing the number of alarms.

Alarm fatigue among nurses working in intensive care and other inpatient clinics

BACKGROUND

Alarm fatigue is an important technological hazard that adversely affects patient safety and the healthcare team. Nurses can be exposed to an excessive amount of alarms during their work which may lead to alarm fatigue.

OBJECTIVE

To determine the experiences of alarm fatigue among nurses working in intensive care units and other inpatient clinics.

METHODS

This descriptive study was conducted in university hospitals in five cities in Turkey between August and December 2019. A total of 592 nurses participated in this study. The data was collected using questionnaires and the Visual Analog Scale (0 to 10 points) was used to determine the level of alarm fatigue.

RESULTS

More than half of the nurses experienced problems, especially false alarms, caused by devices. Alarm fatigue decreased with increasing age and working years. Nurses reported appropriate actions in solving problems, but also had practices that may increase the risk of error, such as turning off or muting alarms or turning off equipment.

CONCLUSION

Alarm fatigue is mostly caused by false alarms. It can lead to physical fatigue, increased workload and decreased concentration, resulting in an increased possibility of error. Management of alarm fatigue is necessary in preventing a compromise in patients' safety and improving quality of care.

Health System Redesign of Cardiac Monitoring Oversight to Optimize Alarm Management, Safety, and Staff Engagement

OBJECTIVE

The purpose of this quality improvement project was to improve health system patient safety by creating a cardiac monitoring structure aligned with national standards.

BACKGROUND

Excessive alarms pose patient safety threats and are often false or clinically insignificant. The Joint Commission identified reduction of nonactionable alarms as a National Patient Safety Goal.

METHODS

The conversion to structured monitoring occurred in 4 phases: 1) defining health system monitoring structure and processes; 2) co-create sessions; 3) implementation and impact analysis; and 4) ongoing evaluation and optimization.

RESULTS

Twenty-two clinical units participated. At the conclusion of phase 4, total 30-day alarm rates decreased by 74% at the academic hospital and by 92% and 95% at the community hospitals and were sustained for 12 months.

CONCLUSIONS

Decreasing alarm frequency can be safely achieved in academic and community hospitals by creating a system-wide monitoring infrastructure and standardized processes that engage interdisciplinary teams.

Computational approaches to alleviate alarm fatigue in intensive care medicine: A systematic literature review

Patient monitoring technology has been used to guide therapy and alert staff when a vital sign leaves a predefined range in the intensive care unit (ICU) for decades. However, large amounts of technically false or clinically irrelevant alarms provoke alarm fatigue in staff leading to desensitisation towards critical alarms. With this systematic review, we are following the Preferred Reporting Items for Systematic Reviews (PRISMA) checklist in order to summarise scientific efforts that aimed to develop IT systems to reduce alarm fatigue in ICUs. 69 peer-reviewed publications were included. The majority of publications targeted the avoidance of technically false alarms, while the remainder focused on prediction of patient deterioration or alarm presentation. The investigated alarm types were mostly associated with heart rate or arrhythmia, followed by arterial blood pressure, oxygen saturation, and respiratory rate. Most publications focused on the development of software solutions, some on wearables, smartphones, or headmounted displays for delivering alarms to staff. The most commonly used statistical models were tree-based. In conclusion, we found strong evidence that alarm fatigue can be alleviated by IT-based solutions. However, future efforts should focus more on the avoidance of clinically non-actionable alarms which could be accelerated by improving the data availability.

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021233461, identifier: CRD42021233461.

Utility and Impact Analysis of Inpatient Pediatric Physiologic Monitoring

This study aimed to study the practice and effect of monitoring hospitalized pediatric patients in terms the length of stay (LOS). We have performed a prospective, observational study of pediatric patients in the general ward from October to December 2016. We have recorded the use of cardiac monitor, pulse oximeter, or both, and as per physician order at patient admission. We have studied the proportions of monitoring in different patient groups. We have applied a linear regression model to investigate the relationship between LOS and cardiopulmonary monitoring, orders, and medical complexity. Among 399 patients, patients with cardiac and pulse oximeter monitoring with orders were 68 and 82%, respectively. The pulmonary group had more monitoring than the neurology group of patients. LOS was shorter in patients without monitoring; the median difference for the cardiac monitoring was one day (interquartile range [IQR] = 1), and the pulse oximeter was 0.5 days (IQR = 1). Cardiac monitoring order increased LOS by 22% (95% confidence interval [CI]: 0.5, 48%) and complex past medical history increased it by 25% (95% CI: 4, 51%). Our study highlights the variable practice in using monitors, emphasizing a standardized approach. The judicious use of monitoring may reduce prolonged hospitalization. Selective use of physiologic monitoring of ill-appearing or at risk of hypoxemia or cardiac dysrhythmia will reduce overuse.

Premature ventricular complexes during continuous electrocardiographic monitoring in the intensive care unit: Occurrence rates and associated patient characteristics

AIMS AND OBJECTIVES

This study examined the occurrence rate of specific types of premature ventricular complex (PVC) alarms and whether patient demographic and/or clinical characteristics were associated with PVC occurrences.

BACKGROUND

Because PVCs can signal myocardial irritability, in-hospital electrocardiographic (ECG) monitors are typically configured to alert nurses when they occur. However, PVC alarms are common and can contribute to alarm fatigue. A better understanding of occurrences of PVCs could help guide alarm management strategies.

DESIGN

A secondary quantitative analysis from an alarm study.

METHODS

The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist was followed. Seven PVC alarm types (vendor-specific) were described, and included isolated, couplet, bigeminy, trigeminy, run PVC (i.e. VT >2), R-on-T and PVCs/min. Negative binomial and hurdle regression analyses were computed to examine the association of patient demographic and clinical characteristics with each PVC type.

RESULTS

A total of 797,072 PVC alarms (45,271 monitoring hours) occurred in 446 patients, including six who had disproportionately high PVC alarm counts (40% of the total alarms). Isolated PVCs were the most frequent type (81.13%) while R-on-T were the least common (0.29%). Significant predictors associated with higher alarms rates: older age (isolated PVCs, bigeminy and couplets); male sex and presence of PVCs on the 12-lead ECG (isolated PVCs). Hyperkalaemia at ICU admission was associated with a lower R-on-T type PVCs.

CONCLUSIONS

Only a few distinct demographic and clinical characteristics were associated with the occurrence rate of PVC alarms. Further research is warranted to examine whether PVCs were associated with adverse outcomes, which could guide alarm management strategies to reduce unnecessary PVC alarms.

RELEVANCE TO CLINICAL PRACTICE

Targeted alarm strategies, such as turning off certain PVC-type alarms and evaluating alarm trends in the first 24 h of admission in select patients, might add to the current practice of alarm management.

Computer Assisted Patient Monitoring: Associated Patient, Clinical and ECG Characteristics and Strategy to Minimize False Alarms

This chapter is a review of studies that have examined false arrhythmia alarms during in-hospital electrocardiographic (ECG) monitoring in the intensive care unit. In addition, we describe an annotation effort being conducted at the UCSF School of Nursing, Center for Physiologic Research designed to improve algorithms for lethal arrhythmias (i.e., asystole, ventricular fibrillation, and ventricular tachycardia). Background: Alarm fatigue is a serious patient safety hazard among hospitalized patients. Data from the past five years, showed that alarm fatigue was responsible for over 650 deaths, which is likely lower than the actual number due to under-reporting. Arrhythmia alarms are a common source of false alarms and 90% are false. While clinical scientists have implemented a number of interventions to reduce these types of alarms (e.g., customized alarm settings; daily skin electrode changes; disposable vs. non-disposable lead wires; and education), only minor improvements have been made. This is likely as these interventions do not address the primary problem of false arrhythmia alarms, namely deficient and outdated arrhythmia algorithms. In this chapter we will describe a number of ECG features associated with false arrhythmia alarms. In addition, we briefly discuss an annotation effort our group has undertaken to improve lethal arrhythmia algorithms.

Reducing Cardiac Telemetry Nuisance Alarms Through Evidence-Based Interventions

BACKGROUND

Cardiac telemetry nuisance alarms due to leads off and poor signal increase staff workflow interruptions, decrease staff trust in technology, and can compromise patient safety.

LOCAL PROBLEM

Interventions were directed at reducing nuisance alarms on a 32-bed, non-intensive care - a cardiac telemetry unit.

METHODS

A nursing staff education module with evidence-based practices for reducing nuisance alarms, a daily care protocol for patients on cardiac telemetry monitoring, and daily audits of protocol adherence were implemented.

RESULTS

Staff pre- and posttest comparisons on their knowledge relating to nuisance alarms and the evidence-based protocol demonstrated a significant mean increase of 3.02 (95% CI, 2.55-3.48). Daily audits for 7 weeks demonstrated an average of 58.46% staff adherence. Telemetry technician call volume reduction was 16% postimplementation, while nuisance alarms were not reduced significantly.

CONCLUSIONS

This rapid-cycle, quality improvement process resulted in minimal reduction in nuisance alarms but improved staff awareness of the issue and reduced workflow interruptions.

Effect of bundle set interventions on physiologic alarms and alarm fatigue in an intensive care unit: A quality improvement project

OBJECTIVE

To determine if the implementation of an evidence-based bundle designed to reduce the number of physiologic monitor alarms reduces alarm fatigue in intensive care nurses.

DESIGN

This quality improvement project retrospectively reviewed alarm data rates, types, and frequency to identify the top three problematic physiologic alarms in an intensive care unit. An alarm management bundle was implemented to reduce the number of alarms. The Nurses' Alarm Fatigue Questionnaire was used to measure nurses' alarms fatigue pre- and post-implementation of the bundle.

SETTING

A combined medical surgical intensive care unit at an accredited hospital in the United States.

RESULTS

The top three problematic alarms identified during the pre-implementation phase were arrhythmia, invasive blood pressure, and respiration alarms. All three identified problematic physiologic alarms had a reduction in frequency with arrhythmia alarms demonstrating the largest decrease in frequency (46.82%). When measuring alarm fatigue, the overall total scores increased from pre- (M = 30.59, SD = 5.56) to post-implementation (M = 32.60, SD = 4.84) indicating no significant difference between the two periods.

CONCLUSION

After implementing an alarm management bundle, all three identified problematic physiologic alarms decreased in frequency. Despite the reduction in these alarms, there was not a reduction in nurses' alarm fatigue.

ECG alarms during left ventricular assist device (LVAD) therapy in the ICU

BACKGROUND

In hospitalized patients with left ventricular assist device (LVAD), electrical interference and low amplitude QRS complexes are common, which could impact the accuracy of electrocardiographic (ECG) arrhythmia detection and create technical alarms. This could contribute to provider alarm fatigue and threaten patient safety.

OBJECTIVES

We examined three LVAD patients in the cardiac intensive care unit (ICU) to determine: 1) the frequency and accuracy of audible arrhythmia alarms; 2) occurrence rates of technical alarms; and 3) alarm burden (# alarms/hour of monitoring) METHODS: Secondary analysis.

RESULTS

During 593 h, there were 549 audible arrhythmia alarms and 98% were false. There were 25,232 technical alarms and 93% were for artifact, which was configured as an inaudible text alert.

CONCLUSION

False-arrhythmia and technical alarms are frequent in LVAD patients. Future studies are needed to identify both clinical and algorithm-based strategies to improve arrhythmia detection and reduce technical alarms in LVAD patients.

Patient Monitoring Alarms in an Intensive Care Unit: Observational Study With Do-It-Yourself Instructions

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.

Double Trouble: Patients With Both True and False Arrhythmia Alarms

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.

"Noise Factory": A qualitative study exploring healthcare providers' perceptions of noise in the intensive care unit

OBJECTIVES

This study aimed to explore healthcare providers' perceptions of noise in the intensive care unit.

DESIGN

A qualitative exploratory study was conducted using group interviews.

SETTING

The setting comprised a total of 15 participants (five physicians and ten registered nurses) working in an 18-bed medical surgical intensive care unit at a teaching hospital in Istanbul, Turkey. Semi-structured questions were formulated and used in focus group interviews, after which the recorded interviews were transcribed by the researchers. Thematic analysis was used to identify significant statements and initial codes.

FINDINGS

Four themes were identified: the meaning of noise, sources of noise, effects of noise and prevention and management of noise. It was found that noise was an inevitable feature of the intensive care unit. The most common sources of noise were human-induced. It was also determined that device-induced noise, such as alarms, did not produce a lot of noise; however, when staff were late in responding, the sound transformed into noise. Furthermore, it was observed that efforts to decrease noise levels taken by staff had only a momentary effect, changing nothing in the long term because the entire team failed to implement any initiatives consistently. The majority of nurses stated that they were now becoming insensitive to the noise due to the constant exposure to device-induced noise.

CONCLUSION

The data obtained from this study showed that especially human-induced noise threatened healthcare providers' cognitive task functions, concentration and job performance, impaired communication and negatively affected patient safety. In addition, it was determined that any precautions taken to reduce noise were not fully effective. A team approach should be used in managing noise in intensive care units with better awareness.

Prospective Study of Use of Edmonton Symptom Assessment Scale Versus Routine Symptom Management During Weekly Radiation Treatment Visits

PURPOSE:

During radiotherapy (RT), patient symptoms are evaluated and managed weekly during physician on-treatment visits (OTVs). The Edmonton Symptom Assessment Scale (ESAS) is a 9-symptom validated self-assessment tool for reporting common symptoms in patients with cancer. We hypothesized that implementation and physician review of ESAS during weekly OTVs may result in betterment of symptom severity during RT for certain modifiable domains.

METHODS:

As an institutional quality improvement project, patients were partitioned into 2 groups: (1) 85 patients completing weekly ESAS (preintervention) but blinded to their providers who gave routine symptom management and (2) 170 completing weekly ESAS (postintervention group) reviewed by providers during weekly OTVs with possible intervention. To determine the independent association with symptom severity of the intervention, multivariate logistic regression was performed. At study conclusion, provider assessments of ESAS utility were also collected.

RESULTS:

Compared with the preintervention group, stable or improved symptom severity was seen in the postintervention group for pain (70.7% v 85.6%; P = .005) and anxiety (79.3% v 92.9%; P = .002). The postintervention group had decreased association (on multivariate analysis) with worsening severity of pain (OR, 0.13; P < .001), nausea (OR, 0.25; P = .023), loss of appetite (OR, 0.30; P = .024), and anxiety (OR, 0.19; P = .005). Most physicians (87.5%) and nurses (75%) found ESAS review useful in symptom management.

CONCLUSION:

Incorporation of ESAS for OTVs was associated with stable or improved symptom severity where therapeutic intervention is more readily available, such as counseling, pain medication, anti-emetics, appetite stimulants, and anti-anxiolytics. The incorporation of validated patient-reported symptom-scoring tools may improve provider management.

Generalizability of SuperAlarm via Cross-Institutional Performance Evaluation

Bedside patient monitors are ubiquitous tools in modern critical care units to provide timely patient status. However, current systems suffer from high volume of false alarms leading to alarm fatigue, one of top technical hazards in clinical settings. Many studies are racing to develop improved algorithms towards precision patient monitoring, while little has been done to investigate the aspect of algorithm generalizability across different health institutions. Our group has been developing an evolving framework termed SuperAlarm that extracts multivariate patterns in data streams (monitor alarms, electronic health records and physiologic waveforms) of modern health enterprise to predict patient deterioration and has demonstrated great potential in mitigating alarm fatigue. In this study, we further investigate the generalizability of SuperAlarm by designing a comprehensive approach to achieve performance comparison in predicting in-hospital code blue (CB) events across two health institutions. SuperAlarm model trained with alarm data in one institution is tested on both internal and external test sets. Results show comparable performance with sensitivity up to 80% within one-hour window of events and over 90% in reduction of false alarms in both institutions. Cross-institutional performance agreement can be further improved by predicting a more stringent CB subtype (cardiopulmonary arrest), with internal sensitivity lying within 95% confident interval of external one up to 8-hour before event onset. The cross-institutional performance comparison offers first-hand knowledge on both advantages and challenges in generalizing a prediction algorithm across different institutions, which hold key information to guide the design of model training and deployment strategy.

Promoting Sleep in the Intensive Care Unit

Introduction

Intensive care nurses face several challenges to facilitating sleep in their critically ill patients. With its high noise levels, hectic around-the-clock activity and constant artificial lights, the intensive care environment does not foster sleep. Intensive care unit patients have significant alterations in their sleep architecture with frequent awakenings and lighter sleep; up to 50% of this sleep also occurs during the daytime. Sleep loss increases the risk of developing delirium (especially in elderly patients) and immune system impairment, which prolongs healing. The aim of this article was to develop an evidence-based bundle of nursing care activities that promote adult intensive care patients’ sleep.

Methods

A broad search was conducted in PubMed, CINAHL, Cochrane Library, and McMaster plus using search words and Medical Subject Headings terms, such as sleep, intensive care unit, intensive care, critical care nursing, sleep promotion, music, white noise, earplugs, pain relief, absence of pain, nonpharmacological intervention, and mechanical ventilation. Eight recommendations emerged from this review: reduce noise, use earplugs and eye masks, use music, promote a natural circadian rhythm, manage pain, use quiet time, cluster nursing care activities at night, and optimize ventilator modes.

Conclusion

Promoting sleep within this patient population needs to be a higher priority for intensive care nurses. Sleep should be a focus throughout the day and night, in order to sustain patients’ natural circadian rhythms. Novel research in this field could change the strength of these recommendations and add new recommendations to the bundle.

Actionable Ventricular Tachycardia During In-Hospital ECG Monitoring and Its Impact on Alarm Fatigue

BACKGROUND

Ventricular tachycardia (V-tach) is the most common lethal arrhythmia, yet 90% of alarms are false and contribute to alarm fatigue. We hypothesize that some true V-tach also causes alarm fatigue because current criteria are too sensitive (i.e., ≥6 beats ≥100 beats/min [bpm]).

PURPOSE

This study was designed to determine (1) the proportion of clinically actionable true V-tach events; (2) whether true actionable versus nonactionable V-tach differs in terms of heart rate and/or duration (seconds); and (3) if actionable V-tach is associated with adverse outcomes.

METHODS

This was a secondary analysis in 460 intensive care unit (ICU) patients. Electronic health records were examined to determine if a V-tach event was actionable or nonactionable. Actionable V-tach was defined if a clinical action(s) was taken within 15 minutes of its occurrence (i.e., new and/or change of medication, defibrillation, and/or laboratory test). Maximal heart rate and duration for each V-tach event were measured from bedside monitor electrocardiography. Adverse patient outcomes included a code blue event and/or death.

RESULTS

In 460 ICU patients, 50 (11%) had 151 true V-tach events (range 1-20). Of the 50 patients, 40 (80%) had only nonactionable V-tach (97 events); 3 (6%) had both actionable and nonactionable V-tach (32 events); and 7 patients (14%) had only actionable V-tach (23 events). There were differences in duration comparing actionable versus nonactionable V-tach (mean 56.19 ± 116.87 seconds vs. 4.28 ± 4.09 seconds; P = 0.001) and maximal heart rate (188.81 ± 116.83 bpm vs. 150.79 ± 28.26 bpm; P = 0.001). Of the 50 patients, 3 (6%) had a code blue, 2 died, and all were in the actionable V-tach group.

CONCLUSIONS

In our sample, <1% experienced a code blue following true V-tach. Heart rate and duration for actionable V-tach were much faster and longer than that for nonactionable V-tach. Current default settings typically used for electrocardiographic monitoring (i.e., ≥6 beats ≥100 bpm) appear to be too conservative and can lead to crisis/red level nuisance alarms that contribute to alarm fatigue. A prospective study designed to test whether adjusting default settings to these higher levels is safe for patients is needed.

Research Outcomes of Implementing CEASE: An Innovative, Nurse-Driven, Evidence-Based, Patient-Customized Monitoring Bundle to Decrease Alarm Fatigue in the Intensive Care Unit/Step-down Unit

INTRODUCTION

The research literature is replete with evidence that alarm fatigue is a real phenomenon in the clinical practice environment and can lead to desensitization of the need to respond among nursing staff. A few studies attest to the effectiveness of incorporating parts of the American Association of Critical-Care Nurses recommended nursing practices for alarm management. No studies could be found measuring the effectiveness of the American Association of Critical-Care Nurses recommendations in their entirety or the effectiveness of a nursing-driven, evidence-based, patient-customized monitoring bundle.

PURPOSE/RESEARCH QUESTION

The purpose of this study was to describe the effect of implementing CEASE, a nurse-driven, evidence-based, patient-customized monitoring bundle on alarm fatigue. CEASE is an acronym for Communication, Electrodes (daily changes), Appropriateness (evaluation), Setup alarm parameters (patient customization), and Education (ongoing).

RESEARCH QUESTIONS

(1) In a 36-bed intensive care unit/step-down unit (ICU/SDU) with continuous hemodynamic and respiratory monitoring, does application of an evidence-based, patient-customized monitoring bundle compared with existing monitoring practice lead to less alarm fatigue as measured by the number of hemodynamic and respiratory monitoring alarms? (2) In a 36-bed ICU/SDU with continuous hemodynamic and respiratory monitoring, does application of an evidence-based, patient-customized monitoring bundle compared with existing monitoring practice lead to less alarm fatigue as measured by duration of alarms? and (3) In a 36-bed ICU/SDU with continuous hemodynamic and respiratory monitoring, does application of an evidence-based, patient-customized monitoring bundle compared with existing monitoring practice lead to less alarm fatigue as measured by nurse perception?

METHODS

This was an institutional review board approved exploratory, nonrandomized, pretest and posttest, 1-group, quasi-experimental study, without-comparators design describing difference in pretest and posttest measures following CEASE Bundle implementation. The study was conducted over a 6-month period. Convenience sample of 74 registered nurses staffing a 36-bed ICU/SDU using the CEASE Bundle participated. Preimplementation/postimplementation number of alarms and alarm duration time for a 30-day period were downloaded from the monitoring system and compared. Nurses completed an electronic 36-item Clinical Alarms Survey provided by the Healthcare Technology Foundation: 35 before implementation and 18 after implementation. Researchers measured CEASE alarm bundle adherence. χ and t-tests determined statistical significance.

RESULTS

Total number of monitoring alarms decreased 31% from 52 880 to 36 780 after CEASE Bundle implementation. Low-priority Level 1 alarms duration time significantly decreased 23 seconds (t = 1.994, P = .045). Level 2 duration time did not change. High-priority Level 3 alarms duration time significantly increased to 246 seconds (t = 4.432, P < .0001). CEASE alarm bundle adherence significantly improved to 22.4% (χ = 5.068, P = .0244). Nurses perceived a significant decrease in nuisance alarm occurrence (68% to 44%) postimplementation (χ = 3.243, P = .0417). No adverse patient events occurred.

CONCLUSIONS

Decreased total number of monitoring alarms improved nurse perception of alarm fatigue. Continued monitoring of CEASE Bundle adherence by nursing staff is required. Longer high-priority Level 3 alarms duration suggests need for further research.

Clinical Requirements of Future Patient Monitoring in the Intensive Care Unit: Qualitative Study

Background

In the intensive care unit (ICU), continuous patient monitoring is essential to detect critical changes in patients’ health statuses and to guide therapy. The implementation of digital health technologies for patient monitoring may further improve patient safety. However, most monitoring devices today are still based on technologies from the 1970s.

Objective

The aim of this study was to evaluate statements by ICU staff on the current patient monitoring systems and their expectations for future technological developments in order to investigate clinical requirements and barriers to the implementation of future patient monitoring.

Methods

This prospective study was conducted at three intensive care units of a German university hospital. Guideline-based interviews with ICU staff—5 physicians, 6 nurses, and 4 respiratory therapists—were recorded, transcribed, and analyzed using the grounded theory approach.

Results

Evaluating the current monitoring system, ICU staff put high emphasis on usability factors such as intuitiveness and visualization. Trend analysis was rarely used; inadequate alarm management as well as the entanglement of monitoring cables were rated as potential patient safety issues. For a future system, the importance of high usability was again emphasized; wireless, noninvasive, and interoperable monitoring sensors were desired; mobile phones for remote patient monitoring and alarm management optimization were needed; and clinical decision support systems based on artificial intelligence were considered useful. Among perceived barriers to implementation of novel technology were lack of trust, fear of losing clinical skills, fear of increasing workload, and lack of awareness of available digital technologies.

Conclusions

This qualitative study on patient monitoring involves core statements from ICU staff. To promote a rapid and sustainable implementation of digital health solutions in the ICU, all health care stakeholders must focus more on user-derived findings. Results on alarm management or mobile devices may be used to prepare ICU staff to use novel technology, to reduce alarm fatigue, to improve medical device usability, and to advance interoperability standards in intensive care medicine. For digital transformation in health care, increasing the trust and awareness of ICU staff in digital health technology may be an essential prerequisite.

Trial Registration

ClinicalTrials.gov NCT03514173; https://clinicaltrials.gov/ct2/show/NCT03514173 (Archived by WebCite at http://www.webcitation.org/77T1HwOzk)

Critical care nurses' clinical reasoning about physiologic monitor alarm customisation: An interpretive descriptive study

AIMS AND OBJECTIVES

To explore clinical reasoning about alarm customisation among nurses in intensive care units.

BACKGROUND

Critical care nurses are responsible for detecting and rapidly acting upon changes in patients' clinical condition. Nurses use medical devices including bedside physiologic monitors to assist them in their practice. Customising alarm settings on these devices can help nurses better monitor their patients and reduce the number of clinically irrelevant alarms. As a result, customisation may also help address the problem of alarm fatigue. However, little is known about nurses' clinical reasoning with respect to customising physiologic monitor alarm settings.

DESIGN

This article is an in-depth report of the qualitative arm of a mixed methods study conducted using an interpretive descriptive methodological approach.

METHODS

Twenty-seven nurses were purposively sampled from three intensive care units in an academic medical centre. Semi-structured interviews were conducted by telephone and were analysed using thematic analysis. Consolidated Criteria for Reporting Qualitative Research (COREQ) reporting guidelines were used.

RESULTS

Four themes were identified from the interview data: unit alarm culture and context, nurse attributes, motivation to customise and customisation "know-how." A conceptual model demonstrating the relationship of these themes was developed to portray the factors that affect nurses' customisation of alarms.

CONCLUSIONS

In addition to drawing on clinical data, nurses customised physiologic monitor alarms based on their level of clinical expertise and comfort. Nurses were influenced by the alarm culture on their clinical unit and colleagues' and patients' responses to alarms, as well as their own technical understanding of the physiologic monitors.

RELEVANCE TO CLINICAL PRACTICE

The results of this study can be used to design strategies to support the application of clinical reasoning to alarm management, which may contribute to more appropriate alarm customisation practices and improvements in safety.

Testing physiologic monitor alarm customization software to reduce alarm rates and improve nurses' experience of alarms in a medical intensive care unit

Background

Clinicians in intensive care units experience alarm fatigue related to frequent false and non-actionable alarms produced by physiologic monitors. To reduce non-actionable alarms, alarm settings may need to be customized for individual patients; however, nurses may not customize alarms because of competing demands and alarm fatigue.

Objective

To examine the effectiveness and acceptance of physiologic monitor software to support customization of alarms.

Methods

This pre/post intervention study was conducted in a 56-bed medical intensive care unit. IntelliVue^® Alarm Advisor customization support software for alarm limit violations was installed on all monitors and education on its use provided. For 2 months before and after implementation of the software, data were collected on patient characteristics from the electronic health record, alarm counts and duration from the monitoring system, and nurses’ experience of alarms from a survey.

Results

Medium-priority heart rate, respiratory rate, and arterial pressure alarms were significantly reduced after software implementation (9.3%, 11.8%, and 15.9% reduction respectively; p<0.001 for all). The duration of these alarms was also significantly shorter (7.8%, 13.3%, and 9.3% reduction respectively; p<0.05 for all). The number and duration of SpO₂ alarms did not decrease (p>0.05 for both). Patients post-intervention had worse Glasgow Coma Scale scores (p = 0.014), but otherwise were comparable to those pre-intervention. Nurses reported less time spent on non-actionable alarms post-intervention than pre-intervention (p = 0.026). Also lower post-intervention were the proportions of nurses who reported that alarms disturbed their workflow (p = 0.027) and who encountered a situation where an important alarm was ignored (p = 0.043). The majority (>50%) agreed that the software supported setting appropriate alarm limits and was easy to use.

Conclusion

Alarm customization software was associated with a reduction in alarms. Use of software to support nurses’ recognition of trends in patients’ alarms and facilitate changes to alarm settings may add value to alarm reduction initiatives.

Challenges of customizing electrocardiography alarms in intensive care units: A mixed methods study

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.

Epidemiology of patient monitoring alarms in the neonatal intensive care unit

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.

Measurement of Physiological Monitor Alarm Accuracy and Clinical Relevance in Intensive Care Units

BACKGROUND

Alarm fatigue threatens patient safety by delaying or reducing clinician response to alarms, which can lead to missed critical events. Interventions to reduce alarms without jeopardizing patient safety target either inaccurate or clinically irrelevant alarms, so assessment of alarm accuracy and clinical relevance may enhance the rigor of alarm intervention studies done in clinical units.

OBJECTIVES

To (1) examine approaches used to measure accuracy and/or clinical relevance of physiological monitor alarms in intensive care units and (2) compare the proportions of inaccurate and clinically irrelevant alarms.

METHODS

An integrative review was used to systematically search the literature and synthesize resulting articles.

RESULTS

Twelve studies explicitly measuring alarm accuracy and/or clinical relevance on a clinical unit were identified. In the most rigorous studies, alarms were annotated retrospectively by obtaining alarm data and parameter waveforms rather than being annotated in real time. More than half of arrhythmia alarms in recent studies were inaccurate. However, contextual data were needed to determine alarms' clinical relevance. Proportions of clinically irrelevant alarms were high, but definitions of clinically irrelevant alarms often included inaccurate alarms.

CONCLUSIONS

Future studies testing interventions on clinical units should include alarm accuracy and/or clinical relevance as outcome measures. Arrhythmia alarm accuracy should improve with advances in technology. Clinical interventions should focus on reducing clinically irrelevant alarms, with careful consideration of how clinical relevance is defined and measured.

Alarm Safety and Alarm Fatigue

Clinical alarm systems have received significant attention in recent years following warnings from hospital accrediting and health care technology organizations regarding patient harm caused by unsafe practices. Alarm desensitization or fatigue from frequent, false, or unnecessary alarms, has led to serious events and even patient deaths. Other concerns include settings inappropriate to patient population or condition, inadequate staff training, and improper use or disabling. Research on human factors in alarm response and of functionality of medical devices will help clinicians develop appropriate policies, practices, and device settings for clinical alarms in neonatal intensive care units.

Alarm Fatigue: Use of an Evidence-Based Alarm Management Strategy

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.

Nurse Competence on Physiologic Monitors Use: Toward Eliminating Alarm Fatigue in Intensive Care Units

BACKGROUND

Studies on nurse competence on alarm management are a few and tend to be focused on limited skills. In response to Phase II of implementing the National Patient Safety Goal on clinical alarm systems safety, this study assessed nurses' perceived competence on physiologic monitors use in intensive care units (ICUs) and developed and validated a tool for this purpose.

METHODS

This descriptive study took place in a Magnet hospital in a Southwestern state of the U.S. A Nurse Competence on Philips Physiologic Monitors Use Survey was created and went through validation by 13 expert ICU nurses. The survey included 5 subscales with 59 rated items and two open-ended questions. Items on the first 4 subscales reflect most common tasks nurses perform using physiologic monitors. Items on the fifth subscale (advanced functions) reflect rarely used skills and were included to understand the scope of utilizing advanced physiologic monitors' features. Thirty nurses from 4 adult ICUs were invited to respond to the survey.

RESULTS

Thirty nurses (100%) responded to the survey. The majority of nurses were from Neuro (47%) and Surgical Trauma (37%) ICUs. The data supported the high reliability and construct validity of the survey. At least one (3%) to 8 nurses (27%) reported lack of confidence on each item on the survey. On the first four subscales, 3% - 40% of the nurses reported they had never heard of or used 27 features/functions on the monitors. No relationships were found between subscales' scores and demographic characteristics (p > .05). Nurses asked for training on navigating the central-station monitor and troubleshooting alarms, and the use of unit-specific super users to tailor training to users' needs.

CONCLUSION

This is the first study to create and test a list of competencies for physiologic monitors use. Rigorous, periodic and individualized training is essential for safe and appropriate use of physiologic monitors and to decrease alarm fatigue. Training should be comprehensive to include all necessary skills and should not assume proficiency on basic skills. Special attention should be focused on managing technical alarms. Increasing the number of super users is a recommended strategy for individualized and unit-specific training. There is a need for a usability testing of complex IT-equipped medical devices, such as physiologic monitors, for effective, efficient and safe navigation of the monitors.

Research: Association of Low-Amplitude QRSs with False-Positive Asystole Alarms

BACKGROUND

Although electrocardiographic monitoring is valuable for continuous surveillance of intensive care unit (ICU) patients, false alarms are common and have been cited as a cause of alarm fatigue. ANSI/AAMI EC12:2002 states that electrocardiograms (ECGs) should not detect a QRS if the waveform is less than 0.15 mV (1.5 mm) for adult patients, in order to avoid mislabeling P waves or baseline noise as QRSs during complete heart block or asystole. However, ECG software algorithms often use more conservative QRS thresholds, which may result in false-positive asystole alarms in patients with low-amplitude QRS complexes.

OBJECTIVES

To 1) assess the frequency of low QRS amplitude in a group of ICU patients with one or more false-positive asystole alarms and 2) determine whether low-amplitude QRSs are associated with false-positive asystole alarms during continuous ECG monitoring.

METHODS

Hospital-acquired standard 12-lead ECGs were examined in a group of 82 ICU patients who had one or more false-positive asystole alarms. Low QRS amplitude was defined as a unidirectional (only positive or negative) QRS of less than 5 mm in two of four leads (I, II, III, and V1).

RESULTS

Low-amplitude QRSs were present in 45 of 82 (55%) patients. The presence of low-amplitude QRSs did not differ according to age, sex, or race. Patients treated in the cardiac ICU had the highest proportion of low-amplitude QRSs. An equivalent proportion of patients had false-positive asystole alarms by group (no low-amplitude QRSs 95% vs. low-amplitude QRSs 87%; P = 0.229). Eight patients (10%) had both true- and false-positive asystole alarms (two [5%] with no low-amplitude QRSs and six [13%] with low-amplitude QRSs; P = 0.229).

CONCLUSION

Low-amplitude QRS, as assessed from hospital 12-lead ECGs, occurs frequently and is more common in cardiac ICU patients. However, this ECG feature did not identify patients with false-positive asystole alarms during continuous ECG monitoring.

Research in Review: Driving Critical Care Practice Change

During the past year, studies were published that will lead to practice change, address challenges at the bedside, and introduce new care strategies. This article summarizes some of this important work and considers it in the context of previous research and practice. Examples of research-based practice changes include the performance and assessment of septic shock resuscitation, and the integration of tourniquets and massive transfusions in civilian trauma. Care challenges addressed include ethical considerations in light of the Ebola epidemic, infection prevention associated with chlorhexidine bathing, bedside alarm management, evidence to enhance moral courage, and interventions to mitigate thirst in critically ill patients. Research that portends future care includes a discussion of fecal microbiota transplant for patients with refractory infection with refractory infection with Clostridium difficile.

Among Unstable Angina and Non-ST-Elevation Myocardial Infarction Patients, Transient Myocardial Ischemia and Early Invasive Treatment Are Predictors of Major In-hospital Complications

BACKGROUND

Treatment for unstable angina (UA) or non-ST-elevation myocardial infarction (NSTEMI) is aimed at plaque stabilization to prevent infarction. Two treatment strategies are (1) invasive (ie, cardiac catheterization laboratory <24 hours after admission) or (2) selectively invasive (ie, medications with cardiac catheterization laboratory >24 hours for recurrent symptoms). However, it is not known if the frequency of transient myocardial ischemia (TMI) or complications during hospitalization varies by treatment.

PURPOSE

We aimed to (1) examine occurrence of TMI in UA/NSTEMI, (2) compare frequency of TMI by treatment pathway, and (3) determine predictors of in-hospital complications (ie, death, myocardial infarction [MI], pulmonary edema, shock, dysrhythmia with intervention).

METHODS

Hospitalized patients with coronary artery disease (ie, history of MI, percutaneous coronary intervention/stent, coronary artery bypass graft, >50% lesion via angiogram, or positive troponin) were recruited, and 12-lead electrocardiogram Holter initiated. Clinicians, blinded to Holter data, decided treatment strategy; offline analysis was done after discharge. Transient myocardial ischemia was defined as more than 1-mm ST segment ↑ or ↓, in more than 1 electrocardiographic lead, more than 1 minute.

RESULTS

Of 291 patients, 91% were white, 66% were male, 44% had prior MI, and 59% had prior percutaneous coronary intervention/stent or coronary artery bypass graft. Treatment pathway was early in 123 (42%) and selective in 168 (58%). Forty-nine (17%) had TMI: 19 (15%) early invasive, 30 (18%) selective (P = .637). Acute MI after admission was higher in patients with TMI regardless of treatment strategy (early: no TMI 4% vs yes TMI 21%; P = .020; selective: no TMI 1% vs yes TMI 13%; P = .0004). Predictors of major in-hospital complication were TMI (odds ratio, 9.9; 95% confidence interval, 3.84-25.78) and early invasive treatment (odds ratio 3.5; 95% confidence interval, 1.23-10.20).

CONCLUSIONS

In UA/NSTEMI patients treated with contemporary therapies, TMI is not uncommon. The presence of TMI and early invasive treatment are predictors of major in-hospital complications.