ALARMED: Adverse events in Low-risk patients with chest pain Receiving continuous electrocardiographic Monitoring in the Emergency Department. A pilot study

Fewer emergency department alarms is associated with reduced use of medications for acute agitation

BACKGROUND AND OBJECTIVES

Patient monitoring systems provide critical information but often produce loud, frequent alarms that worsen patient agitation and stress. This may increase the use of physical and chemical restraints with implications for patient morbidity and autonomy. This study analyzes how augmenting alarm thresholds affects the proportion of alarm-free time and the frequency of medications administered to treat acute agitation.

METHODS

Our emergency department's patient monitoring system was modified on June 28, 2022 to increase the tachycardia alarm threshold from 130 to 150 and to remove alarm sounds for several arrhythmias, including bigeminy and premature ventricular beats. A pre-post study was performed lasting 55 days before and 55 days after this intervention. The primary outcome was change in number of daily patient alarms. The secondary outcomes were alarm-free time per day and median number of antipsychotic and benzodiazepine medications administered per day. The safety outcome was the median number of patients transferred daily to the resuscitation area. We used quantile regression to compare outcomes between the pre- and post-intervention period and linear regression to correlate alarm-free time with the number of sedating medications administered.

RESULTS

Between the pre- and post-intervention period, the median number of alarms per day decreased from 1332 to 845 (-37%). This was primarily driven by reduced low-priority arrhythmia alarms from 262 to 21 (-92%), while the median daily census was unchanged (33 vs 32). Median hours per day free from alarms increased from 1.0 to 2.4 (difference 1.4, 95% CI 0.8-2.1). The median number of sedating medications administered per day decreased from 14 to 10 (difference - 4, 95% CI -1 to -7) while the number of escalations in level of care to our resuscitation care area did not change significantly. Multivariable linear regression showed a 60-min increase of alarm-free time per day was associated with 0.8 (95% CI 0.1-1.4) fewer administrations of sedating medication while an additional patient on the behavioral health census was associated with 0.5 (95% CI 0.0-1.1) more administrations of sedating medication.

CONCLUSION

A reasonable change in alarm parameter settings may increase the time patients and healthcare workers spend in the emergency department without alarm noise, which in this study was associated with fewer doses of sedating medications administered.

The Alarm Fatigue Challenge in the Neonatal Intensive Care Unit: A "before" and "after" Study

OBJECTIVE

Alarm fatigue (AF) happens when professionals are exposed to many alarms and they become desensitized to them. It is related to proliferation of devices, not standardized alarm limits, and high prevalence of "nonactionable alarms," i.e., false alarms (triggered by equipment issues) or nuisance alarms (physiological change not requiring clinical action). When AF happens, response time seems to be longer and important alarms could be dismissed. After evaluating the situation in our neonatal intensive care unit (NICU), an alarm management program (AMP) was developed to reduce AF. The objective of this study were to compare the proportion of true alarms, nonactionable alarms, and to measure response time to alarms in the NICU before and after implementing an AMP and also to determine variables associated with nonactionable alarms and response time.

STUDY DESIGN

This was a cross-sectional study. A total of 100 observations were collected between December 2019 and January 2020. After an AMP was implemented, 100 new observations were collected between June 2021 and August 2021. We estimated the true and nonactionable alarms proportion. Univariate analyses were performed to determine variables associated with nonactionable alarms and response time. Logistic regression was performed to assess independent variables.

RESULTS

The proportion of true alarms before and after AMP was 31 versus 57% (p = 0.001), whereas the proportion of nonactionable alarms was 69 versus 43% (p = 0.001). Median response time was significantly reduced (35 versus 12 seconds; p = 0.001). Before AMP, neonates with less intensive care needs had a higher proportion of nonactionable alarms and a longer response time. After AMP, response time was similar for true and nonactionable alarms. For both periods, the need of respiratory support was significantly associated with true alarms (p = 0.001). In the adjusted analysis, response time (p = 0.001) and respiratory support (p = 0.003) remained associated with nonactionable alarms.

CONCLUSION

AF was highly prevalent in our NICU. This study shows that after the implementation of an AMP, response time to alarms and the proportion of nonactionable alarms can be significantly reduced.

KEY POINTS

· AF happens when professionals are exposed to many alarms and they become desensitized to them.. · The presence of AF can compromise patients' safety.. · The implementation of an AMP can reduce AF..

Ten Years Later, Alarm Fatigue Is Still a Safety Concern

Ten years after the publication of a landmark article in AACN Advanced Critical Care, alarm fatigue continues to be an issue that researchers, clinicians, and organizations aim to remediate. Alarm fatigue contributes to missed alarms and medical errors that result in patient death, increased clinical workload and burnout, and interference with patient recovery. Led by the American Association of Critical-Care Nurses, national patient safety organizations continue to prioritize efforts to battle alarm fatigue and have proposed alarm management strategies to mitigate the effects of alarm fatigue. Similarly, clinical efforts now use simulation studies, individualized alarm thresholds, and interdisciplinary teams to optimize alarm use. Finally, engineering research efforts have innovated the standard alarm to convey information more effectively for medical users. By focusing on patient and provider safety, clinical workflow, and alarm technology, efforts to reduce alarm fatigue over the past 10 years have been grounded in an evidence-based and personnel-focused approach.

Tell-a provider about tele: Reducing overuse of telemetry across 10 hospitals in a safety net system

BACKGROUND

Telemetry is often a scarce resource at hospitals and is important for arrhythmia and myocardial ischemia detection. Overuse of telemetry monitoring leads to alarm fatigue resulting in failure to respond to arrhythmias, patient harm, and possible unnecessary testing.

METHODS

This quality improvement initiative was implemented across NYC Health and Hospitals, an 11-hospital urban safety net system. The electronic health record intervention involved the addition of a mandatory indication in the telemetry order and a best practice advisory (BPA) that would fire after the recommended time period for reassessment had passed.

RESULTS

The average telemetry hours per patient encounter went from 60.1 preintervention to 48.4 postintervention, a 19.5% reduction (p < .001). When stratified by the 11 hospitals, decreases ranged from 9% to 30%. The BPA had a 53% accept rate and fired 52,682 times, with 27,938 "discontinue telemetry" orders placed. The true accept rate was 50.4%, as there was a 2.6% 24-h reorder rate. There was variation based on clinician specialty and clinician type (attending, fellow, resident, physician associate, nurse practitioner).

CONCLUSION

We successfully reduced telemetry monitoring across a multisite safety net system using solely an electronic health record (EHR) intervention. This expands on previous telemetry monitoring reduction initiatives using EHR interventions at single academic sites. Further study is needed to investigate variation across clinician type, specialty, and post-acute sites.

Implementation and experience of an innovative smart patient care system: a cross-sectional study

Background

Although a patient care system may help nurses handle patients’ requests or provide timely assistance to those in need, there are a number of barriers faced by nurses in handling alarms.

Methods

The aim of the study was to describe the implementation and experience of an innovative smart patient care system (SPCS). This study applied a cross-sectional descriptive design. We recruited 82 nurses from a medical center in Taiwan, with 25 nurses from a ward that had introduced an SPCS and 57 nurses from wards that used the traditional patient care system (TPCS). The major advantages of the SPCS compared to the TPCS include the specification of alarm purposes, the routing of alarms directly to the mobile phone; the capability of immediate communication via phone; and three-stage bed-exit alerts with low false alarm rate.

Results

Approximately 56% of nurses in the TPCS wards perceived that the bed-exit alert was easily ignorable, while this rate was reduced to 32% in the SPCS ward. The immediate communication via phone was considered as the most helpful function of the SPCS, with a weighted average score of 3.92/5, and 52% of nurses strongly agreed (5/5) that this function was helpful. The second-highest ranked function was the three-stage bed-exit alert, with an average score of 3.68/5, with approximately 24% of nurses strongly agreeing (5/5) that this function was helpful. The average response time using TPCS was 145.66 s while it was 59.02 s using the SPCS (P < .001). Among the 110 observed alarms in the SPCS ward, none of them were false bed-exit alarms. In comparison, among 120 observed alarms in the TPCS wards, 42 (35%) of them were false bed-exit alarms (P < .001). In this study, we found that 30.91% of alarms using SPCS were processed because nurses received and responded to the alert via mobile phone.

Conclusions

A smart patient care system is needed to help nurses make more informed prioritization decisions between responding to alarms and ongoing tasks and finally assist them in adjusting their work in various situations to improve work efficiency and care quality.

Clinical alarms and alarm fatigue in a University Hospital Emergency Department-A retrospective data analysis

BACKGROUND

Alarm fatigue is hypothesized to be caused by vast amount of patient monitor alarms. Objectives were to study the frequency and types of patient monitor alarms, to evaluate alarm fatigue, and to find unit specific alarm threshold values in a university hospital emergency department.

METHODS

We retrospectively gathered alarm data from 9 September to 6 October 2019, in Jorvi Hospital Emergency department, Finland. The department treats surgical, internal and general medicine patients aged 16 and older. The number of patients is on average 4600 to 5000 per month. Eight out of 46 monitors were used for data gathering and the monitored modalities included electrocardiography, respiratory rate, blood pressure, and pulse oximetry.

RESULTS

Total number of alarms in the study monitors was 28 176. Number of acknowledged alarms (ie acknowledgement indicator pressed in the monitor) was 695 (2.5%). The most common alarm types were: Respiratory rate high, 9077 (32.2%), pulse oximetry low, 4572 (16.2%) and pulse oximetry probe off, 4036 (14.3%). Number of alarms with duration under 10 s was 14 936 (53%). Number of individual alarm sounds was 105 000, 469 per monitor per day. Of respiratory rate high alarms, 2846 (31.4%) had initial value below 30 breaths min^-1 . Of pulse oximetry low alarms, 2421 (53.0%) had initial value above 88%.

CONCLUSIONS

Alarm sound load, from individual alarm sounds, was nearly continuous in an emergency department observation room equipped with nine monitors. Intervention by the staff to the alarms was infrequent. More than half of the alarms were momentary.

The HEART score to identify emergency department patients suspected of an acute coronary syndrome who can be removed from cardiac monitoring: A retrospective chart review

OBJECTIVE

Continuous cardiac monitoring has been recommended for ED patients being evaluated for possible acute coronary syndrome (ACS) due to concern for arrhythmia, although evidence suggests this risk is low. Indiscriminate use of monitored beds restricts access for other critically unwell patients and contributes to overcrowding. The objective of the present study was to determine if a low/intermediate-risk HEART score identified patients at very low risk for a clinically important arrhythmia who could be removed from cardiac monitoring.

METHODS

This was a single centre, retrospective, cohort study of consecutive ED patients in a tertiary referral hospital evaluated for possible ACS from July to August 2017. Patients with ST-elevation myocardial infarction or an arrhythmia at presentation which would mandate monitoring were excluded. Data was obtained by medical chart review. The primary outcome was the occurrence of an arrhythmia requiring treatment while in ED.

RESULTS

Inter-rater reliability for data extraction demonstrated very strong agreement (kappa 0.87, 95% confidence interval 0.83-0.91). There were 653 participants included with 83 (12.7%) having a final diagnosis of ACS. Three (0.5%) clinically important arrhythmias occurred. There were no cases of ventricular tachycardia, ventricular fibrillation or cardiac arrest. Five hundred and forty (82.7%) participants were low/intermediate-risk HEART score and one (0.2%) clinically important arrhythmia occurred (this was supraventricular tachycardia treated by a valsalva manoeuvre).

CONCLUSION

Among ED patients presenting with a possible ACS, a low/intermediate-risk HEART score identified those at very low risk for having a clinically important arrhythmia while in ED.

Effect of default order set settings on telemetry ordering

OBJECTIVE

To investigate the effects of adjusting the default order set settings on telemetry usage.

MATERIALS AND METHODS

We performed a retrospective, controlled, before-after study of patients admitted to a house staff medicine service at an academic medical center examining the effect of changing whether the admission telemetry order was pre-selected or not. Telemetry orders on admission and subsequent orders for telemetry were monitored pre- and post-change. Two other order sets that had no change in their default settings were used as controls.

RESULTS

Between January 1, 2017 and May 1, 2018, there were 1, 163 patients admitted using the residency-customized version of the admission order set which initially had telemetry pre-selected. In this group of patients, there was a significant decrease in telemetry ordering in the post-intervention period: from 79.1% of patients in the 8.5 months prior ordered to have telemetry to 21.3% of patients ordered in the 7.5 months after (χ2 = 382; P < .001). There was no significant change in telemetry usage among patients admitted using the two control order sets.

DISCUSSION

Default settings have been shown to affect clinician ordering behavior in multiple domains. Consistent with prior findings, our study shows that changing the order set settings can significantly affect ordering practices. Our study was limited in that we were unable to determine if the change in ordering behavior had significant impact on patient care or safety.

CONCLUSION

Decisions about default selections in electronic health record order sets can have significant consequences on ordering behavior.

Improving the Safety, Effectiveness, and Efficiency of Clinical Alarm Systems: Simulation-Based Usability Testing of Physiologic Monitors

BACKGROUND

Clinical alarm system safety is a national patient safety goal in the United States. Physiologic monitors are associated with the highest number of device alarms and alarm-related deaths. However, research involving nurses' use of physiologic monitors is rare. Hence, the identification of critical usability issues for monitors, especially those related to patient safety, is a nursing imperative.

OBJECTIVE

This study examined nurses' usability of physiologic monitors in intensive care units with respect to the effectiveness and efficiency of monitor use.

METHODS

In total, 30 nurses from 4 adult intensive care units completed 40 tasks in a simulation environment. The tasks were common monitoring tasks that were crucial for appropriate monitoring and safe alarm management across four categories of competencies: admitting, transferring, and discharging patients using the monitors (7 tasks); managing measurements and monitor settings (23 tasks); performing electrocardiogram (ECG) analysis (7 tasks); and troubleshooting alarm conditions (3 tasks). The nurse-monitor interaction was video-recorded. The principal investigator and two expert intensive care units nurse educators identified, classified, and validated task success (effectiveness) and the time of task completion (efficiency).

RESULTS

Among the 40 tasks, only 2 (5%) were successfully completed by all the nurses. At least 1-27 (3%-90%) nurses abandoned or did not correctly perform 38 tasks. The task with the shortest completion time was "take monitor out of standby" (mean 0:02, SD 0:01 min:s), whereas the task "record a 25 mm/s ECG strip of any of the ECG leads" had the longest completion time (mean 1:14, SD 0:32 min:s). The total time to complete 37 navigation-related tasks ranged from a minimum of 3 min 57 s to a maximum of 32 min 42 s. Regression analysis showed that it took 6 s per click or step to successfully complete a task. To understand the nurses' thought processes during monitor navigation, the authors analyzed the paths of the 2 tasks with the lowest successful completion rates, where only 13% (4/30) of the nurses correctly completed these 2 tasks. Although 30% (9/30) of the nurses accessed the correct screen first for task 1 and task 2, they could not find their way easily from there to successfully complete the 2 tasks.

CONCLUSIONS

Usability testing of physiologic monitors revealed major ineffectiveness and inefficiencies in the current nurse-monitor interactions. The results indicate the potential for safety and productivity issues in completing routine tasks. Training on monitor use should include critical monitoring functions that are necessary for safe, effective, efficient, and appropriate monitoring to include knowledge of the shortest navigation path. It is imperative that vendors' future monitor designs mimic clinicians' thought processes for successful, safe, and efficient monitor navigation.

Lessons Learned from Efforts to Reduce Overuse of Cardiac Telemetry Monitoring

BACKGROUND

Inappropriate use of telemetry monitoring is common, increasing costs, false alarms, and length of stay. The Society of Hospital Medicine and Choosing Wisely encourage the use of discontinuation protocols.

METHODS

This quality improvement initiative measured the impact of an educational intervention and distribution of performance reports for physicians and residents on the general medicine service. The intervention group received a 15-minute didactic session on appropriate indications for telemetry followed by weekly performance reports for 78 weeks. A segmented linear regression model and Student's t-test were used to determine intervention effects on percentage of patients on telemetry and telemetry orders lasting more than 48 hours.

RESULTS

Prior to the intervention, 4.8% of patients received telemetry monitoring; 13.4% of telemetry orders exceeded 48 hours. The control service had a baseline telemetry utilization of 2.4%; 1.2% of telemetry orders exceeded 48 hours. After the intervention, 3.9% of patients received telemetry monitoring; 10.6% of telemetry orders exceeded 48 hours. The control service had a postintervention telemetry utilization of 2.1%; 1.1% of telemetry orders exceeded 48 hours. The Student's t-test showed a statistically significant (p = 0.002) decrease in telemetry ordering rate on the intervention service and no significant change in the control group. However, when using segmented linear regression analysis, these changes could not be attributed to the intervention nor were there any significant changes in balancing metrics.

CONCLUSION

Education and weekly performance feedback did not significantly impact telemetry according to segmented linear regression results. Segmented linear regression analysis of an interrupted time series yielded significantly different results from a pre-post comparison using Student's t-test. Rigorous evaluation is vital to decreasing unnecessary care and successful reduction in unnecessary care may require interventions that capitalize on systems-level change.

Feasibility and Usability of Patch-based Continuous Cardiac Rhythm Monitoring in Comparison with Traditional Telemetry in Noncritically Ill Hospitalized Patients

Research on traditional cardiac telemetry demonstrates that excessive alarms are related to lead failures and noise-related interruptions. Patch-based continuous cardiac rhythm monitoring (CCRM) has emerged in outpatient ambulatory monitoring situations as a means to improve recording fidelity. In this study, patients hospitalized but not in the intensive care unit were simultaneously monitored via telemetry in parallel with the use of the Vital Signs Patch™ (VSP) CCRM system (LifeWatch Services, Rosemont, IL, USA), applying standardized monitoring and notifications provided by an off-site central monitoring unit (CMU). Among 11 patients (55% male; age: 66.8 ± 12.5 years), there were 42 CMU detections and 98 VSP detections. The VSP device was successfully applied by nursing with connectivity established in all 11 patients (100%). There were no VSP device–related adverse events or skin eruptions during the study. The CMU agreed with 59 (60%) of 98 VSP detections. Among those detections marked by disagreement 30 (77%) of 39 VSP detections were related to clinically meaningful arrhythmias (atrial: n = 9; ventricular: n = 7; brady-: n = 14) undetected by VSP due to noise. In two patients (18%), there were four clinically meaningful atrial fibrillation detections not recorded by the CMU. In conclusion, patch-based CCRM requires further development and review to replace traditional cardiac telemetry monitoring but could evolve into an appropriate method to detect clinically meaningful events missed by traditional methods if noise issues can be mitigated.

Routine Continuous Electrocardiographic Monitoring Following Percutaneous Coronary Interventions

BACKGROUND

The clinical utility of routine electrocardiographic monitoring following percutaneous coronary interventions (PCI) is not well studied.

METHODS

We prospectively evaluated the incidence, cost, and the clinical implications of actionable arrhythmia alarms on telemetry monitoring following PCI. One thousand three hundred fifty-eight PCI procedures (989 [72.8%] for acute coronary syndrome and 369 [27.2%] for stable angina) on patients admitted to nonintensive care unit were identified and divided into 2 groups; group 1, patients with actionable alarms (AA) and group 2, patients with non-AA. AA included (1) ≥3 s electrical pause or asystole; (2) high-grade Mobitz type II atrioventricular block or complete heart block; (3) ventricular fibrillation; (4) ventricular tachycardia (>15 beats); (5) atrial fibrillation with rapid ventricular response; (6) supraventricular tachycardia (>15 beats). Primary outcomes were 30-day all-cause mortality. Cost-savings analysis was performed.

RESULTS

Incidence of AA was 2.2% (37/1672). Time from end of procedure to AA was 5.5 (0.5, 24.5) hours. Patients with AA were older, presented with acute congestive heart failure or non-ST-segment-elevation myocardial infarction, and had multivessel or left main disease. The 30-day all-cause mortality was significantly higher in patients with AA (6.5% versus 0.3% in non-AA [P<0.001]). Applying the standardized costing approach and tailored monitoring per the American Heart Association guidelines lead to potential cost savings of $622 480.95 for the entire population.

CONCLUSIONS

AA following PCI were infrequent but were associated with increase in 30-day mortality. Following American Heart Association guidelines for monitoring after PCI can lead to substantial cost saving.

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.

Assessment Of Ambient-Noise Exposure Among Female Nurses In Surgical Cardiac Intensive Care Unit

PURPOSE

To measure noise levels in the Saud Albabtain Cardiac Center cardiac surgical intensive-care unit (CSICU) at different locations to find out the prevalence of noise-induced hearing loss among female nurses.

METHODS

Ambient CSICU noise was measured using a sound-level meter and personal noise dosimeter during morning and night shifts (12 hours each) for 30 days. An audiometry test and questionnaire were used to test nursing responses to noise levels.

RESULTS

Mean 12-hour average noise levels at the station during night shift were 60.3±7.1 dB(A) and inside rooms 62.48±8.02 dB(A). However, during morning shift 64.1±8.4 dB(A) in the rooms was recorded, while 68.8±8.2 dB(A) was recorded at the station, with a significant difference between the shifts (p<0.0001). ICU monitors recorded the highest noise-source levels of 82.7±5.3 dB(A). The lowest significant source was the suction machines, with an average of 67.1±12.5 dB(A). A significant correlation between decibel loss and nurse experience was observed.

CONCLUSION

Noise levels in the CSICU at Saud Albabtain Cardiac Center were higher than World Health Organization standards. CSICU nurses are exposed to noise levels that can affect their hearing capacity. Further research isneeded for effective medical device-alarm management.

Indication-specific event rates among hospitalized patients undergoing continuous cardiac monitoring

Background

Cardiac telemetry monitoring is widely utilized for a variety of clinical indications, yet indication‐specific event rates for monitored patients are seldomly reported.

Hypothesis

High‐risk hospitalized patients for clinical deterioration can be identified using standardized telemetry monitoring indications.

Methods

Adjudicated data from events triggering emergency response team (ERT) activation were systematically characterized at the Cleveland Clinic from among standardized telemetry indications ordered over a 13‐month period.

Results

Among 72 199 orders created for telemetry monitored patients, ERT activation occurred in 2677 patients (3.7%), of which 1326 (49.5%) were cardiac‐related. Patients with deep venous thrombosis or pulmonary embolism (DVT/PE) demonstrated the highest overall event rate (ERT: n = 41 of 593 pts [6.9%]; 25/41 cardiac related [61%]). Cardiac‐related events were proportionally highest among patients with coronary disease awaiting revascularization (ERT: n = 19 of 847 patients [2.2%]; 13/19 cardiac‐related [68.4%]). Arrhythmia‐specific events were highest among patients who underwent cardiac surgery (n = 78 of 193 cardiac‐related ERT [40.4%]), and patients with known or suspected tachyarrhythmias (n = 318 of 788 cardiac‐related ERT [40.4%]). Bubble plot analysis identified patients hospitalized with DVT/PE, drug or alcohol exposures, and acute coronary syndrome as among the highest overall and cardiac‐related events while identifying patients with respiratory disorder monitoring indications as carrying the highest noncardiac event rate.

Conclusion

High‐risk hospitalized patients can be identified by telemetry indication and prioritized according to concerns for cardiac, arrhythmia‐specific and noncardiac clinical deterioration. This is particularly useful when monitored bed resources are constrained.

Supporting multiple patient monitoring with head-worn displays and spearcons

In hospitals, clinicians often need to monitor several patients while performing other tasks. However, visual displays that show patients' vital signs are in fixed locations and auditory alarms intended to alert clinicians may be missed. Information such as spearcons (time-compressed speech earcons) that 'travels' with the clinician and is delivered by earpiece and/or head-worn displays (HWDs), might overcome these problems. In this study, non-clinicians monitored five simulated patients in three 10-min scenarios while performing a demanding tracking task. Monitoring accuracy was better for participants using spearcons and a HWD (88.7%) or a HWD alone (86.2%) than for participants using spearcons alone (74.1%). Participants using the spearcons and HWD (37.7%) performed the tracking task no differently from participants using spearcons alone (37.1%) but participants using the HWD alone performed worse overall (33.1%). The combination of both displays may be a suitable solution for monitoring multiple patients.

Contribution of Electrocardiographic Accelerated Ventricular Rhythm Alarms to Alarm Fatigue

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.

Perceptions and practices related to clinical alarms

BACKGROUND

Clinical alarms represent the top hazard listed in the "Top Ten Health Technology Hazards" report. Frequent false alarms can disrupt patient care and reduce trust in alarms.

AIM

The aim of the present study was to investigate the perceptions and practices of critical and noncritical care nurses regarding clinical alarms.

METHODOLOGY

This was a descriptive analytical study conducted from October 2016 to February 2017 at three hospitals on 197 nurses at Neyshabur University of Medical Sciences in Neyshabur, Northeastern Iran. Participants were selected through stratified random sampling. The perceptions were measured through the 2011 Health care Technology Foundation Clinical Alarms Survey.

RESULTS

More than half of the nurses believed that frequent false alarms reduced trust in alarms, leading nurses to inappropriately disable alarms. The nurses ranked frequent false alarms as the most important issue in response to alarms. More than 60% of the nurses indicated that they needed more training on the use of bedside and central monitors.

CONCLUSION

The result of this study suggested that frequent false alarms, as the most important issue related to alarms, should be taken into account by hospital administrators and researchers to decrease alarm fatigue and improve alarm system safety. More specialized clinical policies and procedures for alarm management should also be considered.

Assessment of a Targeted Electronic Health Record Intervention to Reduce Telemetry Duration: A Cluster-Randomized Clinical Trial

IMPORTANCE

Physicians frequently use cardiac monitoring, or telemetry, beyond the duration recommended by published practice standards, resulting in "alarm fatigue" and excess cost. Prior studies have demonstrated an association between multicomponent quality improvement interventions and safe reduction of telemetry duration.

OBJECTIVE

To determine if a single-component intervention, a targeted electronic health record (EHR) alert, could achieve similar gains to multicomponent interventions and safely reduce unnecessary monitoring.

DESIGN, SETTING, AND PARTICIPANTS

This cluster-randomized clinical trial was conducted between November 2016 and May 2017 on the general medicine service of the Division of Hospital Medicine at the University of California, San Francisco Medical Center and included physicians of 12 inpatient medical teams (6 intervention, 6 control).

INTERVENTIONS

The EHR alert was randomized to half of the teams on the general medicine service. The alert displayed during daytime hours when physicians attempted to place an order for patients not in the intensive care unit whose telemetry order duration exceeded the recommended duration for a given indication.

MAIN OUTCOMES AND MEASURES

The primary outcome was telemetry monitoring hours per hospitalization, which was measured using time-stamped orders data from the EHR database. Physician responses to the alert were collected using EHR reporting tools. The potential adverse outcomes of rapid-response calls and medical emergency events were measured by counting the notes documenting these events in the EHR.

RESULTS

Of the 1021 patients included in this study, in the intervention arm, there was a mean (SD) age of 64.5 (18.9) and 215 (45%) were women; in the control arm, there was a mean (SD) age of 63.8 (19.1) and 249 (46%) were women. The 12 teams were stratified to 8 house-staff teams and 4 hospitalist teams, with 499 hospitalizations analyzed in the intervention arm and 567 hospitalizations analyzed in the control arm. The alert prompted a significant reduction in telemetry monitoring duration (-8.7 hours per hospitalization; 95% CI, -14.1 to -3.5 hours; P = .001) with no significant change in rapid-response calls or medical emergency events. The most common physician response to the alert was to discontinue telemetry monitoring (62% of 200 alerts).

CONCLUSIONS AND RELEVANCE

A targeted EHR alert can safely and successfully reduce cardiac monitoring by prompting discontinuation when appropriate. This single-component electronic intervention is less resource intensive than typical multicomponent interventions that include human resources.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02529176.

Alarm-Related Workload in Default and Modified Alarm Settings and the Relationship Between Alarm Workload, Alarm Response Rate, and Care Provider Experience: Quantification and Comparison Study

Background

Delayed or no response to impending patient safety–related calls, poor care provider experience, low job satisfaction, and adverse events are all unwanted outcomes of alarm fatigue. Nurses often cite increases in alarm-related workload as a reason for alarm fatigue, which is a major contributor to the aforementioned unwanted outcomes. Increased workload affects both the care provider and the patient. No studies to date have evaluated the workload while caring for patients and managing alarms simultaneously and related it to the primary measures of alarm fatigue—alarm response rate and care provider experience. Many studies have assessed the effect of modifying the default alarm setting; however, studies on the perceived workload under different alarm settings are limited.

Objective

This study aimed to assess nurses’ or assistants’ perceived workload index of providing care under different clinical alarm settings and establish the relationship between perceived workload, alarm response rate, and care provider experience.

Methods

In a clinical simulator, 30 participants responded to alarms that occurred on a physiological monitor under 2 conditions (default and modified) for a given clinical condition. Participants completed a National Aeronautics and Space Administration-Task Load Index questionnaire and rated the demand experienced on a 20-point visual analog scale with low and high ratings. A correlational analysis was performed to assess the relationships between the perceived workload score, alarm response rate, and care provider experience.

Results

Participants experienced lower workloads when the clinical alarm threshold limits were modified according to patients’ clinical conditions. The workload index was higher for the default alarm setting (57.60 [SD 2.59]) than for the modified alarm setting (52.39 [SD 2.29]), with a statistically significant difference of 5.21 (95% CI 3.38-7.04), t₂₈=5.838, P<.05. Significant correlations were found between the workload index and alarm response rate. There was a strong negative correlation between alarm response rate and perceived workload, ρ₂₈=−.54, P<.001 with workload explaining 29% of the variation in alarm response rate. There was a moderate negative correlation between the experience reported during patient care and the perceived workload, ρ₂₈=−.49, P<.05.

Conclusions

The perceived workload index was comparatively lower with alarm settings modified for individual patient care than in an unmodified default clinical alarm setting. These findings demonstrate that the modification of clinical alarm limits positively affects the number of alarms accurately addressed, care providers’ experience, and overall satisfaction. The findings support the removal of nonessential alarms based on patient conditions, which can help care providers address the remaining alarms accurately and provide better patient care.

Critical Care Nurses' Cognitive Ergonomics Related to Medical Device Alarms

This study uniquely gained insight into the intricacy of intensive care nurses' decision-making process when responding to and managing device alarms. Difficulty in responding to alarms included low staffing, multiple job responsibilities, and competing priority tasks. Novice nurses are more tolerant of alarms sounding owing to a lower threshold of comfort with resetting or silencing alarms; more experienced nurses are more comfortable resetting alarm limits to the patient's baseline. Understanding the decision-making process used by nurses can guide the development of policies and learning experiences that are crucial clinical support for alarm management.

Does this patient need telemetry? An analysis of telemetry ordering practices at an academic medical center

INTRODUCTION

The American Heart Association and Choosing Wisely campaign recommend guideline-based usage of telemetry. Inappropriate use leads to increased costs, alarm fatigue, and inefficient nursing care. This study assesses provider ordering practices for telemetry at a US-based academic hospital.

METHODS

This retrospective study includes all telemetry orders in the medicine and progressive care units from April 2014 to March 2015. Indications were grouped into categories per American Heart Association guidelines.

RESULTS

The top 3 cardiac indications included angina/acute coronary syndrome (35.3%), arrhythmias (19.7%), and heart failure (10.2%). However, noncardiac indications accounted for 20.2% of orders, including respiratory conditions (17.4%), infection (17.4%), substance abuse (14.0%), bleeding (12.4%), vital sign monitoring (10.4%), altered mental status (7.0%), and pulmonary embolus/deep vein thrombosis (7.0%).

CONCLUSIONS

One-fifth of patients were monitored on telemetry for noncardiac indications. We recommend further study on the benefits and risks of telemetry in these patients and systems-based changes for appropriate usage.

Using a Medical Intranet of Things System to Prevent Bed Falls in an Acute Care Hospital: A Pilot Study

Background

Hospitalized patients in the United States experience falls at a rate of 2.6 to 17.1 per 1000 patient-days, with the majority occurring when a patient is moving to, from, and around the bed. Each fall with injury costs an average of US $14,000.

Objective

The aim was to conduct a technology evaluation, including feasibility, usability, and user experience, of a medical sensor-based Intranet of things (IoT) system in facilitating nursing response to bed exits in an acute care hospital.

Methods

Patients 18 years and older with a Morse fall score of 45 or greater were recruited from a 35-bed medical-surgical ward in a 317-bed Massachusetts teaching hospital. Eligible patients were recruited between August 4, 2015 and July 31, 2016. Participants received a sensor pad placed between the top of their mattress and bed sheet. The sensor pad was positioned to monitor movement from patients’ shoulders to their thighs. The SensableCare System was evaluated for monitoring patient movement and delivering timely alerts to nursing staff via mobile devices when there appeared to be a bed-exit attempt. Sensor pad data were collected automatically from the system. The primary outcomes included number of falls, time to turn off bed-exit alerts, and the number of attempted bed-exit events. Data on patient falls were collected by clinical research assistants and confirmed with the unit nurse manager. Explanatory variables included room locations (zones 1-3), day of the week, nursing shift, and Morse Fall Scale (ie, positive fall history, positive secondary diagnosis, positive ambulatory aid, weak impaired gait/transfer, positive IV/saline lock, mentally forgets limitations). We also assessed user experience via nurse focus groups. Qualitative data regarding staff interactions with the system were collected during two focus groups with 25 total nurses, each lasting approximately 1.5 hours.

Results

A total of 91 patients used the system for 234.0 patient-days and experienced no bed falls during the study period. On average, patients were assisted/returned to bed 46 seconds after the alert system was triggered. Response times were longer during the overnight nursing shift versus day shift (P=.005), but were independent of the patient’s location on the unit. Focus groups revealed that nurses found the system integrated well into the clinical nursing workflow and the alerts were helpful in patient monitoring.

Conclusions

A medical IoT system can be integrated into the existing nursing workflow and may reduce patient bed fall risk in acute care hospitals, a high priority but an elusive patient safety challenge. By using an alerting system that sends notifications directly to nurses’ mobile devices, nurses can equally respond to unassisted bed-exit attempts wherever patients are located on the ward. Further study, including a fully powered randomized controlled trial, is needed to assess effectiveness across hospital settings.

2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry

Ambulatory ECG (AECG) is very commonly employed in a variety of clinical contexts to detect cardiac arrhythmias and/or arrhythmia patterns which are not readily obtained from the standard ECG. Accurate and timely characterization of arrhythmias is crucial to direct therapies that can have an important impact on diagnosis, prognosis or patient symptom status. The rhythm information derived from the large variety of AECG recording systems can often lead to appropriate and patient-specific medical and interventional management. The details in this document provide background and framework from which to apply AECG techniques in clinical practice, as well as clinical research.

Prospective validation of a clinical decision rule to identify patients presenting to the emergency department with chest pain who can safely be removed from cardiac monitoring

BACKGROUND

Most patients with chest pain in the emergency department are assigned to cardiac monitoring for several hours, blocking access for patients in greater need. We sought to validate a previously derived decision rule for safe removal of patients from cardiac monitoring after initial evaluation in the emergency department.

METHODS

We prospectively enrolled adults (age ≥ 18 yr) who presented with chest pain and were assigned to cardiac monitoring at 2 academic emergency departments over 18 months. We collected standardized baseline characteristics, findings from clinical evaluations and predictors for the Ottawa Chest Pain Cardiac Monitoring Rule: whether the patient is currently free of chest pain, and whether the electrocardiogram is normal or shows only nonspecific changes. The outcome was an arrhythmia requiring intervention in the emergency department or within 8 hours of presentation to the emergency department. We calculated diagnostic characteristics for the clinical prediction rule.

RESULTS

We included 796 patients (mean age 63.8 yr, 55.8% male, 8.9% admitted to hospital). Fifteen patients (1.9%) had an arrhythmia, and the rule performed with the following characteristics: sensitivity 100% (95% confidence interval [CI] 78.2%-100%) and specificity 36.4% (95% CI 33.0%-39.6%). Application of the Ottawa Chest Pain Cardiac Monitoring Rule would have allowed 284 out of 796 patients (35.7%) to be safely removed from cardiac monitoring.

INTERPRETATION

We successfully validated the decision rule for safe removal of a large subset of patients with chest pain from cardiac monitoring after initial evaluation in the emergency department. Implementation of this simple yet highly sensitive rule will allow for improved use of health care resources.

Understanding Clinical Alarm Safety

Patient safety organizations and health care accreditation agencies recognize the significance of clinical alarm hazards. The Association for the Advancement of Medical Instrumentation, a nonprofit organization focused on development and use of safe and effective medical equipment, identifies alarm management as a major issue for health care organizations. ECRI Institute, a nonprofit organization that researches approaches for improving patient safety and quality of care, identifies alarm hazards as the most significant of the "Top Ten Health Technology Hazards" for 2014. A new Joint Commission National Patient Safety Goal focusing on clinical alarm safety contains new requirements for accredited hospitals to be fully implemented by 2016. Through a fictional unfolding case study, this article reviews selected contributing factors to clinical alarm hazards present in inpatient, high-acuity settings. Understanding these factors improves contributions by nurses to clinical alarm safety practice.

Proper skin preparation and electrode placement decreases alarms on a telemetry unit

BACKGROUND

An estimated 85% to 99% of electrocardiographic (ECG) alarms are false, leading to alarm fatigue, which is associated with increased risk of death among hospitalized patients.

OBJECTIVE

The aim of this study was to examine the effect of proper skin preparation and electrode placement on frequency of ECG alarms on a telemetry unit.

METHOD

A prospective descriptive design was used to test the effect of proper skin preparation and ECG electrode placement. Purposive sampling of patients (n = 15) admitted to a telemetry hospital in a suburban Veterans Affairs Medical Center was used. Alarms were counted for 24 hours after admission, electrodes were replaced using proper technique, and alarms were counted for 24 hours after electrode change. Bootstrapping was used to double the sample size for analysis.

RESULTS

Electrocardiographic alarms decreased significantly (P < .05) after proper skin preparation and electrode placement (95% confidence interval, 1.273-82.327).

DISCUSSION

Proper skin preparation and ECG electrode placement reduced alarms. Reducing alarm frequency is vital to decreasing alarm fatigue and increasing patient safety.

Safety analysis of proposed data-driven physiologic alarm parameters for hospitalized children

INTRODUCTION

Modification of alarm limits is one approach to mitigating alarm fatigue. We aimed to create and validate heart rate (HR) and respiratory rate (RR) percentiles for hospitalized children, and analyze the safety of replacing current vital sign reference ranges with proposed data-driven, age-stratified 5th and 95th percentile values.

METHODS

In this retrospective cross-sectional study, nurse-charted HR and RR data from a training set of 7202 hospitalized children were used to develop percentile tables. We compared 5th and 95th percentile values with currently accepted reference ranges in a validation set of 2287 patients. We analyzed 148 rapid response team (RRT) and cardiorespiratory arrest (CRA) events over a 12-month period, using HR and RR values in the 12 hours prior to the event, to determine the proportion of patients with out-of-range vitals based upon reference versus data-driven limits.

RESULTS

There were 24,045 (55.6%) fewer out-of-range measurements using data-driven vital sign limits. Overall, 144/148 RRT and CRA patients had out-of-range HR or RR values preceding the event using current limits, and 138/148 were abnormal using data-driven limits. Chart review of RRT and CRA patients with abnormal HR and RR per current limits considered normal by data-driven limits revealed that clinical status change was identified by other vital sign abnormalities or clinical context.

CONCLUSIONS

A large proportion of vital signs in hospitalized children are outside presently used norms. Safety evaluation of data-driven limits suggests they are as safe as those currently used. Implementation of these parameters in physiologic monitors may mitigate alarm fatigue. Journal of Hospital Medicine 2015;11:817-823. © 2015 Society of Hospital Medicine.

Role of Large Clinical Datasets From Physiologic Monitors in Improving the Safety of Clinical Alarm Systems and Methodological Considerations: A Case From Philips Monitors

BACKGROUND

Large datasets of the audit log of modern physiologic monitoring devices have rarely been used for predictive modeling, capturing unsafe practices, or guiding initiatives on alarm systems safety.

OBJECTIVE

This paper (1) describes a large clinical dataset using the audit log of the physiologic monitors, (2) discusses benefits and challenges of using the audit log in identifying the most important alarm signals and improving the safety of clinical alarm systems, and (3) provides suggestions for presenting alarm data and improving the audit log of the physiologic monitors.

METHODS

At a 20-bed transplant cardiac intensive care unit, alarm data recorded via the audit log of bedside monitors were retrieved from the server of the central station monitor.

RESULTS

Benefits of the audit log are many. They include easily retrievable data at no cost, complete alarm records, easy capture of inconsistent and unsafe practices, and easy identification of bedside monitors missed from a unit change of alarm settings adjustments. Challenges in analyzing the audit log are related to the time-consuming processes of data cleaning and analysis, and limited storage and retrieval capabilities of the monitors.

CONCLUSIONS

The audit log is a function of current capabilities of the physiologic monitoring systems, monitor's configuration, and alarm management practices by clinicians. Despite current challenges in data retrieval and analysis, large digitalized clinical datasets hold great promise in performance, safety, and quality improvement. Vendors, clinicians, researchers, and professional organizations should work closely to identify the most useful format and type of clinical data to expand medical devices' log capacity.

A practical algorithm to reduce false critical ECG alarms using arterial blood pressure and/or photoplethysmogram waveforms

There has been a high rate of false alarms for the critical electrocardiogram (ECG) arrhythmia events in intensive care units (ICUs), from which the 'crying-wolf' syndrome may be resulted and patient safety may be jeopardized. This article presents an algorithm to reduce false critical arrhythmia alarms using arterial blood pressure (ABP) and/or photoplethysmogram (PPG) waveform features. We established long duration reference alarm datasets which consist of 573 ICU waveform-alarm records (283 for development set and 290 for test set) with total length of 551 patent days. Each record has continuous recordings of ECGs, ABP and/or PPG signals and contains one or multiple critical ECG alarms. The average length of a record is 23 h. There are totally 2408 critical ECG alarms (1414 in the development set and 994 in the test set), each of which was manually annotated by experts. The algorithm extracts ABP/PPG pulse features on a beat-by-beat basis. For each pulse, five event feature indicators (EFIs), which correspond to the five critical ECG alarms, are generated. At the time of a critical ECG alarm, the corresponding EFI values of those ABP/PPG pulses around the alarm time are checked for adjudicating (accept/reject) this alarm. The algorithm retains all (100%) the true alarms and significantly reduces the false alarms. Our results suggest that the algorithm is effective and practical on account of its real-time dynamic processing mechanism and computational efficiency.

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.

Systematic Review of Physiologic Monitor Alarm Characteristics and Pragmatic Interventions to Reduce Alarm Frequency

BACKGROUND

Alarm fatigue from frequent nonactionable physiologic monitor alarms is frequently named as a threat to patient safety.

PURPOSE

To critically examine the available literature relevant to alarm fatigue.

DATA SOURCES

Articles published in English, Spanish, or French between January 1980 and April 2015 indexed in PubMed, Cumulative Index to Nursing and Allied Health Literature, Scopus, Cochrane Library, Google Scholar, and ClinicalTrials.gov.

STUDY SELECTION

Articles focused on hospital physiologic monitor alarms addressing any of the following: (1) the proportion of alarms that are actionable, (2) the relationship between alarm exposure and nurse response time, and (3) the effectiveness of interventions in reducing alarm frequency.

DATA EXTRACTION

We extracted data on setting, collection methods, proportion of alarms determined to be actionable, nurse response time, and associations between interventions and alarm rates.

DATA SYNTHESIS

Our search produced 24 observational studies focused on alarm characteristics and response time and 8 studies evaluating interventions. Actionable alarm proportion ranged from <1% to 36% across a range of hospital settings. Two studies showed relationships between high alarm exposure and longer nurse response time. Most intervention studies included multiple components implemented simultaneously. Although studies varied widely, and many had high risk of bias, promising but still unproven interventions include widening alarm parameters, instituting alarm delays, and using disposable electrocardiographic wires or frequently changed electrocardiographic electrodes.

CONCLUSIONS

Physiologic monitor alarms are commonly nonactionable, and evidence supporting the concept of alarm fatigue is emerging. Several interventions have the potential to reduce alarms safely, but more rigorously designed studies with attention to possible unintended consequences are needed.

Changes in Default Alarm Settings and Standard In-Service are Insufficient to Improve Alarm Fatigue in an Intensive Care Unit: A Pilot Project

Background

Clinical alarm systems safety is a national concern, specifically in intensive care units (ICUs) where alarm rates are known to be the highest. Interventional projects that examined the effect of changing default alarm settings on overall alarm rate and on clinicians’ attitudes and practices toward clinical alarms and alarm fatigue are scarce.

Objective

To examine if (1) a change in default alarm settings of the cardiac monitors and (2) in-service nursing education on cardiac monitor use in an ICU would result in reducing alarm rate and in improving nurses’ attitudes and practices toward clinical alarms.

Methods

This quality improvement project took place in a 20-bed transplant/cardiac ICU with a total of 39 nurses. We implemented a unit-wide change of default alarm settings involving 17 parameters of the cardiac monitors. All nurses received an in-service education on monitor use. Alarm data were collected from the audit log of the cardiac monitors 10 weeks before and 10 weeks after the change in monitors’ parameters. Nurses’ attitudes and practices toward clinical alarms were measured using the Healthcare Technology Foundation National Clinical Alarms Survey, pre- and postintervention.

Results

Alarm rate was 87.86 alarms/patient day (a total of 64,500 alarms) at the preintervention period compared to 59.18 alarms/patient day (49,319 alarms) postintervention (P=.01). At baseline, Arterial Blood Pressure (ABP), Pair Premature Ventricular Contractions (PVCs), and Peripheral Capillary Oxygen Saturation (SpO2) alarms were the highest. ABP and SpO2 alarms remained among the top three at the postproject period. Out of the 39 ICU nurses, 24 (62%) provided complete pre- and postproject survey questionnaires. Compared to the preintervention survey, no remarkable changes in the postproject period were reported in nurses’ attitudes. Themes in the narrative data were related to poor usability of cardiac monitors and the frequent alarms. The data showed great variation among nurses in terms of changing alarm parameters and frequency of replacing patients' electrodes. Despite the in-service, 50% (12/24) of the nurses specified their need for more training on cardiac monitors in the postproject period.

Conclusions

Changing default alarm settings and standard in-service education on cardiac monitor use are insufficient to improve alarm systems safety. Alarm management in ICUs is very complex, involving alarm management practices by clinicians, availability of unit policies and procedures, unit layout, complexity and usability of monitoring devices, and adequacy of training on system use. The complexity of the newer monitoring systems requires urgent usability testing and multidimensional interventions to improve alarm systems safety and to attain the Joint Commission National Patient Safety Goal on alarm systems safety in critical care units.

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

BACKGROUND

As many as 99% of alarm signals may not need any intervention and can result in patients’ deaths. Alarm management is now a Joint Commission National Patient Safety Goal.

OBJECTIVES

To reduce the number of nuisance electrocardiographic alarm signals in adult patients on the medical cardiovascular care unit.

METHODS

A quality improvement process was used that included eliminating duplicative alarms, customizing alarms, changing electrocardiography electrodes daily, standardizing skin preparation, and using disposable electrocardiography leads.

RESULTS

In the cardiovascular care unit, the mean number of electrocardiographic alarm signals per day decreased from 28.5 (baseline) to 3.29, an 88.5% reduction.

CONCLUSION

Use of a bundled approach to managing alarm signals decreased the mean number of alarm signals in a cardiovascular care unit. (Critical Care Nurse. 2015;35[4]:15–23)

Effect of altering alarm settings: a randomized controlled study

Medical alarm signals are important for alerting clinicians to life-threatening conditions, but the high rate of false alarms can be problematic. Reduction in alarm signals may lead to increased staff responsiveness to alarms and create a quieter environment for patients. The effect of these changes on patient outcomes is uncertain.

METHODS

We conducted a pilot, prospective, randomized, controlled trial in the cardiac care unit (CCU) to test a study protocol and data collection instruments and to examine the differences in alarms between usual care and altered settings. Subjects were randomized daily to either standard or altered CCU alarm settings. Secondary outcomes included the number of clinically significant events (CSEs) detected, event-triggered interventions (ETIs), frequency of alarms per monitored bed, and patient complications.

RESULTS

Over the two-week study time frame, 22 unique patients were enrolled. There were 1,710 alarms over 163 hours of monitoring in the standard group and 1,165 alarms over 169 hours in the study group (P < 0.001). There were more CSEs detected (14 vs. 3) and ETIs (12 vs. 2) in the study group, but sample size was too small to determine efficacy. No cardiac arrests or adverse patient outcomes were observed in either group. All patients were discharged from the hospital. Study protocol and outcomes were feasible and lessons were learned.

CONCLUSION

This study demonstrated feasibility of a study protocol for conducting a randomized controlled trial to evaluate CSEs, ETIs, frequency of alarms, and adverse patient outcomes when altering default alarm settings. A longer study can be performed using a similar study design.

Nurses' Perceptions and Practices Toward Clinical Alarms in a Transplant Cardiac Intensive Care Unit: Exploring Key Issues Leading to Alarm Fatigue

Background

Intensive care units (ICUs) are complex work environments where false alarms occur more frequently than on non-critical care units. The Joint Commission National Patient Safety Goal .06.01.01 targeted improving the safety of clinical alarm systems and required health care facilities to establish alarm systems safety as a hospital priority by July 2014. An important initial step toward this requirement is identifying ICU nurses’ perceptions and common clinical practices toward clinical alarms, where little information is available.

Objective

Our aim was to determine perceptions and practices of transplant/cardiac ICU (TCICU) nurses toward clinical alarms and benchmark the results against the 2011 Healthcare Technology Foundation’s (HTF) Clinical Alarms Committee Survey.

Methods

A quality improvement project was conducted on a 20-bed TCICU with 39 full- and part-time nurses. Nurses were surveyed about their perceptions and attitudes toward and practices on clinical alarms using an adapted HTF clinical alarms survey. Results were compared to the 2011 HTF data. Correlations among variables were examined.

Results

All TCICU nurses provided usable responses (N=39, 100%). Almost all nurses (95%-98%) believed that false alarms are frequent, disrupt care, and reduce trust in alarm systems, causing nurses to inappropriately disable them. Unlike the 2011 HTF clinical alarms survey results, a significantly higher percentage of our TCICU nurses believed that existing devices are complex, questioned the ability and adequacy of the new monitoring systems to solve alarm management issues, pointed to the lack of prompt response to alarms, and indicated the lack of clinical policy on alarm management (P<.01). Major themes in the narrative data focused on nurses’ frustration related to the excessive number of alarms and poor usability of the cardiac monitors. A lack of standardized approaches exists in changing patients’ electrodes and individualizing parameters. Around 60% of nurses indicated they received insufficient training on bedside and central cardiac monitors. A correlation also showed the need for training on cardiac monitors, specifically for older nurses (P=.01).

Conclusions

False and non-actionable alarms continue to desensitize TCICU nurses, perhaps resulting in missing fatal alarms. Nurses’ attitudes and practices related to clinical alarms are key elements for designing contextually sensitive quality initiatives to fight alarm fatigue. Alarm management in ICUs is a multidimensional complex process involving usability of monitoring devices, and unit, clinicians, training, and policy-related factors. This indicates the need for a multi-method approach to decrease alarm fatigue and improve alarm systems safety.

Integrating monitor alarms with laboratory test results to enhance patient deterioration prediction

Patient monitors in modern hospitals have become ubiquitous but they generate an excessive number of false alarms causing alarm fatigue. Our previous work showed that combinations of frequently co-occurring monitor alarms, called SuperAlarm patterns, were capable of predicting in-hospital code blue events at a lower alarm frequency. In the present study, we extend the conceptual domain of a SuperAlarm to incorporate laboratory test results along with monitor alarms so as to build an integrated data set to mine SuperAlarm patterns. We propose two approaches to integrate monitor alarms with laboratory test results and use a maximal frequent itemsets mining algorithm to find SuperAlarm patterns. Under an acceptable false positive rate FPRmax, optimal parameters including the minimum support threshold and the length of time window for the algorithm to find the combinations of monitor alarms and laboratory test results are determined based on a 10-fold cross-validation set. SuperAlarm candidates are generated under these optimal parameters. The final SuperAlarm patterns are obtained by further removing the candidates with false positive rate>FPRmax. The performance of SuperAlarm patterns are assessed using an independent test data set. First, we calculate the sensitivity with respect to prediction window and the sensitivity with respect to lead time. Second, we calculate the false SuperAlarm ratio (ratio of the hourly number of SuperAlarm triggers for control patients to that of the monitor alarms, or that of regular monitor alarms plus laboratory test results if the SuperAlarm patterns contain laboratory test results) and the work-up to detection ratio, WDR (ratio of the number of patients triggering any SuperAlarm patterns to that of code blue patients triggering any SuperAlarm patterns). The experiment results demonstrate that when varying FPRmax between 0.02 and 0.15, the SuperAlarm patterns composed of monitor alarms along with the last two laboratory test results are triggered at least once for [56.7-93.3%] of code blue patients within an 1-h prediction window before code blue events and for [43.3-90.0%] of code blue patients at least 1-h ahead of code blue events. However, the hourly number of these SuperAlarm patterns occurring in control patients is only [2.0-14.8%] of that of regular monitor alarms with WDR varying between 2.1 and 6.5 in a 12-h window. For a given FPRmax threshold, the SuperAlarm set generated from the integrated data set has higher sensitivity and lower WDR than the SuperAlarm set generated from the regular monitor alarm data set. In addition, the McNemar's test also shows that the performance of the SuperAlarm set from the integrated data set is significantly different from that of the SuperAlarm set from the regular monitor alarm data set. We therefore conclude that the SuperAlarm patterns generated from the integrated data set are better at predicting code blue events.

A description of nurses' decision-making in managing electrocardiographic monitor alarms

AIMS AND OBJECTIVES

To describe the cues and factors that nurses use in their decision-making when responding to clinical alarms.

BACKGROUND

Alarms are designed to be very sensitive, and as a result, they are not very specific. Lack of adherence to the practice standards for electrocardiographic monitoring in hospital settings has been observed, resulting in overuse of the electrocardiographic monitoring. Monitoring without consideration of clinical indicators uses scarce healthcare resources and may even produce untoward circumstances because of alarm fatigue. With so many false alarms, alarm fatigue represents a symptom of a larger problem. It cannot be fixed until all of the factors that contribute to its existence have been examined.

DESIGN

This was a qualitative descriptive study.

METHOD

This study was conducted at an academic medical centre located in the Northeast United States. Eight participants were enrolled using purposive sampling. Nurses were observed for two three-hour periods. Following each observation, the nurse was interviewed using the critical decision method to describe the cognitive processes related to the alarm activities. Qualitative data from the conducted interviews were analysed via an a priori framework founded in the critical decision method.

RESULTS

This study reveals information, experience, guidance and decision-making as the four prominent categories contributing to nurses' decision-making in relation to alarm management. Managing technology was a category not identified a priori that emerged in the data analysis.

CONCLUSION

Nurses revealed a breadth of information needed to adequately identify and interpret monitor alarms, and how they used that information to put the alarms into the particular context of an individual patient's situations.

RELEVANCE TO CLINICAL PRACTICE

Understanding the cues and factors nurses use when responding to cardiac alarms will guide the development of learning experiences and inform policies to guide practice.

Alarm setting for the critically ill patient: a descriptive pilot survey of nurses' perceptions of current practice in an Australian Regional Critical Care Unit

AIM

The aim of this survey was to assess registered nurse's perceptions of alarm setting and management in an Australian Regional Critical Care Unit.

BACKGROUND

The setting and management of alarms within the critical care environment is one of the key responsibilities of the nurse in this area. However, with up to 99% of alarms potentially being false-positives it is easy for the nurse to become desensitised or fatigued by incessant alarms; in some cases up to 400 per patient per day. Inadvertently ignoring, silencing or disabling alarms can have deleterious implications for the patient and nurse.

METHOD

A total population sample of 48 nursing staff from a 13 bedded ICU/HDU/CCU within regional Australia were asked to participate. A 10 item open-ended and multiple choice questionnaire was distributed to determine their perceptions and attitudes of alarm setting and management within this clinical area.

RESULTS

Two key themes were identified from the open-ended questions: attitudes towards inappropriate alarm settings and annoyance at delayed responses to alarms. A significant number of respondents (93%) agreed that alarm fatigue can result in alarm desensitisation and the disabling of alarms, whilst 81% suggested the key factors are those associated with false-positive alarms and inappropriately set alarms.

CONCLUSION

This study contributes to what is known about alarm fatigue, setting and management within a critical care environment. In addition it gives an insight as to what nurses' within a regional context consider the key factors which contribute to alarm fatigue. Clearly nursing burnout and potential patient harm are important considerations for practice especially when confronted with alarm fatigue and desensitisation. Therefore, promoting and maintaining an environment of ongoing intra-professional communication and alarm surveillance are crucial in alleviating these potential problems.

Alarm Fatigue

Research has demonstrated that 72% to 99% of clinical alarms are false. The high number of false alarms has led to alarm fatigue. Alarm fatigue is sensory overload when clinicians are exposed to an excessive number of alarms, which can result in desensitization to alarms and missed alarms. Patient deaths have been attributed to alarm fatigue. Patient safety and regulatory agencies have focused on the issue of alarm fatigue, and it is a 2014 Joint Commission National Patient Safety Goal. Quality improvement projects have demonstrated that strategies such as daily electrocardiogram electrode changes, proper skin preparation, education, and customization of alarm parameters have been able to decrease the number of false alarms. These and other strategies need to be tested in rigorous clinical trials to determine whether they reduce alarm burden without compromising patient safety.

Nurses' response to frequency and types of electrocardiography alarms in a non-critical care setting: a descriptive study

BACKGROUND

An important role of the registered nurse is to identify patient deterioration by monitoring the patient condition and vital signs. Increasingly, this is supplemented with continuous electrocardiographic (ECG) monitoring. Continuous monitoring is inefficient in identifying deterioration because of the high number of false and nuisance alarms. Lack of strong evidence or formal guidelines for the care of patients receiving ECG monitoring has led clinicians to rely too heavily on this technology without consideration of its limitations. The nursing workload associated with alarm management remains unexamined.

OBJECTIVE

To describe nurses' routine practices related to continuous ECG monitoring, frequency and types of alarms, their associated nursing interventions, and the impact on the patient's plan of care.

METHODS

Design. Prospective, descriptive, observational study. Setting and participants. Between January 2011 and March 2011 we observed nine Registered Nurses providing care for patients receiving continuous ECG monitoring in non-critical care areas. The PI and two research assistants observed each nurse for two 3-h observation periods and recorded data on a researcher designed observation tool. At the end of each observation period, the observers printed the alarm events as recorded by the central monitoring computer.

RESULTS

Nurses responded to 46.8% of all alarms. During the observation period, there were no dysrhythmia adverse events. One patient had a change in condition requiring transfer to a higher level of care. A range of nursing interventions occurred in response to alarms.

CONCLUSION

Nurses routine practices related to monitoring continue to reveal gaps in practice related to alarm management. Observations of practice also revealed the difficulties and complexities of managing alarm systems and the range of nursing interventions associated with managing alarms.