Supplemental Table 2. KQ2: What are the negative effects on patients/families of alarm fatigue related to medical devices? None of these studies was funded by private industry.
Author, Publication Date, Country
Evidence type Sample Size Setting Intervention Medical device
evaluated? Study Findings Statistical tests Study
Quality
Bonafide et
al., 2015. US Observational
study 40 patients
(20 ward, 20 PICU/36 nurses 5070 alarms
Medical ward and intensive care unit (PICU) in a single pediatric hospital
None Bedside physiologic
monitor; alarms sent to pagers nurses carry
Primary outcome was nurse response time to critical alarms when no clinician was in room Only 12.9% and 1.0% of alarms in the PICU and ward were actionable, respectively
55.6% of potentially critical alarms occurred with no clinicians in the room. In the PICU, median response time was 3.3 minutes (IQR, 0.8–14.4). On the ward, median response time was 9.8 minutes (IQR, 3.2–22.4).
Kaplan-Meier plots and tabulated response times demonstrated the incremental relationships between each nonactionable alarm exposure category in the observed data
Accelerated failure-time regressions revealed significant incremental increases in the modeled response time as the number of preceding nonactionable alarms increased in both the PICU and ward settings.
Kaplan-Meier;
Accelerated failure-time Models
High
Deb et al., 2015, US
Observational study, survey
6 unit clerks and 18 nurses
8 bed ICU
None Telemetry
monitors
Defined alarm fatigue in terms of mental workload to measure the overwhelming situation and affect (boredom, apathy, and distrust) to measure desensitization.
Studied personality factors as an influencing variable.
84.6% of survey respondents confirmed frequent “nuisance” alarms which disrupt patient care, and reduce trust in alarms causing caregivers to disable alarms
1119 alarms (average of 116/pt/day); 88% were false, Only 64 of these alarms went to nurses.
Noise level was 50–70 dB (30–45 dB is recommended) (Konkani and Oakley, 2012).
Performance deterioration is the effect of a combination of alarm fatigue with working conditions and staff individuality for unit clerks and in the case of nurses and response time, alarm fatigue plays no role, only working conditions and staff individuality.
Descriptive;
Hierarchical analysis
Moderate
Buxton et al., 2012, US.
Laboratory study
12 young health adult volunteers
Sleep lab Controlled presentation of 14 sounds that are common in hospitals
Multiple including IV pump alarm
Sounds were administered at calibrated, increasing decibel levels (40 to 70 dB) during specific sleep Stages with measure of EEG documented arousal and sleep interruption
For each of 14 stimuli higher sound levels led to a
greater probability of sleep disruption. IV alarm and similar electronic sounds designed to alert medical staff, were consistently more arousing than other sounds at the same
noise dose. The effect of sound level and type were modified by sleep stage physiology, producing unique arousal probability profiles for each sleep stage.
They also showed arousal effects of even brief yet frequent noise on heart rate.
Generalized linear mixed models
Moderate
Funk et al.,
2014. US Survey 4278
responders (42% were Respiratory Therapists)
Multi- site survey
None None specified, multiple
Follow up survey from 2005 (1327 responders, unmatched) to determine attitudes and practices related to clinical alarms.
See Korniewicz et al., 2008
31% ‘strongly agree” nuisance alarms disrupt patient care.
70% strongly agree nuisance alarms reduce trust in alarms and cause caregivers to inappropriately turn alarms off 70% strongly agree or agree that there were frequent instances where alarms could not be heard and were missed = 32 % strongly agree or agree.
42% strongly agree or agree that environmental background noise has interfered with alarm recognition 18% knew of adverse events related to clinical alarm problems in their institutions in the previous 2 years.
Descriptive Low
Korniewicz et al., 2008.
US
Survey 1327respond
ers (51%
nurses)
Multi- site survey
None None specified, multiple
>90%) agreed or strongly agreed with the statements covering the purpose of clinical alarms and the need for prioritized and easily differentiated audible and visual alarms.
Many respondents identified nuisance alarms as problematic; most agreed or strongly agreed that the alarms are frequent (81%), disrupt patient care (77%), and can reduce trust in alarms and cause caregivers to disable them (78%).
See Funk et al. 2014.
Descriptive Low
Rosman et al., 2013, US
Quality Improvement
86 patients (343 patient days)
Single site PICU
Daily review of arrhythmia alarms in a pediatric ICU to identify relevant alarms that had gone undetected
Bedside monitor
54 656 total alarms (159.3 alarms/patient-day) of which (63%) were non-rhythm alarms, (oxygen saturation, blood pressure) and 37%)were rhythm alarms of which 20% were critical rhythm alarms and 15 938
(80%) were non-critical rhythm alarms. Of the 19 970 total rhythm alarms, 21% were unable to be reviewed due to cache limitations
72% of the critical rhythm alarms reviewed were (false alarms).
50% of the non-critical rhythm alarms reviewed were artifact.
55% of all rhythm alarms were false.
99% of VT alarms were false, 17 VT alarms were true (5 patients), none of which were detected by the clinical staff at the time of occurrence. Management of 2 of the 5 patients was significantly altered on the basis of the arrhythmia detected as a result of this review.
Descriptive Low
Voepel- Lewis et al., 2013. US
Prospective
observational 103 patients, 1616 monitoring hours
Single site 32 bed general post op ward for orthopedi c surgery
None Pulse oximeter This study evaluated nursing response and interventions prompted by a pulse oximetry monitoring (POM) alarm surveillance system on a general postoperative care ward.
1616 monitoring hours were recorded. 88% patients had continuous monitoring for during PCA.
342 desaturation events were identified. 59% experienced at least 1 event,
710 notification pages were transmitted, 12 (1.7%) of which were escalated (triggered after 3 min).
Nurse response time increased with higher notification numbers based on quartiles (F 3.9 (df 2, 708), p = 0.046).
Nurse response time did not differ between clinically relevant desaturation or non-desaturation alarm conditions (51.37 [40.9, 61.9] vs. 53.12 [46.6, 59.7] s; p = 0.769), and did not correlate with either measure of unit staffing (RN-HPPS rho = _0.01; p = 0.784; total-HPPS rho = _0.009; p = 0.804).
Patients who experienced missed events had a higher overall frequency of desaturation events (7.68 [4.4, 11.0] vs. 1.7 [1.0, 2.3]; <0.001). work shift had no differential effect.
No patient in the study required escalation of care or a rapid response team call.
Descriptive Bootstrapping Chi square Spearman’s rho correlation coefficients linear mixed models
Moderate
