Medical devices generate enough false alarms to cause a reduction in responding known as the cry wolf effect. Frequent alarms are distracting and interfere with clinicians performing critical tasks and may lead to staff disabling alarm systems.
Prevalence and Severity of Alarm Fatigue
Evidence-Based Practice Model And Search Strategy
When the alarm is viewed as a “nuisance,” the caregiver may disable, silence, or ignore the warning that is intended to make the environment safer. Rather than creating a safer environment, a large number of nuisance alarms have an opposite effect, resulting in desensitization.
Research Findings Related to Alarm Fatigue
Excessive Alarms and Effects on Staff
Perceived alarm urgency contributes to the nurses' alarm response, but nurses use additional strategies to determine response including the criticality of the patient, signal duration, rarity of alarming device, and workload.
Nurses' Response to Alarms
Alarm Sounds and Audibility
Technology to Reduce False Alarms
Wireless technologies may be viable alternatives to human monitor surveillance. Comparative studies are needed to determine the best approach to promote positive patient outcomes.
Alarm Notification Systems
Noise levels in most hospitals exceed the World Health Organization (WHO) recommendations of 35 decibels (dB) during daytime hours and 30 dB for nighttime hours. Noise levels have been consistently rising since 1960.
Research Strengths and Limitations
Non-Research Evidence Related to Alarm Fatigue
Strategies to Reduce Alarm Desensitization
If the alarm that is being generated is considered insignificant, then it should never be activated because the most that it can do is provide noise.
Alarm notification relies on a combination of technical devices and human factors. The notification system selected should complement the monitoring equipment, staffing model, alarm response protocol, and unit architectural layout.
Alarm Priority and Notification Systems
Gaps in Knowledge, Need for Further Research
Evidence-based Practice Recommendations
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- Katarzyna Lewandowska, Wioletta Mędrzycka-Dąbrowska, Lucyna Tomaszek, Magdalena Wujtewicz, Determining Factors of Alarm Fatigue among Nurses in Intensive Care Units—A Polish Pilot Study, Journal of Clinical Medicine, 10.3390/jcm12093120, 12, 9, (3120), (2023).
- Azize Karahan, Sultan Kav, Banu Çevik, Ebru Akgün Çıtak, Ziyafet Uğurlu, Berrak Fulser, Alarm fatigue among nurses working in intensive care and other inpatient clinics, Work, 10.3233/WOR-220466, (1-9), (2023).
- Meena Andiappan, Lucas Dufour, Senthujan Senkaiahliyan, Addressing Burnout among Healthcare Technology Management Professionals, Biomedical Instrumentation & Technology, 10.2345/0899-8205-57.3.75, 57, 3, (75-80), (2023).
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- Bradford D. Winters, Aarti Sarwal, Pulse Oximetry Con: Stop Living in the Cave, Critical Care Medicine, 10.1097/CCM.0000000000005892, Publish Ahead of Print, (2023).
- Merijn Kuit, Lars Ingmar Veldhuis, Markus Hollmann, Prabath Nanayakkara, Milan Ridderikhof, Recognition of Critically Ill Patients by Acute Healthcare Providers: A Multicenter Observational Study*, Critical Care Medicine, 10.1097/CCM.0000000000005839, 51, 6, (697-705), (2023).
- Steven J. Frank, A deep learning architecture with an object-detection algorithm and a convolutional neural network for breast mass detection and visualization, Healthcare Analytics, 10.1016/j.health.2023.100186, 3, (100186), (2023).
- Liam Foley, Joseph J. Schlesinger, Michael Schutz, Improving detectability of auditory interfaces for medical alarms through temporal variation in amplitude envelope, British Journal of Anaesthesia, 10.1016/j.bja.2022.10.045, 130, 3, (351-359), (2023).
- Ali Movahedi, Afsaneh Sadooghiasl, Fazlollah Ahmadi, Mojtaba Vaismoradi, A grounded theory study of alarm fatigue among nurses in intensive care units, Australian Critical Care, 10.1016/j.aucc.2022.12.004, (2023).
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