Understanding heart rate alarm adjustment in the intensive care units through an analytical approach

Abstract

BackgroundHeart rate (HR) alarms are prevalent in ICU, and these parameters are configurable. Not much is known about nursing behavior associated with tailoring HR alarm parameters to individual patients to reduce clinical alarm fatigue.ObjectivesTo understand the relationship between heart rate (HR) alarms and adjustments to reduce unnecessary heart rate alarms.MethodsRetrospective, quantitative analysis of an adjudicated database using analytical approaches to understand behaviors surrounding parameter HR alarm adjustments. Patients were sampled from five adult ICUs (77 beds) over one month at a quaternary care university medical center. A total of 337 of 461 ICU patients had HR alarms with 53.7% male, mean age 60.3 years, and 39% non-Caucasian. Default HR alarm parameters were 50 and 130 beats per minute (bpm). The occurrence of each alarm, vital signs, and physiologic waveforms was stored in a relational database (SQL server).ResultsThere were 23,624 HR alarms for analysis, with 65.4% exceeding the upper heart rate limit. Only 51% of patients with HR alarms had parameters adjusted, with a median upper limit change of +5 bpm and -1 bpm lower limit. The median time to first HR parameter adjustment was 17.9 hours, without reduction in alarms occurrence (p = 0.57).ConclusionsHR alarms are prevalent in ICU, and half of HR alarm settings remain at default. There is a long delay between HR alarms and parameters changes, with insufficient changes to decrease HR alarms. Increasing frequency of HR alarms shortens the time to first adjustment. Best practice guidelines for HR alarm limits are needed to reduce alarm fatigue and improve monitoring precision.

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

“…Heart rate alarm limits were the most commonly customized types of alarms in this study. In another study of customization of heart rate alarm settings, 51% of patients had heart rate alarms customized during their stay, with a median upper limit change of +5 bpm and lower limit change of -1 bpm (Fidler et al, 2017). We found a similar percentage of heart rate alarm customization in the medical (52.4%) and surgical (50.0%) ICUs.…”

“…This raises concern that restrictions to customization may not sufficiently account for variation in ICU patient conditions. A recent study on customization in the ICU found that minor adjustments to heart rate did not meaningfully affect alarm rates (Fidler et al, 2017).…”

“…initiatives, yet research on alarm customization is limited (Christensen, Dodds, Sauer, & Watts, 2014;Fidler et al, 2017;Graham & Cvach, 2010;Sendelbach, Wahl, Anthony, & Shotts, 2015;Turmell, Coke, Catinella, Hosford, & Majeski, 2017). The Joint Commission (2016) has called for hospitals to implement alarm customization policies;…”

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

“…Alarm fatigue interventions that included customization of individual patients’ alarm settings have resulted in alarm reduction [ 8 , 9 , 13 ]. Although research on alarm customization is limited, recent evidence suggests that nurses do not customize heart rate alarms enough to reduce alarm rates [ 14 ].…”

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

“…Customization may involve either widening parameter limits to reduce 24 alarms or narrowing limits to increase sensitivity to changes in patient condition.25Given the body of research suggesting that monitor alarms are often clinically irrelevant,26 it is likely that alarm customization is not always practiced in ICUs; however, little data exist 27 about whether and how nurses customize alarms. One study exploring alarm customization demonstrated that changes made to patients' heart rate alarm thresholds did not result in a 29 statistically significant difference in the number of alarms per hour (p=0.57)(Fidler et al, 2017). As healthcare technologies become more complex and ubiquitous, device settings will 42 increasingly need to be customized based on individual patient needs to improve device 43 performance and specificity of alerts.…”