Study: Data-Driven Physiologic Alarm Parameters Can Help Reduce Alarm Fatigue

July 22, 2016
Alarm fatigue from clinical decision support systems is a significant hazard in hospitals. In a recent study, researchers found that tailoring bedside monitor alarm limits using data-driven physiologic parameters can mitigate alarm fatigue.

Alarm fatigue from clinical decision support systems is a significant hazard in hospitals. Excessive alarm activations can become so commonplace that physicians miss alarms, and studies have shown that frequent disruptive alarms can impact patients’ sleep and recovery.

According to a study of hospitalized children at Lucile Packard Children’s Hospital Stanford in  Palo Alto, California, researchers found that tailoring physiologic bedside monitor alarm limits using data-driven heart rate and respiratory rate parameters may reduce the frequency of false alarms, thereby mitigating alarm fatigue. The study was published in the Journal of Hospital Medicine.

“Improper alarm settings are one of four major contributing factors to reported alarm-related events, and data-driven HR and RR parameters provide a means by which to address the Joint Commission Sentinel Event Alert and National Patient Safety Goal regarding alarm management safety for hospitalized pediatric patients. Our results suggest that this evidence-based approach may reduce that frequency of false alarms (thereby mitigating alarm fatigue), and should be studied prospectively for implementation in the clinical setting,” the study authors wrote.

The researchers aimed to create and validate heart rate and respiratory rate 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.

According to the study, the researchers performed a cross-sectional study of children less than 18 years of age hospitalized on general medical and surgical units at Lucile Packard Children’s Hospital Stanford, a 311-bed quaternary-care academic hospital with a full complement of pediatric medical and surgical subspecialties and transplant programs. During the study period, the hospital used the Cerner EHR Millennium technology platform and Philips IntelliVue bedside monitors.

In the retrospective cross-sectional study, nurse-charted heart rate and respiratory rate data from a training set of 7,202 hospitalized children were used to develop percentile tables. The researchers compared 5th and 95th percentile values with currently accepted Institutes of Health-recommended reference ranges in a validation set of 2,287 patients. And, researchers analyzed 148 rapid response team and cardiorespiratory arrest events over a year, using heart rate and respiratory rate 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.

The study findings indicate there were 55.6 percent fewer out-of-range measurements using data-driven vital sign limits.

“Overall, 144/148 rapid response team and cardiorespiratory arrest event patients had out-of-range heart rate or respiratory rate values preceding the event using current limits, and 138/ 148 were abnormal using data-driven limits. Chart review of rapid response team and cardiorespiratory arrest event patients with abnormal heart rate and respiratory rate per current limits considered normal by data-driven limits revealed that clinical status change was identified by other vital sign abnormalities or clinical context, the study authors wrote.

The study authors concluded, “A large proportion of heart rate and respiratory rate values for hospitalized children at our institution are out of range according to current vital sign reference ranges. Our new data-driven alarm parameters for hospitalized children provide a potentially safe means by which to modify physiologic bedside monitor alarm limits, a first step toward customization of alarm limit settings in an effort to mitigate alarm fatigue.”

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