Alarm Fatigue, Patient Monitoring, Patient Safety

For Improving Patient Safety and Reducing Nuisance Alarms, Evidence Points to Revising Default Settings

by Sean Power and Michael Wong

Alarm fatigue and nuisance alarms put patient safety at risk. The Joint Commission’s Sentinel Event Alert on alarm safety states that between 85 percent and 99 percent of alarm signals do not require clinical intervention — and these nuisance alarms desensitize clinicians.

According to The Joint Commission:

“In response to this constant barrage of noise, clinicians may turn down the volume of the alarm, turn it off, or adjust the alarm settings outside the limits that are safe and appropriate for the patient – all of which can have serious, often fatal, consequences.”

Alarm fatigue deaths are likely dwarfed by deaths from unrecognized opioid- induced respiratory depression (OIRD), according to Frank Overdyk, MD., MSEE, (Executive Director for Research, North American Partners in Anesthesiology; Professor of Anesthesiology, Hofstra North Shore-LIJ School of Medicine).

Dartmouth-Hitchcock Medical Center, a 353-bed hospital in Lebanon, New Hampshire, approached both problems of alarm fatigue and OIRD by focusing efforts on earlier detection of physiologic deterioration.

Dartmouth is a Tertiary Care and Level 1 Trauma Center facility. It tackled the problem of nuisance alarms in its facility by changing default settings on alarms and introducing tiered orders for monitoring based on demographic and physiologic conditions specific to the patient.

Joshua Pyke, PhD, recently shared the hospital’s study at the recent annual conference of the Association for the Advancement of Medical Instrumentation. Below we have summarized key insights from that presentation alongside context from a review prepared by Andreas Taenzer, M.D., M.S., Dr. Pyke, and Susan McGrath, Ph.D, “A Review of Current and Emerging Approaches to Failure-to-Rescue” published in Anesthesiology in August 2011.

Reducing the Number of Failure to Rescue Events

In the August 2011 review, Dr. Taenzer and his colleagues describe two approaches to reducing failure to rescue (FTR), a widely used indicator of hospital quality:

“Until recently, approaches used to address failure-to-rescue have been focused primarily on improvement of response to a recognized patient crisis, with limited success in terms of patient outcomes. Less attention has been paid to improving the detection of the crisis.”

According to the Failure-to-Rescue Review, rapid response teams (RRTs) were introduced because patients show signs of deterioration six to eight hours before cardiac or respiratory arrest. The Review also indicates that intervention by RRTs has had limited benefit to patients.

In response to these facts, Dr. Taenzer and his colleagues suggest that continuous patient vital sign monitoring with patient surveillance systems facilitates early recognition of physiologic deterioration, leading to more effective clinical interventions.

In the Dartmouth team’s research, Dr. Pyke says they also identified risk factors specific to the non-critical inpatient domain:

“The number of patients per nurse, poor floor layout, noisy environments, and interruptive alarms can all contribute to a potentially dangerous cognitive burden for task-saturated staff.”

These risk factors need to be thought about when considering implementing a patient surveillance system.

The Predictive Value of Physiologic Indicators

In the Failure-to-Rescue Review, existing research on the predictive value of physiologic indicators was discussed and in particular the research by Buist et al. from 2004:

“The strongest predictor of mortality in univariate analysis was found to be low respiratory rate (less than 6 breaths/min), which was associated with a 13.7-fold increase in the risk of mortality by hospital discharge. Changes in consciousness and high respiratory rate (more than 30 breaths/min) were also found to increase risk of mortality in the univariate model. In the multivariate analysis, changes of consciousness, hypotension, high or low respiratory rate, and low SpO2 were all found to be significant independent predictors.”

This analysis suggests that patient surveillance is most effective when continuous electronic monitoring is implemented.

Dartmouth’s Goals for Patient Surveillance and Alarm Fatigue

Dr. Pyke notes that Dartmouth first established goals for the patient surveillance program. One of the primary objectives was to provide early detection of physiologic deterioration while reducing nuisance alarms.

According to Dr. Pyke’s presentation, Dartmouth’s patient surveillance goals included:

  • Monitor all patients in bed and unobserved by staff with surveillance monitoring.
  • One false positive per patient per shift.
  • Eliminate undetected severe deterioration.

These goals, Dartmouth observed, could be achieved by changing default settings on alarms based on demographic and physiologic conditions specific to the patient.

Revising Default Alarm Settings

The Dartmouth team introduced new standard configurations for alarms that were guided by three alarm tiers.

Dr. Pyke describes the new rules:

“To reach a balance between actionable and false positive alarms in this work, the following alarm thresholds were chosen: SpO2 less than 80% and heart rate less than 50 and more than 140 beats per minute.

A three-tier system was implemented to allow for parameter adjustment: (1) standard setting, (2) bracketed adjustment (±10% of baseline) by nursing staff, and (3) physician-ordered settings.

We instituted a 15-s audio alarm delay at the bedside and an additional 15-s delay for pager annunciation. This led to a 30-s delay before a nurse would be notified by pager of violation of alarm thresholds and was the system maximum delay.”

Dartmouth observed the following changes:

  • Staff uses the system as a continuous source of patient information and trends.
  • Both in-room monitors and admitting stations give patient status updates.
  • Pagers are a usability stumbling block.
  • Pager hand-off creates an additional point of failure.
  • Identification of undiagnosed comorbidities can add to workload.

Dr. Pyke says the initiative was nursing-centric from the beginning. Revising default alarm settings received widespread support from the frontline staff and particularly nurses responsible for responding to alarms:

“When asked whether the hospital should remove the surveillance monitoring system, on a scale of 0 (yes) to 6 (no), nurses averaged 5.54. This consensus indicated wide support for the surveillance monitoring system.”

Overall, opioid use, RRT activations, and ICU transfers all declined as a result of reducing nuisance alarms. Earlier detection of physiologic deterioration proved successful at reducing these metrics that estimate FTR.

As the Failure-to-Rescue Review explains:

“Continuous monitoring systems represent a more proactive approach to identifying patient deterioration, based on the premise that physiologic changes can indicate, and perhaps predict, deterioration episodes.”

In short, the Dartmouth case study shows that notification delays and population-appropriate alarm thresholds, combined with bracketed adjustments for patients with abnormal physiological baselines, can reduce the number of nuisance alarms associated with patient surveillance.

What other recommendations would you offer for reducing the number of nuisance alarms? How does your hospital measure the impact of poor alarm management on patient safety?

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