By Cora R. Lehet, DNP, RN, CNL; Julie A. Lopez, DNP, RN, NE-BC, FACHE; Robert J. Frank; and Maria Cvach, DNP, RN, FAAN
Telemetry monitoring is intended to improve patient safety and reduce harm. However, excessive monitor alarms may have the undesired effect of staff ignoring, silencing or delaying a response because the alarm is falsely believed to be a “nuisance alarm.” Nuisance alarms are defined as monitoring device alerts that may be either false or true but are nonactionable. Research has shown that the majority of monitor alarms are nuisance alarms and can occur hundreds of times per day.
Using alarms safely has been a priority of The Joint Commission (TJC) since it published a sentinel event alert in 2013 outlining the severity of alarm fatigue in the United States. Of every 98 alarm-related sentinel events, 80 resulted in patient deaths. TJC subsequently implemented National Patient Safety Goal 6 on clinical alarm systems and began auditing hospital compliance in January 2016.
Research has found that between 72% and 99% of monitor alarms do not require intervention and are nuisance alarms that contribute to alarm fatigue. Bonafide et al. found that nursing staff had slower response times to true alarm events among patients who had a larger number of nuisance alarms preceding a true alarm. Research supports excessive alarms as being an important contributing factor to registered nurses (RNs) failing to respond to critical alarms in a timely fashion.
A major contributing factor to excessive monitor alarms is patient outliers. Patient outliers are those patients whose monitoring devices generate the most alarms. In two studies, only a few patients generated greater than 50% of total telemetry monitor alarms. Yeh et al. noted that two patients caused 54% of all alarms in 24 hours, with 91% of those alarms being due to low heart rate. A team of experts assembled by the National Coalition for Alarm Management Safety found a consistent problem across health settings: Many of the alarms on a given unit were caused by only a few patients. When data were analyzed on a large scale across multiple health systems within this group, it was found that telemetry units had the largest quantity of alarms compared with both intermediate and intensive care unit settings, with high and low heart rate alarms being the most common. In one of the reported practice settings, three patients were responsible for generating 83% of the 719 monitor alarms on a unit. In another, 78% of alarms were attributed to four of 45 patients. Alarm customization, personalized for patient-specific parameters (e.g., heart rate), is suggested as a best practice to reduce the quantity of preventable nuisance alarms. By customizing and adjusting alarm parameters appropriately, the total quantity of nuisance alarms can be reduced.
Alarm technologies (e.g., middleware) are effective at improving alarm notification and response times. Middleware technology allows for customization and filtering of alarms between the primary alarming device and the second receiving device. Using alarm escalation rules within middleware can reduce false alarms and disable alarm escalation after clinical staff acknowledge the alert on the receiving device. In one study in which middleware technology was used to filter alarm tones, the positive predictive value improved, demonstrating a reduction in staff response time to critical alarms.
In many health systems, acute care telemetry units may have the largest quantity of generated monitor alarms; however, limited research exists regarding alarm management in these settings. Most alarm research has occurred in critical care settings. RNs on acute care telemetry units are prone to experiencing the effects of alarm fatigue because they have an increased number of patients, and these patients are more susceptible to frequent false alarms because of increased mobility and care activities. Alarm fatigue was found to be the contributing factor that led to a delayed response to a patient event at the project facility. When RNs were surveyed before project implementation, most responded they “usually/always” become indifferent to alarms when they sound repeatedly. Alarm data from the project facility indicated that patient outliers may be a contributing factor leading to alarm fatigue.
This quality improvement (QI) project took place between August 1, 2021, and December 31, 2021, in the department of medicine (DOM) at a large academic medical center after review by the hospital’s institutional review board.
Alarm data analysis demonstrated a statistically significant reduction in overall alarm duration across the four DOM acute care telemetry units. These data suggest that the technological intervention was a beneficial alarm management strategy. Targeting patient outliers by notifying RNs through their mobile phone when patients exceeded the unit’s average alarms per bed per day empowered them to customize alarm threshold adjustments for patients. Literature supports that nuisance alarms often are caused primarily by only one or two patients and that nuisance alarms are an important cause of alarm fatigue. The four DOM acute care telemetry units’ RNs recommended continued use of this intervention as a method to reduce alarm duration, and plans are in motion to expand to other units within the organization.
An unexpected finding, based on chi-square analysis comparing the pre- to postintervention periods, was that an increase in alarm frequency occurred rather than a decrease. A decrease in alarm frequency was predicted based on the significant reduction in alarm duration. A possible explanation for the increase in alarm frequency was the Omicron variant surge in COVID-19 patients admitted to the four DOM acute care telemetry units during the postintervention data collection period (December 2021). The patients may have required increased monitoring. However, when SpO2 data were excluded from the data set, a statistically significant increase in alarm frequency persisted. Considering the significant reduction in overall alarm duration, paired with an increase in alarm frequency, any alarm duration reduction was viewed as a meaningful finding. Alarm frequency data analysis should be reassessed at a time point not affected by a COVID-19 surge.
In the QI project described here, a technological intervention was implemented with the goal of heightening RN awareness of patient outliers – or those patients responsible for most monitor alarms – and thereby empower RNs to adjust alarms in a meaningful way. The QI project demonstrated a reduction in alarm duration but an increase in alarm frequency. This may have been due to the timing of the project, which occurred during a surge in COVID-19 cases. More research is needed to determine if the technological intervention described here can reduce alarm duration and frequency.
Reference: https://array.aami.org/doi/10.2345/0899-8205-57.2.67#i0899-8205-57-2-67-fig4
