Perceptually Discriminating the Highest Priority Alarms Reduces Response Time: A Retrospective Pre-Post Study at Four...

Area of Science:

• Biomedical Engineering
• Clinical Informatics
• Patient Safety

Background:

• Emergency alarms require immediate action due to high urgency and clinician triggering.
• High-priority alarms are automatically triggered and have lower positive predictive value (PPV).
• Current alarm systems may not effectively discriminate between critical and non-critical alerts, impacting response times.

Purpose of the Study:

• To reduce nurse response time for emergency and high-priority alarms.
• To enhance discriminability between emergency and other alarms.
• To suppress redundant and false high-priority alarms within a secondary alarm notification system (SANS).

Main Methods:

• A retrospective pre-post study analyzed data from four hospitals before and after a SANS redesign.
• Digitized human speech was incorporated for emergency alarms to improve distinctiveness.
• A 20-second delay was implemented for initial onset and escalation of some automatically triggered alarms.
• Linear mixed models, Fisher's exact test, and control charts were used to assess changes in response time and process stability.

Main Results:

• Nurse response time for emergency alarms significantly decreased across all hospitals (e.g., cardiac alarms from 127.10s to 52.43s).
• Improvements in emergency alarm response times were sustained post-implementation.
• The rate of automatically triggered alarms decreased by 25.0%.
• Response times for certain automatically triggered cardiac alarms increased.

Conclusions:

• Auditory sound disambiguation effectively reduced nurse response time for emergency alarms.
• Suppression of some high-priority automatically triggered alarms did not lead to improved response times.
• Distinguishing and escalating urgent, actionable alarms with higher PPV is key to improving response times.