Accurate and timely identification of existing audible medical alarms is not adequate in clinical settings. New alarms that are easily heard, quickly identifiable, and discernable from one another are indicated. The “auditory icons” (brief sounds that serve as metaphors for the events they represent) have been proposed as a replacement to the current international standard. The objective was to identify the best performing icons based on audibility and performance in a simulated clinical environment.
Three sets of icon alarms were designed using empirical methods. Subjects participated in a series of clinical simulation experiments that examined the audibility, identification accuracy, and response time of each of these icon alarms. A statistical model that combined the outcomes was used to rank the alarms in overall efficacy. We constructed the “best” and “worst” performing sets based on this ranking and prospectively validated these sets in a subsequent experiment with a new subject sample.
Experiments were conducted in simulated ICU settings at the University of Miami.
Medical trainees were recruited from a convenience sample of nursing students and anesthesia residents at the institution.
In Experiment 1 (formative testing), subjects were exposed to one of the three sets of alarms; identical setting and instruments were used throughout. In Experiment 2 (summative testing), subjects were exposed to one of the two sets of alarms, assembled from the best and worst performing alarms from Experiment 1.
For each alarm, we determined the minimum sound level to reach audibility threshold in the presence of background clinical noise, identification accuracy (percentage), and response time (seconds). We enrolled 123 medical trainees and professionals for participation (78 with < 6 yr of training). We identified the best performing icon alarms for each category, which matched or exceeded the other candidate alarms in identification accuracy and response time.
We propose a set of eight auditory icon alarms that were selected through formative testing and validated through summative testing for adoption by relevant regulatory bodies and medical device manufacturers.
1Music Engineering Technology, Frost School of Music, University of Miami, Coral Gables, FL.
2Department of Anesthesiology, Perioperative Medicine and Pain Management, Miller School of Medicine, University of Miami, Miami, FL.
3School of Nursing & Health Studies, University of Miami, Coral Gables, FL.
4Cognition Institute, Plymouth University, Plymouth, United Kingdom.
This work was performed at the University of Miami.
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Supported, in part, by grant from Association for the Advancement of Medical Instrumentation.
Drs. Bennett’s, Dudaryk’s, Edworthy’s, and McNeer’s institution received funding from Association for the Advancement of Medical Instrumentation. Dr. Crenshaw disclosed that she does not have any potential conflicts of interest.
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