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Auditory Sequences Presented With Spearcons Support Better Multiple Patient Monitoring Than Single-Patient Alarms: A
Marie-Lys Deschamps1, Penelope Sanderson1, Harald Waxenegger1
1The University of Queensland, Brisbane, Australia.
Objective:
A study of auditory displays for simulated patient monitoring compared the effectiveness of two sound categories (alarm sounds indicating general risk categories from international alarm standard IEC 60601-1-8 versus event-specific sounds according to the type of nursing unit) and two configurations (single-patient alarms versus multi-patient sequences).
Background:
Fieldwork in speciality-focused high dependency units (HDU) indicated that auditory alarms are ambiguous and do not identify which patient has a problem. We tested whether participants perform better using auditory displays that identify the relevant patient and problem.
Method:
During simulated patient monitoring of four patients in a respiratory HDU, 60 non-clinicians heard either (a) IEC risk categories as single-patient alarm sounds, (b) event-specific categories as single-patient alarm sounds, (c) IEC risk categories in multi-patient sequences or (d) event-specific categories in multi-patient sequences. Participants performed a perceptual-motor task while monitoring patients; after detecting abnormal events, they identified the patient and the event.
Results:
Participants hearing multi-patient sequences made fewer wrong patient identifications than participants hearing single-patient alarms. Advantages of event-specific categories emerged when IEC risk category sounds indicated more than one potential event. Even when IEC and event-specific sounds indicated the same unique event, spearcons supported better event identification than did auditory icon sounds.
Conclusion:
Auditory displays that unambiguously convey which patient is having what problem dramatically improve monitoring performance in a preclinical HDU simulation.
Application:
Time-compressed speech assists development of detailed risk categories needed in specific HDU contexts, and multi-patient sound sequences allow multiple patient wellbeing to be monitored.
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