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Overlapping medical alarms are almost indiscriminable

Lacherez, P., Seah, E., & Sanderson, P. (2007) Overlapping medical alarms are almost indiscriminable. Human Factors : The Journal of the Human Factors and Ergonomics Society, 49(4), pp. 637-645.

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Abstract

Objective: We explore how accurately and quickly nurses can identify melodic medical equipment alarms when no mnemonics are used, when alarms may overlap, and when concurrent tasks are performed.

Background: The international standard IEC 60601-1-8 (International Electrotechnical Commission, 2005) has proposed simple melodies to distinguish seven alarm sources. Previous studies with nonmedical participants reveal poor learning of melodic alarms and persistent confusions between some of them. The effects of domain expertise, concurrent tasks, and alarm overlaps are unknown.

Method: Fourteen intensive care and general medical unit nurses learned the melodic alarms without mnemonics in two sessions on separate days. In the second half of Day 2 the nurses identified single alarms or pairs of alarms played in sequential, partially overlapping, or nearly completely overlapping configurations. For half the experimental blocks nurses performed a concurrent mental arithmetic task.

Results: Nurses' learning was poor and was no better than the learning of nonnurses in a previous study. Nurses showed the previously noted confusions between alarms. Overlapping alarms were exceptionally difficult to identify. The concurrent task affected response time but not accuracy.

Conclusion: Because of a failure of auditory stream segregation, the melodic alarms cannot be discriminated when they overlap. Directives to sequence the sounding of alarms in medical electrical equipment must be strictly adhered to, or the alarms must redesigned to support better auditory streaming.

Application: Actual or potential uses of this research include the implementation of IEC 60601-1-8 alarms in medical electrical equipment.

Impact and interest:

14 citations in Scopus
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5 citations in Web of Science®

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ID Code: 49208
Item Type: Journal Article
DOI: 10.1518/001872007X215719
ISSN: 0018-7208
Divisions: Current > Institutes > Institute of Health and Biomedical Innovation
Deposited On: 20 Mar 2012 08:54
Last Modified: 20 Mar 2012 08:54

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