The Impact of Interrupting Nurses on Mental Workload in Emergency Departments

Jung Hyup Kim, Nithin Parameshwara, Wenbin Guo, Kalyan S Pasupathy

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

The primary objective of this study was to investigate the impact of interrupting nurses on mental workload in emergency departments by using a Natural Goals Operators Methods and Selection rules Language (NGOMSL) simulation model. The model advanced our understanding of how interrupting nurses influenced their mental workload. A time study was conducted to collect emergency nurses’ behaviors related to clinical activities at the Mayo Clinic in Minnesota. After that, the NGOMSL simulation model was developed based on the time study data. Compared to the non-interruption scenario, the result showed that the nurse’s mental workload was 2.04 times higher during patient care activities and 4.72 times higher during EMR charting in the interruption scenario. The simulation results indicated that the NGOMSL model could demonstrate the impact on mental workload caused by interruptions in emergency departments. The findings of this study will contribute to developing a new way to measure nursing mental workload caused by the interruptions.

Original languageEnglish (US)
Pages (from-to)1-12
Number of pages12
JournalInternational Journal of Human-Computer Interaction
DOIs
StateAccepted/In press - Mar 9 2018
Externally publishedYes

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Human-Computer Interaction
  • Computer Science Applications

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