Quantifying randomness of clinician mobility and interaction in emergency department using entropy

Min Zhang, Zhe Li, Xiaohui Kong, Jiajie Zhang, Vimla Patel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Entropy is a fundamental measure of randomness in a time series of data. In this paper, we use entropy to quantify the randomness of events in the workflow in an emergency department (ED). We collect data using Radio Identification (RID) sensor system and compute the entropy of mobility and interaction events generated from behaviors of each tagged clinician. The result shows that the event data bears low entropy values and thus contains underlying regular patterns of interaction and mobility of clinicians.

Original languageEnglish (US)
Title of host publicationProceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010
Pages506-510
Number of pages5
DOIs
StatePublished - Dec 13 2010
Event9th IEEE International Conference on Cognitive Informatics, ICCI 2010 - Beijing, China
Duration: Jul 7 2010Jul 9 2010

Publication series

NameProceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010

Other

Other9th IEEE International Conference on Cognitive Informatics, ICCI 2010
CountryChina
CityBeijing
Period7/7/107/9/10

Keywords

  • Behavior patterns
  • Clinical environment
  • Cognitive complexity
  • Entropy
  • RID tag

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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