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

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

doi:10.1109/COGINF.2010.5599688

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

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

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 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 language	English (US)
Title of host publication	Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010
Pages	506-510
Number of pages	5
DOIs	https://doi.org/10.1109/COGINF.2010.5599688
State	Published - 2010
Event	9th IEEE International Conference on Cognitive Informatics, ICCI 2010 - Beijing, China Duration: Jul 7 2010 → Jul 9 2010

Publication series

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

Other

Other	9th IEEE International Conference on Cognitive Informatics, ICCI 2010
Country/Territory	China
City	Beijing
Period	7/7/10 → 7/9/10

Keywords

Behavior patterns
Clinical environment
Cognitive complexity
Entropy
RID tag

ASJC Scopus subject areas

Artificial Intelligence
Information Systems

Access to Document

10.1109/COGINF.2010.5599688

Cite this

Zhang, M., Li, Z., Kong, X., Zhang, J., & Patel, V. (2010). Quantifying randomness of clinician mobility and interaction in emergency department using entropy. In Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010 (pp. 506-510). Article 5599688 (Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010). https://doi.org/10.1109/COGINF.2010.5599688

Quantifying randomness of clinician mobility and interaction in emergency department using entropy. / Zhang, Min; Li, Zhe; Kong, Xiaohui et al.
Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010. 2010. p. 506-510 5599688 (Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhang, M, Li, Z, Kong, X, Zhang, J & Patel, V 2010, Quantifying randomness of clinician mobility and interaction in emergency department using entropy. in Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010., 5599688, Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010, pp. 506-510, 9th IEEE International Conference on Cognitive Informatics, ICCI 2010, Beijing, China, 7/7/10. https://doi.org/10.1109/COGINF.2010.5599688

Zhang M, Li Z, Kong X, Zhang J, Patel V. Quantifying randomness of clinician mobility and interaction in emergency department using entropy. In Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010. 2010. p. 506-510. 5599688. (Proceedings of the 9th IEEE International Conference on Cognitive Informatics, ICCI 2010). doi: 10.1109/COGINF.2010.5599688

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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.",

keywords = "Behavior patterns, Clinical environment, Cognitive complexity, Entropy, RID tag",

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AB - 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.

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

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