A data-integrated nurse activity simulation model

Durai Sundaramoorthi, Victoria C.P. Chen, Seoung B. Kim, Jay M. Rosenberger, Deborah F. Buckley-Behan

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

6 Citations (Scopus)


This research develops a data-integrated approach for constructing simulation models based on a real data set provided by Baylor Regional Medical Center (Baylor) in Grapevine, Texas. Tree-based models and kernel density estimation were utilized to extract important knowledge from the data for the simulation. Classification and Regression Tree model, a data mining tool for prediction and classification, was used to develop two tree structures: (a) a regression tree, from which the amount of time a nurse spends in a location is predicted based on factors, such as the primary diagnosis of a patient and the type of nurse; and (b) a classification tree, from which transition probabilities for nurse movements are determined. Kernel density estimation is used to estimate the continuous distribution for the amount of time a nurse spends in a location. Merits of using our approach for Baylor's nurse activity simulation are discussed.

Original languageEnglish
Title of host publicationProceedings of the 2006 Winter Simulation Conference, WSC
Number of pages7
Publication statusPublished - 2006
Externally publishedYes
Event2006 Winter Simulation Conference, WSC - Monterey, CA, United States
Duration: 2006 Dec 32006 Dec 6

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736


Other2006 Winter Simulation Conference, WSC
Country/TerritoryUnited States
CityMonterey, CA

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation
  • Computer Science Applications


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