• DocumentCode
    2111904
  • Title

    Time based clustering for analyzing acute hospital patient flow

  • Author

    Khanna, Saarthak ; Boyle, Justin ; Good, Nicholas ; Lind, Jonathan ; Zeitz, Kathryn

  • Author_Institution
    Australian E-Health Res. Centre, R. Brisbane & Women´s Hosp., Herston, QLD, Australia
  • fYear
    2012
  • fDate
    Aug. 28 2012-Sept. 1 2012
  • Firstpage
    5903
  • Lastpage
    5906
  • Abstract
    This paper describes a novel approach employing time based clustering of health data for visualization and analysis of patient flow. Clustering inpatient and emergency department patient episodes into hourly slots based on recorded timestamps, and then grouping them on required parameters, the technique provides a powerful tool for visualizing and analyzing interactions and interdependencies between hospital patient flow parameters. To demonstrate the efficacy of the approach, we employ time based clustering to address some typical patient flow related queries and discuss the findings.
  • Keywords
    hospitals; medical information systems; acute hospital patient flow; emergency department patient; health data; hospital patient flow parameter; powerful tool; time based clustering; Australia; Correlation; Data visualization; Discharges (electric); Fluid flow measurement; Hospitals; Robustness; Cluster Analysis; Hospital Administration; Patient Transfer; Queensland; Time Management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4119-8
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2012.6347337
  • Filename
    6347337