• DocumentCode
    2949158
  • Title

    Statewide validation of a patient admissions prediction tool

  • Author

    Boyle, Justin ; Padellec, Remy Le ; Ireland, Derek

  • Author_Institution
    CSIRO ICT Centre, R. Brisbane & Women´´s Hosp., Herston, QLD, Australia
  • fYear
    2010
  • fDate
    Aug. 31 2010-Sept. 4 2010
  • Firstpage
    3887
  • Lastpage
    3890
  • Abstract
    We validate a proprietary system to predict hospital emergency department presentations. A key advantage in planning health service delivery requirements and catering for the large numbers of people presenting to hospitals is the ability to predict their numbers. Year-ahead forecasts of daily hospital presentations were generated for 27 public hospitals in Queensland, Australia from five years of historic data. Forecast accuracy was assessed by calculating the Mean Absolute Percentage Error and Root Mean Squared Error between predictions and observed admissions. Emergency Department presentations were found to be not random and can be predicted with an accuracy of around 90%. Highest accuracy was over weekends and summer months, and Public Holidays had the greatest variance in forecast accuracy. Forecasts for urban facilities were generally more accurate than regional (accuracy is related to sample size).
  • Keywords
    forecasting theory; health care; medical information systems; forecast accuracy; health service delivery requirements; hospital emergency department presentations; mean absolute percentage error; patient admissions prediction tool; proprietary system; root mean squared error; statewide validation; Accuracy; Data mining; Data models; Forecasting; Hospitals; Measurement; Predictive models; Emergency Service, Hospital; Hospitals, Public; Patient Admission; Queensland;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
  • Conference_Location
    Buenos Aires
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4123-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2010.5627673
  • Filename
    5627673