Predicting emergency department admissions

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Title Predicting emergency department admissions
Author Boyle, Justin; Jessup, Melanie; Crilly, Julia; Green, David; Lind, James; Wallis, Marianne; Miller, Peter; Fitzgerald, Gerard
Journal Name Emergency Medicine Journal
Year Published 2012
Place of publication United Kingdom
Publisher B M J Group
Abstract Objective To develop and validate models to predict emergency department (ED) presentations and hospital admissions for time and day of the year. Methods Initial model development and validation was based on 5 years of historical data from two dissimilar hospitals, followed by subsequent validation on 27 hospitals representing 95% of the ED presentations across the state. Forecast accuracy was assessed using the mean average percentage error (MAPE) between forecasts and observed data. The study also determined a daily sample size threshold for forecasting subgroups within the data. Results Presentations to the ED and subsequent admissions to hospital beds are not random and can be predicted. Forecast accuracy worsened as the forecast time intervals became smaller: when forecasting monthly admissions, the best MAPE was approximately 2%, for daily admissions, 11%; for 4-hourly admissions, 38%; and for hourly admissions, 50%. Presentations were more easily forecast than admissions (daily MAPE w7%). When validating accuracy at additional hospitals, forecasts for urban facilities were generally more accurate than regional forecasts (accuracy is related to sample size). Subgroups within the data with more than 10 admissions or presentations per day had forecast errors statistically similar to the entire dataset. The study also included a software implementation of the models, resulting in a data dashboard for bed managers. Conclusions Valid ED prediction tools can be generated from access to de-identified historic data, which may be used to assist elective surgery scheduling and bed management. The paper provides forecasting performance levels to guide similar studies.
Peer Reviewed Yes
Published Yes
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Copyright Statement Copyright remains with the authors 2011. The attached file is reproduced here in accordance with the copyright policy of the publisher. For information about this journal please refer to the journal’s website or contact the authors.
Volume 29
Issue Number 5
Page from 358
Page to 365
ISSN 1472-0205
Date Accessioned 2012-04-10
Language en_US
Research Centre Menzies Health Institute Qld
Faculty Griffith Health Faculty
Subject Clinical Sciences
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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