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
fDate :
Aug. 31 2010-Sept. 4 2010
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;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5627673