Jones, Simon Andrew, Joy, Mark Patrick and Pearson, Jon (2002) Forecasting demand of emergency care. Health Care Management Science, 5(4), pp. 297-305. ISSN (print) 1386-9620Full text not available from this archive.
This paper describes a model that can forecast the daily number of occupied beds due to emergency admissions in an acute hospital. Out of sample forecasts 32 day days in advance. have an RMS error of 3% of the mean number of beds used for emergency admissions. We find that the number of occupied beds due to emergency admissions is related to both air temperature and PHLS data on influenza like illnesses. We find that a period of high volatility, indicated by GARCH errors, will result in an increase in waiting times in the A&E Department. Furthermore. volatility gives more warning of waiting times in A&E than total bed occupancy.
|Research Area:||Allied health professions and studies|
|Faculty, School or Research Centre:||Faculty of Computing, Information Systems and Mathematics (until 2011)|
|Depositing User:||Automatic Import Agent|
|Date Deposited:||10 Mar 2010 14:52|
|Last Modified:||10 Mar 2010 14:52|
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