Forecasting Demand of Emergency Care

被引:73
作者
Simon Andrew Jones
Mark Patrick Joy
Jon Pearson
机构
[1] Kingston University,School of Mathematics
[2] Bromley Hospitals NHS Trust,Applied Research Unit
[3] Farnborough Hospital,undefined
[4] Farnborough Common,undefined
关键词
Influenza; Economic Policy; Public Finance; High Volatility; Acute Hospital;
D O I
10.1023/A:1020390425029
中图分类号
学科分类号
摘要
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.
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页码:297 / 305
页数:8
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