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Planning for the future: Modelling daily emergency department presentations in an Australian capital city
Fern J McAllan1, Diana Egerton-Warburton2,3, Gerard O'Reilly4,5
1Emergency Department, Critical Care Services, Royal Adelaide Hospital, Adelaide, South Australia, Australia.
Objective:
To describe and model a decade of ED presentations in metropolitan Melbourne, Australia, from July 2000 to June 2010 and to validate the model of ED presentations by testing the model's performance in forecasting the subsequent 2 year period of daily presentations, from July 2010 to June 2012.
Methods:
Retrospective analyses of prospectively collected data sourced from the Victorian Emergency Minimum Dataset were performed and included 13 public hospitals. Time series modelling involved unobserved components modelling and forward selection of variables using incidence rate ratios. Forecasting with the model and validation were performed using the 2 year period up to June 2012. Model performance was calculated using the mean average percentage error.
Results:
A total of 7 031 242 patient presentations occurred to the sample metropolitan EDs in the 12 year study period. An absolute increase in mean daily ED presentations of 81.3% was observed. Presentations increased on Sunday and Monday incidence rate ratio of 1.10 (95% CI 1.08-1.11, P < 0.05). No monthly or seasonal pattern was evident. Public holidays were associated with increased presentations, incidence rate ratio of 1.11 (95% CI 1.08-1.15, P < 0.05). The model with the best goodness-of-fit and Wald χ2 value included Sunday-Monday (vs Tuesday-Saturday), public holidays, the trend of gradual increase over time and a stochastic (random white noise) cycle. The mean average percentage error for the 2 year forecast period was 3.6%.
Conclusion:
We have produced and validated a model for predicting daily ED presentations across a major city. Even though ED presentations are multifactorial, city-wide daily presentations are predictable and explained by a small number of variables. The model will have implications for future health planning.
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