Modeling Throughput of Emergency Departments via Time Series: An Expectation Maximization Algorithm

Authors:
Zidong Wang;Julie Eatock;Sally McClean;Dongmei Liu;Xiaohui Liu;Terry Young
Affiliations:
Brunel University, UK;Brunel University, UK;University of Ulster, UK;Nanjing University of Science and Technology, China;Brunel University, UK;Brunel University, UK
Venue:
ACM Transactions on Management Information Systems (TMIS) - Special Issue on Informatics for Smart Health and Wellbeing
Year:
2013

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Abstract

In this article, the expectation maximization (EM) algorithm is applied for modeling the throughput of emergency departments via available time-series data. The dynamics of emergency department throughput is developed and evaluated, for the first time, as a stochastic dynamic model that consists of the noisy measurement and first-order autoregressive (AR) stochastic dynamic process. By using the EM algorithm, the model parameters, the actual throughput, as well as the noise intensity, can be identified simultaneously. Four real-world time series collected from an emergency department in West London are employed to demonstrate the effectiveness of the introduced algorithm. Several quantitative indices are proposed to evaluate the inferred models. The simulation shows that the identified model fits the data very well.