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Improving Health Care Management Through Persistent Homology of Time-Varying Variability of Emergency Department Patient Flow

Abstract : Excessive admissions at the Emergency Department (ED) is a phenomenon very closely linked to the propagation of viruses. It is a cause of overcrowding for EDs and a public health problem. The aim of this work is to give EDs' leaders more time for decision making during this period. Based on the admissions time series associated with specific clinical diagnoses, we will first perform a Detrended Fluctuation Analysis (DFA) to obtain the corresponding variability time series. Next, we will embed this time series on a manifold to obtain a point cloud representation and use Topological Data Analysis (TDA) through persistent homology technic to propose two early real-time indicators. One is the early indicator of abnormal arrivals at the ED whereas the second gives the information on the time index of the maximum number of arrivals. The performance of the detectors is parameter dependent and it can evolve each year. That is why we also propose to solve a bi-objective optimization problem to track the variations of this parameter.
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https://hal.archives-ouvertes.fr/hal-01927284
Contributor : Guillaume Bouleux Connect in order to contact the contributor
Submitted on : Monday, November 19, 2018 - 5:15:37 PM
Last modification on : Saturday, September 24, 2022 - 2:28:05 PM
Long-term archiving on: : Wednesday, February 20, 2019 - 4:13:36 PM

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Maël Dugast, Guillaume Bouleux, Olivier Mory, Eric Marcon. Improving Health Care Management Through Persistent Homology of Time-Varying Variability of Emergency Department Patient Flow. IEEE Journal of Biomedical and Health Informatics, Institute of Electrical and Electronics Engineers, 2018, 23 (5), pp.2174--2181. ⟨10.1109/JBHI.2018.2882748⟩. ⟨hal-01927284⟩

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