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Title: Predictive analysis in healthcare: emergency wait time prediction
Authors: Gonçalves, F.
Pereira, R.
Ferreira, J.
Vasconcelos, J. B.
Melo, F.
Velez, I.
Keywords: Big data
Emergency department
Predictive analytics
Issue Date: 2019
Publisher: Springer
Abstract: Emergency departments are an important area of a hospital, being the major entry point to the healthcare system. One of the most important issues regarding patient experience are the emergency department waiting times. In order to help hospitals improving their patient experience, the authors will perform a study where the Random Forest algorithm will be applied to predict emergency department waiting times. Using data from a Portuguese hospital from 2013 to 2017, the authors discretized the emergency waiting time in 5 different categories: “Really Low”, “Low”, “Average”, “High”, “Really High”. Plus, the authors considered as waiting time, the time from triage to observation. The authors expect to correctly evaluate the proposed classification algorithm efficiency and accuracy in order to be able to conclude if it is valuable when trying to predict ED waiting times.
Peer reviewed: yes
DOI: 10.1007/978-3-030-01746-0_16
ISBN: 978-303001745-3
ISSN: 2194-5357
Appears in Collections:ISTAR-CRI - Comunicações a conferências internacionais

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