Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/16840
Author(s): | Gonçalves, F. Pereira, R. Ferreira, J. Vasconcelos, J. B. Melo, F. Velez, I. |
Date: | 2019 |
Title: | Predictive analysis in healthcare: emergency wait time prediction |
Volume: | 806 |
Pages: | 138 - 145 |
ISSN: | 2194-5357 |
ISBN: | 978-303001745-3 |
DOI (Digital Object Identifier): | 10.1007/978-3-030-01746-0_16 |
Keywords: | Big data Emergency department Healthcare Predictive analytics |
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. |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | ISTAR-CRI - Comunicações a conferências internacionais |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
paper_trab_filipe_final.pdf | Pós-print | 379,91 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.