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Your search keyword '"Marshall, Adele H."' showing total 10 results
Start Over Author "Marshall, Adele H." Publisher springer international publishing
10 results on '"Marshall, Adele H."'

1. Optimizing the Belfast Bike Sharing Scheme

Author

Demidova, Nadezda, Novakovic, Aleksandar, Marshall, Adele H., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, and Arai, Kohei, editor

Published
2022
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2. Knowledge Discovery of the Delays Experienced in Reporting COVID-19 Confirmed Positive Cases Using Time to Event Models

Author

Novakovic, Aleksandar, Marshall, Adele H., McGregor, Carolyn, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Soares, Carlos, editor, and Torgo, Luis, editor

Published
2021
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10. Coxian Phase-Type Regression Models for Understanding the Relationship Between Patient Attributes, Overcrowding, and Length of Stay in Hospital Emergency Departments

Author

Mark Mackay, Laura M. Boyle, Adele H. Marshall, Boyle, Laura M, Marshall, Adele H, Mackay, Mark, and 4th International Conference on Health Care Systems Engineering, HCSE 2019 Montreal, Canada 30 May - 1 June 2019

Subjects
coxian phase-type distributions, business.industry, emergency department overcrowding, patient flow, Emergency department overcrowding, hospital length of stay, Regression analysis, Overcrowding, Disease cluster, medicine.disease, Phase (combat), Patient flow, Diverse population, medicine, Medical emergency, business, Limited resources
Abstract

Hospital emergency departments (EDs) operate under significant pressure worldwide. Overcrowding is a frequent occurrence, caused by a combination of high presentation numbers, and long delays in the admission of patients due to a lack of availability of hospital beds. Understanding the factors which influence length of stay (LoS) in the ED is a vital aspect of any strategy to improve patient flow. The determinants of ED patient flow are complex and varied, due to the diverse population of patients competing for limited resources. This research uses Coxian phase-type distributions to cluster patients into groups by their LoS, using a unique diagram for improved communication of patient flow issues. A novel application of survival analysis is presented to simultaneously evaluate the effect of patient attributes, system factors, and overcrowding on ED LoS. The approach is demonstrated with an application to data from a hospital in South Australia. Refereed/Peer-reviewed

Published
2020

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