Estimating the intensity of ward admission and its effect on emergency department access block

Luo, Wei, Cao, Jiguo, Gallagher, Marcus and Wiles, Janet 2013, Estimating the intensity of ward admission and its effect on emergency department access block, Statistics in medicine, vol. 32, no. 15, pp. 2681-2694, doi: 10.1002/sim.5684.

Attached Files
Name Description MIMEType Size Downloads

Title Estimating the intensity of ward admission and its effect on emergency department access block
Author(s) Luo, WeiORCID iD for Luo, Wei
Cao, Jiguo
Gallagher, Marcus
Wiles, Janet
Journal name Statistics in medicine
Volume number 32
Issue number 15
Start page 2681
End page 2694
Total pages 14
Publisher Wiley
Place of publication London, England
Publication date 2013-07-10
ISSN 0277-6715
Keyword(s) admission intensity
ED access block
functional data analysis
nonhomogeneous Poisson process
Summary Emergency department access block is an urgent problem faced by many public hospitals today. When access block occurs, patients in need of acute care cannot access inpatient wards within an optimal time frame. A widely held belief is that access block is the end product of a long causal chain, which involves poor discharge planning, insufficient bed capacity, and inadequate admission intensity to the wards. This paper studies the last link of the causal chain-the effect of admission intensity on access block, using data from a metropolitan hospital in Australia. We applied several modern statistical methods to analyze the data. First, we modeled the admission events as a nonhomogeneous Poisson process and estimated time-varying admission intensity with penalized regression splines. Next, we established a functional linear model to investigate the effect of the time-varying admission intensity on emergency department access block. Finally, we used functional principal component analysis to explore the variation in the daily time-varying admission intensities. The analyses suggest that improving admission practice during off-peak hours may have most impact on reducing the number of ED access blocks.
Language eng
DOI 10.1002/sim.5684
Field of Research 080109 Pattern Recognition and Data Mining
170203 Knowledge Representation and Machine Learning
080702 Health Informatics
Socio Economic Objective 920299 Health and Support Services not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2013, Wiley-Blackwell Publishing
Persistent URL

Document type: Journal Article
Collection: Centre for Pattern Recognition and Data Analytics
Connect to link resolver
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 6 times in TR Web of Science
Scopus Citation Count Cited 6 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 237 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Tue, 12 Nov 2013, 14:06:55 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact