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Estimating the intensity of ward admission and its effect on emergency department access block
journal contribution
posted on 2013-07-10, 00:00 authored by Wei LuoWei Luo, J Cao, M Gallagher, J WilesEmergency 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.
History
Journal
Statistics in medicineVolume
32Issue
15Pagination
2681 - 2694Publisher
WileyLocation
London, EnglandPublisher DOI
ISSN
0277-6715eISSN
1097-0258Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2013, Wiley-Blackwell PublishingUsage metrics
Categories
Keywords
admission intensityED access blockfunctional data analysisnonhomogeneous Poisson processScience & TechnologyLife Sciences & BiomedicinePhysical SciencesMathematical & Computational BiologyPublic, Environmental & Occupational HealthMedical InformaticsMedicine, Research & ExperimentalStatistics & ProbabilityResearch & Experimental MedicineMathematicsMORTALITYStatistics
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