Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/116257
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Type: Journal article
Title: Probability of severe adverse events as a function of hospital occupancy
Author: Boyle, J.
Zeitz, K.
Hoffman, R.
Khanna, S.
Beltrame, J.
Citation: IEEE journal of biomedical and health informatics, 2014; 18(1):15-20
Publisher: IEEE
Issue Date: 2014
ISSN: 2168-2194
2168-2208
Statement of
Responsibility: 
Justin Boyle, Kathryn Zeitz, Richard Hoffman, Sankalp Khanna, John Beltrame
Abstract: A unique application of regression modeling is described to compare hospital bed occupancy with reported severe adverse events amongst inpatients. The probabilities of the occurrence of adverse events as a function of hospital occupancy are calculated using logistic and multinomial regression models. All models indicate that higher occupancy rates lead to an increase in adverse events. The analysis identified that at an occupancy level of 100%, there is a 22% chance of one severe event occurring and a 28% chance of at least one severe event occurring. This modeling contributes evidence toward the management of hospital occupancy to benefit patient outcomes.
Keywords: Biomedical informatics; hospitals; prediction algorithms; regression analysis
Rights: © 2013 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
DOI: 10.1109/JBHI.2013.2262053
Published version: http://dx.doi.org/10.1109/jbhi.2013.2262053
Appears in Collections:Aurora harvest 3
Medicine publications

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