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BioMed Research International
Volume 2015 (2015), Article ID 685067, 7 pages
Research Article

Risk Factors for Emergency Department Short Time Readmission in Stratified Population

1Emergency Department, Álava University Hospital, 01010 Vitoria, Spain
2Biomedical Research Networking Center in Mental Health (CIBERSAM), 10001 Madrid, Spain
3Faculty of Medicine, University of the Basque Country (UPV/EHU), 01010 Vitoria, Spain
4Computational Intelligence Group (GIC), UPV/EHU, 20018 San Sebastián, Spain
5ACPySS, 20018 San Sebastián, Spain
6Management, Álava University Hospital, 01010 Vitoria, Spain
7Department of Psychiatry, Álava University Hospital, 01010 Vitoria, Spain

Received 21 August 2015; Revised 7 October 2015; Accepted 11 October 2015

Academic Editor: Yudong Cai

Copyright © 2015 Ariadna Besga et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. Emergency department (ED) readmissions are considered an indicator of healthcare quality that is particularly relevant in older adults. The primary objective of this study was to identify key factors for predicting patients returning to the ED within 30 days of being discharged. Methods. We analysed patients who attended our ED in June 2014, stratified into four groups based on the Kaiser pyramid. We collected data on more than 100 variables per case including demographic and clinical characteristics and drug treatments. We identified the variables with the highest discriminating power to predict ED readmission and constructed classifiers using machine learning methods to provide predictions. Results. Classifier performance distinguishing between patients who were and were not readmitted (within 30 days), in terms of average accuracy (AC). The variables with the greatest discriminating power were age, comorbidity, reasons for consultation, social factors, and drug treatments. Conclusions. It is possible to predict readmissions in stratified groups with high accuracy and to identify the most important factors influencing the event. Therefore, it will be possible to develop interventions to improve the quality of care provided to ED patients.