DocumentCode :
139951
Title :
Precise prediction for managing chronic disease readmissions
Author :
Khanna, Saarthak ; Boyle, Justin ; Good, Nicholas
Author_Institution :
Australian E-Health Res. Centre, R. Brisbane & Women´s Hosp., Brisbane, QLD, Australia
fYear :
2014
fDate :
26-30 Aug. 2014
Firstpage :
2734
Lastpage :
2737
Abstract :
Potentially preventable hospital readmissions have a crippling effect on the health of chronic disease patients and on healthcare funding and resource utilization. While several prediction models have been proposed to help identify and manage high risk patients, most offer only moderate predictive power and discriminative ability. We develop and validate several models that utilize cohort population and clinical data and are capable of precisely identifying chronic disease patients with a high risk of rehospitalization within 30 days. Cross validation and receiver operating characteristic curve analysis are used to examine the predictive power of the models. The developed models offer high precision and discrimination and outperform current state of the art models. Delivering between 73% and 79% sensitivity at 93% specificity, the models offer excellent candidate prediction algorithms for the battle against the burden of chronic disease on the public health system.
Keywords :
diseases; health care; medical information systems; patient treatment; sensitivity analysis; candidate prediction algorithms; chronic disease patients; chronic disease readmission managing; clinical data; cohort population; cross validation; discriminative ability; health disease patients; healthcare funding; hospital readmissions; moderate predictive power; precise prediction; prediction models; public health system; receiver operating characteristic curve analysis; rehospitalization; resource utilization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2014.6944188
Filename :
6944188
Link To Document :
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