Clinical and socioeconomic predictors of hospital use and emergency department visits among children with medical complexity: A machine learning approach using administrative data.

Journal: PloS one

PMID: 39471234

Abstract

OBJECTIVES: The primary objective of this study was to identify clinical and socioeconomic predictors of hospital and ED use among children with medical complexity within 1 and 5 years of an initial discharge between 2010 and 2013. A secondary objective was to estimate marginal associations between important predictors and resource use.

Authors

Michael Sidra

School of Public Health, University of Alberta, Edmonton, Canada.
Matthew Pietrosanu

Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Canada.
Jennifer Zwicker

Faculty of Kinesiology, School of Public Policy, University of Calgary, Calgary, Canada.
David Wyatt Johnson

Department of Pediatrics, University of Calgary, Calgary, Canada.
Jeff Round

School of Public Health, University of Alberta, Edmonton, Canada.
Arto Ohinmaa

School of Public Health, University of Alberta, Edmonton, Canada.

Keywords

Adolescent Alberta Child Child, Preschool Emergency Room Visits Emergency Service, Hospital Female Hospitalization Humans Infant Infant, Newborn Length of Stay Machine Learning Male Retrospective Studies Socioeconomic Factors

External Resources

View on PubMed Access via DOI PubMed (39471234)

Clinical and socioeconomic predictors of hospital use and emergency department visits among children with medical complexity: A machine learning approach using administrative data.

Abstract

Authors

Keywords

External Resources

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