Predicting Emergency Department Visits

Overview

Journal AMIA Jt Summits Transl Sci Proc

Specialty Biology

Date 2016 Aug 30

PMID 27570684

Citations 10

Authors

Sarah Poole

Shaun Grannis

Nigam H Shah

Affiliations

Soon will be listed here.

Abstract

High utilizers of emergency departments account for a disproportionate number of visits, often for nonemergency conditions. This study aims to identify these high users prospectively. Routinely recorded registration data from the Indiana Public Health Emergency Surveillance System was used to predict whether patients would revisit the Emergency Department within one month, three months, and six months of an index visit. Separate models were trained for each outcome period, and several predictive models were tested. Random Forest models had good performance and calibration for all outcome periods, with area under the receiver operating characteristic curve of at least 0.96. This high performance was found to be due to non-linear interactions among variables in the data. The ability to predict repeat emergency visits may provide an opportunity to establish, prioritize, and target interventions to ensure that patients have access to the care they require outside an emergency department setting.

Citing Articles

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Lee Y, Ng C, Hsu C, Cheng C, Chen S BMC Emerg Med. 2024; 24(1):20.

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Management of Inflammatory Bowel Disease Patients With Clinical Care Pathways Reduces Emergency Department Utilization.

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Can diverse population characteristics be leveraged in a machine learning pipeline to predict resource intensive healthcare utilization among hospital service areas?.

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Can the adverse childhood experiences (ACEs) checklist be utilized to predict emergency department visits among children and adolescents?.

Bhattarai A, Dimitropoulos G, Marriott B, Paget J, Bulloch A, Tough S BMC Med Res Methodol. 2021; 21(1):195.

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Predictive Modeling of 30-Day Emergency Hospital Transport of German Patients Using a Personal Emergency Response: Retrospective Study and Comparison with the United States.

Op den Buijs J, Pijl M, Landgraf A JMIR Med Inform. 2021; 9(3):e25121.

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