Predicting emergency department visits in a large teaching hospital.

ABSTRACT:

Background

Emergency department (ED) visits show a high volatility over time. Therefore, EDs are likely to be crowded at peak-volume moments. ED crowding is a widely reported problem with negative consequences for patients as well as staff. Previous studies on the predictive value of weather variables on ED visits show conflicting results. Also, no such studies were performed in the Netherlands. Therefore, we evaluated prediction models for the number of ED visits in our large the Netherlands teaching hospital based on calendar and weather variables as potential predictors.

Methods

Data on all ED visits from June 2016 until December 31, 2019, were extracted. The 2016-2018 data were used as training set, the 2019 data as test set. Weather data were extracted from three public

SUBMITTER: Erkamp NS 

PROVIDER: S-EPMC8196936 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature