Synergistic patient factors are driving recent increased pediatric urgent care demand.

ABSTRACT: We aimed to use the high fidelity urgent care patient data to model the factors that have led to the increased demand at our local pediatric urgent care centre. The dataset for this retrospective cohort study was obtained from our local healthcare centre's national reporting data for pediatric urgent care visits from 2006 to 2022. Variables analyzed included: basic patient demographics, chief complaint, triage urgency, date and time of registration/discharge, discharge diagnosis, and discharge destination. Statistical analysis of non-linear trends was summarized by locally estimated scatterplot smoothing splines. For machine learning, we used the tidymodels R package. Models were validated in training using k-fold cross validation with k = 5. We used univariate linear regression as a basel

SUBMITTER: Lehan E 

PROVIDER: S-EPMC11340883 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature