Estimation of racial and language disparities in pediatric emergency department triage using statistical modeling and natural language processing.

ABSTRACT:

Objectives

The study aims to assess racial and language disparities in pediatric emergency department (ED) triage using analytical techniques and provide insights into the extent and nature of the disparities in the ED setting.

Materials and methods

The study analyzed a cross-sectional dataset encompassing ED visits from January 2019 to April 2021. The study utilized analytical techniques, including K-mean clustering (KNN), multivariate adaptive regression splines (MARS), and natural language processing (NLP) embedding. NLP embedding and KNN were employed to handle the chief complaints and categorize them into clusters, while the MARS was used to identify significant interactions among the clinical features. The study also explored important variables, including age-adjusted

SUBMITTER: Lee SJ 

PROVIDER: S-EPMC10990499 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature