Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).

ABSTRACT:

Objective

To improve the performance of International Classification of Disease (ICD) code rule-based algorithms for identifying low acuity Emergency Department (ED) visits by using machine learning methods and additional covariates.

Data sources

We used secondary data on ED visits from the National Hospital Ambulatory Medical Survey (NHAMCS), from 2016 to 2020.

Study design

We established baseline performance metrics with seven published algorithms consisting of International Classification of Disease, Tenth Revision codes used to identify low acuity ED visits. We then trained logistic regression, random forest, and gradient boosting (XGBoost) models to predict low acuity ED visits. Each model was trained on five different covariate sets of demographic and clinical d

SUBMITTER: Chen AT 

PROVIDER: S-EPMC11249839 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature