Predicting all-cause 90-day hospital readmission for dental patients using machine learning methods.

ABSTRACT:

Introduction

Hospital readmission rates are an indicator of the health care quality provided by hospitals. Applying machine learning (ML) to a hospital readmission database offers the potential to identify patients at the highest risk for readmission. However, few studies applied ML methods to predict hospital readmission. This study sought to assess ML as a tool to develop prediction models for all-cause 90-day hospital readmission for dental patients.

Methods

Using the 2013 Nationwide Readmissions Database (NRD), the study identified 9260 cases for all-cause 90-day index admission for dental patients. Five ML classification algorithms including decision tree, logistic regression, support vector machine, k-nearest neighbors, and artificial neural network (ANN) were implemen

SUBMITTER: Li W 

PROVIDER: S-EPMC7822935 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature