Crowd-Out and Emergency Department Utilization

Abstract

When consumers gain Medicaid, their cost of healthcare changes. The direction of this change determines how utilization changes. The previously uninsured see a stark decrease in the price of primary care after gaining public insurance. Due to charity care, they may face an increase in the price of emergency department care. The previously insured see a reduction in emergency department prices and decreased access to primary care. We examine the impact of the prior insurance status of the newly publicly insured on substitution between healthcare. We base our identification on California's LIHP and ACA Medicaid expansions. One challenge we face is estimating crowd-out. We use machine learning techniques to predict prior insurance status based on observable covariates in cross-sectional data. We find an increase in emergency department utilization caused entirely by those crowded-out whose access to primary care has decreased. We find the opposite utilization patterns for the previously uninsured.

Keywords: Charity Care; Crowd Out; Emergency Departments; Machine Learning; Medicaid.