Heterogeneity within the Oregon Health Insurance Experiment: An application of causal forests

PLoS One. 2024 Jan 18;19(1):e0297205. doi: 10.1371/journal.pone.0297205. eCollection 2024.

Abstract

Existing evidence regarding the effects of Medicaid expansion, largely focused on aggregate effects, suggests health insurance impacts some health, healthcare utilization, and financial hardship outcomes. In this study we apply causal forest and instrumental forest methods to data from the Oregon Health Insurance Experiment (OHIE), to explore heterogeneity in the uptake of health insurance, and in the effects of (a) lottery selection and (b) health insurance on a range of health-related outcomes. The findings of this study suggest that the impact of winning the lottery on the health insurance uptake varies among different subgroups based on age and race. In addition, the results generally coincide with findings in the literature regarding the overall effects: lottery selection (and insurance) reduces out-of-pocket spending, increases physician visits and drug prescriptions, with little (short-term) impact on the number of emergency department visits and hospital admissions. Despite this, we detect quite weak evidence of heterogeneity in the effects of the lottery and of health insurance across the outcomes considered.

MeSH terms

  • Health Expenditures
  • Humans
  • Insurance Coverage*
  • Insurance, Health*
  • Medicaid
  • Oregon
  • United States

Grants and funding

The research was supported by funding from the University of Galway Hardiman PhD scholarship scheme. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.