The Impact of Medicaid Expansion on Medicare Quality Measures

TL;DR

This study investigates how Medicaid expansion under the Affordable Care Act affected hospital quality measures for the Medicare population, finding improvements in readmission rates for certain conditions between 2013 and 2021.

Contribution

It provides the first analysis of Medicaid expansion's impact on Medicare hospital quality measures using difference-in-difference methodology.

Findings

Improved readmission rates for acute myocardial infarction and coronary artery bypass graft surgery in expansion states.

Some evidence of improved hospital quality for pneumonia and heart failure measures.

Potential for further significant results with refined methods and datasets.

Abstract

The Affordable Care Act was signed into law in 2010, expanding Medicaid and improving access to care for millions of low-income Americans. Fewer uninsured individuals reduced the cost of uncompensated care, consequently improving the financial health of hospitals. We hypothesize that this amelioration in hospital finances resulted in a marked improvement of quality measures in states that chose to expand Medicaid. To our knowledge, the impact of Medicaid expansion on the Medicare population has not been investigated. Using a difference-in-difference analysis, we compare readmission rates for four measures from the Hospital Readmission Reduction Program: acute myocardial infarction, pneumonia, heart failure, and coronary artery bypass graft surgery. Our analysis provides evidence that between 2013 and 2021 expansion states improved hospital quality relative to non-expansion states as it relates to acute myocardial infarction readmissions (p = 0.015) and coronary artery bypass graft surgery readmissions (p = 0.039). Our analysis provides some evidence that expanding Medicaid improved hospital quality, as measured by a reduction in readmission rates. Using visualizations, we provide some evidence that hospital quality improved for the other two measures as well. We believe that a refinement of our estimation method and an improved dataset will increase our chances of finding significant results for these two other measures.