Early Changes in Employer-Sponsored Insurance and Worker Outcomes under the Affordable Care Act: Real-Time Survey Results from the Health Reform Monitoring Survey
As such, it will be critical for researchers and state and federal decision-makers to monitor changes to employer behavior, group insurance markets, and coverage among workers and their dependents resulting from full implementation of the ACA. Using data from the Urban Institute’s Health Reform Monitoring Survey (HRMS), this paper will provide real-time insights into the early effects of the ACA on various worker outcomes, including:
- Full-time and part-time work status, to assess if employers with more than 50 workers are reducing employee hours to 29 or less to avoid the ACA’s requirement that they offer health insurance to employees working more than 30 hours a week.
- Employer-sponsored insurance (ESI) and ESI offer, to examine if employers stop or start offering ESI in response to the economic incentives created by subsidized care in the marketplace and individual mandate.
- Worker participation in Medicaid and the health insurance marketplaces
We will explore these outcomes at the national and state-level and will provide estimates key subpopulations, including worker firm size (fewer than 50 workers vs. 50 workers or more), income group, age group, and self-reported health status.
The HRMS is fielded once each quarter and provides real-time estimates on ACA implementation and impacts. The HRMS is based on a nationally representative internet panel—GfK’s KnowledgePanel[i]—and began in January 2013 to provide a baseline for rapid-cycle feedback on changes under the ACA in 2014 to supplement other analyses under the Robert Wood Johnson Foundation’s Monitoring and Tracking of the implementation of the ACA project. The overall sample size for the stratified random sample survey is roughly 7,500 non-elderly adults per quarter (randomly recruited through probability-based sampling), which will support statistical tests of relatively small minimum detectable differences over time and across key population groups.