Insurance Patterns and Instability from 2006 to 2016

Tuesday, June 25, 2019
Exhibit Hall C (Marriott Wardman Park Hotel)

Presenter: Yunwei Gai

Co-Author: Kent Jones

Majority of the literature on health insurance focuses on coverage at one point in time while research on insurance (in)stability is underrepresented even though it can lead to drastically different conclusions and serious consequences. Using the Medical Expenditure Panel Survey (MEPS), we examined changes in insurance patterns and instability among nonelderly adults below 65 years old from 2006 to 2016. We conducted additional analyses in sub-populations by age, income, race/ethnicity and medical conditions. We created 16 measures to study the relationship between insurance instability and health-related outcomes. In each model, we controlled respondents’ type of insurance instability, socioeconomic characteristics, demographics, general health status, priority conditions, panel/year and geographic indicators. We used MEPS’ longitudinal weight to account for its complex survey design.

Seven insurance patterns included: (1) always insured, (2) sing gap, (3) transition into coverage, (4) transition out of coverage, (5) temporary coverage, (6) repeatedly uninsured and (7) always uninsured. The impact of the Great Recession was reflected in the increase of insurance instability (i.e., patterns 2 to 7) from 31.80% (or 80.00 million) in the 2006-2007 period to 34.61% (or 88.36 million) in the 2008-2009 period. The impact of ACA was reflected in the steady and gradual increase of the always-insured after 2012-2013. The always-insured rate of 74.23% (or 193.71 million) in 2015-2016 was significantly higher than pre-ACA periods of 2006 to 2010, and during the ACA implementation periods of 2011-2012 and 2012-2013. The ever-uninsured rate (i.e., patterns 2 to 7) of 25.77% (or 67.25 million) in 2015-2016 was the lowest in the entire sample period.

Compared to always-insured, all patterns of insurance instability were associated with significantly lower access to care, decrease in both the probability and numbers of preventive care use, less utilization of health services and lower expenditures. The largest changes were among the always-uninsured followed by the temporarily-insured and repeatedly-uninsured. For example, always-uninsured people, compared to always-insured, were 34.74% less likely to have access to care. The decreases were 30.61% for temporary coverage, 26.25% for repeatedly uninsured, 22.09% for transition-out-of-coverage, 21.65% for transition-into-coverage, and 16.81% for a single gap. People with insurance gaps were more likely to smoke. But they were slightly more likely to exercise and they were slightly healthier in perceived health, BMI, overweight status, Kessler index, Physical Component Summary (PCS) and the Mental Component Summary (MCS). These relationships likely reflected the adverse selection.

Despite improvement in insurance coverage after the ACA, there is still over one quarter of U.S. population with at least one uninsured spell. People with insurance interruptions encounter underutilization of preventive care and loss of usual source of care. Although the problem is less sever relative to continuously uninsured, the decrease remains significant regardless the patterns of instability. It is thus important for policy makers and researchers to continue their attentions on insurance instability and its consequences. Future research is needed to investigate the causality relationship between insurance patterns and health-related outcomes; and the impacts of recent changes in ACA such as the individual mandate repeal on insurance instability.