QuickTake: Health Insurance Coverage Holds Steady among Children through September 2014

 

Nathaniel Anderson, Genevieve M. Kenney, Michael Karpman, Douglas Wissoker, Sharon K. Long, and Stacey McMorrow

March 5, 2015

 

The Urban Institute has been using the Health Reform Monitoring Survey (HRMS) to examine trends in health insurance coverage for nonelderly adults (ages 18 to 64) and their families under the Affordable Care Act (ACA) since the first quarter of 2013 (Long et al. 2014). Beginning in the second quarter of 2013, we added a supplement (HRMS-Kids) that tracks insurance coverage and other outcomes for children from birth to age 17 (McMorrow et al. 2014; Kenney et al. 2014). Though few provisions of the ACA directly affect health insurance options for children, understanding children’s coverage status is important because the future of the Children’s Health Insurance Program (CHIP) is in question. Federal funding for the program will expire by the end of fiscal year 2015 unless it is reauthorized. Failure to renew CHIP funding could put children covered through separate CHIP programs at risk of losing coverage (Kenney et al. 2011), which could lead to increases in uninsurance among children and higher financial burdens for their families in the coming years (Peterson 2015). There is also ongoing concern that the interface between Medicaid and CHIP and the Marketplace is not functioning as intended, particularly in states using the federally facilitated Marketplace. This QuickTake provides an update on children’s coverage by examining its changes between September 2013, just before the first open enrollment period for the ACA’s health insurance Marketplaces, and September 2014, just before the second open enrollment period.

 

We find that insurance rates were stable for children over this period, which is consistent with earlier HRMS-Kids findings (Kenney et al. 2014) and early release results for the first half of 2014 from the National Health Interview Survey (Martinez and Cohen 2014). Thus, children are maintaining the low uninsurance rates they have achieved following expansions of eligibility for Medicaid and CHIP and increased take-up of public coverage (Rosenbaum and Kenney 2014). Additionally, as of June/September 2014, nearly 57 percent of uninsured children had family income at or below 138 percent of the federal poverty level (FPL).

 

Between September 2013 and September 2014, the uninsurance rate was stable for children.

 

The uninsurance rate for children was 7.0 percent (95% CI [5.3, 8.7]) in September 2013 and 6.7 percent in September 2014 (95% CI [5.3, 8.1]; figure 1).

 

 

Over half of the children who remained uninsured in July/September 2014 had family income less than or equal to 138 percent of FPL and thus are likely eligible for public coverage.

 

We also examine the characteristics of the remaining uninsured children in our pooled June/September 2014 sample. We find that adolescents (children ages 13 to 17) represent a plurality (38.8 percent; 95% CI [31.1, 46.5]) of the remaining uninsured children. Over half of uninsured children (56.7 percent; 95% CI [47.9, 65.6]) have family income at or below 138 percent of FPL. More than 4 in 10 (44.1 percent; 95% CI [15.2, 73.1]) live in the South and more than half (53.8 percent; 95% CI [23.9, 83.6]) live in states that had not expanded Medicaid as of September 2014. The prospects for enrolling more uninsured children who are eligible for Medicaid but not enrolled are likely higher in states that have expanded Medicaid to parents under the ACA, given the evidence that eligibility expansions to parents have positive spillover effects on their children’s coverage (Dubay and Kenney 2003; Sommers 2006).

 

 

Methods: The child supplement was added to the HRMS in quarter 2 of 2013 to ask questions about a randomly selected child in respondents’ households, if the household included children. Each round of the HRMS-Kids is weighted to be nationally representative. We use these weights along with a regression adjustment to control for differences in the demographic and socioeconomic characteristics of the respondents across the different rounds of the survey for analyses over time. This allows us to remove any variation in insurance coverage caused by changes in the types of people responding to the survey over time rather than by changes in the health insurance landscape. The basic patterns shown for the regression-adjusted measures are similar to those based solely on simple weighted estimates. In presenting the regression-adjusted estimates, we use the predicted rate of each coverage type in each quarter for the same nationally representative population. For this analysis, we base the nationally representative sample on survey respondents from the most recent 12-month period from the HRMS-Kids (i.e., quarters 4 of 2013 and quarters 1–3 of 2014). We focus on statistically significant changes in insurance coverage over time (defined as differences that are significantly different from zero at the 5 percent level or lower) and highlight changes relative to September 2013, just before the open enrollment period for the Marketplaces began. We provide a 95 percent confidence interval for key estimates. In some rounds of the survey, the interview month starts a few days before or lasts a few days after the target month.

 

Our analysis of the remaining uninsured is unadjusted because it is based on the sample at a point in time. We pool the two most recent quarters of the HRMS-Kids in the analysis of the remaining uninsured to increase the sample size. In discussing composition of the remaining uninsured by Medicaid expansion status, we focus on expansion status as of September 1, 2014. States that had expanded Medicaid by this date are AZ, AR, CA, CO, CT, DE, DC, HI, IL, IA, KY, MD, MA, MI, MN, NH, NV, NJ, NM, NY, ND, OH, OR, RI, VT, WA, and WV. New Hampshire had begun its expansion just before this date, but Indiana and Pennsylvania have expanded since that time and are therefore not classified as expanding for this analysis.

 

Limitations to the analysis: The HRMS and HRMS-Kids were designed to provide early feedback on ACA implementation to complement the more robust assessments that will be possible as more federal survey data become available. Though these HRMS-Kids estimates capture the changes in insurance coverage under the first open enrollment period of the ACA, the estimates understate the full effects of the ACA because the estimates do not reflect the effects of some important ACA provisions (such as the maintenance of eligibility for children) that were implemented before 2013. In addition, these change estimates will reflect changes beyond the effects of the ACA, because they do not control for long-term trends in health insurance coverage that predate the ACA nor do they control for changes in the business cycle. Further, the difference in coverage gains between the states that did and did not expand Medicaid should not be entirely attributed to the Medicaid expansion; there were other policy choices that likely affected enrollment. For example, many of the nonexpansion states did not set up their own Marketplaces and therefore did not get the same access to outreach and enrollment assistance funding. Furthermore, the HRMS-Kids has a sample of between 2,363 and 2,777 children each quarter, substantially smaller than the 7,500 adults interviewed each quarter. Consequently, there is less precision associated with the estimated uninsurance rate for children, especially relative to the low uninsurance rate for children at baseline.

 

References

 

Dubay, Lisa, and Genevieve M. Kenney. 2003. “Expanding Public Health Insurance to Parents: Effects on Children’s Coverage under Medicaid.” Health Services Research 38 (5): 1283–1301.

 

Kenney, Genevieve M., Joan Alker, Nathaniel Anderson, Stacey McMorrow, Sharon K. Long, Douglas Wissoker, Lisa Clemans-Cope, Lisa Dubay, Michael Karpman, and Tricia Brooks. 2014. “A First Look at Children's Health Insurance Coverage under the ACA in 2014.” Washington, DC: Urban Institute.

 

Kenney, Genevieve M., Matthew Buettgens, Jocelyn Guyer, and Martha Heberlein. 2011. “Improving Coverage for Children under Health Reform Will Require Maintaining Current Eligibility Standards for Medicaid and CHIP.” Health Affairs 30 (12): 2371–81.

 

Long, Sharon K., Genevieve M. Kenney, Stephen Zuckerman, Dana E. Goin, Douglas Wissoker, Fredric Blavin, Linda J. Blumberg, Lisa Clemans-Cope, John Holahan, and Katherine Hempstead. 2014. “The Health Reform Monitoring Survey: Addressing Data Gaps to Provide Timely Insights into the Affordable Care Act.” Health Affairs 33 (1): 161–67.

 

Martinez, Michael E., and Robin A. Cohen. 2014. Health Insurance Coverage: Early Release of Estimates from the National Health Interview Survey, January–June 2014. Hyattsville, MD: National Center for Health Statistics. http://www.cdc.gov/nchs/data/nhis/earlyrelease/insur201412.pdf.

 

McMorrow, Stacey, Genevieve M. Kenney, Nathaniel Anderson, Lisa Clemans-Cope, Lisa Dubay, Sharon K. Long, and Douglas Wissoker. 2014. “Trade-Offs between Public and Private Coverage for Low-Income Children Have Implications for Future Policy Debates.”  Health Affairs 33 (8): 1367–74.

 

Peterson, Chris. 2015. “CHIP Analysis Update and Summary of Sources of Coverage if CHIP Funding Is Exhausted.” Presentation to Medicaid and CHIP Payment and Access Commission, January 22.

 

Rosenbaum, Sarah, and Genevieve M. Kenney. 2014. “The Search for a National Child Health Coverage Policy.” Health Affairs 33 (12): 2125–35.

 

Sommers, Benjamin D. 2006. “Insuring Children or Insuring Families: Do Parental and Sibling Coverage Lead to Improved Retention of Children in Medicaid and CHIP?” Journal of Health Economics 25 (6): 1154–69.

 

About the Series

 

This QuickTake is part of a series drawing on the HRMS, a quarterly survey of the nonelderly population that is exploring the value of cutting-edge Internet-based survey methods to monitor the ACA before data from federal government surveys are available. Funding for the core HRMS is provided by the Robert Wood Johnson Foundation and the Urban Institute. This quick take was funded by the David and Lucile Packard Foundation.  It draws on the HRMS-Kids which was conducted in partnership with the Center for Children and Families at Georgetown University and is currently funded by the David and Lucile Packard Foundation. The authors are grateful to Lisa Clemans-Cope, Lisa Dubay, Joan Alker, Tricia Brooks, and Liane Wong for their input on the HRMS-Kids.

 

For more information on the HRMS and for other QuickTakes in this series, visit www.urban.org/hrms.

Urban Institute Robert Wood Johnson Foundation