| Literature DB >> 35913740 |
Rebecca Myerson1, David M Anderson2,3, Laura M Baum4, Erika Franklin Fowler4,5, Sarah E Gollust6, Paul R Shafer7.
Abstract
Importance: Many individuals eligible for coverage in the Patient Protection and Affordable Care Act (ACA) marketplace remain unenrolled because of information barriers. Whether the private sector or the public sector should conduct outreach to address these barriers is a topic of active debate. Objective: To determine whether cuts to the funding of the ACA navigator program were associated with changes in the volume of private sector advertising. Design, Setting, and Participants: Using data from the 2015 to 2019 open enrollment periods, this economic evaluation analyzed the changes in advertising associated with 2017 to 2019 cuts to navigator program funding. A difference-in-difference analysis was used to compare outcomes before and after the cuts in counties with higher and lower exposure to the navigator program. Health insurance advertising was measured using data from Kantar/Campaign Media Analysis Group in collaboration with the Wesleyan Media Project, the most comprehensive data available on local broadcast and national cable advertising. The data set included all counties that met the eligibility criteria for the navigator program from 2015 through 2019. Data were analyzed from August 2021 to May 2022. Exposures: Counties were classified as having higher or lower exposure to the navigator program according to the intensity of program activity in 2016, before the funding cuts. Counties served only by statewide navigator programs were categorized as lower exposure, while those also served by local navigator programs were categorized as higher exposure. Main Outcomes and Measures: Number of privately sponsored television advertisement airings for the ACA individual health insurance marketplace during the 2015 to 2019 open enrollment periods in each county, adjusted for population.Entities:
Mesh:
Year: 2022 PMID: 35913740 PMCID: PMC9344363 DOI: 10.1001/jamanetworkopen.2022.24651
Source DB: PubMed Journal: JAMA Netw Open ISSN: 2574-3805
Baseline Descriptive Statistics for Counties With Higher vs Lower Exposure to Navigator Program Cuts
| Characteristic | Counties, No. | ||
|---|---|---|---|
| Lower exposure (n = 1102) | Higher exposure (n = 1333) | ||
| Kantar/Campaign Media Analysis Group, 2015 | |||
| Airings by private sponsors, Mean (Median; IQR) | 2241 (1947; 800-3560) | 2283 (1354; 406-3156) | .63 |
| Airings by private sponsors: Private non-Medicare, non-Medicaid, Mean (Median; IQR) | 1551(1146; 521-2207) | 1655(986; | .12 |
| Airings by private sponsors: Medicare focus, Mean (Median; IQR) | 633 (319; | 556 (293; | .006 |
| Small Area Health Insurance Estimates data, 2015 | |||
| Population, No. of individuals | 58 093 | 79 930 | .007 |
| Uninsured individuals, No. (%) | 6668 (12.0) | 10 231 (13.5) | <.001 |
| Uninsured individuals if income is 138%-400% Federal Poverty Level, No. (%) | 3084 (5.7) | 4840 (6.3) | <.001 |
| Classified as rural county per 2013 US Department of Agriculture data, No. (%) | 220 (20.0) | 296 (22.0) | .18 |
Lower-exposure column displays the characteristics of low-exposure counties in 2013 or 2015 (baseline was 2015, but data on rural vs urban status were available in 2013 only).
Higher-exposure column displays the characteristics of high-exposure counties in 2013 or 2015 (baseline was 2015, but data on rural vs urban status were available in 2013 only).
Shown are the P values for a test of the null hypothesis that the means of the 2 groups are equal.
Rural-Urban Commuting Area codes from the US Department of Agriculture Economic Research Service,[44] 2013, were used to define rurality. Counties with a code of 8 or 9 were classified as rural.
Figure. Location of Counties With Higher vs Lower Exposure to Navigator Program Cuts (ie, Counties With vs Without Local Navigator Programs in 2016)
The higher-exposure counties in the analysis (shown in navy) were served by 1 or more nonstatewide (local) navigator programs in 2016. The lower-exposure counties (shown in white) were not served by local navigator programs in 2016 and, thus, were less exposed to cuts to these programs. As required by the Patient Protection and Affordable Care Act, all states have assister programs; the states shown in gray were ineligible for navigator grants but received federal funding via other mechanisms to establish alternative assister programs. Map was created by us using Stata version 16.1 (StataCorp) using data from the Centers for Medicare & Medicaid Services.
Changes in Health Insurance Advertising Associated With Higher Exposure to Navigator Program Cuts
| Variable | Baseline in higher-exposure counties, mean (SE) | Difference-in-differences estimate | |
|---|---|---|---|
| Advertisements, No. (95% CI) | |||
| All airings by private sponsors | 2282.9 (69.4) | 28.8 (−130.1 to 160.6) | .67 |
| Airings by private sponsors with Marketplace or other non-Medicaid, non-Medicare focus | 1655.4 (53.5) | −1.0 (−92.0 to 89.9) | .98 |
| Airings by private sponsors with Medicare focus | 556.0 (17.6) | 22.4 (−50 to 95.3) | .55 |
Regression models were adjusted for county population, time-invariant county-level characteristics, state-by-year secular trends, and local marketplace characteristics as noted in the text. SEs are clustered by state-treatment group.