Unknown

Dataset Information

0

The effects of express lane eligibility on Medicaid and CHIP enrollment among children.


ABSTRACT: To estimate the impact of Express Lane Eligible (ELE) implementation on Medicaid/CHIP enrollment in eight states.2007 to 2011 data from the Statistical Enrollment Data System (SEDS) on Medicaid/CHIP enrollment.We estimate difference-in-difference equations, with quarter and state fixed effects. The key independent variable is an indicator for whether the state had ELE in place in the given quarter, allowing the experience of statistically matched non-ELE states to serve as a formal counterfactual against which to assess the changes in the eight ELE states. The model also controls for time-varying economic and policy factors within each state.We obtained SEDS enrollment data from CMS.Across model specifications, the ELE effects on Medicaid enrollment among children were consistently positive, ranging between 4.0 and 7.3 percent, with most estimates statistically significant at the 5 percent level. We also find that ELE increased combined Medicaid/CHIP enrollment.Our results imply that ELE has been an effective way for states to increase enrollment and retention among children eligible for Medicaid/CHIP. These results also imply that ELE-like policies could improve take-up of subsidized coverage under the ACA.

SUBMITTER: Blavin F 

PROVIDER: S-EPMC4239849 | biostudies-other | 2014 Aug

REPOSITORIES: biostudies-other

altmetric image

Publications

The effects of express lane eligibility on Medicaid and CHIP enrollment among children.

Blavin Fredric F   Kenney Genevieve M GM   Huntress Michael M  

Health services research 20140130 4


<h4>Objective</h4>To estimate the impact of Express Lane Eligible (ELE) implementation on Medicaid/CHIP enrollment in eight states.<h4>Data sources/study setting</h4>2007 to 2011 data from the Statistical Enrollment Data System (SEDS) on Medicaid/CHIP enrollment.<h4>Study design</h4>We estimate difference-in-difference equations, with quarter and state fixed effects. The key independent variable is an indicator for whether the state had ELE in place in the given quarter, allowing the experience  ...[more]

Similar Datasets

| S-EPMC4450923 | biostudies-literature
| S-EPMC3037784 | biostudies-literature
| S-EPMC5980223 | biostudies-literature
| S-EPMC6153165 | biostudies-literature
| S-EPMC7287571 | biostudies-literature
| S-EPMC7029817 | biostudies-literature
| S-EPMC8100862 | biostudies-literature
| S-EPMC4799898 | biostudies-other
| S-EPMC6642806 | biostudies-literature