Medicaid Enrollment Leads to More School Absenteeism: EmpiricalEvidence from National Health Interview Survey
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Medicaid is the government insurance program that provides health insurance to the poor. The effect of Medicaid eligibility on children’s health is of great concern. The literature survey demonstrates that Medicaid eligibility largely increased the utilization of medical service. However, there are few studies evaluating the effect of Medicaid eligibility on children’s health conditions. This paper use ‘days of school missed due to illnesses or injury’ as the measurement to illustrate the effect of Medicaid eligibility on children’s health. Four econometric models are used to fully analyze the effect of Medicaid eligibility on children’s health outcome. The four models are probit model, triprobit model, negative binomial model and endogenous negative binomial model. Medicaid eligibility and days of school missed due to illness or injury are positively correlated in all four models.Keywords:
Ordered probit
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Background. Many Medicaid-eligible children are not enrolled in Medicaid and are not covered by private insurance. Reducing persistent lack of insurance for children requires a better understanding of why Medicaid-eligible children do not participate. Research Questions. Does the availability of free or low-cost medical services substitute for Medicaid or private insurance enrollment among Medicaid-eligible children? Does the availability and affordability of insurance coverage, particularly the offer of employer-sponsored insurance (ESI) and the presence of managed care, affect child insurance coverage? Research Design. We use data from the National Health Interview Survey for 1994 and 1995, supplemented with county level measures of insurance and provider supply, to estimate a multinomial choice model of insurance coverage among children identified as Medicaid-eligible. We focus on county supply of public hospitals and community/migrant health centers (C/MHC); and the availability and cost of ESI. We control for child and parent characteristics. Results. A positive effect of C/MHC supply is found on Medicaid enrollment, but no evidence is found of substitution between low-cost providers and Medicaid or private coverage. Local availability of ESI and private HMO penetration increased private insurance enrollment. Conclusions. Local community providers can play an important role in outreach and enrollment for Medicaid. Availability and cost of ESI constrain private coverage for Medicaid-eligible children. Policies that encourage offers of insurance coverage by employers, decrease premiums, and encourage adoption of managed care could have important positive effects on coverage for this population.
Cost sharing
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In addition to providing income-maintenance payments to eligible participants, the Supplemental Security Income (SSI) program provides automatic Medicaid enrollment for applicants upon SSI award in most states. Other states require applicants to file a separate Medicaid application. Some use the SSI eligibility criteria for both programs; others use Medicaid eligibility rules that are more restrictive. The authors use matched monthly longitudinal administrative records to test whether automatic enrollment has a positive effect on Medicaid coverage. Using logistic regression with a combination of repeated cross-section and regression discontinuity approaches, they find positive effects of automatic enrollment on Medicaid coverage relative to other policies. The differences are attributable to a discontinuous increase in Medicaid coverage shortly after the final disability determination decision. The time lag arising from the often-lengthy disability determination process reduces the effectiveness of automatic enrollment, which depends critically on timeliness of the final award decision.
Regression discontinuity design
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This report addresses how Medicaid eligibility expansions have affected low-income children's access to care and service use. It outlines a theoretical model to identify determinants of children's health care use and also uses the model to identify data that would be required to evaluate the effects of expanding eligibility to low-income children on their access to care and service use. The assessment also identifies specific items that should be added to existing surveys to better evaluate the Medicaid eligibility expansions for low-income children. Included is a summary of the model formulated and the survey assessment.
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Objective Millions of low‐income Americans will gain health insurance through Medicaid under the Affordable Care Act. This study assesses the impact of previous Medicaid expansions on mental health services utilization and out‐of‐pocket spending. Data Sources Secondary data from the 1998–2011 Medical Expenditure Panel Survey Household Component merged with National Health Interview Survey and state Medicaid eligibility rules data. Study Design Instrumental variables regression models were used to estimate the impact of expanded Medicaid eligibility on health insurance coverage, mental health services utilization, and out‐of‐pocket spending for mental health services. Data Extraction Methods Person‐year files were constructed including adults ages 21–64 under 300 percent of the Federal Poverty Level. Principal Findings Medicaid expansions significantly increased health insurance coverage and reduced out‐of‐pocket spending on mental health services for low‐income adults. Effects of expanded Medicaid eligibility on out‐of‐pocket spending were strongest for adults with psychological distress. Expanding Medicaid eligibility did not significantly increase the use of mental health services. Conclusions Previous Medicaid eligibility expansions did not substantially increase mental health service utilization, but they did reduce out‐of‐pocket mental health care spending.
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A rapid increase of Medicaid expenditures has been a serious concern, and housing stability has been discussed as a means to reduce Medicaid costs. A program evaluation of a New York City supportive housing program has assessed the association between supportive housing tenancy and Medicaid savings among New York City housing program applicants with serious mental illness and chronic homelessness or dual diagnoses of mental illness and substance use disorder, stratified by distinctive Medicaid expenditure patterns. The evaluation used matched data from administrative records for 2827 people. Sequence analysis identified 6 Medicaid expenditure patterns during 2 years prior to baseline among people placed in the program (n = 737) and people eligible but not placed (n = 2090), including very low Medicaid coverage, increasing Medicaid expenditure, low, middle, high, and very high Medicaid expenditure patterns. We assessed the impact of the program on Medicaid costs for 2 years post-baseline via propensity score matching and bootstrapping. The housing program was associated with Medicaid savings during 2 years post-baseline (−$9526, 95% CI = −$19,038 to -$2003). Stratified by Medicaid expenditure patterns, Medicaid savings were found among those with very low Medicaid coverage (−$15,694, 95% CI = −$35,926 to -$7983), increasing Medicaid expenditures (−$9020, 95% CI = −$26,753 to -$1705), and high Medicaid expenditure patterns (−$14,450, 95% CI = −$38,232 to -$4454). Savings were largely driven by shorter psychiatric hospitalizations in the post-baseline period among those placed. The supportive housing program was associated with Medicaid savings, particularly for individuals with very low Medicaid coverage, increasing Medicaid expenditures, and high Medicaid expenditures pre-baseline.
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With ELE, a state's Medicaid and/or CHIP program can rely on another agency's eligibility findings to qualify children for public coverage. Using 2007 to 2011 quarterly enrollment data, we estimate difference-in-difference equations with quarter and state fixed effects to measure the effect of ELE on enrollment. The estimated impacts of ELE on Medicaid enrollment were consistently positive across model specifications, ranging between 4.0 and 7.3 percent. The analysis also finds that ELE increased Medicaid/CHIP enrollment. Our results imply that ELE has been an effective way for states to increase new enrollment or improve retention among eligible children.
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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.
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To describe the extent and implications of "churn" between different Medicaid eligibility classifications in a pediatric population: (1) aged, blind, and disabled (ABD) Medicaid eligibility, determined by disability status and family income; and (2) Healthy Start Medicaid eligibility, determined by family income alone.As a result of a 2013 policy change, children with ABD eligibility transitioned from fee-for-service to capitated care. We used Ohio Medicaid claims data from July 2013 through June 2015 to explore the relationships among instability in eligibility category, demographics, and utilization.To examine the potential financial effect of categorical churn, an effective capitation rate was created to capture the proportion of the maximum potential capitation rate that was realized.More than 20% of children exited ABD-based eligibility at least once. Switching was associated with younger age and rural residence and was not associated with healthcare use.Switching between eligibility categories is common and affects average capitation but not health service use.
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Categorical variable
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This paper explores enrollment and cost estimates for providing Medicaid coverage to Alaskan children, pregnant women, and nonpregnant adults. It provides enrollment and expenditure estimates of implementing two Medicaid policy options using five different income eligibility criteria. Included are a description of health care reform options under Medicaid; health insurance coverage and health care expenditures under the current system; characteristics of the eligible population; and enrollment and expenditure estimates for selected expansion options. The report concludes with a future projection of expenditures and a discussion of who will pay for the cost of reform.
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This study uses data from the National Longitudinal Survey of Youth to track the health coverage of parents in the year before and the year in which their children enroll in Medicaid. Use of such longitudinal data, compared to cross-sectional data, provides more insight into the dynamics of health insurance coverage and expansions in Medicaid. Using these data, we find that approximately 16% of newly enrolled Medicaid children likely had access to private insurance through a parent. Moreover, most of the children enrolling in Medicaid were previously uninsured. We find little substitution of private for public health insurance among families living at or near the federal poverty line.
Private insurance
Public health insurance
Poverty level
Longitudinal data
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