Objective. In an era when expanding publicly funded health insurance to children in higher income families has been the major strategy to increase access to health care for children, it is important to determine if the benefits to higher income children attributable to the receipt of health coverage are similar to those observed for lower income children. This study investigated how the likely impact of child health insurance expansions varies with family income.
Methods. We surveyed parents or guardians of children who were enrolled in a state-sponsored health insurance program (Massachusetts Children’s Medical Security Plan [CMSP]) that, before the implementation of the State Children’s Health Insurance Plan (SCHIP), was open to all children regardless of income. A stratified sample of children was drawn from administrative files. We grouped children by income category (low-income [LI]: ≤133% of the federal poverty limit [FPL], middle-income [MI]: 134%–200% of the FPL, high-income [HI]: >200% of the FPL) that corresponded to eligibility for public health insurance programs in the state (Medicaid-eligible, SCHIP-eligible, and income that exceeded SCHIP eligibility). The majority of telephone interviews were conducted between November 1998 and March 1999. The overall response rate was 61.8%, yielding a sample of 996 children.
The CSMP benefit package included comprehensive coverage for preventive and specialty care and limited coverage for ancillary services. Children enrolled in CMSP were not covered for inpatient hospital stays but those whose family income was <400% of the FPL were eligible to receive full or partial coverage for inpatient care through the state’s free care pool. Although the CMSP benefit package did not meet the standards for a SCHIP, it is an approximate equivalent for children with incomes <200% of the FPL, who have full coverage for hospitalization through the state’s free care pool.
We used survey responses to develop 2 sets of indicators: the first for reported need for services and the second for unmet need or delays in care among children whose parents reported a need for the service. Within each set, we created indicators for 5 types of service (medical care, dental care, prescription drugs, vision services, and mental health care) and an additional composite indicator. The composite indicator aggregated all categories of services covered under CMSP in a single measure; it included all services except dental services, which, at the time of the study, were not covered by the program. The composite indicator served as the dependent variable in regression models.
We used weighted χ2 tests to identify statistically significant differences in reported need and unmet need for the 5 types of medical services and the aggregate measure of all services covered by CMSP. We examined differences across income groups at 2 points in time: during the period children were uninsured before enrollment and while enrolled. We used weighted logistic regression to assess the independent association of family income with our dependent variables: reported need for health services and the presence of unmet need, controlling for other covariates. To evaluate the impact of participation in a child health insurance program, we examined unmet need before and after program enrollment, testing for statistical significance using McNemar’s test for within-subject changes.
Results. During the period of uninsurance before enrollment, prescription drugs (70%) was the health service needed most frequently, followed by medical (65%) and dental (57%) care. For the composite measure of services covered by CMSP, reported need for services was not significantly different by income. Need for medical care, dental care, and prescription drugs were significantly greater among children who had been uninsured for >6 months before enrollment. In addition, a significantly greater proportion of adolescent participants needed dental, vision, and mental health services than younger enrollees.
While enrolled, among recently enrolled children, 77% need medical services, 68% prescription drugs, and 59% dental. In unadjusted models MI and HI children were more than 2 times as likely to report need for covered services as LI children. After adjusting for possible confounders, the effect of income was no longer significant. Instead, nonadolescents (odds ratio [OR]: 2.44; 95% confidence interval [CI]: 1.25–4.76) and children with white ethnicity (OR: 3.03; 95% CI: 1.43–6.67) were significantly more likely to report need for services.
Before enrollment, unmet need among those who reported need for services was 5% for medical, 4% prescription drugs, 31% dental, 30% vision, and 33% mental health. For the composite measure of services covered by CMSP, LI children were significantly more likely to have had unmet need before enrollment than MI and HI children (20%, 10%, 7% by income). As compared with younger children, adolescents also had significantly greater unmet need for the composite measure (19% vs 10%). In multivariate models, not having a usual site of care was a highly significant predictor of unmet need or delayed care (OR: 3.41; 95% CI: 1.28–9.11). Ninety-eight percent of parents cited cost as the reason they had difficulty obtaining needed care.
After enrollment, the proportion of children who needed care and had difficulty obtaining it decreased for all categories of care. Less than 1% of enrollees reported unmet need or delays in care for medical services and 3% for prescription drugs. Children who needed vision and mental health services continued to experience difficulty obtaining these services (17% for each category of care), although they were covered as part of the benefit package. Unmet need or delays in care for dental services, which at the time of the study were not covered under CMSP, remained high (27%). We found a significant reduction in unmet need among children in all income groups and no significant differences in unmet need by income. Controlling for other covariates, adolescents (OR: 3.11; 95% CI: 1.58–6.12) and children with compromised health (OR: 3.20; 95% CI: 1.35–7.58) were more likely to have had difficulty obtaining needed services while enrolled in the program. Children in larger families (OR: 0.40; 95% CI: 0.17–0.96) and who were previously uninsured for >6 months (OR: 0.45; 95% CI: 0.22–7.58) were less likely to have difficulty obtaining care.
Conclusion. Our findings demonstrate the positive impact of providing health insurance coverage to children regardless of income. The HI children who enrolled in the program looked similar to children with incomes that meet current SCHIP eligibility guidelines, suggesting that expansions of SCHIPs to HI children should not qualitatively change the program dynamics.