Public Insurance Eligibility Thresholds and Receipt of Mental Health Services among Childen from Households with Low

Yidan Xue Zhang1, Adam S Wilk2,3, Janet R Cummings4

  • 1ASRT Inc, Smyrna, GA, USA. yidan.x.zhang@hotmail.com.

Insights

Higher income eligibility for Medicaid and the Children's Health Insurance Program (CHIP) is linked to fewer unmet mental health needs in low-income children. Expanding these programs improves access to care for children needing mental health services.

Area of Science:

  • Child Health
  • Health Services Research
  • Mental Healthcare Access

Background:

  • Only 50% of U.S. children with mental health conditions receive treatment annually.
  • Children from lower-income households face significant barriers to accessing mental health services.
  • Medicaid and the Children's Health Insurance Program (CHIP) provide crucial insurance for accessing care.

Purpose of the Study:

  • To examine the relationship between Medicaid and CHIP income eligibility thresholds and mental health service receipt among low-income children.
  • To investigate how state-level variations in eligibility impact children's access to mental healthcare.

Main Methods:

  • Utilized data from the 2016-2020 National Survey of Children's Health.
  • Included children aged 6-17 with household incomes below 400% of the federal poverty line.
  • Conducted multivariable logistic regressions to assess associations between eligibility thresholds and mental health service use and unmet needs.

Main Results:

  • No significant relationship was found between eligibility thresholds and the use of any mental health services.
  • A higher eligibility threshold was associated with a 20% decrease in the odds of unmet mental health needs (OR: 0.79, p < 0.01).

Conclusions:

  • More generous Medicaid and CHIP eligibility thresholds correlate with reduced unmet mental health care needs in low-income children.
  • Policy implications suggest that expanding eligibility can improve mental healthcare access for vulnerable populations.
Abstract

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