Predict Health Care Accessibility for Texas Medicaid Gap

Area of Science:

• Public Health
• Health Economics
• Health Services Research

Background:

• Medicaid provides essential health insurance coverage for low-income Americans, but coverage gaps exist.
• Twelve states with non-expanded Medicaid have left two million individuals below the poverty line without adequate health insurance.
• This creates significant health insecurity and exacerbates existing healthcare disparities.

Purpose of the Study:

• To analyze the impact of socioeconomic factors on health status within the context of Medicaid coverage.
• To evaluate the effectiveness of Principal Component-based logistical regression (PCA-LA) in assessing health status.
• To provide evidence supporting Medicaid expansion in states like Texas and address healthcare geographical inequity.

Main Methods:

• Utilized Principal Component-based logistical regression (PCA-LA) with health status (HS) as the dependent variable.
• Incorporated fourteen social-economic indexes, including health conditions (no regular source of care, last check-up more than a year ago), demographics, education, and marital status.
• Compared PCA-LA with unadjusted logistical regression (LA), direct adjusted LA, and PCA-unadjusted LA to assess outcomes.

Main Results:

• PCA-LA demonstrated objective and reliable outcomes in presenting odds ratios (OR).
• Health conditions were positively significant to health status (OR > 1).
• Education, demographic impacts, and marital status were negatively significant to health status.

Conclusions:

• The study provides quantitative evidence for the negative impact of the Medicaid gap in Texas.
• Findings highlight significant healthcare geographical inequity.
• Recommendations are made for the Centers for Disease Control and Prevention (CDC) to improve Medicaid policy and achieve political justice.