标題: Predict Health Care Accessibility for Texas Medicaid Gap

作者: Zhang, JT (Zhang, Jinting); Wu, X (Wu, Xiu)來源出版物: HEALTHCARE 卷:9 期:9 DOI: 10.3390/healthcare9091214 出版年: SEP 2021

摘要: Medicaid is a unique approach in ensuring the below poverty population obtains free insurance coverage under federal and state provisions in the United States. Twelve states without expanded Medicaid caused two million people who were under the poverty line into health insecurity. Principal Component-based logistical regression (PCA-LA) is used to consider health status (HS) as a dependent variable and fourteen social-economic indexes as independent variables. Four composite components incorporated health conditions (i.e., "no regular source of care" (NRC), "last check-up more than a year ago" (LCT)), demographic impacts (i.e., four categorized adults (AS)), education (ED), and marital status (MS). Compared to the unadjusted LA, direct adjusted LA, and PCA-unadjusted LA three methods, the PCA-LA approach exhibited objective and reasonable outcomes in presenting an odd ratio (OR). They included that health condition is positively significant to HS due to beyond one OR, and negatively significant to ED, AS, and MS. This paper provided quantitative evidence for the Medicaid gap in Texas to extend Medicaid, exposed healthcare geographical inequity, offered a sight for the Centers for Disease Control and Prevention (CDC) to improve the Medicaid program and make political justice for the Medicaid gap.

作者關鍵詞: Medicaid gap; health access; principal components; logistical regression

地址: [Zhang, Jinting] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Wu, Xiu] Texas State Univ, Dept Geog, San Marcos, TX 78666 USA.

通訊作者地址: Wu, X (通訊作者)，Texas State Univ, Dept Geog, San Marcos, TX 78666 USA.

電子郵件地址: whuzjt@whu.edu.cn; x_w10@txstate.edu

影響因子：2.645