Abstract
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.
Highlights
Health care access is convoluted, emerging with different system constraints depending on the complex healthcare needs, improving access rests on system-targeted facilitators, interventions, and policies [1]
Medicaid gap has the biggest barrier in health condition among all insurance coverages, regarding the comparison between “bad” and “good” answers, including those in Medicaid gap were twice as likely to represent fair or poor health
In the beyond poverty group, the odd ratio (OR) value equals 1.33 response to “no” as referent group in terms of “no regular source of care”, meaning those who had private insurances, but no regular check-up sources had a 133% higher chance of health risks when compared with people who had a regular source of care within private insurances conditions and a 95% confidence interval (CI)
Summary
Health care access is convoluted, emerging with different system constraints depending on the complex healthcare needs, improving access rests on system-targeted facilitators, interventions, and policies [1]. Medicaid is the largest common federal health care coverage program for low-income individuals of diverse ages in the United States and serves as a core institution that shapes public health crises, racial injustice, and electoral politics [6]. It was created by President Lyndon B. The Medicaid gap is defined as those who do not have private insurance and unqualified Medicaid requirements They are exposed to high risks of health care, social security, as well as vulnerability. The general mathematical equation of logistical regression is written as follows, where Y is the dependent variable
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