Honors Thesis Projects

Date of Award

2020

Document Type

Honors Paper

Degree Name

Actuarial Science-BS

Department

Mathematical Sciences

Advisor

Dr. Zhen Huang

First Committee Member

Dr. Pei Pei

Second Committee Member

Louise Captein

Keywords

Insurance Coverage, Perinatal and Neonatal Morbidity, Statistical Analysis, Demographic Effects, Ohio Women

Subject Categories

Applied Statistics | Other Mathematics | Statistical Models

Abstract

In the United States of America, Ohio has one of the worst neonatal and perinatal death rates. Within Ohio, Montgomery County has an above average neonatal and perinatal death rate. This statistic can be lowered if more women in Montgomery County have health insurance. They would be more likely to seek out prenatal health care, since they would no longer have to pay as much money out-of-pocket. This would allow medical professionals to be able to diagnose and treat any potential issues in the mother or child earlier. Having health insurance would also prevent mothers-to-be from seeking out other potentially dangerous options to avoid paying exorbitant amounts of money to deliver their baby, such as at-home births. This project seeks to identify whether women who fall into certain demographics have different likelihoods of having health insurance.

Data was collected from Miami Valley Hospital, located in Montgomery County. The data was then run through several different models, until one was chosen that was the most accurate and adequate. The selected model showed that women with various demographics do have different likelihoods of having health insurance. This would allow an insurance company to be able to design a product specifically for the demographics who are the most likely to be uninsured, thus increasing the number of women who have insurance, and lowering the neonatal and perinatal death rate.

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