Minimizing the Perceived Financial Burden Due to Cancer

Citation data:

Vol: 1, Issue: 3

Publication Year:
2018
Usage 78
Abstract Views 42
Downloads 36
Repository URL:
https://scholar.smu.edu/datasciencereview/vol1/iss3/6
Author(s):
Azhar, Hassan; Allam, Zoheb; Varghese, Gino; Engels, Daniel W; John, Sajiny
Tags:
cancer; reduced cost; financial burden; direct cost; p values; statistics; Categorical Data Analysis; Clinical Trials; Statistical Methodology; Statistical Models; Statistical Theory
article description
In this paper, we present a regression model that predicts perceived financial burden that a cancer patient experiences in the treatment and management of the disease. Cancer patients do not fully understand the burden associated with the cost of cancer, and their lack of understanding can increase the difficulties associated with living with the disease, in particular coping with the cost. The relationship between demographic characteristics and financial burden were examined in order to better understand the characteristics of a cancer patient and their burden, while all subsets regression was used to determine the best predictors of financial burden. Age, household income, and breast cancer are the strongest predictors of financial burden, while breast cancer patients are most at risk to suffer from high financial burden. Our findings indicate that certain demographic characteristics have a larger impact on perceived financial burden than others, making it possible to target certain demographic groups with increased education in order to aid in the management of the disease.