Graphical models (GM) are statistical methods for modeling relationships between variables as a graph; where nodes depict variables and edges depict their dependencies. GM can illustrate complex interactions among variables in clinical and epidemiologic data. However, the application of GM to these studies are limited. This study aims to understand the usage of GM in medical literature involving clinical and epidemiologic studies and demonstrate the utility of GM in analyzing a dataset of post-liver transplant patients. For each article found through the literature review; the study design, sample size, number of variables, and type of GM method was recorded. Multivariate regression and a GM method were used to model the relationship between numerous clinical characteristics and quality of life among post-liver transplant patients. Altogether, the literature review and data analysis motivate the uptake of GM in future healthcare research.