Exploring Adverse Drug Events Through Interactive Visualizations
Abstract
Adverse drug events (ADEs) pose a significant challenge in pharmacovigilance due to their complex, multidimensional nature and the limitations of static visualization methods. This thesis presents ENVISION—OpenFDA Adverse Drug Events Database Exploratory Interactive Visualization—an interactive system that transforms raw ADE data into visual insights. ENVISION addresses the important need of generating user friendly visualization of data by combining the hierarchical visualizations that utilize a tree map and Sankey diagram within it and real-time filtering and drill down capabilities. In this work, we use a representative openFDA ADE dataset as our project and it uses human–computer interaction principles and web technologies (e.g., D3.js and JavaScript) to visualize intricate relationships between patient demographics and drug information with reported outcomes. This system facilitates efficient hypothesis generation and informed decision-making by enabling exploration of ADE data across multiple dimensions. Ultimately, ENVISION enhances data comprehension and supports effective drug safety monitoring in dynamic healthcare environments. This interactive system paves the way for safer healthcare.