IRVINE: An Interactive Visualization for Spontaneous Reporting Systems Databases Missing Values

Large-scale post-marketing drug safety data from spontaneous reporting systems offer new opportunities to explore adverse drug events (ADEs). However, these datasets often contain high rates of missing and incomplete data, undermining the reliability and interpretability of pharmacovigilance analyses. Effective management of these data quality issues requires interactive tools to explore patterns of missingness across multiple dimensions. We present IRVINE (Interactive Visualization for Spontaneous Reporting Systems Databases Missing Values), an interactive visualization system designed to explore and compare missing data in spontaneous reporting systems. IRVINE integrates multiple coordinated components—including a global overview, detailed attribute-level breakdowns, a temporal analysis interface, and a cross-database comparison environment—allowing users to fluidly transition between global summaries and fine-grained diagnostic views. The system supports dynamic filtering, drill-down exploration, and interactive temporal analysis to examine changes in data completeness over time and across categories. Through three usage scenarios and a user study, we demonstrate how IRVINE supports effective exploration of reporting completeness. Results indicate that users perceived the system as easy to use and effective for identifying missingness patterns, with particular strengths in comparative and detail-level analysis. This work lays a foundation for improved transparency, interpretability, and data quality assessment in large-scale pharmacovigilance systems.