Despite the widespread adoption of clinical guidelines (i.e. canonical treatment plan templates that represent generally accepted best practices), significant variations in care are often found across a population of patients. Gaps between the actual treatment programs performed on patients and the recommended guidelines are inevitable given the complexity of disease, differences between patients, and the individualized patient-centered decisions made by clinicians during each encounter. The GapFlow project is exploring interactive visualization techniques designed to help clinical organizations better understand these gaps in care. Combined with analytics algorithms that classifyWe describe the input data, our analysis technique to classify individual gap events, and an interactive visualization technique which aggregates and summarizes the results for clinical interpretation.
David Gotz, Nan Cao, Esther Goldbraich, and Boaz Carmeli. GapFlow: Visualizing Gaps in Care for Medical Treatment Plans. IEEE VIS Poster, Atlanta, GA (2013).