Identifying Diagnostic Paths for Undifferentiated Abdominal Pain from Electronic Health Record Data

The diagnostic process is a complex, uncertain, and highly variable process which is under-studied and lacks evidence from randomized clinical trials. This study used a novel visual analytics method to identify and visualize diagnostic paths for undifferentiated abdominal pain, by leveraging electronic health record (EHR) data of 501 patients in the ambulatory setting of a single institution. A total of 63 patients reached diagnoses in the study sample. We illustrate steps in identifying diagnostic paths of the study patients, both individually and collectively, and visually present the diversity in their diagnostic processes. Patients in whom diagnoses were obtained generally had more clinical encounters and health services utilization, although their diagnostic paths were more variable than those of the undiagnosed group. The capability of identifying diagnostic paths demonstrated from this study allows us to study larger data sets to determine diagnostic paths associated with more timely, accurate, and cost-efficient diagnosis processes.