LAUSR

Abstract Diagnostic error is a serious public health problem to which knowledge gaps and associated cognitive error contribute significantly. Identifying diagnostic approaches to common problems in ambulatory care associated with more timely and accurate diagnosis and lower cost and harm associated with diagnostic evaluation is an important priority for health care systems, clinicians, and of course patients. Unfortunately, guidance on how best to approach diagnosis in patients with common presenting complaints such as abdominal pain, dizziness, and fatigue is lacking. Exploring diagnostic practice variation and patterns of diagnostic evaluation is a potentially valuable approach to identifying best current diagnostic practices. A “diagnostic path” is the sequence of actions taken to evaluate a new complaint from first presentation until a diagnosis is established, or the evaluation ends for other reasons. A “big data” approach to identifying diagnostic paths from electronic health records can be used to identify practice variation and best practices from a large number of patients. Limitations of this approach include incompleteness and inaccuracy of electronic medical record data, the fact that diagnostic paths may not represent clinician thinking, and the fact that diagnostic paths may be used to identify best current practices, rather than optimal practices.