#4-37E. Uncovering Diagnostic Error Patterns: A Cluster Analysis Approach (Diagnosis, 2026)

Are diagnostic errors in outpatient settings merely isolated mistakes, or do they follow predictable patterns tied to our daily clinical environment? In this cross-sectional study, researchers analyzed unexpected readmissions in a general internal medicine clinic to characterize outpatient diagnostic errors. By applying hierarchical cluster analysis to the Diagnostic Error Evaluation and Research (DEER) taxonomy, they evaluated 50 error cases among 146 patients. The key clinical takeaway is that diagnostic errors aggregate into four distinct failure modes—prioritization, data-gathering, information synthesis, and undertesting failures—that map directly to contextual factors like late-day sessions, personal protective equipment (PPE) usage, and referral letter anchoring. However, when critically appraising this study, one must consider its single-center retrospective design and the use of a 14-day hospitalization trigger, which inherently introduces selection bias by missing errors that do not result in admission. For practicing physicians, this research is highly relevant because it shifts the focus from individual blame to context-specific vulnerabilities. Recognizing how environmental pressures affect clinical reasoning allows for the implementation of targeted safety measures, such as late-shift handoffs or structured checklists, ultimately improving everyday diagnostic accuracy.

Citation: Suzuki Y, Nishizawa T, et al. Patterns of diagnostic errors using hierarchical cluster analysis: a single-center, cross-sectional study in general internal medicine. Diagnosis. 2026. DOI: 10.1515/dx-2025-0190

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