Examining atypical presentations associated with a higher risk of diagnostic errors using a new classification model
Abstract
OBJECTIVES: To apply a new classification model for clinical presentations and detect a new subtype of atypical presentations associated with a higher risk of diagnostic errors, using a dataset of diagnostic errors collected with disease-agnostic approaches. METHODS: We classified cases of diagnostic errors from a previous systematic review of case reports using a new classification model for clinical presentations. Based on a previous study, we defined four clinical presentation patterns as atypical presentations associated with a higher risk of diagnostic errors (atypical group). We described the characteristics of the atypical group, including codes from the Diagnostic Error Evaluation and Research (DEER) and Reliable Diagnosis Challenges (RDC) taxonomies. We compared them with those of the most typical presentation (typical group). RESULTS: We included 382 cases in this study. The atypical groups accounted for 36 (9.4 %). For the RDC taxonomy, the codes "Atypical presentations", "Findings masking/mimicking another diagnosis", "Equivocal results/interpretation", and "Recognizing misdiagnosis occurrence" were assigned more frequently in the atypical group. There was no difference in the distribution of DEER taxonomy codes between the two groups. CONCLUSIONS: We detected atypical presentations associated with a higher risk of diagnostic errors by using the new model. Cases with such atypical presentations had more specific diagnostic challenges than those with the most typical presentation. The new model facilitates future studies to identify and address the target to reduce diagnostic errors in patients with atypical presentations associated with a higher risk of diagnostic errors.
Fields of Study & Subjects
Clinical Reasoning and Diagnostic Skills
Meta-analysis and systematic reviews
Patient Safety and Medication Errors
Publication details
- Journal / source
- Diagnosis
- Publisher
- Walter de Gruyter GmbH
- Volume
- 13
- Issue
- 3
- Pages
- 451–459
- Publication date
- 7 April 2026
- Language
- EN