Renowned Physicians’ Perceptions of Expert Diagnostic Practice
Bibliographic record
Abstract
PURPOSE: To further the development of a substantive theory of expert diagnostic practice, the authors explored the ways in which exceptional physicians, nominated by their peers, conceptualized their own diagnostic expertise specifically and diagnostic excellence generally. METHOD: In this grounded theory, interview-based study, physicians at six North American research sites were nominated by their peers as exceptional diagnosticians and exceptional professionals and invited to participate in the study. A saturation sample included 34 participants, 20 exceptional diagnosticians, and 14 exceptional professionals. Using a constant comparative approach, the authors conducted one-on-one interviews with participants, transcribed the audiotapes of those interviews, and analyzed them for emergent themes. They developed a stable thematic structure and applied it to the entire data set. RESULTS: Four interconnected themes emerged that inform the community's understanding of how physicians conceptualize expert diagnostic practice: (1) possession of extensive knowledge built through purposeful, continuous engagement in clinical practice, (2) possession of the skills to effectively gather patient stories, (3) reflective integration of that knowledge and those patient stories during diagnosis, and (4) continuous learning through clinical practice. CONCLUSIONS: Exploring these results within the context of current discourses in medical education brings to the forefront two key features of physicians' construction of diagnostic excellence: (1) the integrated nature of the medical competencies that underpin the diagnostic process and (2) the optimally adaptive nature of the diagnostic process. These findings can inform the development of practical and effective pedagogical strategies to guide trainees, clinicians, and medical educators who strive for excellence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.258 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".