Prognosis: the “missing link” within the CanMEDS competency framework
Bibliographic record
Abstract
BACKGROUND: The concept of prognosis dates back to antiquity. Quantum advances in diagnostics and therapeutics have relegated this once highly valued core competency to an almost negligible role in modern medical practice. Medical curricula are devoid of teaching opportunities focused on prognosis. This void is driven by a corresponding relative dearth within physician competency frameworks. This study aims to assess the level of content related to prognosis within CanMEDS (Canadian Medical Education Directives for Specialists), a leading and prototypical physician competency framework. METHODS: A quantitative content analysis of CanMEDS competency framework was carried out to measure the extent of this deficiency. Foxit Reader 5.1 (Foxit Corporation), a keyword scanning software, was used to assess the CanMEDS 2005 framework documents of 29 physician specialties and 37 subspecialties across the seven physician roles (medical expert, communicator, collaborator, manager, health advocate, scholar, and professional). The keywords used in the search included prognosis, prognostic, prognosticate, and prognostication. RESULTS: Of the 29 specialties six (20.7%) contained at least one citation of the keyword "prognosis", and one (3.4%) contained one citation of the keyword "prognostic". Of the 37 subspecialties, sixteen (43.2%) contained at least one citation of the keyword "prognosis", and three (8.1%) contained at least one citation of the keyword "prognostic". The terms "prognosticate" and "prognostication" were completely absent from all CanMEDS 2005 documents. Overall, the combined citations for "prognosis" and "prognostic" were linked with the following competency roles: Medical Expert (80.3%), Scholar (11.5%), and Communicator (8.2%). CONCLUSIONS: Given the fundamental and foundational importance of prognosis within medical practice, it is recommended that physicians develop appropriate attitudes, skills and knowledge related to the formulation and communication of prognosis. The deficiencies within CanMEDS, demonstrated by this study, should be addressed in advance of the launch of its updated version in 2015.
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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 | 0.002 | 0.354 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".