Canadian College of Medical Geneticists (CCMG) position statement on the storage of patient genetic and genomic information in electronic health records
Bibliographic record
Abstract
The aim of this document is to provide an updated statement from the Canadian College of Medical Geneticists (CCMG) regarding the current state and some future considerations on the collection, distribution, and storage of genomic information within electronic health records (EHRs), including which aspects of genomic data might warrant special attention. The original version of this document was written by the CCMG Ethics and Public Policy committee in 2010 based on data collected via an online survey of the CCMG membership at the time. It is updated here to reflect the current state of healthcare in 2024, where EHRs are almost ubiquitously used, and genomic medicine has expanded in its breadth and scope. The document was circulated to the general membership for review and feedback and has been approved by the CCMG Board of Directors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.063 | 0.154 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.016 | 0.015 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".