Endorsement of clinical practice guidelines
Bibliographic record
Abstract
OBJECTIVE: To refine the process for endorsement of guidelines and establish the expectations of the College of Family Physicians of Canada (CFPC) regarding the quality and relevance of clinical practice guidelines targeting family physicians and their patients. COMPOSITION OF THE COMMITTEE: Initially, a group of 6 CFPC staff and selected College members reviewed the previous process for endorsement with the aim of providing a new direction, if needed. The work was then assumed by the Guideline and Knowledge Translation Expert Working Group, a purposefully selected group of 9 family physicians from across Canada with expertise in research, evidence, guidelines, knowledge translation, and continuing professional development and education. METHODS: The initial task force reviewed the endorsement process and identified areas for improvement. A draft new process and core criteria for high-quality guidelines were developed. This was approved by the CFPC board. A Guideline and Knowledge Translation Expert Working Group was then formed to further refine the process and the criteria. Multiple resources were used to inform the criteria. The Guideline and Knowledge Translation Expert Working Group will manage the endorsement process of external submitted guidelines, as well as provide high-level guidance to the CFPC regarding in-house guidelines and continuing professional development content. REPORT: This article provides the expectations of the CFPC regarding clinical practice guidelines and describes in detail the process and criteria for endorsement. Key principles include family physician involvement and guideline funding unlikely to introduce bias, with most criteria falling under 4 themed areas: relation to family medicine, CFPC values, patient engagement and decision making, and scientific rigour. The Guideline and Knowledge Translation Expert Working Group will report to the CFPC board at least once a year. It is hoped that this fully transparent process and these criteria will help advance the quality and standards of clinical practice guideline production in Canada. CONCLUSION: A comprehensive but reasonable list has been provided that reflects the best standards and recommendations and is consistent with the CFPC's values while recognizing the landscape of guideline development for its national partners and colleagues. As with all processes, careful consideration and evaluation will be essential.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 |
| 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 | 0.000 |
| 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".