A systematic approach to adaptation of clinical practice guidelines (CPGs)
Bibliographic record
Abstract
6094 Background: The number of evidence-based guidelines (CPGs) is increasing, with many developed on the same topic. Development of high-quality CPGs requires substantial resources. Unnecessary duplication of effort could be avoided by adapting existing CPGs. However to date there is no validated process for a systematic approach to the adaptation of guidelines produced in a distinct cultural and organisational setting, i.e. trans-contextual adaptation. Methods: We developed a systematised process based on the results of a literature review and the experience of an international group of guidelines researchers. The pivotal steps of the process (assessment of CPG quality and content) were pilot tested by two multidisciplinary expert groups in Quebec (16 experts) using two French cancer guidelines (treatment of ovarian cancer and metastatic colon cancer (www.fnclcc.fr)). Results: The developed adaptation process involves: 1) search and selection of CPGs corresponding to the clinical question(s); 2) evaluation of selected guidelines: assessment of quality, internal validity and applicability to the context of use; 3) adaptation of the recommendations from one or more CPGs using standard guideline methodology; 4) adoption and implementation. All the experts found the steps assessed useful, complete and easy to use. Most (15/16) said that the explicit evaluation process is a guarantee of the validity and credibility of the adapted guideline. 13/16 felt that they would have as much confidence in a guideline adapted by this process as in a de novo guideline. Conclusions: This is the first systematic approach to trans-contextual guideline adaptation. The preliminary results confirm the need for an explicit assessment of all aspects of guideline quality. The amount of adaptation and time needed is dependent on the differences in the cultural and organisational context, and the number and quality of the sources guidelines. Further assessment will enable us to determine if our approach reduces duplication of effort and will foster uptake by end-users. No significant financial relationships to disclose.
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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 | 0.457 | 0.550 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.028 | 0.017 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.006 | 0.016 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".