Recommendations of the Canadian Consensus Conference on Dementia - Dissemination, Implementation, and Evaluation of Impact
Bibliographic record
Abstract
BACKGROUND: Subsequent to the development of consensus statements on a clinical topic, it is vital to establish a plan for dissemination, implementation and evaluation of impact. Consensus statements can be used for both guiding continuing medical education (CME) and producing clinical practice guidelines (CPGs). Insufficient attention to dissemination can lead to a failure to change physician behaviour and improve patient outcomes. METHODS: A plan to disseminate the conclusions of the Canadian Consensus Conference on Dementia (CCCD) was developed. This plan was based on a literature review of CME and CPGs. A Medline search was performed on the dissemination and evaluation of the 1989 Canadian Consensus Conference on the Assessment of Dementia (CCCAD) and other published guides for physicians on dementia care. CCCD dissemination that has occurred to date (June, 2000) was reviewed in this paper. RESULTS: Lectures and unsolicited printed material are weak forms of CME. Small-group interactive CME that provides practice opportunities appears to be the most effective way to change physician behaviour. The ability of CPGs to change physician behaviour is uncertain. It appears that inadequate attention has been placed on CPG dissemination and implementation. The CCCAD had a modest impact on clinical practice in Canada. While dissemination of the conclusions of the CCCD has taken place, evaluation of the impact of the CCCD has yet to be done. Local initiatives utilizing the conclusions of the CCCD are on-going. CONCLUSIONS: Further work is needed on how to optimize the impact of consensus statements and CPGs. While dissemination of the CCCD has occurred, it is currently unknown whether it has led to any change in physician practices.
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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 | 0.336 | 0.467 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.009 | 0.016 |
| Bibliometrics | 0.028 | 0.019 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.026 | 0.015 |
| Research integrity | 0.030 | 0.031 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".