Quality, Patient Safety and the Implementation of Best Evidence: Provinces in the Country of Knowledge Translation
Bibliographic record
Abstract
ong a world model, Canada's healthcare system faces many challenges to ensure its sustainability.Research evidence, generated at an exponential rate, is not readily available to clinicians.When available, it is often infrequently or incorrectly applied in clinical practice (Davenport and Glaser 2002;Covell et al. 1985;Ramos et al. 2003).This failure of rapid evidence adoption leads to sizable gaps between high-quality evidence and practice, significant practice variation, and in many cases lapses in patient safety (Chassin and Galvin 1998;Buchan 2004).This gap is deleterious to the health of Canadians, increasing morbidity and mortality and generating serious and detrimental cost implication (Olson et al. 2001;Villar et al. 2001;Boissel et al. 2004;Tsuyuki et al. 2005).This finding, that providing evidence from research or from quality assessments is a necessary but not sufficient condition for the provision of care, has created the field of knowledge translation, the scientific study of the methods for closing the knowledge-to-practice gap and the analysis of barriers and facilitators inherent in the process.As defined by the Cambridge Conference, KT is "the iterative, timely and effective process of integrating best evidence into the routine practices of patients, practitioners, health care teams and systems, in order to effect optimal health care outcomes and to maximize the potential of the health care system" (11th Cambridge Conference 2003).For our purposes, KT is intended to subsume issues of patient safety, continuing education and guideline implementation, in order to achieve, in the words of CIHR, the "optimization of health care and health care systems" (CIHR 2005); they are, in this view, "provinces in the country of KT." Patient safety and quality improvement provide compelling examples of both process (how to improve care) and content innovation (what to do to improve it).The significant gap in care and the quest for patient safety and in the Canadian context call for a programmatic approach to the testing and implementation of evidence-based health knowledge translation strategies.
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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 | 0.170 | 0.367 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.013 | 0.026 |
| Scholarly communication | 0.035 | 0.013 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.014 | 0.023 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".