Bibliographic record
Abstract
The Conundrum of Clinical Practice GuidelinesClarence Chant C linical practice guidelines (CPGs) have been defined by the Institute of Medicine as "systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances". 1 The purported benefits of CPGs include improving patient outcomes, standardizing practice by ensuring a certain minimal level of care and discouraging non-evidence-based care, improving consistency and efficiency, highlighting knowledge gaps, stimulating professional discussions, and lowering the cost of care. 2 However, whether such benefits are realized in actual practice is not clearly documented in the literature.Notwithstanding these potential benefits, implementation of CPGs is a complex and labour-intensive process, and a recent large-scale cluster randomized controlled trial found that multifaceted and comprehensive knowledge translation interventions reaching up to 96% of the targeted audience in a variety of intensive care units resulted in an increase of only 8% over 2 years in concordance with a set of evidence-based guideline recommendations for ventilator-associated pneumonia.3 At the same time, clinicians have voiced several concerns about CPGs, including poor uptake of guidelines by practitioners, their potential to replace clinical judgment and to impede teaching and curiosity, and their inappropriate use for legal and insurance coverage purposes.In this issue of the Canadian Journal of Hospital Pharmacy (CJHP), the Point Counterpoint question asks whether clinical practitioners, as part of institutional or accreditation standards, should be required to document rationale when they choose to not adhere to widely accepted clinical practice guidelines.4,5 The authors on both sides present many valid lines of reasoning to support their cases.One of the points raised, relating to the degree to which guidelines are actually evidence-based, 5 merits further discussion.In fact, I believe that the evidentiary basis of guidelines is fundamental, as evidence-based medicine is considered the standard for current practice in the health sciences, and is certainly something we clinical pharmacists all try very hard to instill in our students, fellow practitioners, and even administrators.So, before consideration of whether it should be mandatory for practitioners to cite their rationale for deviation from CPGs, it must be asked whether the guidelines
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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 | 0.386 | 0.638 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.008 | 0.042 |
| Scholarly communication | 0.023 | 0.023 |
| Open science | 0.015 | 0.015 |
| Research integrity | 0.032 | 0.061 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".