The quality of clinical practice guidelines over the last two decades: a systematic review of guideline appraisal studies
Bibliographic record
Abstract
BACKGROUND: Despite the increasing number of manuals on how to develop clinical practice guidelines (CPGs) there remain concerns about their quality. The aim of this study was to review the quality of CPGs across a wide range of healthcare topics published since 1980. METHODS: The authors conducted a literature search in MEDLINE to identify publications assessing the quality of CPGs with the Appraisal of Guidelines, Research and Evaluation (AGREE) instrument. For the included guidelines in each study, the authors gathered data about the year of publication, institution, country, healthcare topic, AGREE score per domain and overall assessment. RESULTS: In total, 42 reviews were selected, including a total of 626 guidelines, published between 1980 and 2007, with a median of 25 CPGs. The mean scores were acceptable for the domain 'Scope and purpose' (64%; 95% CI 61.9 to 66.4) and 'Clarity and presentation' (60%; 95% CI 57.9 to 61.9), moderate for domain 'Rigour of development' (43%; 95% CI 41.0 to 45.2), and low for the other domains ('Stakeholder involvement' 35%; 95% CI 33.9 to 37.5, 'Editorial independence' 30%; 95% CI 27.9 to 32.3, and 'Applicability' 22%; 95% CI 20.4 to 23.9). From those guidelines that included an overall assessment, 62% (168/270) were recommended or recommended with provisos. There was a significant improvement over time for all domains, except for 'Editorial independence.' CONCLUSIONS: This review shows that despite some increase in quality of CPGs over time, the quality scores as measured with the AGREE Instrument have remained moderate to low over the last two decades. This finding urges guideline developers to continue improving the quality of their products. International collaboration could help increasing the efficiency of the process.
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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 | 0.106 | 0.374 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.026 | 0.033 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".