Adapting evidence‐based clinical practice guidelines at university teaching hospitals: A model for the Eastern Mediterranean Region
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
RATIONALE, AIMS, AND OBJECTIVES: Clinical practice guidelines (CPGs) are significant tools for evidence-based health care quality improvement. The CPG program at King Saud University was launched as a quality improvement program to fulfil the international accreditation standards. This program was a collaboration between the Research Chair for Evidence-Based Healthcare and Knowledge Translation and the Quality Management Department. This study aims to develop a fast-track method for adaptation of evidence-based CPGs and describe results of the program. METHODS: Twenty-two clinical departments participated in the program. Following a CPGs awareness week directed to all health care professionals (HCPs), 22 teams were trained to set priorities, search, screen, assess, select, and customize the best available CPGs. The teams were technically supported by the program's CPG advisors. To address the local health care context, a modified version of the ADAPTE was used where recommendations were either accepted or rejected but not changed. A strict peer-review process for clinical content and methodology was employed. RESULTS: In addition to raising awareness and building capacity, 35 CPGs were approved for implementation by March 2018. These CPGs were integrated with other existing projects such as accreditation, electronic medical records, performance management, and training and education. Preliminary implementation audits suggest a positive impact on patient outcomes. Leadership commitment was a strength, but the high turnover of the team members required frequent and extensive training for HCPs. CONCLUSION: This model for CPG adaptation represents a quick, practical, economical method with a sense of ownership by staff. Using this modified version can be replicated in other countries to assess its validity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.166 | 0.847 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it