Institutionalising an evidence-informed approach to guideline development: progress and challenges at the World Health Organization
Bibliographic record
Abstract
This study explored experiences, perceptions and views among World Health Organization (WHO) staff about the changes, progress and challenges brought by the guideline development reforms initiated in 2007. Thirty-five semistructured interviews were conducted with senior WHO staff. Sixteen of the interviewees had in-depth experience with WHO's formal guideline development process. Thematic analysis was conducted to identify key themes in the qualitative data, and these were interpreted in the context of the existing literature on WHO's guideline development processes. First, the reforms were seen to have transformed and improved the quality of WHO's guidelines. Second, independent evaluation and feedback by the Guidelines Review Committee (GRC) was described to have strengthened the legitimacy of WHO's recommendations. Third, WHO guideline development processes are not yet designed to systematically make use of all types of research evidence needed to inform decisions about health systems and public health interventions. For example, several interviewees expressed dissatisfaction with the insufficient attention paid to qualitative evidence and evidence from programme experience, and how the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process evaluates the quality of evidence from non-randomised study designs, while others believed that GRADE was just not properly understood or applied. Fourth, some staff advocated for a more centralised quality assurance process covering all outputs from WHO's departments and scientific advisory committees, especially to eliminate strategic efforts aimed at bypassing the GRC's requirements. Overall, the 'culture change' senior WHO staff called for over 10 years ago appears to have gradually spread throughout the organisation. However, at least two major challenges remain: (1) ensuring that all issued advice benefits from independent evaluation, monitoring and feedback for quality and (2) designing guideline development processes to better acquire, assess, adapt and apply the full range of evidence that can inform recommendations on health systems and public health interventions.
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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 | 0.213 | 0.248 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.006 | 0.016 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".