Variations in processes for guideline adaptation: a qualitative study of World Health Organization staff experiences in implementing guidelines
Bibliographic record
Abstract
BACKGROUND: The World Health Organisation (WHO) publishes a large number of clinical practice and public health guidelines to promote evidence-based practice across the world. Due to the variety of health system capacities and contextual issues in different regions and countries, adapting the recommendations in the guidelines to the local situation is vital for the success of their implementation. We aim to understand the range of experiences with guideline adaptation from the perspectives of those working in WHO regional and country offices. Our findings will inform development of guidance on how to improve adaptability of WHO guidelines. METHODS: A grounded theory-informed, qualitative study was carried out between March 2018 and December 2018. Seventeen semi-structured interviews were conducted with participants who included WHO guideline developers and staff in the headquarters, regional and country offices recruited from a sample of published WHO guidelines. Participants were eligible for recruitment if they had recent experience in clinical practice or public health guideline implementation. Deidentified transcripts of these interview were analysed through three cycles of coding. RESULTS: We categorised the adaptation processes described by the participants into two dominant models along a spectrum of guideline adaptation processes. First, the Copy or Customise Model is a pragmatic approach of either copying or customising WHO guidelines to suit local needs. This is done by local health authorities and/or clinicians directly through consultations with WHO staff. Selections and adjustments of guideline recommendations are made according to what the implementers deemed important, feasible and applicable through the consensus discussions. Second, the Capacity Building Model focuses on WHO building local capacity in evidence synthesis methods and adaptation frameworks to support local development of a national guideline informed by international guidelines. CONCLUSIONS: In comparing and contrasting these two models of guideline adaptation, we outline the different kinds of support from WHO that may be necessary to improve the effectiveness and efficiency of the respective models. We also suggest clarifications in the descriptions of the process of guideline adaptation in WHO and academic literature, to help guideline adaptors and implementers decide on the appropriate course of action according to their specific circumstances. ETHICS: This project was conducted with ethics approval from The University of Sydney (Project number: 2017/723) and WHO (Protocol ID: 00001).
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How this classification was reachedexpand
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 | 0.009 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".