A Hybrid Type II Hub-and-Spoke Model Evaluation Framework in the Commonwealth Partnerships for Antimicrobial Stewardship Programme—A Study Protocol
Bibliographic record
Abstract
Introduction: The hub-and-spoke model (HSM) offers a methodological and hierarchical project management framework for efficient healthcare service delivery. The Commonwealth Partnerships for Antimicrobial Stewardship (CwPAMS) programme supports the development and implementation of antimicrobial stewardship (AMS) interventions to optimise the use of antimicrobials across eight African countries: Ghana, Kenya, Malawi, Nigeria, Sierra Leone, Tanzania, Uganda, and Zambia. Currently the second phase of the programme (CwPAMS 2.0) is being implemented, between March 2023 and March 2025, in which six countries are adopting the HSM to deliver AMS interventions. The aim of this study was to design a hybrid II monitoring, evaluation and learning (MEL) framework to assess the implementation and effectiveness of the HSM in delivering and adapting AMS interventions. Methods: A mixed-methods Hybrid II Implementation trial design was used to develop the MEL framework, guided by the Theory of Change, Socio-Ecological Theory, and Normalisation Process Theory and in alignment with the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Data collection will be continuous and longitudinal (pre-, mid- and post-implementation). The evaluation framework has been designed to study implementation evaluation at three ecological levels: programme, partnership, and individual site level. Data collection will encompass mixed methodologies and include non-participant observations, formal and informal feedback (from individual key stakeholders and groups), knowledge tools and surveys, scored evaluations, pre-and post-assessments, semi-structured interviews, focus groups, and data collected during formal and informal meetings. This approach will facilitate continuous data collection for evaluation and help study the utilisation and adaptation of AMS interventions. Discussion: This study provides a protocol for developing and utilising an MEL framework to study the application of the HSM in delivering AMS interventions. Developing an evaluation framework requires meticulous planning and a robust implementation and evaluation protocol to ensure methodological rigour, transparency, and effective resource management throughout the project lifecycle. Despite comprehensive consideration of developing progress and programmatic indicators and measures across all domains, the study acknowledges limitations in definitively attributing causality to individual AMS interventions due to their complexity and varied implementation contexts.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".