The Implementation Playbook: study protocol for the development and feasibility evaluation of a digital tool for effective implementation of evidence-based innovations
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
BACKGROUND: Evidence-based innovations can improve health outcomes, but only if successfully implemented. Implementation can be complex, highly susceptible to failure, costly and resource intensive. Internationally, there is an urgent need to improve the implementation of effective innovations. Successful implementation is best guided by implementation science, but organizations lack implementation know-how and have difficulty applying it. Implementation support is typically shared in static, non-interactive, overly academic guides and is rarely evaluated. In-person implementation facilitation is often soft-funded, costly, and scarce. This study seeks to improve effective implementation by (1) developing a first-in-kind digital tool to guide pragmatic, empirically based and self-directed implementation planning in real-time; and (2) exploring the tool's feasibility in six health organizations implementing different innovations. METHODS: Ideation emerged from a paper-based resource, The Implementation Game©, and a revision called The Implementation Roadmap©; both integrate core implementation components from evidence, models and frameworks to guide structured, explicit, and pragmatic planning. Prior funding also generated user personas and high-level product requirements. This study will design, develop, and evaluate the feasibility of a digital tool called The Implementation Playbook©. In Phase 1, user-centred design and usability testing will inform tool content, visual interface, and functions to produce a minimum viable product. Phase 2 will explore the Playbook's feasibility in six purposefully selected health organizations sampled for maximum variation. Organizations will use the Playbook for up to 24 months to implement an innovation of their choosing. Mixed methods will gather: (i) field notes from implementation team check-in meetings; (ii) interviews with implementation teams about their experience using the tool; (iii) user free-form content entered into the tool as teams work through implementation planning; (iv) Organizational Readiness for Implementing Change questionnaire; (v) System Usability Scale; and (vi) tool metrics on how users progressed through activities and the time required to do so. DISCUSSION: Effective implementation of evidence-based innovations is essential for optimal health. We seek to develop a prototype digital tool and demonstrate its feasibility and usefulness across organizations implementing different innovations. This technology could fill a significant need globally, be highly scalable, and potentially valid for diverse organizations implementing various innovations.
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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 | 0.040 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it