Examining Strategies for-, Determinants of-, and Associated Outcomes Related to the Dissemination and Implementation of Aspirational Guidelines: An Exploratory Multiple-Case Study of the Person-Centred Care Guideline in Ontario’s Regional Cancer Centres
Bibliographic record
Abstract
Clinical practice guidelines (CPGs) are a key tool for translating evidence into clinical practice. In contrast, aspirational guidelines (AGs) provide system-level recommendations aimed at informing how healthcare services should be resourced, organized, and delivered. While AGs are increasingly used to guide health system transformation, little is known about how they are implemented. This study aimed to generate knowledge on how to optimize the dissemination and implementation of AGs in healthcare. The objectives were to: 1. identify strategies, determinants and outcomes related to AG implementation in the published literature, 2. explore these same elements within the context of Ontario’s Regional Cancer Centres’ implementation of the Person-Centred Care Guideline, and 3. develop a conceptual framework to guide AG dissemination and implementation within healthcare settings. A sequential, multi-method design was employed, beginning with a scoping review, followed by a multiple-case study using interviews with administrators and frontline staff, and culminating in the development of a conceptual framework. The Expert Recommendations for Implementing Change (ERIC) model and the Tailored Implementation for Chronic Diseases (TICD) checklist underpinned all study components. The scoping review revealed that AGs differ from CPGs by engaging a broader range of healthcare professionals and emphasizing organizational change. Implementation strategies and determinants related to AGs focused more on organizational and contextual factors, suggesting that existing implementation frameworks may require adaptation to fully support AG uptake. Multiple-case study findings were organized to six main themes. Results indicated that deeper frontline engagement, stronger leadership, and alignment with organizational priorities may suggest greater awareness and uptake of PCC practices. Coordinated dissemination appears to have led to better implementation outcomes. However, challenges in measuring outcomes highlight the complexity of implementing value-based practices. Both established and novel, context-specific implementation strategies and determinants were identified. Findings from both studies were synthesized into a new AG Implementation Conceptual Framework. This framework emphasizes the dynamic interplay of strategies, determinants, and outcomes, highlighting the importance of structured planning, organizational readiness, and stakeholder engagement. In conclusion, this research contributes new knowledge to implementation science, providing actionable guidance for healthcare leaders and policy-makers to improve the uptake of AGs and advance system-level change.
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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 | 0.029 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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; a candidate call from one source (direct Gemma or distilled Codex), 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".