Process Evaluation of a Hub-and-Spoke Model to Deliver Coordinated Care for Children with Medical Complexity across Ontario: Facilitators, Barriers and Lessons Learned
Bibliographic record
Abstract
BACKGROUND: Complex Care for Kids Ontario (CCKO) is a multi-year strategy aimed at expanding a hub-and-spoke model to deliver coordinated care for children with medical complexity (CMC) across Ontario. OBJECTIVE: This paper aims to identify the facilitators, barriers and lessons learned from the implementation of the Ontario CCKO strategy. METHOD: Alongside an outcome evaluation of the CCKO strategy, we conducted a process evaluation to understand the implementation context, process and mechanisms. Semi-structured interviews were conducted with 38 healthcare leaders, clinicians and support staff from four regions involved in CCKO care delivery and/or governance. RESULTS: Facilitators to CCKO implementation were sustained engagement of system-wide stakeholders, inter-organizational partnerships, knowledge sharing and family engagement. Barriers to CCKO implementation were resources and funding, fragmentation of care, aligning perspectives between providers and clinical staff recruitment and retention. CONCLUSION: A flexible approach is required to implement a complex, multi-centre policy strategy. Other jurisdictions considering such a model of care delivery would benefit from attention to contextual variations in implementation setting, building cross-sector engagement and buy-in, and offering continuous support for modifications to the intervention as and when required.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".