Implementing a Care Coordination Strategy for Children with Medical Complexity in Ontario, Canada: A Process Evaluation
Bibliographic record
Abstract
Introduction: A provincial strategy to expand care coordination and integration of care for children with medical complexity (CMC) was launched in Ontario, Canada in 2015. A process evaluation of the roll-out examined the processes, mechanisms of impact, and contextual factors affecting the implementation of the Complex Care for Kids Ontario (CCKO) intervention strategy. Methods: This process evaluation was conducted and analyzed according to the United Kingdom Medical Research Council (UK-MRC) process evaluation framework. To evaluate the implementation of the CCKO intervention, a multi-method study design was used, including semi-structured interviews with 38 key informants and 10 families of CMC involved in CCKO. To further understand implementation details across regional sites, provincial-level implementation plans, and process documents were reviewed. Discussion: Strengths of CCKO included novel collaborations and partnerships between complex care teams, community partners and regional sites. Issues relating to communication and coordination across care sectors created challenges to holistic care coordination objectives. Provincial system fragmentation limited the ability of CCKO to provide seamless care coordination due to the multiple care sectors involved. Conclusion: This study adds to the understanding of the processes involved in a population-level care coordination intervention for CMC. Lessons learned through CCKO can help facilitate reproducibility and necessary adjustments of the intervention in different settings.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".