Integrated Complex Care Model: Lessons Learned from Inter-organizational Partnership
Bibliographic record
Abstract
Providing integrated care for children with medical complexity in Canada is challenging as these children are, by definition, in need of coordinated care from disparate providers, organizations and funders across the continuum in order to optimize health outcomes. We describe the development of an inter-organizational team constructed as a unique tripartite partnership of an acute care hospital, a children's rehabilitation hospital and a home/community health organization focused on children who frequently use services across these three organizations. Model building and operationalization within the Canadian healthcare system is emphasized. Key challenges identified to date include communication and policy barriers as well as optimizing interactions with families; critical enablers have been alignment with policy trends in healthcare and inter-organizational commitment to integrate at the point of care. Considerations for policy developments supporting full integration across service sectors are raised. Early indicators of success include the enrolment of 34 clients and patients and the securing of funds to evaluate and expand the model to serve more children.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".