The reimagination of sustainable integrated care in Ontario, Canada
Bibliographic record
Abstract
PURPOSE/SETTING: To encourage clinical and financial efficiency, the Canadian province of Ontario initiated an integrated care program - Integrated Funding Models (IFMs) that required collaboration and coordination across acute and post-acute care sectors. This research shows how program implementers went beyond policy-makers' original designs, to make integrated care sustainable for chronic diseases. METHODS: Forty-five interviews were conducted with program participants at three chronic disease programs, as well as with policymakers. Interviews were conducted over two phases; during early implementation in 2016, and as programs matured in 2018. Data were analyzed through a cultural constructivist lens to understand how participants shaped programs. FINDINGS: Participants desired greater accountability and control. Participants in the first program wanted localized control over decision-making. In the second, participants initiated greater control over financial uncertainty. In the third program, hospital participants sought greater control over community care. Participants across programs simultaneously wanted integrated care to be expanded holistically, spatially, and temporally for patients, extending the length of care, and expanding the spaces in which care was provided. Findings also suggest a gap between program implementers' and policymakers' conceptualizations of integrated care. CONCLUSION: This work shows how IFMs were reimagined in ways that transcended their original conceptualization as spatially and temporally delimited initiatives aimed at improving coordination and efficiency. It has practical implications for those facing sustainability challenges in other contexts.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".