Building integrated, adaptive and responsive healthcare systems – lessons from paramedicine in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Being responsive and adaptive to local population needs is a key principle of integrated care, and traditional top-down approaches to health system governance are considered to be ineffective. There is need for more guidance on taking flexible, complexity-aware approaches to governance that foster integration and adaptability in the health system. Over the past two decades, paramedics in Ontario, Canada have been filling gaps in health and social services beyond their traditional mandate of emergency transport. Studying these grassroots, local programs can provide insight into how health systems can be more integrated, adaptive and responsive. METHODS: Semi-structured interviews were conducted with people involved in new, integrated models of paramedic care in Ontario. Audio recordings of interviews were transcribed and coded inductively for participants' experiences, including drivers, enablers and barriers to implementation. Thematic analysis was done to ascertain key concepts from across the dataset. RESULTS: Twenty-six participants from across Ontario's five administrative health regions participated in the study. Participants described a range of programs that included acute, urgent and preventative care driven by local relationship networks of paramedics, hospitals, primary care, social services and home care. Three themes were developed that represent participants' experiences implementing these programs in the Ontario context. The first theme, adapting and being nimble in tension with system structures, related to distributed versus central control of programs, a desire to be nimble and skepticism towards prohibitive legal and regulatory systems. The second theme, evolving and flexible professional role identity, highlighted the value and challenges of a functionally flexible workforce and interest in new roles amongst the paramedic profession. The third theme, unpredictable influences on program implementation, identified events such as the COVID-19 pandemic and changing government priorities as accelerating, redirecting or inhibiting local program development. CONCLUSIONS: The findings of this study add to the discourse on governing health systems towards being more integrated, adaptive and responsive to population needs. Governance strategies include: supporting networks of local organizational relationships; considering the role of a functionally flexible health workforce; promoting a shared vision and framework for collaboration; and enabling distributed, local control and experimentation.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.030 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".