Longitudinal costs and health service utilisation associated with primary care reforms in Ontario: a retrospective cohort study protocol
Bibliographic record
Abstract
INTRODUCTION: Over the last 20 years, the Canadian province of Ontario implemented several new models of primary care focusing on changes to physician remuneration, clinics led by nurse practitioners and the introduction of interprofessional primary care teams. Health outcome and cost evaluations of these models thus far have been mostly cross-sectional and in some cases results from these studies were conflicting. The aim of this population-based study is to investigate short, medium and long-term effectiveness of these reforms over the past 15-20 years. METHODS AND ANALYSIS: This is the protocol for a retrospective cohort study including fee-for-service (FFS) and community health centre cohorts (control cohorts) or patients who switched from either being unattached or from FFS to a new practice model (eg, capitation, enhanced FFS, team, nurse practitioner-led) from 1997 to 2020. The primary outcome is total healthcare costs and secondary outcomes are primary care costs, other (non-primary care) health costs, hospitalisations, length of stay, emergency department visits, accessibility and mortality. A combination of hard and propensity matching will be used where relevant. Outcomes will be adjusted for demographic and health factors and measured annually. Interrupted time series models will be used where data permits and difference-in-differences methods will be used otherwise. ETHICS AND DISSEMINATION: Ethics approval has been received from Queens University and Memorial University. The dissemination plan includes conference presentations, papers, brief evidence summaries targeted at select audiences and knowledge brokering sessions with key stakeholders.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".