Government policies targeting primary care physician practice from 1998-2018 in three Canadian provinces: A jurisdictional scan
Bibliographic record
Abstract
Primary care is the foundation of health care systems around the world. Physician autonomy means that governments rely on a limited selection of levers to implement reforms in primary care delivery, and these policies may impact the practice choices, intentions, and patterns of primary care physicians. Using a systematic search strategy to capture publicly available policy documents, we conducted a scan of such policies from 1998 to 2018 in three Canadian provinces: British Columbia, Nova Scotia, and Ontario. We reviewed 388 documents and extracted 170 policies from their texts, followed by analysis of the policies' instruments, actors, and topic areas. Policy reforms across the three provinces were primarily focused on physician payment, with governments relying on both targeted incentives and reformed payment models. Policies also employed various instruments to target priority areas of practice: 24/7 access to care, team-based primary care, unattached patients, eHealth, and rural/Northern recruitment of physicians. Across the three provinces and the 20-year timespan, reform priorities and instruments were largely uniform, with Ontario's policies tending to be the most diverse. Physicians helped shape reforms through the agreements negotiated between provincial governments and medical associations, influencing the topics and timing of reforms. Future research should evaluate impacts on the delivery of primary care and explore opportunities for policy innovation.
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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 | 0.010 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.026 | 0.073 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".