Shaping Primary Health Care Teams and Integrated Care in Québec: An Overview of Policies (2000-2020)
Bibliographic record
Abstract
Primary Health Care (PHC) teams are an important component of the health system – particularly in terms of integrating care for vulnerable patients living with complex health and social needs. Over the last two decades, PHC teams have been implemented in different forms across Canadian provinces and territories. This article explores the health care policies that shaped the form and functions of PHC team-based care in Québec over the past 20 years (2002-2022). In Québec, the main model of multidisciplinary PHC teams – Family Medicine Groups or Groupe de médecine de famille (GMFs) – were created in 2002. In 2004, structural reforms led to the creation of local health networks (LHNs). LHNs promoted coordinated and collaborative activities between health and social services providers such as GMFs located in the same geographic regions. This was followed by another structural reform of the health system in 2015, leading to the creation of broader territorial health networks with the aim to heighten coordination and collaboration among provider organizations. Various policies have strengthened the PHC team-based model. For instance, the introduction of nurse practitioners, pharmacists, and social workers with extended scopes of practice shaped the configuration of GMFs while enhancing inter-professional collaborative practices. This article highlights important insights that could advance the understanding and creation of future PHC policy initiatives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".