Impacts of Québec Primary Healthcare Reforms on Patients’ Experience of Care, Unmet Needs, and Use of Services
Bibliographic record
Abstract
Introduction. Healthcare reforms launched in the early 2000s in Québec, Canada, involved the implementation of new forms of primary healthcare (PHC) organizations: Family Medicine Groups (FMGs) and Network Clinics (NCs). The objective of this paper is to assess how the organizational changes associated with these reforms have impact on patients' experience of care, use of services, and unmet needs. Methods. We conducted population and organization surveys in 2005 and 2010 in two regions of the province of Québec. The design was a before-and-after natural experiment. Changes over time between new models and other practices were assessed using difference-in-differences statistical procedures. Results. Accessibility decreased between 2003 and 2010, but less so in the treatment than in the comparison group. Continuity of care generally improved, but the increase was less for patients in the treatment group. Responsiveness also increased during the period and more so in the treatment group. There was no other significant difference between the two groups. Conclusion. PHC reform in Québec has brought about major organizational changes that have translated into slight improvements in accessibility of care and responsiveness. However, the reform does not seem to have had an impact on continuity, comprehensiveness, perceived care outcomes, use of services, and unmet needs.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".