Public experiences and perspectives of primary care in Canada: results from a cross-sectional survey
Bibliographic record
Abstract
<h3>Background:</h3> Through medicare, residents in Canada are entitled to medically necessary physician services without paying out of pocket, but still many people struggle to access primary care. We conducted a survey to explore people’s experience with and priorities for primary care. <h3>Methods:</h3> We conducted an online, bilingual survey of adults in Canada in fall 2022. We distributed an anonymous link through diverse channels and a closed link to 122 053 people via a national public opinion firm. We weighted completed responses to mirror Canada’s population and adjusted for sociodemographic characteristics using regression models. <h3>Results:</h3> We analyzed 9279 completed surveys (5.9% response rate via closed link). More than one-fifth of respondents (21.8%) reported having no primary care clinician, and among those who did, 34.5% reported getting a same or next-day appointment for urgent issues. Of respondents, 89.4% expressed comfort seeing another team member if their doctor recommended it, but only 35.9%, 9.5%, and 12.4% reported that their practice had a nurse, social worker, or pharmacist, respectively. The primary care attribute that mattered most was having a clinician who “knows me as a person and considers all the factors that affect my health.” After we adjusted for respondent characteristics, people in Quebec, the Atlantic region, and British Columbia had lower odds of reporting a primary care clinician than people in Ontario (adjusted odds ratio 0.30, 0.33, and 0.39, respectively; <i>p</i> < 0.001). We also observed large provincial variations in timely access, interprofessional care, and walk-in clinic use. <h3>Interpretation:</h3> More than 1 in 5 respondents did not have access to primary care, with large variation by province. Reforms should strive to expand access to relationship-based, longitudinal care in a team setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".