Room for improvement: patients' experiences of primary care in Quebec before major reforms.
Bibliographic record
Abstract
OBJECTIVE: To investigate variations in accessibility, continuity of care, and coordination of services as experienced by patients in Quebec on the eve of major reforms, and to provide baseline information against which reforms could be measured. DESIGN: Multilevel cross-sectional survey of practice. SETTING: One hundred primary health care settings were randomly selected in urban, suburban, rural, and remote locations in 5 health regions in Quebec. PARTICIPANTS: In each clinic, we chose up to 4 physicians and 20 consecutive patients consulting each physician. MAIN OUTCOME MEASURES: Patients' responses to a self-administered questionnaire, the Primary Care Assessment Tool, that assessed patient-provider affiliation, accessibility, relational continuity, coordination of primary and specialty care, and whether patients received health promotion and preventive services. RESULTS: A total of 3441 patients participated (87% acceptance rate) in 100 clinics (64% response rate). Timely access was difficult; only 10% expressed confidence they could be seen by their regular doctors within a day if they became suddenly ill. Average waiting time for a doctor's appointment was 24 days. Coordination of care with specialists was at minimally acceptable levels. Patients with family physicians recalled them addressing only 56% of the health promotion and preventive issues appropriate for their age and sex, and patients without family physicians recalled physicians addressing substantially fewer (38%). Most patients reported they were highly confident that their physicians knew them well and would manage their care beyond clinical encounters (relational continuity). The exception was the 16% of patients overall who did not have family physicians (34% of patients at walk-in clinics). CONCLUSION: This survey highlights serious problems with accessibility. Improvement is needed urgently to avoid deterioration of patients' confidence in the health system even though patients rate their relationships with their physician highly. Health promotion, preventive services, and coordination with specialists also needed to be improved, and careful thought must be given to the plight of those without family physicians.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".