Improved access to and continuity of primary care after attachment to a family physician: longitudinal cohort study on centralized waiting lists for unattached patients in Quebec, Canada
Bibliographic record
Abstract
BACKGROUND: Having a regular family physician is associated with many benefits. Formal attachment - an administrative patient-family physician agreement - is a popular feature in primary care, intended to improve access to and continuity of care with a family physician. However, little evidence exists about its effectiveness. In Quebec, Canada, where over 20% of the population is unattached, centralized waiting lists help attach patients. This provides a unique opportunity to observe the influence of attachment in previously unattached patients. The aim was to evaluate changes in access to and continuity of primary care associated with attachment to a family physician through Quebec's centralized waiting lists for unattached patients. METHODS: We conducted an observational longitudinal population cohort study, using medical services billing data from public health insurance in the province of Québec, Canada. We included patients attached through centralized waiting lists for unattached patients between 2012 and 2014 (n = 410,140). Our study was informed by Aday and Andersen's framework for the study of access to health services. We compared outcomes during four 12-month periods: two periods before and two periods after attachment, with T0-2 years as the reference period. Outcome measures were number of primary care visits and Bice-Boxerman Concentration of Care Index at the physician and practice level (for patients with ≥2 visits in a given period). We included age, sex, region remoteness, medical vulnerability, and Charlson Comorbidity Index as covariates in regression models fitted with generalized estimating equations. RESULTS: The number of primary care visits increased by 103% in the first post attachment year and 29% in the second year (p < 0.001). The odds of having all primary care visits concentrated with a single physician increased by 53% in the first year and 22% (p < 0.001) in the second year after attachment. At the practice level, the odds of perfect concentration of care increased by 19% (p < 0.001) and 15% (p < 0.001) respectively, in first and second year after attachment. CONCLUSION: Our results show an increase in patients' number of primary care visits and concentration of care at the family physician and practice level after attachment to a family physician. This suggests that attachment may help improve access to and continuity of primary care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".