Primary health care organizational characteristics associated with better accessibility: data from the QUALICO-PC survey in Quebec
Bibliographic record
Abstract
BACKGROUND: First-contact accessibility remains an important problem in Canada, with this indicator staying the worst of all Organization for Economic Co-operation and Development countries. In the province of Quebec, a number of primary healthcare (PHC) organizations have adopted measures to improve access (e.g. advance access scheduling, expanded nursing role, electronic medical record, financial incentives). The impact of those changes is unknown. The goal of this study is to assess which PHC organizations' characteristics are associated with improved first-contact accessibility. METHODS: We conducted a secondary data analysis of the Quebec survey, conducted as part of the QUALICO-PC study on primary care performance. QUALICO-PC is a cross-sectional study to assess quality, costs and equity in PHC across 35 countries and jurisdictions. Organizational characteristics were measured from the family practitioners' questionnaire. First-contact accessibility was measured from the patient questionnaire filled by patients who received care in the participating PHC organizations. Multi-level logistic regression was used to assess the association of organizational characteristics as predictors of patient-reported accessibility. RESULTS: A total of 218 family practitioners participated in the study with 1798 of their patients. PHC organizations characteristics associated with increased first-contact accessibility included the possibility to have a same-day appointment or to walk in the clinic without an appointment, higher number of physicians per clinic and higher number of hours worked by the family physician. Electronic medical record and expanded nursing role were not associated with increased accessibility. CONCLUSIONS: Same-day access and higher family physician working hours are associated with improved patient-reported accessibility. Other PHC organizations characteristics targeted by recent reforms were not associated with improved accessibility.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".