Changes in Family Physicians Over Time in Alberta, Canada: A 16-Year Population-Based Cohort Study
Bibliographic record
Abstract
PURPOSE Most studies evaluating access to primary care have focused on changes in family physicians (FPs), with less exploration of patient differences over time. We examined both physicians and patients, including changes over time in the age and medical complexity of people seeing FPs. METHODS We conducted a population-based cohort study using administrative health data, including physician claims and hospital data, examining patients cared for by FPs providing comprehensive primary care from 2004 to 2020 in Alberta, Canada. We assessed changes in FPs and used validated algorithms to examine changes in comorbidity among adults cared for by those physicians. RESULTS There were notable changes in FPs over time including more physicians who were women (46.7% in 2020 vs 39% in 2004; P < .001) and trained in low/middle-income countries (17.2% vs 6.3%; P < .001). Patient age and number of comorbidities increased over time. The proportion aged 61-80 years increased from 16.1% in 2004 to 22.1% in 2020 (P < .001). Those with ≥5 comorbid conditions increased from 2.8% to 5.2% (P < .001). There were changes in physician practice over time including decreases in average days worked each year (167 in 2004, 156 in 2020; P = .007) and number of adult patients seen each day (23 vs 20; P < .001). CONCLUSIONS From 2004 to 2020, there were substantial changes in the characteristics and practices of FPs. In addition, there were notable trends in the characteristics of their patients, including an increasing proportion of older adults, often with more complex comorbidities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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 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".