Characterizing the services provided by family physicians in Ontario, Canada: A retrospective study using administrative billing data
Bibliographic record
Abstract
Family physicians in Ontario provide most of the primary care to the healthcare system. However, given their broad scope of practice, they often provide additional services including emergency medicine, hospital medicine, and palliative care. Understanding the spectrum of services provided by family physicians across different regions is important for health human resource planning (HHRP). We investigated the services provided by family physicians in Ontario, Canada using a provincial physician database and administrative physician billing data from 2017. Billing codes were used to define 18 general services that family physicians may provide. We then evaluated variation in the services provided by different physicians based on the physicians' geographic location (north-urban, north-rural, south-urban, and south-rural) and career stage (i.e., years in practice). Ontario had 14,443 family physicians in 2017, with most practicing in urban communities in southern Ontario and only 6.5% practicing in any setting in northern Ontario. In general, rural physicians provided a greater range of services than their urban colleagues. Their practices most often included clinic medicine, mental health services, emergency medicine, palliative care, and hospital medicine. Physicians in urban southern Ontario and those at a more advanced career stage were more likely to provide a narrower range of services. Overall, our findings have the potential to shape HHRP, medical education curriculum development, and clinical services planning in Ontario and elsewhere. Moreover, our results provide policy- and decision-makers with a basis for integrating knowledge of the specific clinical services delivered by family physicians into their future planning, with the goal of ensuring a fit-for-purpose workforce able to meet community healthcare needs.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".