Tracking family medicine graduates. Where do they go, what services do they provide and whom do they see?
Bibliographic record
Abstract
BACKGROUND: There are continued concerns over an adequate supply of family physicians (FPs) practicing in Canada. While most resource planning has focused on intake into postgraduate education, less information is available on what postgraduate medical training yields. We therefore undertook a study of Family Medicine (FM) graduates from the University of Toronto (U of T) to determine the type of information for physician resource planning that may come from tracking FM graduates using health administrative data. This study compared three cohorts of FM graduates over a 10 year period of time and it also compared FM graduates to all Ontario practicing FPs in 2005/06. The objectives for tracking the three cohorts of FM graduates were to: 1) describe where FM graduates practice in the province 2) examine the impact of a policy introduced to influence the distribution of new FM graduates in the province 3) describe the services provided by FM graduates and 4) compare workload measures. The objectives for the comparison of FM graduates to all practicing FPs in 2005/06 were to: 1) describe the patient population served by FM graduates, 2) compare workload of FM graduates to all practicing FPs. METHODS: The study cohort consisted of all U of T FM postgraduate trainees who started and completed their training between 1993 and 2003. This study was a descriptive record linkage study whereby postgraduate information for FM graduates was linked to provincial health administrative data. Comprehensiveness of care indicators and workload measures based on administrative data where determined for the study cohort. RESULTS: From 1993 to 2003 there were 857 University of Toronto FM graduates. While the majority of U of T FM graduates practice in Toronto or the surrounding Greater Toronto Area, there are FM graduates from U of T practicing in every region in Ontario, Canada. The proportion of FM graduates undertaking further emergency training had doubled from 3.6% to 7.8%. From 1993 to 2003, a higher proportion of the most recent FM graduates did hospital visits, emergency room care and a lower proportion undertook home visits. Male FM graduates appear to have had higher workloads compared with female FM graduates, though the difference between them was decreasing over time. A 1997 policy initiative to discount fees paid to new FPs practicing in areas deemed over supplied did result in a decrease in the proportion of FM graduates practicing in metropolitan areas. CONCLUSIONS: We were able to profile the practices of FM graduates using existing and routinely collected population-based health administrative data. Further work tracking FM graduates could be helpful for physician resource forecasting and in examining the impact of policies on family medicine practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".