Short report: Scope of family practice in rural and urban settings.
Bibliographic record
Abstract
amily physicians in all settings provide a variety of procedures.1,2 Rural doctors tend to provide a greater number or variety of procedures than their urban counterparts.1,2 What has not been studied well is where practice patterns diff er on the rural-urban continuum and the relative importance of variables that contribute to the diff erences. Our hypothesis was that geography is the predominant predictor of scope of practice and might be a more signifi cant predictor than physicians’ age1,2 or sex.3 Primary data source for this study was the 1997 College of Family Physicians of Canada’s National Family Physician Survey.4 A practice breadth score was calculated by totaling the survey responses from each of 16 questions on procedures and eight on on-call activities. Geographic location of practices was determined using the postal codes provided by the 2981 respondents matched with 1996 census data and geography. Straight-line distances were computed between practice location and nearest hospitals and communities of various sizes. Th e practice breadth score was modeled using independent variables: sex, age, practice type, straight-line distance to large referral hospital (>299 beds), municipal population size, and general region (Atlantic, Quebec, Ontario, Prairies, Alberta, British Columbia, Northern). Multivariate logistic regression was done to confi rm independence of variables and to determine the relative weight of each parameter in determining the total practice breadth score. A sum of squares analysis was done to determine how close the model fi t to observed variation in practice breadth. In smaller centres, 21 of the 24 procedures and on-call items were found to be more common (Table 1). When all 24 items were combined in the practice breadth score, a progression (Figure 1) was noted in association with increasing distance from a large city (>100 000 population). A multivariate statistical model based on factors of sex, age, practice type, distance to large hospital, municipal population, and region was found to explain 38% of the variation in practice breadth score. Pearson correlates to practice breadth were strongest for the geographic variables of distance to large hospital (0.401, P < .01), community size (-0.363, P < .01) and region (0.184, P < .01), which together accounted for 30% of the variation. An additional 8% of the variation in practice breadth was explained by personal characteristics of sex (0.172, P < .01), age (-0.123, P < .01), and type of medical practice (-0.083, P < .01). Our analyses suggest that, as geographic isolation increases, Canadian family physicians provide an increasingly broad spectrum of services. Our study confi rms earlier work that male sex,3 youth of physician,1,2 and FP group practice5 are associated with increased breadth of practice. Focusing Dr Hutten-Czapski is a family physician in rural practice in Haileybury, Ont. He is an Assistant Professor at the University of Ottawa and at the Northern Ontario School of Medicine. Dr Pitblado is a Professor of Geography at Laurentian University in Sudbury, Ont. Mr Slade is a research consultant at the Canadian Institute for Health Information.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".