A Comprehensive Assessment of Family Physician Gender and Quality of Care
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Studies evaluating primary care quality across physician gender are limited to primary and secondary prevention. OBJECTIVES: Investigate the relationship between family physician gender and quality of primary care using indicators that cover 5 key dimensions of primary care. RESEARCH DESIGN: Cross-sectional analysis using linked health administrative datasets (April 1, 2008 to March 31, 2010). SUBJECTS: All family physicians working in the 3 main primary care models in the province of Ontario (Canada), providing general care and having a panel size >1200. MEASURES: Indicators of cancer screening (3), chronic disease management (9), continuity (2), comprehensiveness (2), and access (5). RESULTS: A total of 4195 physicians (31% female) were eligible. Adjusting for provider and patient factors, patients of female physicians were more likely to have received recommended cancer screening (odds ratios [95% confidence interval (CI)] (OR) range: 1.24 [1.18-1.30], 1.85 [1.78-1.92]) and diabetes management (OR: 1.04 [1.01-1.08], 1.28 [1.05-1.57]). They had fewer emergency room visits (rate ratio [95% CI] (RR) range: 0.83 [0.79-0.87]) and hospitalizations (RR: 0.89 [0.86-0.93]), and higher referrals (RR: 1.12 [1.09-1.14]). There was evidence of effect modification by patient gender (female vs. male) for hospitalization (RR: 0.74 [0.70-0.79] vs. 0.96 [0.90-1.02]) and emergency room visits (RR: 0.84 [0.81-0.88] vs. 0.98 [0.94-1.01]). Lower emergency room visits were also more evident in more complex patients of female physicians. There were no significant differences in the continuity or comprehensiveness measures. CONCLUSIONS: The indicators assessed in this study point to a benefit for patients under the care of female physicians. Potential explanations are discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it