Comparison of prescribing practices for older adults treated by female versus male physicians: A retrospective cohort study
Bibliographic record
Abstract
IMPORTANCE: Subtle but important differences have been described in the way that male and female physicians care for their patients, with some evidence suggesting women are more likely to adhere to best practice recommendations. OBJECTIVE: To determine if male and female physicians differ in their prescribing practices as measured by the initiation of lower-than-recommended dose cholinesterase inhibitor (ChEI) drug therapy for dementia management. DESIGN, SETTING, AND PARTICIPANTS: All community-dwelling Ontario residents aged 66 years and older with dementia and newly dispensed an oral ChEI drug (donepezil, galantamine, or rivastigmine) between April 1, 2010 and June 30, 2016 were included. MAIN OUTCOME AND MEASURES: The association between physician sex and the initiation of a lower than recommended-dose ChEI was examined using generalized linear mixed regression models, adjusting for patient and physician characteristics. Data were stratified by specialty. Secondary analyses explored the association between physician sex and cardiac screening as well as shorter duration of the initial prescription. RESULTS: The analysis included 3,443 female and 5,811 male physicians and the majority (83%) were family physicians, Female physicians were more likely to initiate ChEI therapy at a lower-than-recommended dose (Adjusted odds ratio = 1.43,95% confidence interval = 1.17 to 1.74). Compared to their male counterparts, female physicians were also more likely to follow other conservative prescribing practices including cardiac screening (55.1% vs. 49.2%, P-value<0.001) around the time of ChEI initiation, and dispensing a shorter duration of initial prescription (41.8% vs 35.5% P-value<0.001). CONCLUSIONS: There is a statistically significant and important difference in ChEI prescribing patterns between female and male physicians, suggesting that female physicians may be more careful and conservative in their approaches. This will inform future research to determine if patients receiving lower-than-recommended initial doses also have better outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".