Examining the role of physician areas of practice on the gender pay gap in family medicine in Ontario
Notice bibliographique
Résumé
Context Previous research has shown a pay gap between male and female family physicians (FPs) in Ontario. Physician payment models can explain part of the gap, but a lot remains unknown about what factors contribute to the gap and how to reduce it. Another factor that impacts FPs total payments is the area of practice. It is estimated that over 30% of FPs in Ontario provide care in an area of practice other than primary care, some of which are known to have compensation levels much higher than primary care. Objective The objective of this study is to determine how much of the gender pay gap among FPs is explained by the physician areas of practice. Study design We analyzed the gender pay gap among FPs, while accounting for previously observed factors that contribute to it. These previously studied variables included physician activity and practice factors such as: years of practice, part-time status, work setting, work after-hours, and physician sex. The areas of practice were identified based on the billing activity and incorporated into our analysis, which changed the estimated effect of physician sex on total payments. We also stratified the analysis by physician payment model: FFS, enhanced-FFS, and capitation. Data Set Family physician billing and payment data provided by the Ontario Ministry of Health for April 1, 2022, to March 31, 2023. Population Studied All FPs who submitted billings to the Ontario Health Insurance Plan between April 2022 and March 2023. Intervention/Instrument Inclusion of FPs areas of practice in multivariable linear regressions. Outcome measures Family physician average daily payments, by sex, areas of practice, and predominant payment model. Results The inclusion of physician areas of practice reduced the unexplained gender pay gap from 16.5 (95% CI: 14.2 - 18.7) to 13.3 percent (11.1 - 15.5). The effect was observed on all the stratified payment models, changing from 21.6 (16.7 - 26.4) to 15.7% (11.1 - 20.3) for FFS; from 19.3 (14.8 - 23.8) to 16.7 (12.3 - 21.0) on enhanced FFS; and from 12.0 (10.0 - 14.0) to 10.8% (8.8 - 12.8) among FPs in capitation plans. Conclusion The reduction of the unexplained gender pay gap suggests that areas of practice where women are underrepresented tend to be more highly remunerated. Addressing the pay gap between areas of practice can help lowering the gender pay gap, but other unexplained gender-related differences contributing to the gender pay gap persist.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».