Do Gender-Predominant Primary Health Care Organizations Have an Impact on Patient Experience of Care, Use of Services, and Unmet Needs?
Bibliographic record
Abstract
Physicians' gender can have an impact on many aspects of patient experience of care. Organization processes through which the influence of gender is exerted have not been fully explored. The aim of this article is to compare primary health care (PHC) organizations in which female or male doctors are predominant regarding organization and patient characteristics, and to assess their influence on experience of care, preventive care delivery, use of services, and unmet needs. In 2010, we conducted surveys of a population stratified sample (N = 9180) and of all PHC organizations (N = 606) in 2 regions of the province of Québec, Canada. Patient and organization variables were entered sequentially into multilevel regression analyses to measure the impact of gender predominance. Female-predominant organizations had younger doctors and nurses with more expanded role; they collaborated more with other PHC practices, used more tools for prevention, and allotted more time to patient visits. However, doctors spent fewer hours a week at the practice in female-predominant organizations. Patients of these organizations reported lower accessibility. Conversely, they reported better comprehensiveness, responsiveness, counseling, and screening, but these effects were mainly attributable to doctors' younger age. Their reporting unmet needs and emergency department attendance tended to decrease when controlling for patient and organization variables other than doctors' age. Except for accessibility, female-predominant PHC organizations are comparable with their male counterparts. Mean age of doctors was an important confounding variable that mitigated differences, whereas other organization variables enhanced them. These findings deserve consideration to better understand and assess the impacts of the growing number of female-predominant PHC organizations on the health care system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".