The implications of the feminization of the primary care physician workforce on service supply: a systematic review
Bibliographic record
Abstract
There is a widespread perception that the increasing proportion of female physicians in most developed countries is contributing to a primary care service shortage because females work less and provide less patient care compared with their male counterparts. There has, however, been no comprehensive investigation of the effects of primary care physician (PCP) workforce feminization on service supply. We undertook a systematic review to examine the current evidence that quantifies the effect of feminization on time spent working, intensity and scope of work, and practice characteristics. We searched Medline, Embase, and Web of Science from 1991 to 2013 using variations of the terms 'primary care', 'women', 'manpower', and 'supply and distribution'; screened the abstracts of all articles; and entered those meeting our inclusion criteria into a data abstraction tool. Original research comparing male to female PCPs on measures of years of practice, time spent working, intensity of work, scope of work, or practice characteristics was included. We screened 1,271 unique abstracts and selected 74 studies for full-text review. Of these, 34 met the inclusion criteria. Years of practice, hours of work, intensity of work, scope of work, and practice characteristics featured in 12%, 53%, 42%, 50%, and 21% of studies respectively. Female PCPs self-report fewer hours of work than male PCPs, have fewer patient encounters, and deliver fewer services, but spend longer with their patients during a contact and deal with more separate presenting problems in one visit. They write fewer prescriptions but refer to diagnostic services and specialist physicians more often. The studies included in this review suggest that the feminization of the workforce is likely to have a small negative impact on the availability of primary health care services, and that the drivers of observed differences between male and female PCPs are complex and nuanced. The true scale of the impact of these findings on future effective physician supply is difficult to determine with currently available evidence, given that few studies looked at trends over time, and results from those that did are inconsistent. Additional research examining gender differences in practice patterns and scope of work is warranted.
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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 | 0.026 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".