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Record W4406447338 · doi:10.1186/s12913-025-12247-1

The association between physician sex and patient outcomes: a systematic review and meta-analysis

2025· review· en· W4406447338 on OpenAlexafffund
Kiyan Heybati, Ashton Chang, Hodan Mohamud, Raj Satkunasivam, Natalie Coburn, Arghavan Salles, Yusuke Tsugawa, Ryo Ikesu, Natsumi Saka, Allan S. Detsky, Dennis T. Ko, Heather J. Ross, Mamas A. Mamas, Angela Jerath, Christopher J.D. Wallis

Bibliographic record

VenueBMC Health Services Research · 2025
Typereview
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsUniversity Health NetworkSunnybrook HospitalUniversity of TorontoMount Sinai HospitalSunnybrook Health Science Centre
FundersHealth CanadaUniversity of TorontoHeart and Stroke Foundation of Canada
KeywordsMedicineNursing researchHealth administrationHealth informaticsPublic healthMeta-analysisFamily medicineMEDLINEAssociation (psychology)Health services researchNursingInternal medicinePsychology

Abstract

fetched live from OpenAlex

Abstract Background Some prior studies have found that patients treated by female physicians may experience better outcomes, as well as lower healthcare costs than those treated by male physicians. Physician–patient sex concordance may also contribute to better patient outcomes. However, other studies have not identified a significant difference. There is a paucity of pooled evidence examining the association of physician sex with clinical outcomes. Methods This random-effects meta-analysis was conducted according to the PRISMA guidelines and prospectively registered on PROSPERO. MEDLINE and EMBASE were searched from inception to October 4th, 2023, and supplemented by a hand-search of relevant studies. Observational studies enrolling adults (≥ 18 years of age) and assessing the effect of physician sex across surgical and medical specialties were included. The risk of bias was assessed using ROBINS-I. A priori subgroup analysis was conducted based on patient type (surgical versus medical). All-cause mortality was the primary outcome. Secondary outcomes included complications, hospital readmission, and length of stay. Results Across 35 ( n = 13,404,840) observational studies, 20 ( n = 8,915,504) assessed the effect of surgeon sex while the remaining 15 ( n = 4,489,336) focused on physician sex in medical/anesthesia care. Fifteen studies were rated as having a moderate risk of bias, with 15 as severe, and 5 as critical. Mortality was significantly lower among patients of female versus male physicians (OR 0.95; 95% CI: 0.93 to 0.97; P Q = 0.13; I 2 = 26%), which remained consistent among surgeon and non-surgeon physicians (P interaction = 0.60). No significant evidence of publication bias was detected (P Egger = 0.08). There was significantly lower hospital readmission among patients receiving medical/anesthesia care from female physicians (OR 0.97; 95% CI: 0.96 to 0.98). In a qualitative synthesis of 9 studies ( n = 7,163,775), patient-physician sex concordance was typically associated with better outcomes, especially among female patients of female physicians. Conclusions Patients treated by female physicians experienced significantly lower odds of mortality, along with fewer hospital readmissions, versus those with male physicians. Further work is necessary to examine these effects in other care contexts across different countries and understand underlying mechanisms and long-term outcomes to optimize health outcomes for all patients. Review registration PROSPERO – CRD42023463577.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.037
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.039
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.283
GPT teacher head0.541
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations23
Published2025
Admission routes2
Has abstractyes

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