Comparison of Postoperative Outcomes Among Patients Treated by Male Versus Female Surgeons

Abstract

Objective:

To compare clinical outcomes of patients treated by female surgeons versus those treated by male surgeons.

Background:

It remains unclear as to whether surgical performance and outcomes differ between female and male surgeons.

Methods:

We conducted a meta-analysis to compare patients’ clinical outcomes—including patients’ postoperative mortality, readmission, and complication rates—between female versus male surgeons. MEDLINE, Embase, CENTRAL, ICTRP, and ClinicalTrials.gov were searched from inception to September 8, 2022. The update search was conducted on July 19, 2023. We used random-effects models to synthesize data and GRADE to evaluate the certainty.

Results:

A total of 15 retrospective cohort studies provided data on 5,448,121 participants. We found that patients treated by female surgeons experienced a lower postoperative mortality compared with patients treated by male surgeons [8 studies; adjusted odds ratio (aOR), 0.93; 95% CI, 0.88–0.97; I ²=27%; moderate certainty of the evidence]. We found a similar pattern for both elective and nonelective (emergent or urgent) surgeries, although the difference was larger for elective surgeries (test for subgroup difference P=0.003). We found no evidence that female and male surgeons differed for patient readmission (3 studies; aOR, 1.20; 95% CI, 0.83–1.74; I ²=92%; very low certainty of the evidence) or complication rates (8 studies; aOR, 0.94; 95% CI, 0.88–1.01; I ²=38%; very low certainty of the evidence).

Conclusion:

This systematic review and meta-analysis suggests that patients treated by female surgeons have a lower mortality compared with those treated by male surgeons.

Although the number of female doctors is increasing over time, women are still underrepresented in surgery compared with their male counterparts. In 2019, women comprised only 22% of general surgeons in the United States,^1,2 18% of surgeons in the United Kingdom,³ 6% of surgeons in Japan,⁴ and 16% of surgeons in 8 general surgical societies in North America, Europe, and Oceania.⁵ These rates were even lower in surgical subspecialties, including thoracic and orthopedic surgery.^1,2 These numbers are notably lower than the proportions of female physicians in fields such as medicine and pediatrics, where female physicians may outnumber male counterparts in some countries.^6,7

The success of a surgical procedure can be attributed to several factors, including the quality of preoperative planning, the surgeon’s technical expertize and skill sets, and the ability to manage complications that may arise during the operation and in the postoperative period. These factors are determined by the surgeon’s clinical knowledge, communication skills with other team members, and the ability to make sound clinical judgments.⁸ Research on gender differences in clinical practice patterns suggests that female and male surgeons may treat patients differently. For example, female surgeons treating breast cancer patients have been found to be more likely to offer guideline-concordant therapies,⁹ recommend adjuvant radiotherapy following breast-conservation surgery (BCS),¹⁰ perform contralateral prophylactic mastectomy,¹¹ and are less likely perform lymph node dissection along with BCS.¹² Considering the existing structural barriers that hinder women from pursuing a career in surgery,¹³ the current pool of female surgeons might be a selected group displaying greater expertize, determination, and attentiveness than their male counterparts. These differences could potentially influence the outcomes after surgery. However, existing studies that have compared patient outcomes between female and male surgeons have produced mixed findings^2,14–16 with some studies showing better patient outcomes for female surgeons² and others showing no difference between the 2 groups of surgeons. However, to our knowledge, no study to date using quantitative meta-analysis exists that provides a summative comparison of postoperative outcomes between female and male surgeons across a large number of surgical procedures.

Given that female surgeons are compensated less and less likely to be promoted than male surgeons,^17–24 a better understanding of the performance of female surgeons has important clinical and policy implications. In this context, we performed a systematic review and meta-analysis of available evidence comparing patients’ postoperative outcomes (mortality, readmission, and complication rates) between female and male surgeons.

METHODS

We followed a registered protocol (https://osf.io/pgh78/)²⁵ and reported this systematic review in accordance with the Reporting Checklist for Meta-analyses of Observational Studies (MOOSE)²⁶ and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance.²⁷ The amendments from the registered protocol are available in Methods section in the Supplemental Digital Content 1 (http://links.lww.com/SLA/F109).

Data Source

We searched Medline, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL) from database inception to September 8, 2022 and updated the search on July 19, 2023. We also searched the World Health Organization International Clinical Trials Platform Search Portal (ICTRP) and ClinicalTrials.gov for unpublished and ongoing trials. The details of the full search strategy, which were constructed by investigators and a research librarian, are available in Methods section in the Supplemental Digital Content 1 (http://links.lww.com/SLA/F109). We investigated the reference lists of eligible studies and articles citing eligible studies that reported the surgical outcome of female surgeons using Citationchaser.²⁸ We also examined the reference lists of the studies that were included in the previously published meta-analysis of surgical outcomes based on the surgeons’ factors.^29,30 We also evaluated the major surgical guidelines (Methods section in the Supplemental Digital Content 1, http://links.lww.com/SLA/F109).

Study Eligibility

We included studies that have stratified their results by the sex or gender of the surgeon and evaluated health outcomes (ie, mortality, readmission, and complication rates) of patients who underwent surgeries for our eligibility criteria. We included both longitudinal/cohort studies and case-control studies, as well as controlled before and after studies, cross-sectional studies without the restriction of language, country, or publication year. We included observational studies which was conducted using the data from randomized controlled trials (RCTs) for other objective. We included the studies that report the outcome of surgical trainees (eg, surgical residents), not only surgical attending physicians. We excluded case reports, case series, studies that use surveys to gather data from surgeons or patients. We did not include RCTs that were not conducted to assess the effect of surgeon gender, even if they contain some information on surgeon gender, due to limited information available to assess their generalizability. We also excluded studies that were published as conference abstracts due to difficulty in assessing their quality, but conducted the sensitivity analysis including those studies to assess the robustness of our analysis. We selected studies with the largest cohorts or the most detailed information for analyses if multiple studies used the same or overlapping data.

Study participants were defined as patients undergoing any surgeries, including major and minor surgery,³¹ outpatient surgery, both emergent and elective surgery, and revision surgery. We defined exposure as surgical treatment performed by female versus male surgeons. The definition of surgeon gender was decided by the original authors by either biological sex or socially constructed gender.

Two independent reviewers (N.S. and one of the others: H.S., M.H., K.K., or T.A.) screened titles and abstracts using Rayyan,³² followed by the assessment of eligibility based on the full texts. Disagreements between the 2 reviewers were resolved by discussion, and if that failed, a third reviewer acted as an arbiter (N.Y. or J.W.).

Data Extraction and Quality Assessment

Two reviewers (N.S. and one of the others: H.S., M.H., K.K., or T.A.) conducted independent data extraction of the included studies using a standardized data collection form. Data collection included study characteristics (study design, study setting, study location, sample size, language of the published study, age of participants, enrollment period, type of surgery, follow-up period, exposure, outcomes, the definition of complications, adjusted confounders) and outcomes. The outcomes of interest were patients’ postoperative mortality, patients’ readmission and complication rates. We defined the postoperative period as 30 days after the surgery, a definition widely used in previous studies.^2,14,33,34 When the data on 30-day follow-up was unavailable, we used the outcome variables’ follow-up period closest to 30 days after the surgery. For the effect measure of the outcomes, we extracted both unadjusted and adjusted odds ratios (ORs), and if there were several analyses conducted in the study, we used the data on the most extensively adjusted ORs. For the studies which reported the adjusted result from matched cohort and entire cohort, we used the adjusted effect estimate from entire cohort to reflect the result from larger sample. We contacted the original authors and requested unpublished data whenever necessary.

Risk of Bias and Certainty of the Evidence Assessment

Two reviewers (N.S. and one of the others: H.S., M.H., K.K., or T.A.) independently evaluated the risk of bias using the Risk Of Bias In Non-randomised Studies–of Interventions (ROBINS-I) tool.³⁵ We a priori defined the following possible confounders for the evaluation of study confounding—surgeons’ age, specialty, and surgical volume; and patients’ sex/gender, age, and comorbidities—based on the previous studies.^{2,30,33,36–38} The overall risk of bias was determined based on the ratings of the ROBINS-I domains. Traffic light plots were generated on each outcome using a robvis tool.³⁹

We evaluated the certainty of evidence based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach,⁴⁰ which divided evidence as either very low, low, moderate, or high. We rated the certainty of the observational evidence as high in the beginning and downgraded based on the risk of bias, imprecision, inconsistency, indirectness, and publication bias and rated up for size and trend of the effect, using the ROBINS-I tool.⁴¹ A summary of findings (SoF) table was created to describe the evidence and absolute effect for each outcome. The risk in control groups in the SoF table was calculated from the median of event rates in the control group across studies, based on the recommendation in the Cochrane Handbook.⁴²

Data Synthesis

We conducted the meta-analysis of the crude and adjusted ORs using a random-effects model. When both crude and adjusted ORs were reported in the original articles, most adjusted ORs were used for the synthesis. If ORs are not available and if the risk ratios (RRs) are reported in original studies, we used a method reported by Zhang and Yu⁴³ to transform RRs into ORs. We calculated the ORs with 95% CIs for the following binary outcome variables: patient mortality, complications, and readmission rates using Review Manager software (RevMan 5.4). We evaluated the statistical heterogeneity by visual inspection of the Forest plot and calculating the I ² statistic, with 0% to 40%: might not be important; 30% to 60%: may represent moderate heterogeneity; 50% to 90%: may represent substantial heterogeneity; and 75% to 100%: considerable heterogeneity.⁴² All significance testing was considered statistically significant if P-value was <0.05.

Subgroup Analysis

To examine whether our findings varied by factors related to procedures, we conducted subgroup analyses by: types of surgery (for procedures with sufficiently large sample sizes; types of surgeries based on the specialty, or major surgery versus minor surgery based on the definition from the study by Powell et al³¹), the location where the study was conducted (North America vs Europe vs Asia Pacific), and elective versus nonelective (ie, emergent or urgent) surgeries.

Sensitivity Analysis

We conducted a series of sensitivity analyses to evaluate the robustness of our findings. First, to test whether our findings were sensitive to the adjustment for potential confounders in individual studies, we reanalyzed the data after restricting it to studies that reported adjusted ORs. Second, as the duration of the follow-up period may affect our findings, we reanalyzed the data restricting it to studies that reported 30-day postoperative outcomes. Third, to examine whether our results were sensitive by the selection of studies in our analyses, we reanalyzed the data including the data from studies published as conference abstracts. Fourth, we reanalyzed the data after excluding studies in which surgical trainees conducted the operations or the qualification of the operators was unclear. Finally, for the outcome of complication, we excluded studies in which only reoperation was defined as a complication. Publication bias using funnel plots and the Egger test were not assessed since there were <10 included studies for each outcome.⁴²

RESULTS

Study Selection, Characteristics, and Quality Assessment

Figure 1 describes the flow of review. We identified 3722 records after removing duplicates. After screening the titles and citation of the research, 123 records were subsequently reviewed. A list of the studies that were excluded and the reason for their exclusion can be found in the in Supplemental Digital Content 1, Table 1 (http://links.lww.com/SLA/F109). Twenty-one studies were included in the qualitative synthesis.^{2,14–16,44–60} Finally, 15 studies with 5,448,121 participants were eligible for data extraction and quantitative synthesis.^{2,14–16,44–48,50,54–56,59,60} Supplemental Digital Content 1, Table 2 (http://links.lww.com/SLA/F109) summarizes the characteristics of the studies included in the quantitative synthesis and Supplemental Digital Content 1, Table 3 (http://links.lww.com/SLA/F109) summarizes the further details of study characteristics included in the qualitative synthesis. Among the studies included in the qualitative synthesis, 6 studies were excluded from the quantitative analysis because 2 of them reported only the composite outcome of mortality and readmission rate,^51,53 1 study did not report the quantitative result,⁵² and 3 studies were conference abstracts.^49,57,58 Among the studies that were included only in the qualitative synthesis, all studies reported the equivalent outcomes between female surgeons and male surgeons. The included studies for the quantitative synthes were published from 2000 to 2023. All studies were observational studies. All studies were published in English. A total of 15 studies were included, exhibiting a diverse geographic composition, with a predominance from North America and Asia, followed by contributions from European countries. While 3 studies included surgical procedures across a broad spectrum of specialties,^2,14,54 others focused on specific surgical fields. The definition of postoperative complication varied among the studies, with 2 studies using reoperation as the criterion.^47,48 The majority of studies used population-based or registry-based data, while the remaining studies employed hospital-based data. The time frames for measuring outcomes were evenly divided among 30-day, intrahospital, and outcomes exceeding 30 days. A small number of studies (n=4) included surgical trainees as surgeons, while other studies either exclusively involved attending surgeons or did not specify the qualifications of the surgeons.

FIGURE 1.

Literature search flow diagram.

The overall risk of bias evaluated by the Risk Of Bias In Non-randomised Studies—of Interventions (ROBINS-I) tool was moderate in 8 studies,^{2,14,16,45,48,54,55,60} and serious in 7 studies.^{15,44,46,47,50,56,59}

Overall risk of bias for each study was rated as serious when at least 1 of 7 domains in ROBINS-I tool (Confounding, Selection bias, Bias in classification of interventions, Bias due to deviations from intended interventions, Bias due to missing data, Bias in measurement of outcomes, and Bias in selection of the reported result) were rated as serious, and rated as moderate if one domain rated as moderate. For example, whether the studies prespecified potential confounders and adjusted for them was defined as one of the domains of the assessment of the risk of bias. Studies which did not include prespecified potential confounders in their analysis plan were rated as serious or moderate risk of bias in confounding, based on the number of confounders they used. The risk of bias on each outcome is described in Supplemental Digital Content 1, Figures 1 to 3 (http://links.lww.com/SLA/F109).

Synthesized Results

Table 1 summarizes the findings using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.

TABLE 1.

Summary of Findings Table on Postoperative Outcomes

	Anticipated absolute effects
Outcomes	Risk with male surgeons*	Risk with female surgeons (95% CI)†	Relative effect (95% CI)	No. participants (studies)	Certainty of the evidence‡
Mortality	10 per 1000	9 per 1000 (9–10)	OR 0.93 (0.88–0.97)	5,390,762 (8 studies)	Moderate§
Readmission	66 per 1000	78 per 1000 (55 –109)	OR 1.20 (0.83–1.74)	1,179,107 (3 studies)	Very low‖
Complication	94 per 1000	89 per 1000 (84–95)	OR 0.94 (0.88–1.01)	1,306,128 (8 studies)	Very Low¶

^*Median event rate of the included studies.

^†Risk in the exposed group and its 95% CI was based on the assumed risk in the nonexposed group and the relative effect of the exposure (and its 95% CI).

^‡GRADE Working Group grades of evidence.

^§Two of 8 studies were rated as having a serious risk of bias due to confounding factors. Consequently, the certainty of the evidence was downgraded by one level because of this serious risk of bias.

^‖Two of 3 studies of the studies were rated as serious risk of bias due to confounding factors. The result from each study were inconsistent and the CI was wide. Consequently, the certainty of the evidence was downgraded by 3 levels by serious risk of bias, inconsistency, and imprecision.

^¶Four of 8 studies were rated as serious risk of bias due to confounding factors. The result from each study were inconsistent and the CI was wide. Consequently, the certainty of the evidence was downgraded by 3 levels by serious risk of bias, inconsistency, and imprecision.

OR indicates odds ratio.

Eight studies with 5,390,762 participants reported postoperative mortality.^{2,14–16,44,45,54,60} Figure 2 shows the forest plot of the synthesized result. Due to the risk in confounding, 2 of the 8 studies were assessed as having a serious risk of bias. Consequently, this risk led to the downgrading of the evidence certainty by one level. Moderate certainty of the evidence supported that postoperative mortality is lower among patients treated by female surgeons compared with patients treated by male surgeons [adjusted odds ratio (aOR), 0.93; 95% CI, 0.88–0.97; I ²=27%].

FIGURE 2.

Pooled estimates in postoperative mortality. Effect size was determined using the random-effects model weighted by the inverse of the variance estimate. Squares represent effect size, with marker size reflecting the statistical weight of the study, obtained using random-effects meta-analysis; diamond represents the overall odds ratios and 95% CI.

Subgroup analyses performed to assess postoperative mortality showed significant differences among surgical specialties (test for subgroup differences, P=0.007) with a significantly lower mortality rate seen for patients treated by female general surgeons (aOR, 0.90; 95% CI, 0.87–0.93; I ²=19%), but no differences found in other specialties (Supplemental Digital Content 1, Fig. 4, http://links.lww.com/SLA/F109). Although most of the large cohort studies were from North American region, there was no subgroup differences stratified by the location of the studies (test for subgroup differences P=0.53) (Supplemental Digital Content 1, Fig. 5, http://links.lww.com/SLA/F109). We found significant differences in the effect of surgeons’ gender on mortality both in elective and nonelective (emergent or urgent) procedures. The difference in patient mortality between female and male surgeons was larger for elective surgeries compared with nonelective surgeries (test for subgroup differences, P=0.003) (Supplemental Digital Content 1, Fig. 6, http://links.lww.com/SLA/F109).

Three studies with 1,179,107 participants reported postoperative readmission rates (Fig. 3A).^2,15,46 In an assessment of 3 studies, 2 were identified as exhibiting a serious risk of bias attributed to confounding variables. Moreover, the evidence derived from these studies demonstrated a lack of consistency, accompanied by wide CIs. Consequently, the certainty of the evidence was downgraded by 3 levels due to serious risks of bias, heterogeneity, and imprecision. Very low certainty of the evidence supports that the rates of postoperative readmission were not different between female and male surgeons (aOR, 1.20; 95% CI, 0.83–1.74; I ²=92%). Eight studies with 1,360,128 participants reported rates of postoperative complications (Fig. 3B).^{2,47,48,50,55,56,59,60} In an assessment of 8 studies, 4 were identified as exhibiting a serious risk of bias attributed to confounding variables. Moreover, the evidence derived from these studies demonstrated a lack of consistency, accompanied by wide CIs. Consequently, the certainty of the evidence was downgraded by 3 levels due to serious risks of bias, heterogeneity, and imprecision. Very low certainty of the evidence supported that the rate of postoperative complications was not different between female and male surgeons (aOR, 0.94; 95% CI, 0.88–1.01; I ²=38%).

FIGURE 3.

Pooled estimates in postoperative readmission rate and complication rate. A, Postoperative readmission rate. B, Complication rate. Effect size was determined using the random-effects model weighted by the inverse of the variance estimate. Squares represent effect size, with marker size reflecting the statistical weight of the study, obtained using random-effects meta-analysis; diamonds represent the overall odds ratios and 95% CI.

Subgroup analyses of readmission rate showed no significant differences stratified by major and minor surgery and by the elective versus nonelective (emergent or urgent) surgery (Supplemental Digital Content 1, Figs. 7 and 8, http://links.lww.com/SLA/F109), but showed the significant subgroup effect by the location of studies (test for subgroup differences P<0.00001), due to the effect of one study (Supplemental Digital Content 1, Fig. 9, http://links.lww.com/SLA/F109).⁴⁶ When assessing the effect of surgeon gender on complications, the results did not vary by type of the surgery, location where the studies were conducted, and elective versus nonelective (emergent or urgent) surgery (Supplemental Digital Content 1, Figs. 10–12, http://links.lww.com/SLA/F109).

Sensitivity Analysis

For mortality and readmission, our findings were qualitatively unaffected by restricting to studies that reported adjusted outcomes; restricting to studies using 30-day postoperative outcomes, including studies with conference abstract,⁴⁹ and excluding studies in which surgical trainees conducted the operations or the qualification of the operators remained undisclosed (Supplemental Digital Content 1, Figs. 13–20, http://links.lww.com/SLA/F109). For complication, the result showed the lower complication rate for female surgeons when we restricted our analysis to studies with 30-day follow-up period, and also when we restricted our analysis to studies which included only attending surgeons (Supplemental Digital Content 1, Figs. 21 and 22, http://links.lww.com/SLA/F109). The sensitivity analysis also showed better patient outcomes for female surgeon when we excluded studies in which only reoperation was defined as complication (Supplemental Digital Content 1, Fig. 23, http://links.lww.com/SLA/F109). Other sensitivity analysis on complication showed the similar result as main analysis (Supplemental Digital Content 1, Figs. 24 and 25, http://links.lww.com/SLA/F109).

DISCUSSION

We conducted a systematic review and meta-analysis, which encompassed ∼5.5 million patients, and found a lower mortality among patients treated by female surgeons compared with male surgeons with a moderate certainty of evidence. When we stratified by electiveness of surgeries, a lower patient mortality for female surgeons was observed for both elective and nonelective surgeries. We found no evidence that patient readmission and complication rates differed between female and male surgeons, although the certainty of evidence was very low. Taken together, these findings suggest that the performance of female surgeons is equivalent to, or better than, that of male surgeons with respect to patients’ clinical outcomes. Despite substantial efforts to improve gender diversity in the field of surgery, prior studies have shown that female surgeons are compensated less,^18,61 and are less likely to be promoted to the rank of full professor,^18,19 compared with their male peers. Our findings, which exemplify the equivalent or slightly superior performance of female surgeons, highlight the need for more equitable opportunities for female surgeons.

Possible Explanation for the Findings

There are several potential mechanisms that could explain why female surgeons exhibited a lower patient mortality than male surgeons. First, it is possible that female surgeons may be more compliant with clinical guidelines,^9,10 deliver more patient-centered care, and exhibit superior communication skills compared with male surgeons. Although evidence regarding differential practice patterns between female and male surgeons is limited, one study found that patients treated by female surgeons were more likely to receive evidence-based care (defined as adjuvant radiotherapy after BCS).¹⁰ Existing evidence showing that female primary care physicians are more likely to provide guideline-concordant care and communicate better also support this hypothesis.^62–64 Research indicates that for medical care, patients of physicians who adhere to guidelines generally experience better outcomes than patients of physicians less likely to adhere to guidelines.⁶⁵ Research has also shown that hospitals that adhere to guidelines more exhibit better outcomes among patients undergoing surgery.^66,67 Although it remains unknown as to whether surgeons who adhere to guidelines show better outcomes, it is possible that differences in guideline concordance between female and male surgeons may explain our findings.

Second, research in economics and psychology suggests that women are generally more risk-averse than men,^68,69 which also may influence decision-making processes in surgical care that affect patient outcomes. While no study clarified the details of practicing pattern among female surgeons for preoperative and postoperative care, female surgeons may be more risk-averse and deliberately manage surgical risks, including addressing preexisting comorbidities before surgery and maintaining vigilant postoperative observation. Third, female surgeons may be more willing to collaborate with other team members, such as nurses, than male surgeons, which may avert scenarios that could otherwise result in the “failure to rescue.”⁷⁰ Fourth, female surgeons may have better surgical knowledge than male surgeons, as reported in a relatively small study of medical students showing that female students completed tests of basic surgical skills more efficiently and had higher scores on tests of theoretical surgical knowledge compared with male students.⁷¹ Finally, it is also possible that the observed difference in patient mortality may not solely be attributed to the surgeons’ gender, but also to the health care system to which they are affiliated. An extensive body of research on medical mistakes suggests that systems, rather than individual practitioners, tend to offer stronger explanations for undesirable outcomes in health care.^72,73 It could be the case that female surgeons often operate in environments that adhere closely to guidelines, and offer a better surgical skill training, which could potentially result in improved surgical results.

Previous studies have found that female surgeons face several obstacles in choosing their careers and acquiring surgical proficiency, including an imbalance in the distribution of surgical cases assigned to female versus male surgeons during their training.^13,52 For example, a study from the United Kingdom reported that female medical students are advised not to choose surgical careers and are subjected to sexual discrimination.¹³ As another example, Foley et al⁷⁴ reported differences based on gender in experience with robotic surgery among male and female trainees in colorectal surgery training programs, with females having fewer opportunities to operate the consoles and complete procedures. Notably, the same study reported that male supervisors offered fewer opportunities for console participation to female residents compared with male residents, whereas female supervisors provided an equal number of opportunities to use the console to both female and male trainees. These obstacles might set a higher entry standard for women aiming to join the surgical profession compared with their male counterparts. As a result, the existing population of female surgeons may exhibit a relatively higher level of expertize, determination, and meticulousness, which consequently contributes to the superior outcomes observed among female surgeons in our study. Given the recent surge in the number of female surgeons and possible change in their characteristics, it is plausible that there will be a shift in our outcomes in the future.

There are several reasons as to why we did not observe difference in readmission and complication rates between female and male surgeons. First, compared with the mortality which included 5 million patients, the sample size for the analyses of readmission and complication rates was smaller, potentially limiting the statistical power to detect small differences. Second, the certainty of the evidence was “very low” for the analyses of readmission and complication rates; the potential bias may explain null findings for these outcomes. Last, patient mortality and readmission/complication rates may be reflecting different aspects of surgeons’ practice patterns. For example, a lower patient mortality rate for female surgeons could be attributed not only to their superior surgical skills but also to their overall better management of surgical patients, such as improved preoperative and postoperative care. However, this difference may be less noticeable concerning complication and readmission rates.

Comparison With Other Studies

To our knowledge, this is the first meta-analysis that compared the surgical outcomes of patients treated by female versus male surgeons. Our findings were largely consistent with existing large, observational studies. For example, previous literature analyzed the nationally representative sample of older Americans who underwent 1 of 20 surgical procedures (n=892,187) and found that female surgeons have a lower patient mortality than male surgeons for elective surgeries, but no difference was observed for nonelective surgeries.¹⁴ In addition, Wallis et al² studied patients who underwent 1 of 12 surgical procedures in Ontario, Canada (n=1,159,687), and reported similar findings.

Limitations

This study has limitations. First, as is the case with any observational studies, unmeasured confounding may exist. In particular, while a significant proportion of the data was derived from studies that adjusted for potential confounders—such as surgeon age and surgical volume; and patient age, sex/gender, and comorbidities—the presence of unmeasured and residual confounders, such as surgical complexity or disease stage, remains possible. However, it is important to note that unmeasured confounding is unlikely to explain our findings for the analyses of emergent surgeries. This is because, in the context of emergency surgeries, surgeons are unlikely to select their patients, and patients are also unlikely to select their surgeons. Therefore, patients are plausibly “quasi-randomized” to surgeons based on the timing of when they required a surgical procedure. Our findings that female surgeons exhibit lower patient mortality rates not only for elective surgeries but also for emergency surgeries (Supplemental Digital Content 1, Fig. 6, http://links.lww.com/SLA/F109) indicate that these findings could not be explained by unmeasured confounding. Second, the certainty of evidence for readmissions and complication was very low; therefore, the results for readmission and complication rates should be interpreted with caution. Third, most of the studies included in our analysis relied on self-reported data to identify the gender of patients and surgeons. This may lead to misclassification of this variable, especially for patients and surgeons who are transgender. Nevertheless, given that the estimated prevalence of transgender and gender nonconforming individuals ranges from 0.1% to 2% in the general population,⁷⁵ a misclassification is unlikely to substantially impact the overall outcome. Finally, a significant proportion of the synthesized results were derived from samples in North America. Other areas included in our meta-analysis were European countries, Taiwan, and Japan. The proportion of female surgeons, surgical training, and how surgical care is provided may vary substantially among the countries, and therefore, the findings from our meta-analysis might not be generalizable to health systems in countries that were not included in our analysis.

CONCLUSIONS

Our meta-analysis on 15 studies found that patients treated by female surgeons had a small but statistically significantly lower postoperative mortality and similar readmission and complication rates, compared with those treated by male surgeons. These findings support ongoing efforts to recruit and retain women in surgery, as well as to better understand the differences in the processes of care that contribute to these outcomes.

Supplementary Material

sla-280-945-s001.docx ^{(6.6MB, docx)}