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Figure.  Inclusion and Exclusion Step Flowchart
Inclusion and Exclusion Step Flowchart

GIM indicates general internal medicine; MRP, most responsible physician.

Table 1.  Characteristics of Female and Male Physicians
Characteristics of Female and Male Physicians
Table 2.  Patient Characteristics by Physician Gender
Patient Characteristics by Physician Gender
Table 3.  Association Between Physician Gender and Patient Outcomes
Association Between Physician Gender and Patient Outcomes
Table 4.  Association Between Physician Gender and Processes of Care
Association Between Physician Gender and Processes of Care
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    Jeoffry Gordon, MD, MPH | Retired
    Although it would be nice to know if quality of medical care varies by sex of the treating physician, this study does not establish that. To dwell on one technical point: Hospitalized patients treated by female physicians were shown a lower mortality, but this difference was not significant when adjusted by "physician characteristics." Only a limited number of characteristics were assessed: gender, specialty, years of experience, and medical school. It should be noted that specific medical schools were not studied and the overwhelming majority of physicians went generically to Canadian medical schools. It should be noted that evidently no surgical hospital patients were included but the article does not mention this issue.

    For me the most striking finding of the study is that hospital outcomes were worse the longer the admitting physician had been out of training (a confounding factor in the article). In some sense this is counterintuitive, but the data show an important insight that familiarity with up-to-date medical technology and technique may be more important than accrued clinical experience. This is an important observation and should have been in the title of the article. Interestingly, there is no analysis of outcomes by sex for medical school cohorts. Thus no exploration is made of the fact that the relatively recent increase in females admitted to medical school may have had an artifactual, confounding impact on outcomes by MD sex.

    Unfortunately all this is lost on media reports about the article which in general tout that female doctors are better (as is much discussed in the article to the detriment of these other considerations).
    CONFLICT OF INTEREST: None Reported
    READ MORE
    Original Investigation
    July 16, 2021

    Variations in Processes of Care and Outcomes for Hospitalized General Medicine Patients Treated by Female vs Male Physicians

    Author Affiliations
    • 1McMaster University, Hamilton, Ontario, Canada
    • 2St Michael’s Hospital, Toronto, Ontario, Canada
    • 3Unity Health Toronto, Toronto, Ontario, Canada
    • 4Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
    • 5University of Toronto, Ontario, Canada
    • 6Women’s College Hospital, Ontario, Canada
    JAMA Health Forum. 2021;2(7):e211615. doi:10.1001/jamahealthforum.2021.1615
    Key Points

    Question  Is physician gender associated with mortality and other patient outcomes in a general internal medicine inpatient setting?

    Findings  In this cross-sectional study of 171 625 hospitalized patients, patients cared for by female physicians had lower in-hospital mortality after adjustment for hospital and for patient characteristics, but this was no longer statistically different after adjustment for physician characteristics.

    Meaning  The lower mortality rate in patients cared for by female physicians may be partially explained by differences in physician characteristics.

    Abstract

    Importance  Hospitalized medical patients cared for by female physicians may have decreased mortality rates compared with patients of male physicians. However, this association has yet to be assessed outside of the US, and little is known about factors that may explain this difference.

    Objective  To determine whether mortality, other hospital outcomes, and processes of care differed between the patients cared for by female and male physicians.

    Design, Setting, and Participants  This retrospective cross-sectional study included patients admitted to general medical wards at 7 hospitals in Ontario, Canada, between April 1, 2010, and October 31, 2017. The association of physician gender with patient outcomes was examined while adjusting for hospital fixed effects, patient characteristics, physician characteristics, and processes of care. All patients were admitted to a general internal medicine service through the emergency department and were cared for by a general internist or family physician-hospitalist. Patients were excluded if length of stay was greater than 30 days or if the attending physician cared for less than 100 hospitalized general medicine patients over the study period. Statistical analyses were performed from October 15, 2020, to May 8, 2021.

    Main Outcomes and Measures  In-hospital mortality, length of stay, intensive care unit admission, 30-day readmissions, and process-of-care measures (blood tests, medications, imaging, endoscopy, and interventional radiology services).

    Results  A total of 171 625 hospitalized patients with a median age of 73 years (interquartile range, 56-84 years) were included (84 221 men [49.1%], 87 402 women [50.9%], and 2 patients with unspecified sex). Patients were cared for by 172 attending physicians (54 female physicians [31.4%] and 118 male physicians [68.6%]). In fully adjusted models, female physicians ordered more imaging tests, including computed tomography (adjusted difference, −1.70%; 95% CI, −2.78% to −0.61%; P = .002), magnetic resonance imaging (−0.88%; 95% CI, −1.37% to −0.38%; P = .001), and ultrasonography (−1.90%; 95% CI, −3.21% to −0.59%; P = .005). Patients treated by female physicians had lower in-hospital mortality (2256 of 46 772 patients [4.8%] vs 6452 of 124 853 patients [5.2%]). This difference persisted after adjustment for patient characteristics but was no longer statistically different after adjustment for other physician characteristics (adjusted difference, 0.29%; 95% CI, −0.08% to 0.65%; P = .12). The difference was similar after further adjustment for processes of care.

    Conclusions and Relevance  In this cross-sectional study of patients admitted to general medical units in Canada, patients cared for by female physicians had lower mortality rates than those treated by male physicians, adjusting for patient characteristics. This finding was nonsignificant after adjustment for other physician characteristics.

    Introduction

    A 2017 study of patients admitted to internal medicine wards in the US noted that those cared for by female physicians had a lower 30-day mortality rate.1 This finding added to prior evidence, largely from primary care settings, of differences in practice patterns between female and male physicians. Specifically, female physicians are more likely to provide preventive care,2-9 adhere to clinical guidelines,10-13 take a patient-centered approach,14-16 perform better on qualifying examinations,17 and spend more time in direct patient care for lower remuneration.18 However, to our knowledge, the difference in patient mortality between female and male physicians has not been evaluated outside of the US, and little is known about what factors may be contributing to this difference in outcomes.

    There is a dearth of research examining sex and gender differences in processes of care, which are defined as “technical interventions and interpersonal interactions between users and members of a healthcare system”19(p1613) and include the physician’s diagnostic and therapeutic actions.20 Our study seeks to improve the understanding of differences between male and female physicians in the processes of care and patient outcomes. We hypothesize that female physicians perform more diagnostic tests than male physicians, which may explain a lower patient mortality rate.

    We examined inpatients from the General Medicine Inpatient Initiative (GEMINI) retrospective cohort, which involves 7 hospitals in the greater Toronto area.21,22 Our study objectives were to (1) examine differences in blood tests, imaging tests, and medications ordered by male and female physicians; (2) determine whether female and male physicians have differences in major patient outcomes, including mortality; and (3) assess whether patient characteristics, physician characteristics (eg, specialty, years of experience), or processes of care explain any observed differences in outcomes.

    Methods
    Design and Setting

    This was a cross-sectional study of patients from the GEMINI cohort, a multicenter retrospective study that includes patient data from hospital sites associated with the University of Toronto in Ontario, Canada, from April 1, 2010, to October 31, 2017. The participating organizations are St Michael’s Hospital, Sinai Health System (Mount Sinai Hospital), Sunnybrook Health Sciences Centre, Trillium Health Partners (Credit Valley and Mississauga hospitals), and the University Health Network (Toronto General Hospital and Toronto Western Hospital). These organizations are independent care providers with distinct governance and health records.21 Ethics approval was obtained from the research ethics boards at all participating hospitals before the collection of retrospective data. Participant consent was waived as the data were deidentified before use. This study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.23

    Inclusion and Exclusion Criteria

    Our study included patients who were admitted to or discharged from a general medical service from April 1, 2010, to October 31, 2017.21 Only patients admitted to the general internal medicine (GIM) ward via the emergency department were included; we excluded patients admitted from any other source to avoid elective admissions or interhospital transfers for which physician assignment may be nonrandom. For emergency department admissions, the Canadian Institute of Health Information (CIHI) database retrospectively assigns admitted patients to a most responsible physician (MRP). The MRP is defined as the attending physician who is most “responsible for the patient’s care or who cared for the patient the longest” during their hospital stay,24(p17) and this definition is widely applied in epidemiological studies.25-28 We excluded hospitalizations if the MRP’s gender was not recorded or if patient length of stay (LOS) in the hospital was more than 30 days (as longer stays often lead to multiple physician handoffs).22 Physicians who cared for fewer than 100 patients over the study period in the GIM ward and patients admitted to nongeneralist specialty wards that existed at some hospitals (eg, poststroke care ward) were also excluded.

    Data Collection

    As described in detail elsewhere,21,29 patient data from hospital administrative sources were collected from hospitals as reported to the CIHI Discharge Abstract Database. Data extracted from electronic health records included laboratory tests, medical imaging, and in-hospital medication orders and were linked to hospital administrative data.

    All data pertaining to physician characteristics, including physician gender, years of practice, medical school, and specialty, were collected from the publicly accessible College of Physicians and Surgeons of Ontario (CPSO) website.30 Sex and gender are distinct, but often overlapping, identifiers.31 We use the term gender in reference to physicians because the CPSO categorizes gender as male or female based on physician self-classification upon application for a medical license.32

    Measures

    Baseline patient characteristics in descriptive statistics and multivariable adjustment include patient age at admission (linear in models), patient sex, time of admission (weekday vs weekend and daytime vs nighttime), fiscal year of admission (linear), and admitting hospital (categorical). We included the patient’s most responsible diagnosis, grouped into major disease categories based on the Clinical Classifications Software.33 We measured comorbidity using the Charlson Comorbidity Index score (0, 1, 2+), where higher numerical scores estimate a decreased 10-year survival rate.34 Severity of illness was assessed using the Laboratory-Based Acute Physiology Score (linear), a validated predictor of inpatient mortality.35,36 We also included prior admission to 1 of the 7 GIM hospital sites in the previous 30 days. Baseline characteristics were compared using standardized mean differences (mean difference between female and male physicians, divided by the SD across all admissions), where values greater than 0.1 are considered meaningful markers of imbalance.37 A multivariate Mahalanobis distance-based method was used for multinomial outcomes.38

    Physician characteristics included in descriptive statistics and multivariable analysis were physician gender, physician specialty (family medicine vs internal medicine), years of experience (defined as years in independent medical practice at time of encounter and modeled linearly), and graduating medical school location (categorized as Canadian, US, or international).

    Outcomes

    The primary outcome was in-hospital patient mortality; secondary outcomes included intensive care unit admission, hospital LOS, cost of care, and readmission to GIM at 1 of the GEMINI hospitals within 30 days of discharge. Processes of care can encompass a wide range of physician activity39,40; we included commonly ordered laboratory tests,21 imaging,21 and medications41,42 available in electronic medical records. These variables included routine blood tests ordered per patient day; acute blood tests ordered; imaging tests (ie, x-ray, computed tomography [CT] scan, magnetic resonance imaging [MRI], and ultrasound), interventional radiology procedures; in-hospital endoscopy; transfusions; and select medications ordered in the hospital (ie, antimicrobials, anticoagulants, benzodiazepines, and antipsychotics) that carry a substantial risk of adverse events in a GIM population.43-45 A detailed description of the medications included is available in eTable 10 in the Supplement. Data on blood transfusions were derived from blood bank orders or CIHI-reported fields, depending on availability by site.

    To estimate costs of hospitalization across study sites and years, we used the CIHI Resource Intensity Weight46 for each patient admitted and multiplied this value by the annual cost per weighted case using the Ontario Cost Distribution Methodology.47 By accounting for patient age, comorbidities, and diagnosis at discharge, this method provides an estimation in Canadian dollars of the average amount of hospital resources used for each hospitalization but does not include fee-for-service physician billing.48

    Statistical Analysis

    A key assumption applied in this analysis was that nonelective admissions from the emergency department to internal medicine wards were assigned in a quasirandomized process to the physician who was on call for general medical admissions. This process implies that patient characteristics should be balanced between female and male physicians within each hospital at the start of the admission process and that any differences in processes of care and clinical outcomes may then be related to differences in physician practice.22 This assumption was an underlying principle applied in the study by Tsugawa and colleagues,1 and it has been tested rigorously in GEMINI.21,22

    Following the approach used by Tsugawa and colleagues,1 we used generalized linear models to estimate the association of physician gender with patient outcomes and processes of care with SEs adjusted for clustering of patients within physicians. We used logistic regression for binary outcomes (in-hospital death, intensive care unit admission, 30-day readmission, use of advanced imaging, endoscopy, interventional radiology, and transfusion and medication orders); linear regression for log-transformed in-hospital costs; and negative binomial regression for LOS and routine blood tests per day (with an offset for LOS). A staged multivariable modeling approach was used. Model 1 included physician gender and hospital fixed effects. Hospital fixed effects enable an effective comparison of female and male physicians practicing within different hospitals.1 Model 2 added patient factors, model 3 added physician characteristics, and model 4 added processes of care. Additionally, we examined the effect of adjusting for processes of care without physician characteristics included. For differences of interest, marginal standardization was used to estimate adjusted prevalence of outcome and process variables by physician gender.49 We tested for collinearity by calculating generalized variance inflation factors, which were fewer than 2 for all variables in the fully specified models.

    Multiple sensitivity analyses were performed to assess the robustness of our findings. First, a more restrictive cohort was used in which the same physician was the MRP, the admitting physician, and discharging physician. We used this model to increase the likelihood that a patient was treated by the same physician across their entire stay. A second sensitivity analysis excluded patients receiving palliative care as defined by the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision Canada code Z515. Third, we examined the differences in in-hospital mortality among cohorts including only female patients or only male patients in order to investigate whether the physician gender association differed by the sex of the patient. Fourth, we included models adjusting for hospital, patient characteristics, and physician years of experience to evaluate whether years of experience was sufficient to attenuate mortality differences. Fifth, we repeated the models of the main analysis with physician years of experience as a categorical variable and also as a linear variable with quadratic and cubic terms. Statistical analyses were performed from October 15, 2020, to May 8, 2021, using R software, version 4.0.2 (R Core Team). All P values were 2-sided, and P < .05 was considered significant.

    Results

    From an initial 228 450 hospitalizations in the GEMINI database, 171 625 hospitalized patients cared for by 172 MRPs were included in this study on the basis of the inclusion and exclusion criteria (Figure). The median patient age was 73 years (interquartile range [IQR], 56-84 years); 84 221 (49.1%) were men, 87 402 (50.9%) were women, and 2 had no sex specified. The proportions of female and male physicians in the study (54 female physicians [31.4%] and 118 male physicians [68.6%]) were not significantly affected by any of the inclusion or exclusion steps. The proportion of female physicians at each hospital ranged from 23% to 38%. The characteristics of the 54 female and 118 male physicians are presented in Table 1. Median duration in practice was 4.3 years (IQR, 2.5-11.5 years) for female physicians and 7.4 years (IQR, 3.3-16.4 years) for male physicians. No significant differences were noted between female and male physicians in location of medical school training, specialty, or hospital of practice. Patient characteristics were largely balanced between female and male physicians, with standardized differences less than 0.3 for all characteristics (Table 2). Fiscal year of admission showed an increased proportion of patients attributed to female physicians in more recent years (eTable 1 in the Supplement).

    Table 3 depicts the differences in hospital outcomes by physician gender. The in-hospital mortality rate was lower among patients treated by female physicians compared with those cared for by male physicians (unadjusted rates, 2256 of 46 772 [4.8%] vs 6452 of 124 853 [5.2%]). The mortality difference persisted after adjustment for hospital fixed effects (adjusted odds ratio [AOR], 1.11; 95% CI, 1.01-1.23; P = .04) and patient baseline characteristics (AOR, 1.12; 95% CI, 1.01-1.24; P = .03). The adjusted mortality was 4.7% for patients of female physicians and 5.2% for those of male physicians (risk difference [RD], 0.47%; 95% CI, 0.03%-0.9%; P = .03). This difference was no longer significant after adjustment for physician characteristics (RD, 0.29%; 95% CI, –0.08% to 0.65%; AOR, 1.07; 95% CI, 0.99-1.17; P = .12). The estimate was not further attenuated after adjustment for processes of care (AOR, 1.07; 95% CI, 0.99-1.17; P = .10). Additionally, without adjusting for physician characteristics, adjusting for processes of care did not attenuate the mortality difference (AOR, 1.13; 95% CI, 1.03-1.24; P = .01) (eTable 2 in the Supplement). Patients of female physicians had a higher median cost per admission ($4694.50; IQR, $2587.60-$8727.10 vs $4386.90; IQR, $2390.00-$8305.30), which persisted in all adjusted models (fully adjusted effect, −3.44%; 95% CI, −5.08% to −1.77%; P < .001). Although the unadjusted median LOS was identical for female and male physicians, patients of female physicians had higher LOS in adjusted models (fully adjusted rate ratio, 0.98; 95% CI, 0.96-0.99; P = .006). Differences in intensive care unit admission and 30-day readmission rates were not significant.

    Processes of care are presented in Table 4. Female physicians ordered more imaging tests than male physicians (CT, 25 615 of 46 772 patients [54.8%] vs 64 868 of 124 853 patients [52.0%]; MRI, 5202 patients [11.1%] vs 12 688 patients [10.2%]; and ultrasound, 14 832 patients [31.7%] vs 36 195 patients [29.0%]). For CT, MRI, and ultrasound, this difference persisted in all adjusted models (CT AOR, 0.93; 95% CI, 0.89-0.97; P = .002; MRI AOR, 0.90; 95% CI, 0.85-0.96; P = .001; and ultrasound AOR, 0.91; 95% CI, 0.85-0.97; P = .005). The fully adjusted order rate for CT scans was 54.0% and 52.3% for female and male physicians, respectively (RD, −1.70%; 95% CI, −2.78% to −0.61%). For MRI, the adjusted rates were 11.1% vs 10.2% (RD, −0.88%; 95% CI, −1.37% to −0.38%]). For ultrasound, the adjusted rates were 31.1% vs 29.2% (RD, −1.90%; 95% CI, −3.21% to −0.59%). The use of x-ray, endoscopy procedures, interventional radiology procedures, blood transfusion, routine or acute blood tests, and medication orders did not differ significantly.

    Sensitivity Analyses

    When we included only those hospitalizations for which the MRP was also the attending and discharging physician, patients of female physicians had significantly lower mortality, which persisted in all adjusted models (AOR, 1.10; 95% CI, 1.01-1.19; P = .03) (eTable 3 in the Supplement). Processes of care findings were similar to the main model (eTable 4 in Supplement). In a second sensitivity analysis, we excluded palliative encounters (eTables 5 and 6 in the Supplement). Mortality decreased by greater than 50%, and the unadjusted difference between female and male physicians was significant (AOR, 1.09; 95% CI, 1.01-1.18; P = .02) and was attenuated after adjustment for physician characteristics, similar to the main model. Estimates of the association of physician gender in unadjusted models and models adjusting for patient characteristics were similar when limited only to male or female patients, and these associations were attenuated after adjustment for physician characteristics (eTable 7 in the Supplement). Models additionally adjusting for patient characteristics and physician years of experience demonstrated attenuation of the physician gender association as well (eTable 8 in the Supplement). This attenuation persisted whether years of experience was added as a linear term, categorical term, or quadratic and cubic terms (eTable 9 in the Supplement).

    Discussion

    In a Canadian population, we observed that hospitalized general medicine patients of female physicians had lower in-hospital mortality rates compared with their male counterparts. Specifically, the in-hospital mortality rate was 0.47% lower for patients of female physicians in the cohort after adjustment for hospital effects and patient characteristics. This finding is similar to the 0.43% adjusted 30-day mortality difference noted by Tsugawa et al1 in a US Medicare population. Similar to the study by Tsugawa and colleagues,1 we found that male physicians had more years of experience than female physicians and that adjusting for this variable and other physician characteristics attenuated the mortality difference associated with physician gender.

    We were able to account for many processes of care: routine and acute blood tests, invasive and noninvasive diagnostic imaging tests, and medications ordered by the MRP. We hypothesized that physician gender–based differences in care may explain a difference in patient mortality. The limited literature on physician gender-mediated differences in care suggests that female physicians may spend more time reading electronic health records50 and may prescribe certain medications with additional caution.51-53 Furthermore, evidence from previous studies suggests that female physicians perceive clinical risks more highly54,55 and, perhaps as a result, order more tests56,57 and request more referrals57,58 than their male counterparts. In line with this hypothesis, we found that female physicians ordered more diagnostic CT, MRI, and ultrasound imaging tests than male physicians. However, the frequency and type of diagnostic tests ordered by physicians did not attenuate the difference in mortality rate. These findings raise the question: what drives the lower mortality rate in patients of female physicians?

    The in-hospital mortality difference between patients of female and male physicians was attenuated after adjustment for other physician characteristics. Physician years of experience was the only physician characteristic in our model that differed significantly between male and female physicians, and greater years of experience was independently associated with increased patient mortality. Some suggest that physicians closer to their residency training are more up to date on clinical guidelines and more likely to follow evidence-based practice, which may improve patient outcomes.59 Recent studies in internal medicine reported that a longer period of time since medical school graduation60 and older physician age61 were significantly associated with increased patient mortality. This association may be diminished when physicians treat higher volumes of patients.60,61 The growing proportion of female physicians entering the Canadian workforce62 may help to explain our finding that the mortality difference was attenuated after adjusting for other physician characteristics.

    Gender-mediated behavioral differences that are difficult to measure through routinely collected electronic data may also play a role in explaining the mortality difference. Some studies have shown than female physicians are more likely than male physicians to provide patient-centered care,63 spend longer communicating with their patients,64 provide more nonverbal feedback,65 and show higher levels of empathic concern.66,67 Humanistic relationships with patients may enable increased patient disclosure of medical information65,68 and foster stronger relationships among health team members, thereby improving patient care. Furthermore, female physicians, on average,51-54 may obtain more frequent informal consultations with colleagues and be more focused on reading clinical research studies or reviewing a patient’s chart when making clinical decisions. Taken together, these differences in process may help to explain the modestly lower mortality rates among general medical patients treated by female physicians in ways that cannot be captured through electronic health records or administrative data.

    The results of this study raise pertinent questions regarding the factors contributing to physician gender-mediated differences in processes of care and patient outcomes. In interpreting these findings, we exercise caution to avoid perpetuating gender stereotypes. Female and male physicians may have been socialized to adhere to gender norms and expectations within a health care context,69,70 but such behavioral differences are modifiable and not fixed.71

    Limitations

    Our study had several limitations. First, we were restricted to reporting in-hospital deaths as opposed to 30-day mortality. Second, the 30-day readmission rate only accounted for readmissions to the 7 hospital sites included. In the greater Toronto area, 82% of readmissions are estimated to occur at the same hospital72; because our study included patients readmitted to 6 other local hospitals, our coverage of all readmissions was probably higher. Third, the designation of the MRP for each patient was an approximation, as it was common for more than 1 physician to be involved in the care of complex hospitalized patients. Our assumption that 1 physician provided most of the care may have either minimized or exaggerated our findings. We sought to reduce the possibility of transitions between physicians by only including patients whose total LOS was less than 30 days. In a sensitivity analysis in which the MRP, admitting physician, and discharging physician were the same, thereby limiting the possibility of patient handover, the mortality difference persisted (eTable 2 in the Supplement).

    Another limitation of our study was that we could not define physician gender beyond a binary framing of female and male. Furthermore, we could not include other relevant physician characteristics, such as race/ethnicity, religion, sexual orientation, and country of origin, because these variables were unavailable in the CPSO physician database. Using a more intersectional lens would better capture the complexities of physician identity and its role in patient care.73

    This study was also limited in its generalizability, as the care was provided by 172 physicians in 1 region in Canada. Although these data may not be representative of Canadian hospitals at large, our analysis did include GIM and hospitalist physicians working at both academic and community hospitals in urban and suburban areas.

    Conclusions

    This multisite, retrospective, cross-sectional study assessed the association of physician gender with processes of care and outcomes of patients hospitalized in Canadian GIM wards. Patients of female physicians had lower mortality than those of male physicians when adjusted for hospital and patient characteristics. However, this difference was nonsignificant after adjustment for other physician characteristics including age, years of experience, and location of medical school training. Future research should seek to validate these findings and explore additional processes of care and behaviors of physicians that may explain differences in patient mortality associated with physician gender.

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    Article Information

    Accepted for Publication: May 22, 2021.

    Published: July 16, 2021. doi:10.1001/jamahealthforum.2021.1615

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Sergeant A et al. JAMA Health Forum.

    Corresponding Author: Fahad Razak, MD, MSc, Li Ka Shing Knowledge Institute, 30 Bond St, Room 345, Toronto, ON M5B 1W8, Canada (fahad.razak@mail.utoronto.ca).

    Author Contributions: Ms Sergeant and Mr Saha had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Verma and Razak share senior authorship of this publication.

    Concept and design: Sergeant, Rochon, Verma, Razak.

    Acquisition, analysis, or interpretation of data: Sergeant, Saha, Shin, Weinerman, Kwan, Lapointe-Shaw, Tang, Hawker, Verma, Razak.

    Drafting of the manuscript: Sergeant, Razak.

    Critical revision of the manuscript for important intellectual content: Saha, Shin, Weinerman, Kwan, Lapointe-Shaw, Tang, Hawker, Rochon, Verma, Razak.

    Statistical analysis: Sergeant, Saha, Shin.

    Obtained funding: Verma, Razak.

    Administrative, technical, or material support: Sergeant, Shin, Verma, Razak.

    Supervision: Razak.

    Conflict of Interest Disclosures: Dr Hawker reported receiving a salary and research support as the Sir John and Lady Eaton Professor and Chair of Medicine, Department of Medicine, University of Toronto outside the submitted work. Dr Verma reported receiving personal fees from Ontario Health as a part-time employee outside the submitted work. Dr Razak reported receiving an award from the Mak Pak Chiu and Mak-Soo Lai Hing Chair in General Internal Medicine, University of Toronto outside the submitted work and being an employee of Ontario Health. No other disclosures were reported.

    Additional Contributions: We thank Sharon Straus, MD, MSc, and the GEMINI investigators for their contributions to this work. No one was financially compensated for their contributions.

    Additional Information: Ms Sergeant is an MD candidate for 2022. The development of the GEMINI data platform was supported by the Canadian Cancer Society, the Canadian Frailty Network, the Canadian Institutes of Health Research, the Canadian Medical Protective Council of Canada, Ontario Health, the St Michael’s Hospital Association Innovation Fund, the University of Toronto Department of Medicine, and in-kind support from partner hospitals and Vector Institute.

    References
    1.
    Tsugawa  Y, Jena  AB, Figueroa  JF, Orav  EJ, Blumenthal  DM, Jha  AK.  Comparison of hospital mortality and readmission rates for Medicare patients treated by male vs female physicians.   JAMA Intern Med. 2017;177(2):206-213. doi:10.1001/jamainternmed.2016.7875 PubMedGoogle ScholarCrossref
    2.
    Andersen  MR, Urban  N.  Physician gender and screening: do patient differences account for differences in mammography use?   Women Health. 1997;26(1):29-39. doi:10.1300/J013v26n01_03 PubMedGoogle ScholarCrossref
    3.
    Frank  E, Dresner  Y, Shani  M, Vinker  S.  The association between physicians’ and patients’ preventive health practices.   CMAJ. 2013;185(8):649-653. doi:10.1503/cmaj.121028 PubMedGoogle ScholarCrossref
    4.
    Frank  E, Harvey  LK.  Prevention advice rates of women and men physicians.   Arch Fam Med. 1996;5(4):215-219. doi:10.1001/archfami.5.4.215 PubMedGoogle ScholarCrossref
    5.
    Franks  P, Clancy  CM.  Physician gender bias in clinical decisionmaking: screening for cancer in primary care.   Med Care. 1993;31(3):213-218. doi:10.1097/00005650-199303000-00003 PubMedGoogle ScholarCrossref
    6.
    Franks  P, Bertakis  KD.  Physician gender, patient gender, and primary care.   J Womens Health (Larchmt). 2003;12(1):73-80. doi:10.1089/154099903321154167 PubMedGoogle ScholarCrossref
    7.
    Kruger  J, Shaw  L, Kahende  J, Frank  E.  Health care providers’ advice to quit smoking, National Health Interview Survey, 2000, 2005, and 2010.   Prev Chronic Dis. 2012;9:E130. doi:10.5888/pcd9.110340 PubMedGoogle Scholar
    8.
    Lurie  N, Slater  J, McGovern  P, Ekstrum  J, Quam  L, Margolis  K.  Preventive care for women. does the sex of the physician matter?   N Engl J Med. 1993;329(7):478-482. doi:10.1056/NEJM199308123290707 PubMedGoogle ScholarCrossref
    9.
    Ramirez  AG, Wildes  KA, Nápoles-Springer  A, Pérez-Stable  E, Talavera  G, Rios  E.  Physician gender differences in general and cancer-specific prevention attitudes and practices.   J Cancer Educ. 2009;24(2):85-93. doi:10.1080/08858190802664396 PubMedGoogle ScholarCrossref
    10.
    Kim  C, McEwen  LN, Gerzoff  RB,  et al.  Is physician gender associated with the quality of diabetes care?   Diabetes Care. 2005;28(7):1594-1598. doi:10.2337/diacare.28.7.1594 PubMedGoogle ScholarCrossref
    11.
    Berthold  HK, Gouni-Berthold  I, Bestehorn  KP, Böhm  M, Krone  W.  Physician gender is associated with the quality of type 2 diabetes care.   J Intern Med. 2008;264(4):340-350. doi:10.1111/j.1365-2796.2008.01967.x PubMedGoogle ScholarCrossref
    12.
    Baumhäkel  M, Müller  U, Böhm  M.  Influence of gender of physicians and patients on guideline-recommended treatment of chronic heart failure in a cross-sectional study.   Eur J Heart Fail. 2009;11(3):299-303. doi:10.1093/eurjhf/hfn041 PubMedGoogle ScholarCrossref
    13.
    Reid  RO, Friedberg  MW, Adams  JL, McGlynn  EA, Mehrotra  A.  Associations between physician characteristics and quality of care.   Arch Intern Med. 2010;170(16):1442-1449. doi:10.1001/archinternmed.2010.307 PubMedGoogle ScholarCrossref
    14.
    Bertakis  KD, Helms  LJ, Callahan  EJ, Azari  R, Robbins  JA.  The influence of gender on physician practice style.   Med Care. 1995;33(4):407-416. doi:10.1097/00005650-199504000-00007 PubMedGoogle ScholarCrossref
    15.
    Krupat  E, Rosenkranz  SL, Yeager  CM, Barnard  K, Putnam  SM, Inui  TS.  The practice orientations of physicians and patients: the effect of doctor-patient congruence on satisfaction.   Patient Educ Couns. 2000;39(1):49-59. doi:10.1016/S0738-3991(99)00090-7 PubMedGoogle ScholarCrossref
    16.
    Roter  DL, Hall  JA.  Physician gender and patient-centered communication: a critical review of empirical research.   Annu Rev Public Health. 2004;25:497-519. doi:10.1146/annurev.publhealth.25.101802.123134 PubMedGoogle ScholarCrossref
    17.
    Ferguson  E, James  D, Madeley  L.  Factors associated with success in medical school: systematic review of the literature.   BMJ. 2002;324(7343):952-957. doi:10.1136/bmj.324.7343.952 PubMedGoogle ScholarCrossref
    18.
    Ganguli  I, Sheridan  B, Gray  J, Chernew  M, Rosenthal  MB, Neprash  H.  Physician work hours and the gender pay gap—evidence from primary care.   N Engl J Med. 2020;383(14):1349-1357. doi:10.1056/NEJMsa2013804PubMedGoogle ScholarCrossref
    19.
    Campbell  SM, Roland  MO, Buetow  SA.  Defining quality of care.   Soc Sci Med. 2000;51(11):1611-1625. doi:10.1016/S0277-9536(00)00057-5 PubMedGoogle ScholarCrossref
    20.
    Donabedian  A.  The quality of care: how can it be assessed?   JAMA. 1988;260(12):1743-1748. doi:10.1001/jama.1988.03410120089033 PubMedGoogle ScholarCrossref
    21.
    Verma  AA, Guo  Y, Kwan  JL,  et al.  Patient characteristics, resource use and outcomes associated with general internal medicine hospital care: the General Medicine Inpatient Initiative (GEMINI) retrospective cohort study.   CMAJ Open. 2017;5(4):E842-E849. doi:10.9778/cmajo.20170097 PubMedGoogle ScholarCrossref
    22.
    Verma  AA, Guo  Y, Jung  HY,  et al.  Physician-level variation in clinical outcomes and resource use in inpatient general internal medicine: an observational study.   BMJ Qual Saf. 2021;30(2):123-132. doi:10.1136/bmjqs-2019-010425 PubMedGoogle Scholar
    23.
    von Elm  E, Altman  DG, Egger  M, Pocock  SJ, Gøtzsche  PC, Vandenbroucke  JP; STROBE Initiative.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.   Ann Intern Med. 2007;147(8):573-577. doi:10.7326/0003-4819-147-8-200710160-00010 PubMedGoogle ScholarCrossref
    24.
    Canadian Institute for Health Information. CIHI portal: DAD metadata dictionary. Accessed June 2, 2021. https://www.cihi.ca/sites/default/files/document/dad-metadata-dictionary-en_0.pdf
    25.
    Cujec  B, Quan  H, Jin  Y, Johnson  D.  Association between physician specialty and volumes of treated patients and mortality among patients hospitalized for newly diagnosed heart failure.   Am J Med. 2005;118(1):35-44. doi:10.1016/j.amjmed.2004.08.013 PubMedGoogle ScholarCrossref
    26.
    McAlister  FA, Youngson  E, Bakal  JA, Holroyd-Leduc  J, Kassam  N.  Physician experience and outcomes among patients admitted to general internal medicine teaching wards.   CMAJ. 2015;187(14):1041-1048. doi:10.1503/cmaj.150316 PubMedGoogle ScholarCrossref
    27.
    Jackevicius  CA, Tsadok  MA, Essebag  V,  et al.  Early non-persistence with dabigatran and rivaroxaban in patients with atrial fibrillation.   Heart. 2017;103(17):1331-1338. doi:10.1136/heartjnl-2016-310672PubMedGoogle ScholarCrossref
    28.
    Boom  NK, Lee  DS, Tu  JV.  Comparison of processes of care and clinical outcomes for patients newly hospitalized for heart failure attended by different physician specialists.   Am Heart J. 2012;163(2):252-259. doi:10.1016/j.ahj.2011.11.012 PubMedGoogle ScholarCrossref
    29.
    Verma  AA, Pasricha  SV, Jung  HY,  et al.  Assessing the quality of clinical and administrative data extracted from hospitals: the General Medicine Inpatient Initiative (GEMINI) experience.   J Am Med Inform Assoc. 2021;28(3):578-587. doi:10.1093/jamia/ocaa225 PubMedGoogle ScholarCrossref
    30.
    The College of Physicians and Surgeons of Ontario. Doctor search. Accessed 15 July, 2020. https://doctors.cpso.on.ca/?doctors
    31.
    Clayton  JA, Tannenbaum  C.  Reporting sex, gender, or both in clinical research?   JAMA. 2016;316(18):1863-1864. doi:10.1001/jama.2016.16405 PubMedGoogle ScholarCrossref
    32.
    College of Physicians and Surgeons of Ontario. CPSO data-sharing strategy: vision, governance, decision tool FAQ. Accessed December 5, 2020. https://www.cpso.on.ca/admin/CPSO/media/Documents/public/services/data-sharing-faq.pdf
    33.
    Agency for Healthcare Research and Quality. Clinical classifications software (CCS) for ICD-10-PCS (beta version). Accessed July 8, 2020. https://www.hcup-us.ahrq.gov/toolssoftware/ccs10/ccs10.jsp
    34.
    Quan  H, Li  B, Couris  CM,  et al.  Updating and validating the Charlson Comorbidity Index and score for risk adjustment in hospital discharge abstracts using data from 6 countries.   Am J Epidemiol. 2011;173(6):676-682. doi:10.1093/aje/kwq433 PubMedGoogle ScholarCrossref
    35.
    van Walraven  C, Escobar  GJ, Greene  JD, Forster  AJ.  The Kaiser Permanente inpatient risk adjustment methodology was valid in an external patient population.   J Clin Epidemiol. 2010;63(7):798-803. doi:10.1016/j.jclinepi.2009.08.020 PubMedGoogle ScholarCrossref
    36.
    Escobar  GJ, Greene  JD, Scheirer  P, Gardner  MN, Draper  D, Kipnis  P.  Risk-adjusting hospital inpatient mortality using automated inpatient, outpatient, and laboratory databases.   Med Care. 2008;46(3):232-239. doi:10.1097/MLR.0b013e3181589bb6 PubMedGoogle Scholar
    37.
    Austin  PC.  Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research.   Commun Stat Simul Comput. 2009;38(6):1228-1234. doi:10.1080/03610910902859574 Google ScholarCrossref
    38.
    Yang  D, Dalton  JE. A unified approach to measuring the effect size between two groups using SAS®. Accessed December 15, 2020. https://support.sas.com/resources/papers/proceedings12/335-2012.pdf
    39.
    DuBose  JJ, Inaba  K, Shiflett  A,  et al.  Measurable outcomes of quality improvement in the trauma intensive care unit: the impact of a daily quality rounding checklist.   J Trauma. 2008;64(1):22-27. doi:10.1097/TA.0b013e318161b0c8 PubMedGoogle Scholar
    40.
    Weiss  CH, Moazed  F, McEvoy  CA,  et al.  Prompting physicians to address a daily checklist and process of care and clinical outcomes: a single-site study.   Am J Respir Crit Care Med. 2011;184(6):680-686. doi:10.1164/rccm.201101-0037OC PubMedGoogle ScholarCrossref
    41.
    Giardina  C, Cutroneo  PM, Mocciaro  E,  et al.  Adverse drug reactions in hospitalized patients: results of the FORWARD (Facilitation of Reporting in Hospital Ward) study.   Front Pharmacol. 2018;9:350. doi:10.3389/fphar.2018.00350 PubMedGoogle ScholarCrossref
    42.
    Sera  L, McPherson  ML, Holmes  HM.  Commonly prescribed medications in a population of hospice patients.   Am J Hosp Palliat Care. 2014;31(2):126-131. doi:10.1177/1049909113476132 PubMedGoogle ScholarCrossref
    43.
    Woolcott  JC, Richardson  KJ, Wiens  MO,  et al.  Meta-analysis of the impact of 9 medication classes on falls in elderly persons.   Arch Intern Med. 2009;169(21):1952-1960. doi:10.1001/archinternmed.2009.357 PubMedGoogle ScholarCrossref
    44.
    Tamma  PD, Avdic  E, Li  DX, Dzintars  K, Cosgrove  SE.  Association of adverse events with antibiotic use in hospitalized patients.   JAMA Intern Med. 2017;177(9):1308-1315. doi:10.1001/jamainternmed.2017.1938PubMedGoogle ScholarCrossref
    45.
    Damen  NL, Baines  R, Wagner  C, Langelaan  M.  Medication-related adverse events during hospitalization: a retrospective patient record review study in the Netherlands.   Pharmacoepidemiol Drug Saf. 2017;26(1):32-39. doi:10.1002/pds.4037 PubMedGoogle ScholarCrossref
    46.
    Canadian Institute for Health Information. Resource indicators: DAD resource intensity weights and expected length of stay. Accessed December 6, 2020. https://www.cihi.ca/en/resource-indicators-dad-resource-intensity-weights-and-expected-length-of-stay
    47.
    Wodchis  W, Bushmeneva  K, Nikitovic  M, McKillop  I.  Guidelines on Person-Level Costing Using Administrative Databases in Ontario. University of Toronto; 2013.
    48.
    University of Manitoba. Concept: case mix groups (CMG™)—overview. Accessed December 6, 2020. http://mchp-appserv.cpe.umanitoba.ca/viewConcept.php?conceptID=1094
    49.
    Muller  CJ, MacLehose  RF.  Estimating predicted probabilities from logistic regression: different methods correspond to different target populations.   Int J Epidemiol. 2014;43(3):962-970. doi:10.1093/ije/dyu029 PubMedGoogle ScholarCrossref
    50.
    Tait  SD, Oshima  SM, Ren  Y,  et al.  Electronic health record use by sex among physicians in an academic health care system.   JAMA Intern Med. 2021;181(2)288-290. doi:10.1001/jamainternmed.2020.5036PubMedGoogle Scholar
    51.
    Rochon  PA, Gruneir  A, Bell  CM,  et al.  Comparison of prescribing practices for older adults treated by female versus male physicians: a retrospective cohort study.   PLoS One. 2018;13(10):e0205524. doi:10.1371/journal.pone.0205524 PubMedGoogle Scholar
    52.
    Lazkani  A, Delespierre  T, Benattar-Zibi  L,  et al.  Do male and female general practitioners differently prescribe chronic pain drugs to older patients?   Pain Med. 2015;16(4):696-705. doi:10.1111/pme.12659 PubMedGoogle ScholarCrossref
    53.
    Larue  F, Colleau  SM, Fontaine  A, Brasseur  L.  Oncologists and primary care physicians’ attitudes toward pain control and morphine prescribing in France.   Cancer. 1995;76(11):2375-2382. doi:10.1002/1097-0142(19951201)76:11<2375::AID-CNCR2820761129>3.0.CO;2-C PubMedGoogle ScholarCrossref
    54.
    Bogacheva  N, Kornilova  T, Pavlova  E.  Relationships between medical doctors’ personality traits and their professional risk perception.   Behav Sci (Basel). 2019;10(1):6. doi:10.3390/bs10010006 PubMedGoogle ScholarCrossref
    55.
    Lee  H, Tan  MK, Yan  AT,  et al; FREEDOM AF and CONNECT AF Investigators.  Association between patient and physician sex and physician-estimated stroke and bleeding risks in atrial fibrillation.   Can J Cardiol. 2019;35(2):160-168. doi:10.1016/j.cjca.2018.11.023PubMedGoogle ScholarCrossref
    56.
    Miró  Ò, Busca  P.  Emergency physician sex and emergency department resource use.   Eur J Emerg Med. 2017;24(4):277-283. doi:10.1097/MEJ.0000000000000345 PubMedGoogle ScholarCrossref
    57.
    Sood  R, Sood  A, Ghosh  AK.  Non-evidence-based variables affecting physicians’ test-ordering tendencies: a systematic review.   Neth J Med. 2007;65(5):167-177.PubMedGoogle Scholar
    58.
    Franks  P, Williams  GC, Zwanziger  J, Mooney  C, Sorbero  M.  Why do physicians vary so widely in their referral rates?   J Gen Intern Med. 2000;15(3):163-168. doi:10.1046/j.1525-1497.2000.04079.x PubMedGoogle ScholarCrossref
    59.
    Choudhry  NK, Fletcher  RH, Soumerai  SB.  Systematic review: the relationship between clinical experience and quality of health care.   Ann Intern Med. 2005;142(4):260-273. doi:10.7326/0003-4819-142-4-200502150-00008 PubMedGoogle ScholarCrossref
    60.
    Norcini  JJ, Boulet  JR, Opalek  A, Dauphinee  WD.  Patients of doctors further from medical school graduation have poorer outcomes.   Med Educ. 2017;51(5):480-489. doi:10.1111/medu.13276 PubMedGoogle ScholarCrossref
    61.
    Tsugawa  Y, Newhouse  JP, Zaslavsky  AM, Blumenthal  DM, Jena  AB.  Physician age and outcomes in elderly patients in hospital in the US: observational study.   BMJ. 2017;357:j1797. doi:10.1136/bmj.j1797 PubMedGoogle Scholar
    62.
    Lorello  GR, Silver  JK, Moineau  G, McCarthy  K, Flexman  AM.  Trends in representation of female applicants and matriculants in Canadian residency programs across specialties, 1995 to 2019.   JAMA Netw Open. 2020;3(11):e2027938. doi:10.1001/jamanetworkopen.2020.27938 PubMedGoogle Scholar
    63.
    Henderson  JT, Weisman  CS.  Physician gender effects on preventive screening and counseling: an analysis of male and female patients’ health care experiences.   Med Care. 2001;39(12):1281-1292. doi:10.1097/00005650-200112000-00004 PubMedGoogle ScholarCrossref
    64.
    Jefferson  L, Bloor  K, Birks  Y, Hewitt  C, Bland  M.  Effect of physicians’ gender on communication and consultation length: a systematic review and meta-analysis.   J Health Serv Res Policy. 2013;18(4):242-248. doi:10.1177/1355819613486465 PubMedGoogle ScholarCrossref
    65.
    Hall  JA, Roter  DL.  Do patients talk differently to male and female physicians? a meta-analytic review.   Patient Educ Couns. 2002;48(3):217-224. doi:10.1016/S0738-3991(02)00174-X PubMedGoogle ScholarCrossref
    66.
    Chaitoff  A, Sun  B, Windover  A,  et al.  Associations between physician empathy, physician characteristics, and standardized measures of patient experience.   Acad Med. 2017;92(10):1464-1471. doi:10.1097/ACM.0000000000001671PubMedGoogle ScholarCrossref
    67.
    Gleichgerrcht  E, Decety  J.  Empathy in clinical practice: how individual dispositions, gender, and experience moderate empathic concern, burnout, and emotional distress in physicians.   PLoS One. 2013;8(4):e61526. doi:10.1371/journal.pone.0061526 PubMedGoogle Scholar
    68.
    Roter  DL, Hall  JA, Aoki  Y.  Physician gender effects in medical communication: a meta-analytic review.   JAMA. 2002;288(6):756-764. doi:10.1001/jama.288.6.756 PubMedGoogle ScholarCrossref
    69.
    Linzer  M, Poplau  S.  Building a sustainable primary care workforce: where do we go from here?   J Am Board Fam Med. 2017;30(2):127-129. doi:10.3122/jabfm.2017.02.170014 PubMedGoogle ScholarCrossref
    70.
    Mast  MS, Kadji  KK.  How female and male physicians’ communication is perceived differently.   Patient Educ Couns. 2018;101(9):1697-1701. doi:10.1016/j.pec.2018.06.003 PubMedGoogle ScholarCrossref
    71.
    Butler  J.  Performative acts and gender constitution: An essay in phenomenology and feminist theory.   Theatre J. 1988;40(4):519-531. doi:10.2307/3207893 Google ScholarCrossref
    72.
    Staples  JA, Thiruchelvam  D, Redelmeier  DA.  Site of hospital readmission and mortality: a population-based retrospective cohort study.   CMAJ Open. 2014;2(2):E77-E85. doi:10.9778/cmajo.20130053 PubMedGoogle ScholarCrossref
    73.
    Fehrenbacher  AE, Patel  D.  Translating the theory of intersectionality into quantitative and mixed methods for empirical gender transformative research on health.   Cult Health Sex. 2020;22(sup1):145-160. doi:10.1080/13691058.2019.1671494PubMedGoogle ScholarCrossref
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