Women physicians receive lower Press Ganey patient satisfaction scores in a multicenter study of outpatient gynecology care

BACKGROUND

Emerging data suggest that patient satisfaction data are subject to inherent biases that negatively affect women physicians.

OBJECTIVE

This study aimed to describe the association between the Press Ganey patient satisfaction survey and physician gender in a multi-institutional study of outpatient gynecologic care.

STUDY DESIGN

This was a multisite, observational, population-based survey study using the results of Press Ganey patient satisfaction surveys from 5 unrelated community-based and academic medical institutions with outpatient gynecology visits between January 2020 and April 2022. The primary outcome variable was the likelihood to recommend a physician, and individual survey responses served as the unit of analysis. Patient demographic data were collected through the survey, including self-reported age, gender, and race and ethnicity (categorized as White, Asian, or Underrepresented in Medicine, which groups together Black, Hispanic or LatinX, American Indian or Alaskan Native, and Hawaiian or Pacific Islander). Bivariate comparisons between demographics (physician gender, patient and physician age quartile, patient and physician race) and likelihood to recommend were assessed using generalized estimating equation models clustered by physician. Odds ratios, 95% confidence intervals, and P values for these analyses are reported, and results were considered statistically significant at P<.05. Analysis was performed using SAS, version 9.4 (SAS Institute Inc., Cary, NC).

RESULTS

Data were obtained from 15,184 surveys for 130 physicians. Most physicians were women (n=95 [73%]) and White (n=98 [75%]), and patients were also predominantly White (n=10,495 [69%]). A little over half of all visits were race-concordant, meaning that both patient and physician reported the same race (57%). Women physicians were less likely to receive a topbox survey score (74% vs 77%) and in the multivariate model had 19% lower odds of receiving a topbox score (95% confidence interval, 0.69-0.95). Patient age had a statistically significant relationship with score, with patients aged ≥63 years having >3-fold increase in odds of providing a topbox score (odds ratio, 3.10; 95% confidence interval, 2.12-4.52) compared with the youngest patients. After adjustment, patient and physician race and ethnicity showed similar effects on the odds of a topbox likelihood-to-recommend score, with Asian physicians and Asian patients having lower odds of a topbox likelihood-to-recommend score when compared with White physicians and patients (odds ratio: 0.89 [95% confidence interval, 0.81-0.98] and 0.62 [95% confidence interval, 0.48-0.79], respectively). Underrepresented in medicine physicians and patients showed significantly increased odds of a topbox likelihood-to-recommend score (odds ratio: 1.27 [95% confidence interval, 1.21-1.33] and 1.03 [95% confidence interval, 1.01-1.06], respectively). The physician age quartile was not significantly associated with odds of a topbox likelihood-to-recommend score.

CONCLUSION

Women gynecologists were 18% less likely to receive top patient satisfaction scores compared with men in this multisite, population-based survey study using the results of Press Ganey patient satisfaction surveys. The results of these questionnaires should be adjusted for bias given that they provide data currently being used to understand patient-centered care.

Development and Validation of a Model for Opioid Prescribing Following Gynecological Surgery

IMPORTANCE

Overprescription of opioid medications following surgery is well documented. Current prescribing models have been proposed in narrow patient populations, which limits their generalizability.

OBJECTIVE

To develop and validate a model for predicting outpatient opioid use following a range of gynecological surgical procedures.

DESIGN, SETTING, AND PARTICIPANTS

In this prognostic study, statistical models were explored using data from a training cohort of participants undergoing gynecological surgery for benign and malignant indications enrolled prospectively at a single institution's academic gynecologic oncology practice from February 2018 to March 2019 (cohort 1) and considering 39 candidate predictors of opioid use. Final models were internally validated using a separate testing cohort enrolled from May 2019 to February 2020 (cohort 2). The best final model was updated by combining cohorts, and an online calculator was created. Data analysis was performed from March to May 2020.

EXPOSURES

Participants completed a preoperative survey and weekly postoperative assessments (up to 6 weeks) following gynecological surgery. Pain management was at the discretion of clinical practitioners.

MAIN OUTCOMES AND MEASURES

The response variable used in model development was number of pills used postoperatively, and the primary outcome was model performance using ordinal concordance and Brier score.

RESULTS

Data from 382 female adult participants (mean age, 56 years; range, 18-87 years) undergoing gynecological surgery (minimally invasive procedures, 158 patients [73%] in cohort 1 and 118 patients [71%] in cohort 2; open surgical procedures, 58 patients [27%] in cohort 1 and 48 patients [29%] in cohort 2) were included in model development. One hundred forty-seven patients (38%) used 0 pills after hospital discharge, and the mean (SD) number of pills used was 7 (10) (median [IQR], 3 [0-10] pills). The model used 7 predictors: age, educational attainment, smoking history, anticipated pain medication use, anxiety regarding surgery, operative time, and preoperative pregabalin administration. The ordinal concordance was 0.65 (95% CI, 0.62-0.68) for predicting 5 or more pills (Brier score, 0.22), 0.65 (95% CI, 0.62-0.68) for predicting 10 or more pills (Brier score, 0.18), and 0.65 (95% CI, 0.62-0.68) for predicting 15 or more pills (Brier score, 0.14).

CONCLUSIONS AND RELEVANCE

This model provides individualized estimates of outpatient opioid use following a range of gynecological surgical procedures for benign and malignant indications with all model inputs available at the time of procedure closing. Implementation of this model into the clinical setting is currently ongoing, with plans for additional validation in other surgical populations.

Venous thromboembolism prophylaxis in ambulatory cancer patients initiating chemotherapy: A cost-effectiveness analysis

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Background: Venous thromboembolism (VTE) is a major cause of morbidity and mortality among cancer patients. The Apixaban for the Prevention of Venous Thromboembolism in High-Risk Ambulatory Cancer Patients (AVERT) randomized controlled trial concluded that apixaban is a safe and effective option for VTE prophylaxis in high-risk ambulatory cancer patients initiating a new chemotherapy regimen. We performed a cost-effectiveness analysis from a health system perspective to determine if apixaban is a feasible prophylactic strategy for this population. Methods: A decision model was created from a third party payer perspective with a time horizon of 6 months, based on the treatment arms of the AVERT trial: (1) apixaban 2.5 mg twice daily for 6 months during active chemotherapy versus (2) placebo. Rates of VTE (4.2% apixaban vs 10.2% placebo), major bleeding (3.5% vs 1.8%) and clinically relevant nonmajor bleeding (CRNMB) (7.3% vs 5.5%) were modeled from the results of the AVERT trial. Cost estimates for treatments and events were obtained from wholesale drug costs, previously published studies and Medicare reimbursement data, and adjusted for inflation to 2018 dollars. Quality adjusted life years were calculated based on previously published utility values for the health states of advanced cancer, DVT, PE, and major bleeding events. An exploratory analysis was performed comparing prophylactic aspirin to no prophylaxis assuming a VTE rate of 7.2%, major bleeding rate of 3.5%, and CRNMB rate of 7.3%, based on the conservative assumptions that while aspirin may not be as effective at preventing VTE, the rate of clinically significant bleeding events would be similar or greater than that of apixaban. Results: In the base case model, apixaban is more costly and more effective than placebo (ICER = $5,013,190/QALY), and the cost per VTE prevented in the apixaban arm is $33,000. In one-way sensitivity analysis, if the cost of apixaban were reduced by 40% from $3,197 to $1,250 for a 6 month course, this could potentially be a cost-effective prophylaxis strategy with an ICER less than $100,000/QALY. In the alternative analysis, aspirin dominates placebo as it is both more effective and less expensive, and remains cost-effective even when the rate of clinically recognized bleeding with aspirin exceeds 15%. Conclusions: Further investigation into less costly prophylactic options such as generic direct oral anticoagulants (once available) and aspirin is warranted prior to broader implementation of a VTE prophylaxis strategy in this population.