Raymond Fang

The AUA Quality Registry: Engaging Stakeholders to Improve the Quality of Care for Patients with Prostate Cancer

Introduction: Determining the most effective treatments for complex medical conditions requires robust clinical data. Clinical registries comprise real‐world observational data, which allow rapid assessment of the effectiveness of treatments and care processes. In 2014 the AUA (American Urological Association) launched the AQUA (AUA Quality) Registry, a national urological disease registry intended to measure and report health care quality and patient outcomes, and support health services and comparative effectiveness research. The initial focus of the registry is newly diagnosed prostate cancer. In July 2014 the AUA convened a Stakeholder Forum with more than 20 organizations interested in improving the quality of care provided to patients with prostate cancer. Methods: We discuss the rationale and need for the AQUA Registry, define quality of care for prostate cancer, prioritize data and information needs, and identify potential future uses for AQUA data beyond quality improvement. Results: AQUA data will provide high quality data on effective treatments. Good quality of care for prostate cancer focuses on patient centered outcomes based on current evidence. The highest priority data collection needs are patient characteristics, evaluation and intervention utilization data, clinical and patient reported outcomes, and cost and resource use. In the future the registry data may be used to fulfill urologist quality reporting requirements. The AQUA Registry will also allow for a range of local and national quality improvement, and health services research efforts driven by urologists. Conclusion: The AQUA Registry will provide an essential platform to improve health care quality and support the next generation of clinical urology research and policy initiatives.

The Near-future Impact of Retirement on the Urologic Workforce: Results From the American Urological Association Census

OBJECTIVE To assess self-perceived planned retirement patterns among urologists by using the American Urological Association Census Data. With an expanding elderly population and an aging urologic workforce, concerns regarding increased demand and decreased supply of urologists have been raised. MATERIALS AND METHODS We analyzed data from the 2014 American Urological Association Census, which is a specialty representative survey distributed to the urologists who practice in the United States. A total of 2204 census samples were weighted to represent 11,703 urologists who practiced in the United States in 2014. We compared urologists who are nearing retirement (within 5 years of their planned retirement) with the rest of urologists on their demographic, geographic, and practice characteristics. RESULTS Of the 11,703 practicing urologists in the United States, 3181 (95% confidence interval: 2884-3479) or 27% (95% confidence interval: 25%-30%) are nearing planned retirement. The mean age (standard deviation [SD]) of urologists nearing retirement (69, SD = 8.2) was older than nonretiring urologists (48, SD = 10.3), P < .01. Nearly double the proportion of nearing retirement urologists is found in nonmetropolitan compared to nonretiring urologists, 534 (17%) vs 782 (9%), P < .01, respectively. Urologists nearing retirement are more likely to practice general urology compared to nonretiring urologists, 2341 (74%) vs 5072 (60%), P < .01. Among urologists nearing retirement, 2155 (68%) of them still perform inpatient operations. CONCLUSION More than one-fourth of existing practicing urologists plan to retire in the next 5 years. General urology and urology practices outside of metropolitan areas will be impacted the most by the planned retiring workforce.

Burnout in Urology - Findings from the 2016 AUA Annual Census

Introduction: Physician burnout is linked to decreased job performance, increased medical errors, interpersonal conflicts and depression. Two recent multispecialty studies showed that urologists had the highest rate of burnout. However, these reports were limited by a low sample size of urologists (119). We aimed to establish the prevalence of urologist burnout and associated factors. Methods: In the 2016 American Urological Association Census, Maslach Burnout Inventory questions were randomly assigned to half of the respondents. Using matrix sampling, the 1,126 practicing urologists who received and answered the Maslach Burnout Inventory questions represented the entire 2,301 who completed the census. Burnout was defined as scoring high on the scales of emotional exhaustion or depersonalization. Demographic and practice variables were assessed to establish factors correlating to burnout. Results: Overall 38.8% of urologists met the criteria for burnout, with 17.2% scoring high for emotional exhaustion and 37.1% scoring high for depersonalization. Multivariate analysis revealed that urologist burnout is associated with more patient visits per week, younger age, being in a subspecialty area other than pediatric or oncology, in solo or multispecialty practice, practice size greater than 2 and greater number of work hours per week. Conclusions: These results suggest that the burnout rate for urologists is lower than previously reported, and are consistent with rates reported in other medical and surgical specialties. However, burnout continues to be an important issue. Greater workload correlated with increased burnout while other practice patterns appeared to be protective. It is critical to keep urologists in the workforce to help lessen projected shortages.

PNFBA-07 THE CURRENT MANAGEMENT OF PROSTATE CANCER IN THE UNITED STATES: DATA FROM THE AQUA REGISTRY

INTRODUCTION AND OBJECTIVES: Clinical registries increasingly provide physicians with a means for making data-driven decisions; however, few opportunities exist for patients to interact with registry data to support their own decisions. Herein, we report a webbased system that uses a prostate cancer (CaP) registry to provide newly-diagnosed men with a platform to understand treatment decisions made by others with similar characteristics. METHODS: The Michigan Urological Surgery Improvement Collaborative (MUSIC) is a consortium of 43 diverse urology practices that maintains a prospective registry of men with CaP. We developed a patient-facing, web-based tool that uses self-reported information and registry data to generate a personalized prediction of the likelihood of receiving a given treatment for CaP (Figure 1). The treatment predictions rely on registry data from 1/2011 to 12/2015 and were generated using a random forest machine learning model derived in a 2/3 random sample of the data. Predictive performance was measured in this derivation cohort (using 10-fold cross validation) and verified in the remaining data using multinomial area-under-the-curve (AUC) and calibration plots. RESULTS: Between the included dates, 11,456 men were diagnosed with CaP and 44.7% underwent prostatectomy, 22.0% surveillance, 19.5% radiation (RT), 8.8% androgen deprivation, and 3.6% watchful waiting (WW). The predictive model demonstrated consistent discrimination between treatments in the derivation and validation cohorts (AUCs 0.762 and 0.744, respectively). The predicted likelihood of receiving a given treatment was accurate for the most common treatment types in the derivation and validation cohorts although the model overpredicted the likelihood of receiving WW in both cohorts and RT in the validation cohort (Figure 2). CONCLUSIONS: With MUSIC registry data and machine learning methods, we were able to create a tool, designed for patients, that generates accurate predictions for most CaP treatments. As a newly diagnosed man considers treatment options, this tool will provide insight into choices made by similar men. Source of Funding: Blue Cross and Blue Shield of Michigan and grant 1T32-CA180984 from the National Cancer Institute.

MP76-10 BURNOUT IN UROLOGY: RESULTS FROM THE 2016 AUA CENSUS

INTRODUCTION AND OBJECTIVES: Few large series in the literature examine predictors of metastatic disease at time of testicular cancer diagnosis. We performed an analysis of the National Cancer Database (NCDB) to examine predictors of metastatic disease at the time of diagnosis and overall survival (OS) based on site of metastatic disease. METHODS: Utilizing the NCDB, 44,354 patients were identified with data available for metastatic disease at time of diagnosis and tumor histology. Metastases were stratified as either absent, lymph node only, lung, brain, liver or bone metastases. Demographic characteristics, socioeconomic indicators and tumor histology were compared using the chi-squared test. Univariate survival analysis was performed using the Kaplan Meier method. Multivariate survival analysis was performed using cox proportional hazard model. RESULTS: Mean age of diagnosis was 35 and mean follow-up was 53 months. On univariate analysis decreased age at diagnosis (p<0.001), non-white race (p1⁄40.002), uninsured status (p1⁄4<0.001), <

MP51-02 SLING REOPERATION RATES IN THE AUA QUALITY (AQUA) REGISTRY

38,000 annual income (p1⁄4<0.001), distance from treating hospital (p<0.001), and pure choriocarcinoma histology (166/202, 82%, p<0.001) were associated with metastases at time of diagnosis. 3,504 (7.9%) patients had metastatic disease at diagnosis. Kaplan Meier survival analysis showed significant differences in OS between metastatic sites at presentation, with 5 yr OS of 87% for lymph node only metastases compared to 48% OS in those with brain metastases (p<0.001). On multivariate analysis while controlling for age, race, insurance status, income, comorbidities, histology, receipt of chemotherapy, and primary tumor size, metastases to any site were associated with worsened survival compared to no metastases (referent): metastasis to lymph nodes (3.4, 95% CI: 2.70-4.50, p<0.001), lung (4.48, 95% CI: 3.69-5.43, p<0.001), liver (10.32, 95% CI: 6.78-15.7), bone (12.99, 95% CI: 7.93-21.29) and brain (14.4, 95% CI: 9.53-21.89). Private insurance status (0.48, 95% CI: 0.40-0.56, p<0.001) and income >

MP51-19 IS THERE A GENDER OR RACIAL PROMOTION DISPARITY IN ACADEMIC UROLOGY?

63,000 (0.72, 95% CI: 0.60-0.87, p1⁄40.001) were favorable predictors of OS. CONCLUSIONS: There are significant differences in OS dependent on site of metastases at time of testicular cancer diagnosis. Several sociodemographic factors likely contribute to likelihood of metastases at presentation as well. Further prospective studies are warranted to better characterize the impact of sociodemographic factors on metastases at presentation and to improve access to care in high-risk populations.