Racial and ethnic disparities in robot-assisted radical prostatectomy: testing the physician-level segregated and differential treatment hypotheses.

BACKGROUND: Mechanisms underlying racial and ethnic disparities in robot-assisted radical prostatectomy (RARP) vs open radical prostatectomy (ORP) are unclear. We sought to test 2 physician-level hypotheses: 1) Segregated Treatment and 2) Differential Treatment. METHODS: This observational study used the New York State Cancer Registry linked to discharge records and included patients undergoing radical prostatectomy for localized prostate cancer from October 1, 2008 to December 31, 2018. For hypothesis 1, we examined the association between patient race and ethnicity and treating surgeon RARP use (high-use surgeons, low-use surgeons, and surgeons at non-RARP facilities). For hypothesis 2, we determined the association between patient race and ethnicity and receipt of RARP when matching on treating surgeon, age, year of procedure, and Gleason group. We explored the role of insurance in both analyses. RESULTS: This study included 18 926 patients (8.0% Hispanic, 16.9% non-Hispanic Black, 75.1% non-Hispanic White), with a mean age of 60.4 ± 7.1 years. Compared with non-Hispanic White patients, Hispanic and non-Hispanic Black patients had higher odds of being treated by low-RARP-use surgeons (odds ratio [OR] = 2.16, 95% confidence interval [CI] = 1.20 to 3.88; OR = 1.76, 95% CI = 1.06 to 2.94, respectively) and by surgeons at non-RARP facilities (OR = 4.19, 95% CI = 2.18 to 8.07; OR = 4.60, 95% CI = 2.58 to 8.23, respectively). In the matched cohorts, Hispanic and non-Hispanic Black patients were less likely to receive RARP than non-Hispanic White patients (OR = 0.78, 95% CI = 0.62 to 0.98; OR = 0.75, 95% CI = 0.57 to 1.00, respectively). These associations were partially attenuated after accounting for insurance. CONCLUSIONS: Racial and ethnic disparities in RARP use are related to patients being treated by different surgeons and treated differently by the same surgeons. Identifying and addressing multilevel barriers to equitable surgical treatment is needed to reduce disparities among prostate cancer patients.

Health Care Utilization Prior to Ovarian Cancer Diagnosis in Publicly Insured Individuals in New York State.

Background: Women with early-stage ovarian cancer may be asymptomatic or present with nonspecific symptoms. We examined health care utilization prior to ovarian cancer diagnosis to assess whether women with higher utilization differed in their prognosis and outcomes compared to women with low utilization. Methods: Using Medicaid, Medicare, and New York State Cancer Registry data for ovarian cancer cases diagnosed in 2006-2015, we examined selected health care visits that occurred 1-6 months before ovarian cancer diagnosis. We used multivariable-adjusted logistic regression to estimate odds ratios (ORs) and 95% CIs for associations of sociodemographic factors with number of prediagnostic visits and number of visits with tumor characteristics, and Cox proportional hazards regression to examine differences in survival by number of visits. Results: Women with >5 vs 0 prediagnostic visits were statistically significantly less likely to be diagnosed with distant vs local stage disease (OR, 0.72; 95% CI, 0.54-0.96), and women with 3-5 or >5 vs 0 prediagnostic visits had better overall survival (hazard ratio [HR], 0.88; 95% CI, 0.80-0.96 and HR, 0.90; 95% CI, 0.83-0.98, respectively). In stratified analyses, the association with improved survival was observed only among cases with regional or distant stage disease. Conclusions: Women with high health care utilization prior to ovarian cancer diagnosis may have better prognosis and survival, possibly because of earlier detection or better access to care throughout treatment. Women and their health care providers should not ignore symptoms potentially indicative of ovarian cancer and should be persistent in following up on symptoms that do not resolve.

Health Care Access Dimensions and Racial Disparities in End-of-Life Care Quality among Patients with Ovarian Cancer.

This study investigated the association between health care access (HCA) dimensions and racial disparities in end-of-life (EOL) care quality among non-Hispanic Black (NHB), non-Hispanic White (NHW), and Hispanic patients with ovarian cancer. This retrospective cohort study used the Surveillance, Epidemiology, and End Results-linked Medicare data for women diagnosed with ovarian cancer from 2008 to 2015, ages 65 years and older. Health care affordability, accessibility, and availability measures were assessed at the census tract or regional levels, and associations between these measures and quality of EOL care were examined using multivariable-adjusted regression models, as appropriate. The final sample included 4,646 women [mean age (SD), 77.5 (7.0) years]; 87.4% NHW, 6.9% NHB, and 5.7% Hispanic. In the multivariable-adjusted models, affordability was associated with a decreased risk of intensive care unit stay [adjusted relative risk (aRR) 0.90, 95% confidence interval (CI): 0.83-0.98] and in-hospital death (aRR 0.91, 95% CI: 0.84-0.98). After adjustment for HCA dimensions, NHB patients had lower-quality EOL care compared with NHW patients, defined as: increased risk of hospitalization in the last 30 days of life (aRR 1.16, 95% CI: 1.03-1.30), no hospice care (aRR 1.23, 95% CI: 1.04-1.44), in-hospital death (aRR 1.27, 95% CI: 1.03-1.57), and higher counts of poor-quality EOL care outcomes (count ratio:1.19, 95% CI: 1.04-1.36). HCA dimensions were strong predictors of EOL care quality; however, racial disparities persisted, suggesting that additional drivers of these disparities remain to be identified. SIGNIFICANCE: Among patients with ovarian cancer, Black patients had lower-quality EOL care, even after adjusting for three structural barriers to HCA, namely affordability, availability, and accessibility. This suggests an important need to investigate the roles of yet unexplored barriers to HCA such as accommodation and acceptability, as drivers of poor-quality EOL care among Black patients with ovarian cancer.

Using LexisNexis to Improve Social Security Number Information in the New York State Cancer Registry.

Background: Social Security numbers (SSNs) collected by cancer surveillance registries in the United States are used for patient matching, deduplication, follow-up, and linkage studies. However, due to various reasons, a small proportion of patient records have missing or inaccurate SSNs. Recently, New York State Cancer Registry (NYSCR) data have been linked to LexisNexis data to obtain patient demographic information, including SSNs. The current study evaluated the feasibility of using LexisNexis to improve SSN information in the NYSCR. Materials and Methods: Patients diagnosed during the years 2005-2016, aged 21 or older, in the NYSCR were linked to LexisNexis data. For the matched patients, LexisNexis returned demographic information, including SSNs as available. Percentages of patients without LexisNexis matches or without LexisNexis SSNs were examined by demographic characteristics. We used multivariate logistic regression analyses to further evaluate how patient demographic characteristics affected the likelihood of no LexisNexis matches or of no SSNs returned. For patients with SSNs returned, LexisNexis SSNs were compared with registry SSNs. If patients had prior missing registry SSNs or if LexisNexis SSNs were inconsistent with registry SSNs, we used Match*Pro to review and verify match status. Registry SSNs were updated for those confirmed to be true matches. Improvement of SSNs was assessed based on percentage reduction of missingness. Results: Of 1,396,078 patient records submitted for LexisNexis linkage, 1.6% were not matched. Among those matched, 1.5% did not have SSNs returned. Multivariate logistic regression analyses indicated that patients who were female, Black, Asian Pacific Islander (API), Hispanic, born outside the United States, deceased, or living in poorer census tracts were more likely to not have LexisNexis matches, or to not have SSNs returned. Among 47,271 patients with missing registry SSNs (3.4%), 26,895 had SSNs returned from LexisNexis, and 24,919 were confirmed to be true matches. After registry SSNs updates, the percentage of SSN missingness was reduced to 1.7%, with a larger absolute reduction observed among those who were younger than 60 years, API, or alive. For 33,057 patients with inconsistent SSNs, 11,474 were due to incorrect consolidations of SSNs in the registry, and those SSNs were subsequently fixed. Conclusions: LexisNexis is a valuable resource for improving the quality of SSN information in registries. Our results showed that the overall percentage of patients with missing SSNs was reduced from 3.4% to 1.7% after LexisNexis link-age, and SSNs that were initially incorrectly consolidated for some patients were also identified and subsequently fixed. However, the magnitude of SSN improvement varied by patient demographic characteristics. Data quality improvements often require resources, and this evaluation can assist registries with decisions related to similar efforts.