Changes in Facility Share of Medicaid-insured Patients With Urologic Cancers Following Implementation of the Patient Protection and Affordable Care Act.

OBJECTIVE: To examine Medicaid-insurance acceptance at facilities treating urologic cancers following implementation of the Affordable Care Act (ACA). METHODS: We conducted a retrospective, longitudinal study with a pre-post design. We accessed 2010-2017 data from the National Cancer Database, calculating the facility-level change in proportion of urologic cancer patients with Medicaid following implementation of the ACA. We used multivariable logistic regression to assess baseline clinical and demographic factors associated with changes in the proportion of patients at a facility insured through Medicaid. RESULTS: We identified 630 facilities, including 287 in Medicaid expansion states and 343 in non-expansion states associated with 436,082 urologic cancer patients. The mean facility-level change in proportion of patients with Medicaid was + 5.8% (95% CI 5.0%-6.5%) in expansion states versus + 0.6% (95% CI 0.2%-0.9%) in non-expansion states. There were 179 facilities that experienced a decrease in the post-ACA period, representing 13.6% of facilities in expansion states and 40.8% in non-expansion states (P <.001). Factors associated with a decrease in proportion of urologic cancer patients insured by Medicaid included non-expansion state status (OR 8.9, 95% CI 5.3-15.6, P <.001), higher baseline proportion of patients with Medicaid (highest quartile vs lowest: OR 4.6, 95% CI 2.3-9.4, P <.001) and high-income zip code (highest vs lowest quartile: OR 3.1, 95% CI 1.5-6.6, P <.001). CONCLUSION: Urologic cancer care for Medicaid-insured Americans remains unevenly distributed across cancer care centers, even in states that expanded coverage. Our findings suggest that this variation may reflect the effort of some facilities to reduce their financial exposure to increased numbers of Medicaid patients in the wake of ACA-supported state expansions.

Validation of the Prognostic Usefulness of the Gene Expression Profiling Test in Patients with Uveal Melanoma.

PURPOSE: To validate the prognostic usefulness of gene expression profile (GEP) testing in patients with uveal melanoma. To determine whether combining tumor size with the GEP classification provides additional prognostic value. DESIGN: Retrospective analysis. PARTICIPANTS: Patients with a diagnosis of choroidal melanoma examined at Yale New Haven Hospital; University of California, San Diego; and Memorial Sloan Kettering Cancer Center. METHODS: Patients' demographic and clinical data and tumor characteristics were collected. Univariate and multivariate Cox hazard regression analysis were used to assess the association between tumor characteristics and GEP classification with metastasis as an outcome. MAIN OUTCOME MEASURES: Metastasis-free survival (MFS). RESULTS: Of the 337 individuals included in the study, 87 demonstrated metastases. The mean follow-up time was 37.2 (standard deviation [SD], 40.2) months for patients with metastases and 55.0 (SD, 49.3) months for those without metastases. Tumors of larger thickness and GEP class 2 (vs. class 1) were associated significantly with increased risk of metastasis. Tumor thickness showed better prognostic usefulness than GEP classification (Wald statistic, 40.7 and 24.2, respectively). Class 2 tumors with a thickness of 7.0 mm or more were associated with increased risk of metastasis than tumors with a thickness of < 7.0 mm (hazard ratio [HR], 3.23; 95% confidence interval [CI], 1.61-6.51), whereas class 1 tumors with a thickness of 9.0 mm or more were associated with increased risk of metastasis than tumors with a thickness of < 9.0 mm (HR, 2.07; 95% CI, 0.86-4.99). No difference in MFS was found between patients with class 1A tumors compared with those with class 1B tumors (P = 0.8). Patients with class 2 tumors showed an observed 5-year MFS of 47.5% (95% CI, 36.0%-62.8%). CONCLUSIONS: Tumor size was the most significant predictor of metastasis and provided additional prognostic value independent of GEP classification. In addition, rates of metastasis for class 2 tumors were lower than estimates reported by Castle Bioscience, and no difference in rates of metastasis were found between class 1A and 1B tumors. This indicates that tumor size should be accounted for when relying on GEP for prognostication and that patients with GEP class 1A or 1B tumors may benefit from the same metastatic surveillance protocols. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Urology Practice Acquisitions by Private Equity Firms from 2011-2021.

INTRODUCTION: Private equity firms have recently acquired several large urology practices in the United States. As little is known about these acquisitions, we sought to characterize trends in urology practice consolidation. METHODS: We compiled urology practice acquisition data via financial databases, news outlets, practice websites, and Internet keyword search for the time period January 1, 2011 through March 15, 2021. For each acquisition, we determined the acquiring group, number of employed urologists, practice locations, and status of ancillary services (pathology, radiology, or surgery centers). We estimated workforce effects based on the 2019 American Urological Association workforce census. RESULTS: We identified 69 independent practice acquisitions in the study period, including 19 (28.4%) by hospital systems, 7 (10.4%) by multispecialty physician groups, 23 (34.3%) by urology practices, and 20 (29.9%) by private equity-backed platforms. Private equity firms initially targeted large urology practices (mean of 60.8±32.6 urologists) with ownership of ancillary services and consolidated local market share through acquisitions of smaller practices (mean of 15.9±14.5 urologists). As of March 2021, we estimate that 7.2% of private practice urologists in the U.S. were employed by one of 5 private equity-backed platforms; over 25% of all urologists practicing in New Jersey and Maryland are employed by a private equity-backed platform. CONCLUSIONS: Private equity acquisitions have accelerated to become a dominant form of urology practice consolidation in recent years and have achieved significant market influence in certain regions. Future research should assess the impact of private equity investment on practice patterns, health outcomes, and expenditures.