Date of Award

January 2023

Document Type

Thesis

Degree Name

Medical Doctor (MD)

Department

Medicine

First Advisor

Michael Leapman

Abstract

Background:While there has been much improvement in urologic cancer care, disparities in access and outcomes persist. These disparities can be attributed to several factors, including insurance status, access to quality healthcare, healthcare utilization, and sociodemographic determinants of health such as patient race. Disparities in patient access and surgical outcomes remain important areas of improvement in urologic oncologic outcomes. To develop strategies to improve healthcare access and understand the effects of sociodemographic factors on patient mortality outcomes, we characterized access to new urologic cancer care for patients with Medicaid insurance in the United States and we assessed the incidence and risk factors of mortality within 90 days of radical prostatectomy.

Methods: Using a secret shopper approach, we contacted a representative sample of facilities designated for cancer care in the United States. Trained volunteers posed as a family member seeking urologic cancer care using a simulated scenario of a parent with a new diagnosis of a localized kidney tumor. The primary study outcome was acceptance of Medicaid. In addition, we assessed facility characteristics associated with Medicaid acceptance relating to state Medicaid expansion status, Medicare reimbursement rates, and teaching hospital status using data from the Medicare & Medicaid Services Hospital General Information data file, the American Hospital Directory, and the American Medical Association of Colleges Organizational Characteristics Database. Separately, we conducted a retrospective analysis of The National Cancer Database, to identify patients undergoing radical prostatectomy from 2004-2017. We characterized the incidence of death within 90 days of surgery and described clinical, demographic and facility-level factors associated with the outcome, including surgical volume.Mixed effect logistic regression models incorporating a facility random intercept were constructed to examine factors associated with 90-day mortality.

Results: We sampled a total of 389 cancer-care facilities, of which 14.4% did not accept new Medicaid-insured patients. Medicaid acceptance was higher in facilities located in states that elected to expand Medicaid through the ACA versus non-expansion states (90.1% versus 77.4% respectively, p<0.001). Facilities accepting patients with Medicaid were in states with higher mean Medicaid-to-Medicare fee indexes (0.70 for Medicaid-accepting versus 0.65 for non-accepting facilities, p<0.001). In addition, Medicaid acceptance was higher in teaching hospitals versus non-teaching facilities (93.8% versus 83.4%, p=0.02), medical school affiliated (89.2% versus 79.7%, p=0.01). Within the NCDB we identified 305,262 patients who underwent prostatectomy in the study period. The incidence of 90-day mortality was 0.22%. Mixed effect logistic regression revealed that 90-day mortality was associated with Black race relative to White race (OR 1.91, 95 % CI 1.57-2.32), older age (1.08 OR per year, 95% CI 1.07-1.09), higher PSA (>20 mg/mL, OR 2.25, 95% CI 1.88-2.68), receipt of lymph node dissection (OR 1.26, 95% CI 1.05-1.51), residence in areas with lower proportion of high-school degrees (<82.4% with degrees, OR 1.43, 95% CI 1.11-1.82), higher Charlson-Deyo Morbidity Index (OR 1.50 95% CI 1.25-1.81 for score of 1; OR 2.72 95% CI 2.00-3.72 score of 2; OR 3.72 95% CI 2.36-5.88 for score of 3+) and surgical volume above median (OR 0.80, 95% CI 0.66-0.97).

Conclusion: We identified access disparities for patients with Medicaid insurance seeking urologic cancer care at centers. Additionally, 90-day mortality after radical prostatectomy is rare, but associated with hospital surgical volume and patient level factors including higher risk disease, higher comorbidity, and race. These findings highlight opportunities to improve the quality and timeliness of cancer care.

Comments

This thesis is restricted to Yale network users only. It will be made publicly available on 07/24/2024

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