Disparities in the receipt of robot-assisted radical prostatectomy: between-hospital and within-hospital analysis using 2009–2011 California inpatient data. Issue 4 (3rd May 2015)

• Record Type: Journal Article
• Authors: Kim, Jungyoon; ElRayes, Wael; Wilson, Fernando; Su, Dejun; Oleynikov, Dmitry; Morien, Marsha; Chen, Li-Wu
• Is Part Of: BMJ open. Volume 5:Issue 4(2015)
• Publication Date: 2015-05-03
• Subjects: HEALTH SERVICES ADMINISTRATION & MANAGEMENT -- Prostate disease < UROLOGY; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2014-007409
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objectives: Despite the rapid proliferation of robot-assisted radical prostatectomy (RARP), little attention has been paid to patient utilisation of this newest surgical innovation and barriers that may result in disparities in access to RARP. The goal of this study is to identify demographic and economic factors that decrease the likelihood of patients with prostate cancer (PC) receiving RARP. Design, setting and participants: A retrospective, pooled, cross-sectional study was conducted using 2009–2011 California State Inpatient Data and American Hospital Association data. Patients who were diagnosed with PC and underwent radical prostatectomy (RP) from 225 hospitals in California were identified, using ICD-9-CM diagnosis and procedure codes. Primary outcome measures: Patients&#39; likelihood of receiving RARP was associated with patient and hospital characteristics using the two models: (1) between-hospital and (2) within-hospital models. Multivariate binomial logistic regression was used for both models. The first model predicted patient access to RARP-performing hospitals versus non-RARP-performing hospitals, after adjusting for patient and hospital-level covariates (between-hospital variation). The second model examined the likelihood of patients receiving RARP within RARP-performing hospitals (within-hospital variation). Results: Among 20 411 patients who received RP, 13 750 (67.4%) received RARP, while 6661 (32.6%) received non-RARP. This study found significant differences in access to RARP-performing hospitals when race/ethnicity, income and insurance status were compared, after controlling for selected confounding factors (all p&lt;0.001). For example, Hispanic, Medicare and Medicaid patients were more likely to be treated at non-RARP-performing hospitals versus RARP-performing hospitals. Within RARP-performing hospitals, Medicaid patients had 58% lower odds of receiving RARP versus non-RARP (adjusted OR 0.42, p&lt;0.001). However, there were no significant differences by race/ethnicity or income within RARP-performing hospitals. Conclusions: Significant differences exist by race/ethnicity and payer status in accessing RARP-performing hospitals. Furthermore, payer status continues to be an important predictor of receiving RARP within RARP-performing hospitals.