Erin A Blake1, Jeanelle Sheeder2, Kian Behbakht3, Saketh R Guntupalli3, Michael S Guy4. 1. Department of Obstetrics and Gynecology, University of Colorado, 12631 East 17th Avenue, Room 4007, Aurora, 80045, CO, USA. erin.blake@ucdenver.edu. 2. Department of Obstetrics and Gynecology, University of Colorado, 12631 East 17th Avenue, Room 4007, Aurora, 80045, CO, USA. 3. Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Colorado, Denver, CO, USA. 4. Division of Gynecologic Oncology and Advanced Pelvic Surgery, Department of Obstetrics and Gynecology, University of Cincinnati, Cincinnati, OH, USA.
Abstract
OBJECTIVE: This study was designed to examine the impact of patient socioeconomic, clinical, and hospital characteristics on the utilization of robotics in the surgical staging of endometrial cancer. METHODS: Patients surgically treated for endometrial cancer at facilities that offered robotic and open approaches were identified from the National Inpatient Sample Database from 2008 to 2012. The groups were compared for socioeconomic, clinical, and hospital differences. Medical comorbidity scores were calculated using the Charlson comorbidity index. T tests and χ (2) were used to compare groups. Multivariable analyses were used to determine factors that were independently associated with a robotic approach. RESULTS: A total of 18,284 patients were included (robotic, n = 7169; laparotomy, n = 11,115). Significant differences were noted in all patient clinical and socioeconomic characteristics and all hospital characteristics. Multivariable analyses identified factors that independently predicted patients undergoing robotic surgery. These patients were older [adjusted odds ratio (aOR) 1.008; 95 % confidence interval (CI) 1.004-1.011], white (aOR 1.38; 95 % CI 1.27-1.50), and privately insured (aOR 1.16; 95 % CI 1.07-1.26). Clinically, these women were more likely to be obese (aOR 1.20; 95 % CI 1.11-1.30) and to be undergoing an elective case (aOR 1.25; 95 % CI 1.11-1.40). Hospitals were more likely to be under private control (aOR 1.55, 95 % CI 1.39-1.71) but less likely to be located in the south (aOR 0.87; 0.81-0.93), quantified as large or medium (aOR 0.57; 95 %CI 0.50-0.67), or teaching hospitals (aOR 0.68; 95 % CI 0.63-0.74). CONCLUSIONS: Socioeconomic status and hospital characteristics are factors that independently predict robotic utilization in the United States. These racial, socioeconomic, and geographic disparities warrant further study regarding the utilization of this important technology.
OBJECTIVE: This study was designed to examine the impact of patient socioeconomic, clinical, and hospital characteristics on the utilization of robotics in the surgical staging of endometrial cancer. METHODS:Patients surgically treated for endometrial cancer at facilities that offered robotic and open approaches were identified from the National Inpatient Sample Database from 2008 to 2012. The groups were compared for socioeconomic, clinical, and hospital differences. Medical comorbidity scores were calculated using the Charlson comorbidity index. T tests and χ (2) were used to compare groups. Multivariable analyses were used to determine factors that were independently associated with a robotic approach. RESULTS: A total of 18,284 patients were included (robotic, n = 7169; laparotomy, n = 11,115). Significant differences were noted in all patient clinical and socioeconomic characteristics and all hospital characteristics. Multivariable analyses identified factors that independently predicted patients undergoing robotic surgery. These patients were older [adjusted odds ratio (aOR) 1.008; 95 % confidence interval (CI) 1.004-1.011], white (aOR 1.38; 95 % CI 1.27-1.50), and privately insured (aOR 1.16; 95 % CI 1.07-1.26). Clinically, these women were more likely to be obese (aOR 1.20; 95 % CI 1.11-1.30) and to be undergoing an elective case (aOR 1.25; 95 % CI 1.11-1.40). Hospitals were more likely to be under private control (aOR 1.55, 95 % CI 1.39-1.71) but less likely to be located in the south (aOR 0.87; 0.81-0.93), quantified as large or medium (aOR 0.57; 95 %CI 0.50-0.67), or teaching hospitals (aOR 0.68; 95 % CI 0.63-0.74). CONCLUSIONS: Socioeconomic status and hospital characteristics are factors that independently predict robotic utilization in the United States. These racial, socioeconomic, and geographic disparities warrant further study regarding the utilization of this important technology.
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