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.
Similar content being viewed by others
References
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65(1):5–29.
DeSantis CE, Lin CC, Mariotto AB, Siegel RL, Stein KD, Kramer JL, et al. Cancer treatment and survivorship statistics, 2014. CA Cancer J Clin. 2014;64(4):252–71.
Bradley CJ, Given CW, Roberts C. Race, socioeconomic status, and breast cancer treatment and survival. J Natl Cancer Inst. 2002;94(7):490–6.
Morris AM, Rhoads KF, Stain SC, Birkmeyer JD. Understanding racial disparities in cancer treatment and outcomes. J Am Coll Surg. 2010;211(1):105–13.
Shavers VL, Brown ML. Racial and ethnic disparities in the receipt of cancer treatment. J Natl Cancer Inst. 2002;94(5):334–57.
Bach PB, Schrag D, Brawley OW, Galaznik A, Yakren S, Begg CB. Survival of blacks and whites after a cancer diagnosis. JAMA. 2002;287(16):2106–13.
Parsons HM, Habermann EB, Stain SC, Vickers SM, Al-Refaie WB. What happens to racial and ethnic minorities after cancer surgery at American College of Surgeons National Surgical Quality Improvement Program hospitals? J Am Coll Surg. 2012;214(4):539–47; discussion 47–9.
Liu FW, Randall LM, Tewari KS, Bristow RE. Racial disparities and patterns of ovarian cancer surgical care in California. Gynecol Oncol. 2014;132(1):221–6.
Aranda MA, McGory M, Sekeris E, Maggard M, Ko C, Zingmond DS. Do racial/ethnic disparities exist in the utilization of high-volume surgeons for women with ovarian cancer? Gynecol Oncol. 2008;111(2):166–72.
Robinson CN, Balentine CJ, Sansgiry S, Berger DH. Disparities in the use of minimally invasive surgery for colorectal disease. J Gastrointest Surg. 2012;16(5):897–903; discussion -4.
Loehrer AP, Song Z, Auchincloss HG, Hutter MM. Massachusetts health care reform and reduced racial disparities in minimally invasive surgery. JAMA Surg. 2013;148(12):1116–22.
Varela JE, Nguyen NT. Disparities in access to basic laparoscopic surgery at U.S. academic medical centers. Surg Endosc. 2011;25(4):1209–14.
Greenberg CC, Weeks JC, Stain SC. Disparities in oncologic surgery. World J Surg. 2008;32(4):522–8.
Koh W-Jea. NCCN Clinical Practice Guidelines in Oncology (NCCN guidelines):Uterine Neoplasms. National Cancer Center Network; Version 2.2015.
Walker JL, Piedmonte MR, Spirtos NM, Eisenkop SM, Schlaerth JB, Mannel RS, et al. Laparoscopy compared with laparotomy for comprehensive surgical staging of uterine cancer: Gynecologic Oncology Group Study LAP2. J Clin Oncol. 2009;27(32):5331–6.
Walker JL, Piedmonte MR, Spirtos NM, Eisenkop SM, Schlaerth JB, Mannel RS, et al. Recurrence and survival after random assignment to laparoscopy versus laparotomy for comprehensive surgical staging of uterine cancer: Gynecologic Oncology Group LAP2 Study. J Clin Oncol. 2012;30(7):695–700.
Sinno AK, Fader AN. Robotic-assisted surgery in gynecologic oncology. Fertil Steril. 2014;102(4):922–32.
Gehrig PA, Cantrell LA, Shafer A, Abaid LN, Mendivil A, Boggess JF. What is the optimal minimally invasive surgical procedure for endometrial cancer staging in the obese and morbidly obese woman? Gynecol Oncol. 2008;111(1):41–5.
Doo DW, Guntupalli SR, Corr BR, Sheeder J, Davidson SA, Behbakht K, et al. Comparative surgical outcomes for endometrial cancer patients 65 years old or older staged with robotics or laparotomy. Ann Surg Oncol. 2015;22(11):3687–3694.
Yu X, Lum D, Kiet TK, Fuh KC, Orr J, Jr., Brooks RA, et al. Utilization of and charges for robotic versus laparoscopic versus open surgery for endometrial cancer. J Surg Oncol. 2013;107(6):653–8.
HCUP Databases. Healthcare Cost and Utilization Project (HCUP). 2006–2009. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/databases.jsp.
HCUP Nationwide Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). 2011. Agency for Healthcare Research and Quality, Rockville, MD.http://www.hcup-us.ahrq.gov/nisoverview.jsp.
NIS H. (citation: http://www.hcup-us.ahrq.gov/tech_assist/sampledesign/508_compliance/508course.htm).
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis. 1987;40(5):373–83.
Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613–9.
Long B, Liu FW, Bristow RE. Disparities in uterine cancer epidemiology, treatment, and survival among African Americans in the United States. Gynecol Oncol. 2013;130(3):652–9.
Fedewa SA, Lerro C, Chase D, Ward EM. Insurance status and racial differences in uterine cancer survival: a study of patients in the National Cancer Database. Gynecol Oncol. 2011;122:63–8.
Liang MI, Rosen MA, Rath KS, Hade EM, Clements AE, Backes FJ, et al. Predicting inpatient stay lasting two midnights or more after robotic surgery for endometrial cancer. J Minim Invasive Gynecol. 2015;22(4):583–589.
Collins Y, Holcomb K, Chapman-Davis E, Khabele D, Farley JH. Gynecologic cancer disparities: a report from the Health Disparities Taskforce of the Society of Gynecologic Oncology. Gynecol Oncol. 2014;133(2):353–61.
Chan JK, Gardner AB, Taylor K, Blansit K, Thompson CA, Brooks R, et al. The centralization of robotic surgery in high-volume centers for endometrial cancer patients: a study of 6560 cases in the U.S. Gynecol Oncol. 2015;138(1):128–32.
Bell MC, Torgerson J, Seshadri-Kreaden U, Suttle AW, Hunt S. Comparison of outcomes and cost for endometrial cancer staging via traditional laparotomy, standard laparoscopy and robotic techniques. Gynecol Oncol. 2008;111:407–11.
Conflict of interest
The authors report no conflict of interest.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Blake, E.A., Sheeder, J., Behbakht, K. et al. Factors Impacting Use of Robotic Surgery for Treatment of Endometrial Cancer in the United States. Ann Surg Oncol 23, 3744–3748 (2016). https://doi.org/10.1245/s10434-016-5252-x
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1245/s10434-016-5252-x