Diffusion of robotic-assisted laparoscopic technology across specialties: a national study from 2008 to 2013
Robotic-assisted procedures were frequently found to have similar outcomes and indications to their laparoscopic counterparts, yet significant variation existed in the acceptance of robotic-assisted technology between surgical specialties and procedures. We performed a retrospective cohort study investigating factors associated with the adoption of robotic assistance across the United States from 2008 to 2013.
Using the Nationwide Inpatient Sample database, patient- and hospital-level variables were examined for differential distribution between robotic-assisted and conventional laparoscopic procedures. Multilevel logistic regression models were constructed to identify independent factors associated with robotic adoption. Furthermore, cases were stratified by procedure and specialty before being ranked according to proportion of robotic-assistance adoption. Correlation was examined between robotic-assistance adoption and relative outcome in comparison with conventional laparoscopic procedures.
The national robotic case volume doubled over the five-year period while a gradual decline in laparoscopic case volume was observed, resulting in an increase in the proportion of procedures performed with robotic assistance from 6.8 to 17%. Patients receiving robotic procedures were more likely to be younger, males, white, privately insured, more affluent, and with less comorbidities. These differences have been decreasing over the study period. The three specialties with the highest proportion of robotic-assisted laparoscopic procedures were urology (34.1%), gynecology (11.0%), and endocrine surgery (9.4%). However, no significant association existed between the frequency of robotic-assistance usage and relative outcome statistics such as mortality, charge, or length of stay.
The variation in robotic-assistance adoption between specialties and procedures could not be attributable to clinical outcomes alone. Cultural readiness toward adopting new technology within specialty and target anatomic areas appear to be major determining factors influencing its adoption.
KeywordsRobotic-assisted Laparoscopic Minimally-invasive surgery Temporal trend
Compliance with ethical standards
Drs. Juo, Lin, Dutson, Ahmad, and Aditya have no conflicts of interest or financial ties to disclose.
- 1.Rogers EM (2003) Diffusion of innovations, 5th edn. Free Press, New YorkGoogle Scholar
- 2.Barkun JS, Aronson JK, Feldman LS, Maddern GJ, Strasberg SM, Altman DG, Blazeby JM, Boutron IC, Campbell WB, Clavien PA, Cook JA, Ergina PL, Flum DR, Glasziou P, Marshall JC, McCulloch P, Nicholl J, Reeves BC, Seiler CM, Meakins JL, Ashby D, Black N, Bunker J, Burton M, Campbell M, Chalkidou K, Chalmers I, de Leval M, Deeks J, Grant A, Gray M, Greenhalgh R, Jenicek M, Kehoe S, Lilford R, Littlejohns P, Loke Y, Madhock R, McPherson K, Rothwell P, Summerskill B, Taggart D, Tekkis P, Thompson M, Treasure T, Trohler U, Vandenbroucke J (2009) Evaluation and stages of surgical innovations. Lancet 374:1089–1096CrossRefPubMedGoogle Scholar
- 15.Robertson C, Close A, Fraser C, Gurung T, Jia X, Sharma P, Vale L, Ramsay C, Pickard R (2013) Relative effectiveness of robot-assisted and standard laparoscopic prostatectomy as alternatives to open radical prostatectomy for treatment of localised prostate cancer: a systematic review and mixed treatment comparison meta-analysis. BJU Int 112:798–812CrossRefPubMedGoogle Scholar
- 22.Gala RB, Margulies R, Steinberg A, Murphy M, Lukban J, Jeppson P, Aschkenazi S, Olivera C, South M, Lowenstein L, Schaffer J, Balk EM, Sung V (2014) Systematic review of robotic surgery in gynecology: robotic techniques compared with laparoscopy and laparotomy. J Minim Invasive Gynecol 21:353–361CrossRefPubMedGoogle Scholar
- 28.HCUP Nationwide Inpatient Sample (NIS) (2010) Healthcare Cost and Utilization Project (HCUP). Agency for healthcare research and quality. Rockville. http://www.hcup-us.ahrq.gov/nisoverview.jsp. Accessed 30 Jan 2013
- 30.Romano PS, Roos LL, Jollis JG (1993) Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol 46: 1075–1079; discussion 1081–1090Google Scholar
- 32.StataCorp (2005) Stata data management reference manual, Release 9. Stata Press, College StationGoogle Scholar
- 33.Karthikesalingam A, Holt PJ, Vidal-Diez A, Bahia SS, Patterson BO, Hinchliffe RJ, Thompson MM (2016) The impact of endovascular aneurysm repair on mortality for elective abdominal aortic aneurysm repair in England and the United States. J Vasc Surg 64:321.e322–327.e322Google Scholar
- 54.Guru KA, Hussain A, Chandrasekhar R, Piacente P, Bienko M, Glasgow M, Underwood W, Wilding G, Mohler JL, Menon M, Peabody JO (2009) Current status of robot-assisted surgery in urology: a multi-national survey of 297 urologic surgeons. Can J Urol 16: 4736–4741; discussion 4741Google Scholar