Robotic surgical systems have become increasingly popular worldwide. Robotic assisted radical prostatectomies have been widely adopted in the treatment of localized prostate cancer, replacing the conventional open surgeries.
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However, it is not clear whether this was achieved by substitution within the same treatment type (i. e. , replacing open surgeries with robotic-assisted surgeries) or substitution across treatment types (i. e. , expanding the proportion of patients receiving surgery while crowding out other forms of treatment for localized prostate cancer). Given the large number of patients undergoing these procedures each year, it is important to study the impact of the fast diffusion of robotic surgical systems on the overall treatment pattern of localized prostate cancer. We addressed this question using state-level cancer epidemiology data (256 observations) extracted from 2002 to 2010 National Cancer Database, and supply-side variables (e. g. density of robotic surgical systems, urologists) obtained from Area Resource File as well as investor presentations posted at the website of the manufacturer of robotic surgical systems. Recognizing that the purchase decision of robotic systems is potentially endogenous, we used an optimal instrumental variables panel estimation method to examine the impact while taking into account of the panel structure and the potential endogeneity of the density of robotic surgical systems and its quadratic term. We found that the density of robotic systems at state-level had a significantly positive impact on the rate of surgery and a significantly negative impact on the rate of radiation therapy. Further, our age-stratified analysis showed that the increase in surgery rate was most pronounced in the younger population. In conclusion, our findings suggest that part of the increase in the rate of surgery was driven by substitution across treatment types with a large proportion originating from the younger population.
Social science & medicine (1982). 2016 Jan 11 [Epub ahead of print]
Chan Shen, Ya-Chen Tina Shih
Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.