title: Are hospitals "keeping up with the Joneses"?: Assessing the spatial and temporal diffusion of the surgical robot.
abstract: BACKGROUND
  The surgical robot has been widely adopted in the United States in spite of its high cost and controversy surrounding its benefit. Some have suggested that a "medical arms race" influences technology adoption. We wanted to determine whether a hospital would acquire a surgical robot if itsnearestneighboring hospital already owned one.
  
  
  METHODS
  We identified 554 hospitals performing radical prostatectomy from the Healthcare Cost and Utilization Project Statewide Inpatient Databases for seven states. We used publicly available data from the website of the surgical robot's sole manufacturer (Intuitive Surgical, Sunnyvale, CA) combined with data collected from the hospitals to ascertain the timing of robot acquisitionduring year 2001 to2008. One hundred thirty four hospitals (24%) had acquired a surgical robot by the end of 2008. We geocoded the address of each hospital anddetermined a hospital's likelihood to acquire a surgical robot based on whether its nearest neighbor owned a surgical robot. We developed a Markov chain method to model the acquisition process spatially and temporally and quantified the "neighborhood effect" on the acquisition of the surgical robot while adjusting simultaneously for known confounders.
  
  
  RESULTS
  After adjusting for hospital teaching status, surgical volume, urban status and number of hospital beds, the Markov chain analysis demonstrated that a hospital whose nearest neighbor had acquired a surgical robot had a higher likelihood itself acquiring a surgical robot. (OR=1.71,95% CI: 1.07-2.72, p=0.02).
  
  
  CONCLUSIONS
  There is a significant spatial and temporal association for hospitals acquiring surgical robots during the study period. Hospitals were more likely to acquire a surgical robot during the robot's early adoption phase if their nearest neighbor had already done so.
authors.affiliation: Department of Population Health, New York University, New York, NY, 10016 ; New York University Cancer Institute.
authors.forename: Huilin
authors.initials: H
authors.lastname: Li
authors.affiliation: Division of Cancer Epidemiology and Genetics, Biostatistics Branch, National Cancer Institute, NIH, Rockville, MD, 20852-7242.
authors.forename: Mitchell H
authors.initials: MH
authors.lastname: Gail
authors.affiliation: Department of Population Health, New York University, New York, NY, 10016.
authors.forename: R Scott
authors.initials: RS
authors.lastname: Braithwaite
authors.affiliation: Department of Population Health, New York University, New York, NY, 10016 ; New York University Cancer Institute ; Robert F. Wagner Graduate School of Public Service.
authors.forename: Heather T
authors.initials: HT
authors.lastname: Gold
authors.affiliation: Department of Urology, New York University School of Medicine.
authors.forename: Dawn
authors.initials: D
authors.lastname: Walter
authors.affiliation: Department of Population Health, New York University, New York, NY, 10016 ; New York University Cancer Institute.
authors.forename: Mengling
authors.initials: M
authors.lastname: Liu
authors.affiliation: Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, and Division of General Internal Medicine, Yale University School of Medicine ; United States Department of Veterans Affairs.
authors.forename: Cary P
authors.initials: CP
authors.lastname: Gross
authors.affiliation: Department of Population Health, New York University, New York, NY, 10016 ; New York University Cancer Institute ; Robert F. Wagner Graduate School of Public Service ; Department of Urology, New York University School of Medicine ; United States Department of Veterans Affairs.
authors.forename: Danil V
authors.initials: DV
authors.lastname: Makarov
references.citation: Urology. 2002 Nov;60(5):864-8
references.pmid: 12429317
references.citation: J Urol. 2004 Oct;172(4 Pt 1):1431-5
references.pmid: 15371862
references.citation: Curr Opin Urol. 2008 Mar;18(2):173-9
references.pmid: 18303539
references.citation: Urology. 2006 Feb;67(2):360-3
references.pmid: 16461085
references.citation: JAMA. 2009 Oct 14;302(14):1557-64
references.pmid: 19826025
references.citation: Curr Urol Rep. 2006 May;7(3):193-9
references.pmid: 16770855
references.citation: JAMA. 2003 Apr 16;289(15):1969-75
references.pmid: 12697800
references.citation: Urology. 2007 Jul;70(1):96-100
references.pmid: 17656216
references.citation: Health Serv Res. 2004 Apr;39(2):417-30
references.pmid: 15032962
references.citation: BJU Int. 2003 Feb;91(3):175-6
references.pmid: 12580996
references.citation: Urology. 2004 May;63(5):819-22
references.pmid: 15134953
references.citation: Health Policy. 2006 Dec;79(2-3):221-30
references.pmid: 16473435
references.citation: Rev Econ Stat. 2015 Dec;97(5):951-964
references.pmid: 26989267
references.citation: Rand J Econ. 1992 Summer;23(2):247-62
references.pmid: 10119678
references.citation: N Engl J Med. 2010 Aug 19;363(8):701-4
references.pmid: 20818872