Do Robotic Surgical Systems Improve Profit Margins? A Cross-Sectional Analysis of California Hospitals

Ya Chen Tina Shih, Chan Shen, Jim C. Hu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Background The aim of this study was to examine the association between ownership of robotic surgical systems and hospital profit margins. Methods This study used hospital annual utilization data, annual financial data, and discharge data for year 2011 from the California Office of Statewide Health Planning and Development. We first performed bivariate analysis to compare mean profit margin by hospital and market characteristics and to examine whether these characteristics differed between hospitals that had one or more robotic surgical systems in 2011 and those that did not. We applied the t test and the F test to compare mean profit margin between two groups and among three or more groups, respectively. We then conducted multilevel logistic regression to determine the association between ownership of robotic surgical systems and having a positive profit margin after controlling for other hospital and market characteristics and accounting for possible correlation among hospitals located within the same market. Results The study sample included 167 California hospitals with valid financial information. Hospitals with robotic surgical systems tended to report more favorable profit margins. However, multilevel logistic regression showed that this relationship (an association, not causality) became only marginally significant (odds ratio [OR] = 6.2; P = 0.053) after controlling for other hospital characteristics, such as ownership type, teaching status, bed size, and surgical volumes, and market characteristics, such as total number of robotic surgical systems owned by other hospitals in the same market area. Conclusions As robotic surgical systems become widely disseminated, hospital decision makers should carefully evaluate the financial and clinical implications before making a capital investment in this technology.

Original languageEnglish (US)
Pages (from-to)1221-1225
Number of pages5
JournalValue in Health
Volume20
Issue number8
DOIs
StatePublished - Sep 2017

All Science Journal Classification (ASJC) codes

  • Health Policy
  • Public Health, Environmental and Occupational Health

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