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Factors Associated With Hospital Decisions to Purchase Robotic Surgical Systems.
Shen, Chan; Gu, Dian; Klein, Roger; Zhou, Shouhao; Shih, Ya-Chen T; Tracy, Thomas; Soybel, David; Dillon, Peter.
Afiliação
  • Shen C; Department of Surgery, Division of Outcomes Research and Quality, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvani.
  • Gu D; Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Klein R; Department of Economics, Rutgers University, New Brunswick, New Jersey.
  • Zhou S; Department of Public Health Sciences, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvania.
  • Shih YT; Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Tracy T; Department of Surgery, Division of Outcomes Research and Quality, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvani.
  • Soybel D; Department of Surgery, Division of Outcomes Research and Quality, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvani.
  • Dillon P; Department of Surgery, Division of Outcomes Research and Quality, The Pennsylvania State University, College of Medicine, Hershey, Pennsylvani.
MDM Policy Pract ; 5(1): 2381468320904364, 2020.
Article em En | MEDLINE | ID: mdl-32072012
ABSTRACT
Background. Robotic surgical systems are expensive to own and operate, and the purchase of such technology is an important decision for hospital administrators. Most prior literature focuses on the comparison of clinical outcomes between robotic surgery and other laparoscopic or open surgery. There is a knowledge gap about what drives hospitals' decisions to purchase robotic systems. Objective. To identify factors associated with a hospital's acquisition of advanced surgical systems. Method. We used 2002 to 2011 data from the State of California Office of Statewide Health Planning and Development to examine robotic surgical system purchase decisions of 476 hospitals. We used a probit estimation allowing heteroscedasticity in the error term including a set of two equations one binary response equation and one heteroscedasticity equation. Results. During the study timeframe, there were 78 robotic surgical systems purchased by hospitals in the sample. Controlling for hospital characteristics such as number of available beds, teaching status, nonprofit status, and patient mix, the probit estimation showed that market-level directly relevant surgery volume in the previous year (excluding the hospital's own volume) had the largest impact. More specifically, hospitals in high volume (>50,000 surgeries v. 0) markets were 12 percentage points more likely to purchase robotic systems. We also found that hospitals in less competitive markets (i.e., Herfindahl index above 2500) were 2 percentage points more likely to purchase robotic systems. Limitations. This study has limitations common to observational database studies. Certain characteristics such as cultural factors cannot be accurately quantified. Conclusions. Our findings imply that potential market demand is a strong driver for hospital purchase of robotic surgical systems. Market competition does not significantly increase the adoption of new expensive surgical technologies.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article