IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/114535.html
   My bibliography  Save this paper

The diffusion of robotic surgery: examining technology use in the English NHS

Author

Listed:
  • Maynou, Laia
  • Pearson, Georgia
  • McGuire, Alistair
  • Serra-Sastre, Victoria

Abstract

This paper examines the adoption and diffusion of medical technology as associated with the dramatic recent increase in the surgical use of robots. We consider specifically the sequential adoption and diffusion patterns of three interrelated surgical technologies within a single healthcare system (the English NHS): robotic, laparoscopic and open radical prostatectomy. Robotic and laparoscopic techniques are minimally invasive procedures with similar patient benefits, but the newer robotic technique requires a high initial investment cost to purchase the robot and carries high maintenance costs over time. Using data from a large UK administrative database, Hospital Episodes Statistics, for the period 2000–2018, we analyse 173 hospitals performing radical prostatectomy, the most prevalent and earliest surgical area of adoption of robotic surgery. Our empirical analysis first identifies substitution effects, with robotic surgery replacing the incumbent technology, including the recently diffused laparoscopic technology. We then quantify the spillover of robotic surgery as it diffuses to other surgical specialties. Finally, we perform time-to-event analysis at the hospital level to quantitatively examine the adoption. Results show that a higher number of urologists and a wealthier referral area favor robot adoption.

Suggested Citation

  • Maynou, Laia & Pearson, Georgia & McGuire, Alistair & Serra-Sastre, Victoria, 2022. "The diffusion of robotic surgery: examining technology use in the English NHS," LSE Research Online Documents on Economics 114535, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:114535
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/114535/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dranove, David & Garthwaite, Craig & Li, Bingyang & Ody, Christopher, 2015. "Investment subsidies and the adoption of electronic medical records in hospitals," Journal of Health Economics, Elsevier, vol. 44(C), pages 309-319.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tafti, Elena Ashtari, 2023. "Technology, Skills, and Performance: The Case of Robots in Surgery," CINCH Working Paper Series (since 2020) 78746, Duisburg-Essen University Library, DuEPublico.
    2. Elena Ashtari Tafti, 2022. "Technology, skills, and performance: the case of robots in surgery," IFS Working Papers W22/46, Institute for Fiscal Studies.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Venugopal Gopalakrishna-Remani & Robert Paul Jones & Kerri M. Camp, 2019. "Levels of EMR Adoption in U.S. Hospitals: An Empirical Examination of Absorptive Capacity, Institutional Pressures, Top Management Beliefs, and Participation," Information Systems Frontiers, Springer, vol. 21(6), pages 1325-1344, December.
    2. Maynou, L. & McGuire, A. & Serra-Sastre, V., 2019. "Exploring the Impact of New Medical Technology on Workforce Planning," Working Papers 19/07, Department of Economics, City University London.
    3. Seth Freedman & Haizhen Lin & Jeffrey Prince, 2018. "Does Competition Lead to Agglomeration or Dispersion in EMR Vendor Decisions?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 53(1), pages 57-79, August.
    4. Maynou, Laia & Pearson, Georgia & McGuire, Alistair & Serra-Sastre, Victoria, 2022. "The diffusion of robotic surgery: Examining technology use in the English NHS," Health Policy, Elsevier, vol. 126(4), pages 325-336.
    5. Elisabet Rodriguez Llorian & Gregory Mason, 2021. "Electronic medical records and primary care quality: Evidence from Manitoba," Health Economics, John Wiley & Sons, Ltd., vol. 30(5), pages 1124-1138, May.
    6. Seth Freedman & Haizhen Lin & Jeffrey Prince, 2018. "Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms," American Journal of Health Economics, University of Chicago Press, vol. 4(1), pages 51-79, Winter.
    7. Marlow, Michael, 2017. "Should Government Subsidize Electronic Health Records?," Working Papers 06886, George Mason University, Mercatus Center.
    8. Ghandour, Ziad & Siciliani, Luigi & Straume, Odd Rune, 2022. "Investment and quality competition in healthcare markets," Journal of Health Economics, Elsevier, vol. 82(C).
    9. Yanfei Wang, 2022. "Competition And Multilevel Technology Adoption: A Dynamic Analysis Of Electronic Medical Records Adoption In U.S. Hospitals," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1357-1395, August.

    More about this item

    Keywords

    adoption; diffusion; robotic surgery; substitution; technology; Efficiency Research Program funded by The Health Foundation; Award Reference Number 7432.;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:114535. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.