IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v151y2016icp110-120.html
   My bibliography  Save this article

Therapeutic substitutions in the midst of new technology diffusion: The case of treatment for localized prostate cancer

Author

Listed:
  • Shen, Chan
  • Tina Shih, Ya-Chen

Abstract

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. 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.

Suggested Citation

  • Shen, Chan & Tina Shih, Ya-Chen, 2016. "Therapeutic substitutions in the midst of new technology diffusion: The case of treatment for localized prostate cancer," Social Science & Medicine, Elsevier, vol. 151(C), pages 110-120.
    • Handle: RePEc:eee:socmed:v:151:y:2016:i:c:p:110-120
    DOI: 10.1016/j.socscimed.2016.01.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953616300168
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.socscimed.2016.01.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mick P. Couper & Eleanor Singer & Carrie A. Levin & Floyd J. Fowler Jr. & Angela Fagerlin & Brian J. Zikmund-Fisher, 2010. "Use of the Internet and Ratings of Information Sources for Medical Decisions: Results from the DECISIONS Survey," Medical Decision Making, , vol. 30(5_suppl), pages 106-114, September.
    2. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    3. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    4. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    5. Bronwyn H. Hall & Beethika Khan, 2003. "Adoption of New Technology," NBER Working Papers 9730, National Bureau of Economic Research, Inc.
    6. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    7. Newey, Whitney K, 1990. "Efficient Instrumental Variables Estimation of Nonlinear Models," Econometrica, Econometric Society, vol. 58(4), pages 809-837, July.
    8. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
    9. Amemiya, Takeshi, 1977. "The Maximum Likelihood and the Nonlinear Three-Stage Least Squares Estimator in the General Nonlinear Simultaneous Equation Model," Econometrica, Econometric Society, vol. 45(4), pages 955-968, May.
    10. Koenker, Roger, 1981. "A note on studentizing a test for heteroscedasticity," Journal of Econometrics, Elsevier, vol. 17(1), pages 107-112, September.
    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. Gagliardi, Dimitri & Ramlogan, Ronnie & Navarra, Pierluigi & Dello Russo, Cinzia, 2018. "Diffusion of complementary evolving pharmaceutical innovations: The case of Abacavir and its pharmacogenetic companion diagnostic in Italy," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 223-233.
    2. Horn, Danea & Sacarny, Adam & Zhou, Annetta, 2022. "Technology adoption and market allocation: The case of robotic surgery," Journal of Health Economics, Elsevier, vol. 86(C).

    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. Miomir Jovanović & Ljiljana Kašćelan & Aleksandra Despotović & Vladimir Kašćelan, 2015. "The Impact of Agro-Economic Factors on GHG Emissions: Evidence from European Developing and Advanced Economies," Sustainability, MDPI, vol. 7(12), pages 1-21, December.
    2. Romano, Joseph P. & Wolf, Michael, 2017. "Resurrecting weighted least squares," Journal of Econometrics, Elsevier, vol. 197(1), pages 1-19.
    3. Wooldridge, Jeffrey M., 1990. "A Unified Approach to Robust, Regression-Based Specification Tests," Econometric Theory, Cambridge University Press, vol. 6(1), pages 17-43, March.
    4. Matthew Backus & Christopher Conlon & Michael Sinkinson, 2021. "Common Ownership and Competition in the Ready-to-Eat Cereal Industry," NBER Working Papers 28350, National Bureau of Economic Research, Inc.
    5. Leonardo Rocha Andrade & Leonardo Q. Cardenas & Fernando Dias Lopes & Fernando P. S. Oliveira & Kaio Cesar Fernandes, 2018. "The Impact of R&D Investments on Performance of Firms in Different Degrees of Proximity to the Technological Frontier," Economics Bulletin, AccessEcon, vol. 38(2), pages 1156-1170.
    6. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
    7. Zdravko Šergo & Amorino Poropat & Pavlo Ružić, 2014. "The determinants of length of stay and arrivals of tourists in the Croatia: a panel data approach," Tourism and Hospitality Industry section8-4, University of Rijeka, Faculty of Tourism and Hospitality Management.
    8. Troeger, Vera, 2012. "De Facto Capital Mobility, Equality, and Tax Policy in Open Economies," CAGE Online Working Paper Series 84, Competitive Advantage in the Global Economy (CAGE).
    9. MacKinnon, James G, 1992. "Model Specification Tests and Artificial Regressions," Journal of Economic Literature, American Economic Association, vol. 30(1), pages 102-146, March.
    10. George E. Halkos & Apostolos S. Tsirivis, 2023. "Electricity Production and Sustainable Development: The Role of Renewable Energy Sources and Specific Socioeconomic Factors," Energies, MDPI, vol. 16(2), pages 1-21, January.
    11. Kendix, Michael & Walls, W.D., 2010. "Estimating the impact of refinery outages on petroleum product prices," Energy Economics, Elsevier, vol. 32(6), pages 1291-1298, November.
    12. Michael O'Connor Keefe & David Gallagher, 2014. "Does the effect of revealed private information on initial public offering (IPO) first trading day return differ by IPO market heat?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 54(3), pages 921-964, September.
    13. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    14. Richard H. Spady & Sami Stouli, 2018. "Simultaneous Mean-Variance Regression," Bristol Economics Discussion Papers 18/697, School of Economics, University of Bristol, UK.
    15. Wooldridge, Jeffrey M., 1991. "On the application of robust, regression- based diagnostics to models of conditional means and conditional variances," Journal of Econometrics, Elsevier, vol. 47(1), pages 5-46, January.
    16. Haenssgen, Marco J. & Savage, Jessica & Yeboah, Godwin & Charoenboon, Nutcha & Srenh, Sorn, 2021. "In a network of lines that intersect: The socio-economic development impact of marine resource management and conservation in Southeast Asia," World Development, Elsevier, vol. 146(C).
    17. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    18. Ali Uyar & Simone Pizzi & Fabio Caputo & Cemil Kuzey & Abdullah S. Karaman, 2022. "Do shareholders reward or punish risky firms due to CSR reporting and assurance?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(5), pages 1596-1620, July.
    19. Pedro Delicado & Juan Romo, 1998. "Constant coefficient tests for random coefficient regression," Economics Working Papers 329, Department of Economics and Business, Universitat Pompeu Fabra.
    20. Kendix, Michael & Walls, W.D., 2010. "Oil industry consolidation and refined product prices: Evidence from US wholesale gasoline terminals," Energy Policy, Elsevier, vol. 38(7), pages 3498-3507, July.

    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:eee:socmed:v:151:y:2016:i:c:p:110-120. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    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.