IDEAS home Printed from https://ideas.repec.org/p/gat/wpaper/1809.html
   My bibliography  Save this paper

What underlies the observed hospital volume-outcome relationship?

Author

Listed:
  • Marius Huguet

    (Univ Lyon, Université Lumière Lyon 2, GATE UMR 5824, F-69130 Ecully, France)

  • Xavier Joutard

    (Aix Marseille Univ, CNRS, LEST, Aix-en-Provence; OFCE, sciences Po, Paris)

  • Isabelle Ray-Coquart

    (Univ Lyon, Université Claude Bernard Lyon 1, Centre Léon Bérard, EA7425 HESPER, F-69008 Lyon, France)

  • Lionel Perrier

    (Univ Lyon, Université Lumière Lyon 2, Centre Léon Bérard, GATE UMR 5824, F-69008 Lyon, France)

Abstract

Studies of the hospital volume-outcome relationship have highlighted that a greater volume activity improves patient outcomes. While this finding has been known for years in health services research, most studies to date have failed to delve into what underlies this relationship. This study aimed to shed light on the basis of the hospital volume effect by comparing treatment modalities for epithelial ovarian carcinoma patients. Hospital volume activity was instrumented by the distance from patients’ homes to their hospital, the population density, and the median net income of patient municipalities. We found that higher volume hospitals appear to more often make the right decisions in regard to how to treat patients, which contributes to the positive impact of hospital volume activities on patient outcomes. Based on our parameter estimates, we found that the rate of complete tumor resection would increase by 10% with centralized care, and by 6% if treatment decisions were coordinated by high volume centers compared to the ongoing organization of care. In both scenarios, the use of neoadjuvant chemotherapy would increase by 10%. As volume alone is an imperfect correlate of quality, policy makers need to know what volume is a proxy for in order to devise volume-based policies.

Suggested Citation

  • Marius Huguet & Xavier Joutard & Isabelle Ray-Coquart & Lionel Perrier, 2018. "What underlies the observed hospital volume-outcome relationship?," Working Papers 1809, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
  • Handle: RePEc:gat:wpaper:1809
    as

    Download full text from publisher

    File URL: ftp://ftp.gate.cnrs.fr/RePEc/2018/1809.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Avdic, Daniel & Lundborg, Petter & Vikström, Johan, 2014. "Learning-by-Doing in a Highly Skilled Profession When Stakes Are High: Evidence from Advanced Cancer Surgery," IZA Discussion Papers 8099, Institute of Labor Economics (IZA).
    2. Mesman, Roos & Westert, Gert P. & Berden, Bart J.M.M. & Faber, Marjan J., 2015. "Why do high-volume hospitals achieve better outcomes? A systematic review about intermediate factors in volume–outcome relationships," Health Policy, Elsevier, vol. 119(8), pages 1055-1067.
    3. Marius Huguet & Lionel Perrier & Olivia Bally & David Benayoun & Pierre de Saint Hilaire & Dominique Beal Ardisson & Magali Morelle & Nathalie Havet & Xavier Joutard & Pierre Méeus & Philippe Gabelle , 2018. "Being Treated In Higher Volume Hospitals Leads To Longer Progression-Free Survival For Epithelial Ovarian Carcinoma Patients in the Rhone-Alpes region of France," Post-Print halshs-01670155, HAL.
    4. Ho, Vivian & Town, Robert J. & Heslin, Martin J., 2007. "Regionalization versus competition in complex cancer surgery," Health Economics, Policy and Law, Cambridge University Press, vol. 2(1), pages 51-71, January.
    5. Walter Beckert & Elaine Kelly, 2017. "Divided by choice? Private providers, patient choice and hospital sorting in the English National Health service," IFS Working Papers W17/15, Institute for Fiscal Studies.
    6. Avdic, Daniel & Lundborg, Petter & Vikström, Johan, 2014. "Learning-by-Doing in a High-Skill Profession when Stakes are High: Evidence from Advanced Cancer Surgery," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100278, Verein für Socialpolitik / German Economic Association.
    7. Baker, Laurence C. & Bundorf, M. Kate & Kessler, Daniel P., 2016. "The effect of hospital/physician integration on hospital choice," Journal of Health Economics, Elsevier, vol. 50(C), pages 1-8.
    8. Corinna Hentschker & Roman Mennicken, 2015. "The Volume‐Outcome Relationship and Minimum Volume Standards – Empirical Evidence for Germany," Health Economics, John Wiley & Sons, Ltd., vol. 24(6), pages 644-658, June.
    9. Hugh Gravelle & Rita Santos & Luigi Siciliani & Rosalind Goudie, 2012. "Hospital Quality Competition Under Fixed Prices," Working Papers 080cherp, Centre for Health Economics, University of York.
    Full references (including those not matched with items on IDEAS)

    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. Marius Huguet & Xavier Joutard & Isabelle Ray-Coquard & Lionel Perrier, 2018. "What underlies the observed hospital volume- outcome relationship?," Working Papers halshs-01801598, HAL.
    2. Marius Huguet & Xavier Joutard & Isabelle Ray-Coquard & Lionel Perrier, 2022. "What underlies the observed hospital volume- outcome relationship?," SciencePo Working papers Main halshs-01801598, HAL.
    3. repec:zbw:rwirep:0527 is not listed on IDEAS
    4. Hentschker, Corinna & Mennicken, Roman, 2014. "Selective-referral and Unobserved Patient Heterogeneity – Bias in the Volume-outcome Relationship," Ruhr Economic Papers 527, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Corinna Hentschker & Roman Mennicken, 2014. "Selective-referral and Unobserved Patient Heterogeneity – Bias in the Volume-outcome Relationship," Ruhr Economic Papers 0527, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    6. Versteeg, S.E. & Ho, V.K.Y. & Siesling, S. & Varkevisser, M., 2018. "Centralisation of cancer surgery and the impact on patients’ travel burden," Health Policy, Elsevier, vol. 122(9), pages 1028-1034.
    7. De Grip, Andries & Sauermann, Jan & Sieben, Inge, 2016. "The role of peers in estimating tenure-performance profiles: Evidence from personnel data," Journal of Economic Behavior & Organization, Elsevier, vol. 126(PA), pages 39-54.
    8. Martin Gaynor & Kate Ho & Robert J. Town, 2015. "The Industrial Organization of Health-Care Markets," Journal of Economic Literature, American Economic Association, vol. 53(2), pages 235-284, June.
    9. Huguet, Marius, 2020. "Centralization of care in high volume hospitals and inequalities in access to care," Social Science & Medicine, Elsevier, vol. 260(C).
    10. Dardanoni, V.; & Laudicella, M.; & Li Donni, P.;, 2018. "Hospital Choice in the NHS," Health, Econometrics and Data Group (HEDG) Working Papers 18/04, HEDG, c/o Department of Economics, University of York.
    11. Avdic, Daniel & Lundborg, Petter & Vikström, Johan, 2018. "Mergers and Birth Outcomes: Evidence from Maternity Ward Closures," IZA Discussion Papers 11772, Institute of Labor Economics (IZA).
    12. Raf Van Gestel & Tobias Müller & Johan Bosmans, 2018. "Learning from failure in healthcare: Dynamic panel evidence of a physician shock effect," Health Economics, John Wiley & Sons, Ltd., vol. 27(9), pages 1340-1353, September.
    13. Piia Pekola & Ismo Linnosmaa & Hennamari Mikkola, 2017. "Competition and quality in a physiotherapy market with fixed prices," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(1), pages 97-117, January.
    14. Daniel Avdic & Tugba Bueyuekdurmus & Giuseppe Moscelli & Adam Pilny & Ieva Sriubaite, 2018. "Subjective and objective quality reporting and choice of hospital: Evidence from maternal care services in Germany," CINCH Working Paper Series 1803, Universitaet Duisburg-Essen, Competent in Competition and Health.
    15. Walter Beckert & Elaine Kelly, 2021. "Divided by choice? For‐profit providers, patient choice and mechanisms of patient sorting in the English National Health Service," Health Economics, John Wiley & Sons, Ltd., vol. 30(4), pages 820-839, April.
    16. Charlotte Davies, 2020. "The supply side to procurement in a health market: competition and innovation in hip implants," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2020-01, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    17. Anne‐Fleur Roos & Ramsis R. Croes & Victoria Shestalova & Marco Varkevisser & Frederik T. Schut, 2019. "Price effects of a hospital merger: Heterogeneity across health insurers, hospital products, and hospital locations," Health Economics, John Wiley & Sons, Ltd., vol. 28(9), pages 1130-1145, September.
    18. Richards-Shubik, Seth & Roberts, Mark S. & Donohue, Julie M., 2022. "Measuring quality effects in equilibrium," Journal of Health Economics, Elsevier, vol. 83(C).
    19. Davies, Charlotte & Davies, Stephen, 2021. "Assessing competition in the hip implant industry in the light of recent policy guidance," Social Science & Medicine, Elsevier, vol. 287(C).
    20. Ho Vivian & Short Marah N. & Ku-Goto Meei-Hsiang, 2012. "Can Centralization of Cancer Surgery Improve Social Welfare?," Forum for Health Economics & Policy, De Gruyter, vol. 15(1), pages 1-25, October.
    21. Mesman, Roos & Faber, Marjan J. & Berden, Bart J.J.M. & Westert, Gert P., 2017. "Evaluation of minimum volume standards for surgery in the Netherlands (2003–2017): A successful policy?," Health Policy, Elsevier, vol. 121(12), pages 1263-1273.

    More about this item

    Keywords

    Volume outcome relationship; France; Epithelial Ovarian Cancer; Instrumental variable; Organization of care; Care pathway; Learning effect; Centralization of care;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms

    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:gat:wpaper:1809. 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: Nelly Wirth (email available below). General contact details of provider: https://edirc.repec.org/data/gateefr.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.