IDEAS home Printed from https://ideas.repec.org/a/spr/eujhec/v17y2016i8d10.1007_s10198-015-0743-4.html
   My bibliography  Save this article

Is higher nursing home quality more costly?

Author

Listed:
  • L. Di Giorgio

    (University of Washington
    Università della Svizzera italiana (USI))

  • M. Filippini

    (Università della Svizzera italiana (USI)
    ETH)

  • G. Masiero

    (Università della Svizzera italiana (USI)
    University of Bergamo)

Abstract

Widespread issues regarding quality in nursing homes call for an improved understanding of the relationship with costs. This relationship may differ in European countries, where care is mainly delivered by nonprofit providers. In accordance with the economic theory of production, we estimate a total cost function for nursing home services using data from 45 nursing homes in Switzerland between 2006 and 2010. Quality is measured by means of clinical indicators regarding process and outcome derived from the minimum data set. We consider both composite and single quality indicators. Contrary to most previous studies, we use panel data and control for omitted variables bias. This allows us to capture features specific to nursing homes that may explain differences in structural quality or cost levels. Additional analysis is provided to address simultaneity bias using an instrumental variable approach. We find evidence that poor levels of quality regarding outcome, as measured by the prevalence of severe pain and weight loss, lead to higher costs. This may have important implications for the design of payment schemes for nursing homes.

Suggested Citation

  • L. Di Giorgio & M. Filippini & G. Masiero, 2016. "Is higher nursing home quality more costly?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 1011-1026, November.
    • Handle: RePEc:spr:eujhec:v:17:y:2016:i:8:d:10.1007_s10198-015-0743-4
    DOI: 10.1007/s10198-015-0743-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10198-015-0743-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10198-015-0743-4?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. Joshua D. Angrist & Alan B. Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 69-85, Fall.
    2. Nils Gutacker & Chris Bojke & Silvio Daidone & Nancy J. Devlin & David Parkin & Andrew Street, 2013. "Truly Inefficient Or Providing Better Quality Of Care? Analysing The Relationship Between Risk‐Adjusted Hospital Costs And Patients' Health Outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 22(8), pages 931-947, August.
    3. William D. Spector & Thomas M. Selden & Joel W. Cohen, 1998. "The impact of ownership type on nursing home outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 7(7), pages 639-653, November.
    4. Di Giorgio, Laura & Filippini, Massimo & Masiero, Giuliano, 2014. "Implications of global budget payment system on nursing home costs," Health Policy, Elsevier, vol. 115(2), pages 237-248.
    5. Hahn, Jinyong & Ham, John C. & Moon, Hyungsik Roger, 2011. "The Hausman test and weak instruments," Journal of Econometrics, Elsevier, vol. 160(2), pages 289-299, February.
    6. R. G. Evans, 1971. "'Behavioural' Cost Functions for Hospitals," Canadian Journal of Economics, Canadian Economics Association, vol. 4(2), pages 198-215, May.
    7. Gertler, Paul J & Waldman, Donald M, 1992. "Quality-Adjusted Cost Functions and Policy Evaluation in the Nursing Home Industry," Journal of Political Economy, University of Chicago Press, vol. 100(6), pages 1232-1256, December.
    8. William Rogers, 1994. "Regression standard errors in clustered samples," Stata Technical Bulletin, StataCorp LP, vol. 3(13).
    9. John R. Bowblis & Stephen Crystal & Orna Intrator & Judith A. Lucas, 2012. "Response To Regulatory Stringency: The Case Of Antipsychotic Medication Use In Nursing Homes," Health Economics, John Wiley & Sons, Ltd., vol. 21(8), pages 977-993, August.
    10. James H. Stock & Mark W. Watson, 2008. "Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression," Econometrica, Econometric Society, vol. 76(1), pages 155-174, January.
    11. John Bowblis & Judith Lucas, 2012. "The impact of state regulations on nursing home care practices," Journal of Regulatory Economics, Springer, vol. 42(1), pages 52-72, August.
    12. David M. Drukker, 2003. "Testing for serial correlation in linear panel-data models," Stata Journal, StataCorp LP, vol. 3(2), pages 168-177, June.
    13. Grabowski, David C. & Feng, Zhanlian & Hirth, Richard & Rahman, Momotazur & Mor, Vincent, 2013. "Effect of nursing home ownership on the quality of post-acute care: An instrumental variables approach," Journal of Health Economics, Elsevier, vol. 32(1), pages 12-21.
    14. Mehdi Farsi & Massimo Filippini & Diego Lunati, 2008. "Economies of Scale and Efficiency Measurement in Switzerland's Nursing Homes," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(III), pages 359-378, September.
    15. Bowblis, John R. & McHone, Heather S., 2013. "An instrumental variables approach to post-acute care nursing home quality: Is there a dime's worth of evidence that continuing care retirement communities provide higher quality?," Journal of Health Economics, Elsevier, vol. 32(5), pages 980-996.
    16. Richard Hirth & David Grabowski & Zhanlian Feng & Momotazur Rahman & Vincent Mor, 2014. "Effect of nursing home ownership on hospitalization of long-stay residents: an instrumental variables approach," International Journal of Health Economics and Management, Springer, vol. 14(1), pages 1-18, March.
    17. Harrington, C. & Woolhandler, S. & Mullan, J. & Carrillo, H. & Himmelstein, D.U., 2001. "Does investor ownership of nursing homes compromise the quality of care?," American Journal of Public Health, American Public Health Association, vol. 91(9), pages 1452-1455.
    18. repec:fth:prinin:455 is not listed on IDEAS
    19. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2005. "Unobserved heterogeneity in stochastic cost frontier models: an application to Swiss nursing homes," Applied Economics, Taylor & Francis Journals, vol. 37(18), pages 2127-2141.
    20. David C. Grabowski, 2004. "A Longitudinal Study of Medicaid Payment, Private-Pay Price and Nursing Home Quality," International Journal of Health Economics and Management, Springer, vol. 4(1), pages 5-26, March.
    21. John Shea, 1997. "Instrument Relevance in Multivariate Linear Models: A Simple Measure," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 348-352, May.
    22. Joshua Angrist & Alan Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Working Papers 834, Princeton University, Department of Economics, Industrial Relations Section..
    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. Cutler, Henry & Gu, Yuanyuan & Bilgrami, Anam & Partington, Andrew, 2023. "The 2021 proposal to increase market forces in the Australian residential aged-care sector," Health Policy, Elsevier, vol. 127(C), pages 60-65.

    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. Laura Di Giorgio & Massimo Filippini & Giuliano Masiero, 2014. "The relationship between costs and quality in nonprofit nursing homes," IdEP Economic Papers 1402, USI Università della Svizzera italiana.
    2. Martin, Cécile, 2014. "Concurrence, prix et qualité de la prise en charge en EHPAD en France : Analyses micro-économétriques," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/13712 edited by Dormont, Brigitte.
    3. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    4. Di Giorgio, L. & Filippini, M. & Masiero, G., 2015. "Structural and managerial cost differences in nonprofit nursing homes," Economic Modelling, Elsevier, vol. 51(C), pages 289-298.
    5. Asadul Islam & Dietrich K. Fausten, 2008. "Skilled Immigration and Wages in Australia," The Economic Record, The Economic Society of Australia, vol. 84(s1), pages 66-82, September.
    6. Alla Koblyakova & Larisa Fleishman & Orly Furman, 2022. "Accuracy of Households’ Dwelling Valuations, Housing Demand and Mortgage Decisions: Israeli Case," The Journal of Real Estate Finance and Economics, Springer, vol. 65(1), pages 48-74, July.
    7. Duchin, R. & Sosyura, D., 2012. "Safer Rations, Riskier Portfolios : Banks’ responses to Government Aid," Other publications TiSEM e67533e7-f388-4860-b65e-0, Tilburg University, School of Economics and Management.
    8. Ahmad Reshad Osmani, 2021. "Conditional Cash Incentive and Use of Health Care Services: New Evidence from a Household Experiment," Journal of Family and Economic Issues, Springer, vol. 42(3), pages 518-532, September.
    9. Norton, E.C., 2016. "Health and Long-Term Care," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 951-989, Elsevier.
    10. Eric Christensen & Richard Arnould, 2005. "The Impact of Asymmetric Information and Ownership on Nursing Home Access," International Journal of Health Economics and Management, Springer, vol. 5(3), pages 273-297, September.
    11. Matthew H Bonds & Andrew P Dobson & Donald C Keenan, 2012. "Disease Ecology, Biodiversity, and the Latitudinal Gradient in Income," PLOS Biology, Public Library of Science, vol. 10(12), pages 1-12, December.
    12. Reece, Christopher & Sam, Abdoul G., 2012. "Impact of Pension Privatization on Foreign Direct Investment," World Development, Elsevier, vol. 40(2), pages 291-302.
    13. Di Giorgio, Laura & Filippini, Massimo & Masiero, Giuliano, 2014. "Implications of global budget payment system on nursing home costs," Health Policy, Elsevier, vol. 115(2), pages 237-248.
    14. Peter Schmidt, 2016. "Internal migration and EU regional policy transfer payments: A panel data analysis for the EU-28 member countries," ERSA conference papers ersa16p172, European Regional Science Association.
    15. Mark Carlson & Kris James Mitchener, 2009. "Branch Banking as a Device for Discipline: Competition and Bank Survivorship during the Great Depression," Journal of Political Economy, University of Chicago Press, vol. 117(2), pages 165-210, April.
    16. Ilona Babenko & Benjamin Bennett & John M Bizjak & Jeffrey L Coles & Jason J Sandvik, 2023. "Clawback Provisions and Firm Risk," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 12(2), pages 191-239.
    17. Henrekson, Magnus & Johansson, Dan, 2010. "Firm Growth, Institutions and Structural Transformation," Ratio Working Papers 150, The Ratio Institute.
    18. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    19. KAMKOUM, Arnaud Cedric, 2023. "The Federal Reserve’s Response to the Global Financial Crisis and its Effects: An Interrupted Time-Series Analysis of the Impact of its Quantitative Easing Programs," Thesis Commons d7pvg, Center for Open Science.
    20. Wang, Xu & Zhang, Xiaobo & Xie, Zhuan & Huang, Yiping, 2016. "Roads to innovation: Firm-level evidence from China:," IFPRI discussion papers 1542, International Food Policy Research Institute (IFPRI).

    More about this item

    Keywords

    Nursing home; Costs; Nonprofit; Single quality indicators; Composite quality indicators; Cost-quality tradeoff; Process quality; Outcome quality; Structure quality;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • L3 - Industrial Organization - - Nonprofit Organizations and Public Enterprise

    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:spr:eujhec:v:17:y:2016:i:8:d:10.1007_s10198-015-0743-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.