IDEAS home Printed from https://ideas.repec.org/p/msh/ebswps/2017-20.html
   My bibliography  Save this paper

A panel data analysis of hospital variations in length of stay for hip replacements: Private versus public

Author

Listed:
  • Yan Meng
  • Xueyan Zhao
  • Xibin Zhang
  • Jiti Gao

Abstract

Inequality between private and public patients in Australia has been an ongoing concern due to its two tiered insurance system. This paper investigates the variations in hospital length of stay for hip replacements using Victorian Admitted Episodes Dataset from 2003/2004 to 2014/2015, employing a Bayesian hierarchical random coefficient model with trend allowing for structural break. We find systematic differences in the length of stay between public and private hospitals, after observable patient complexity is controlled. This suggests shorter stay in public hospitals due to pressure from Activity-based funding scheme, and longer stay in private system due to potential moral hazard. Our counterfactual analysis shows that public patients stay 1.4 days shorter than private in 2014, which leads to the 'quicker but sicker' concern that is commonly voiced by the public. We also identify widespread variations among individual hospitals. Sources for such variation warrant closer investigation by policy makers.

Suggested Citation

  • Yan Meng & Xueyan Zhao & Xibin Zhang & Jiti Gao, 2017. "A panel data analysis of hospital variations in length of stay for hip replacements: Private versus public," Monash Econometrics and Business Statistics Working Papers 20/17, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:2017-20
    as

    Download full text from publisher

    File URL: https://www.monash.edu/business/econometrics-and-business-statistics/research/publications/ebs/wp20-17.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    2. Paul H. Jensen & Elizabeth Webster & Julia Witt, 2009. "Hospital type and patient outcomes: an empirical examination using AMI readmission and mortality records," Health Economics, John Wiley & Sons, Ltd., vol. 18(12), pages 1440-1460, December.
    3. Martin, Stephen & Street, Andrew & Han, Lu & Hutton, John, 2016. "Have hospital readmissions increased in the face of reductions in length of stay? Evidence from England," Health Policy, Elsevier, vol. 120(1), pages 89-99.
    4. Sørensen, Torben H. & Olsen, Kim R. & Gyrd-Hansen, Dorte, 2009. "Differences in general practice initiated expenditures across Danish local health authorities--A multilevel analysis," Health Policy, Elsevier, vol. 92(1), pages 35-42, September.
    5. Damien S. Eldridge & Ilke Onur & Malathi Velamuri, 2017. "The impact of private hospital insurance on the utilization of hospital care in Australia," Applied Economics, Taylor & Francis Journals, vol. 49(1), pages 78-95, January.
    6. Orelien, Jean G. & Edwards, Lloyd J., 2008. "Fixed-effect variable selection in linear mixed models using R2 statistics," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1896-1907, January.
    7. Terence C. Cheng & Alfons Palangkaraya & Jongsay Yong, 2014. "Hospital utilization in mixed public--private system: evidence from Australian hospital data," Applied Economics, Taylor & Francis Journals, vol. 46(8), pages 859-870, March.
    8. Rosenberg, Marjorie A & Andrews, Richard W & Lenk, Peter J, 1999. "A Hierarchical Bayesian Model for Predicting the Rate of Nonacceptable In-Patient Hospital Utilization," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 1-8, January.
    9. Savage, Elizabeth & Wright, Donald J., 2003. "Moral hazard and adverse selection in Australian private hospitals: 1989-1990," Journal of Health Economics, Elsevier, vol. 22(3), pages 331-359, May.
    10. Xiaohui Zhang & Katharina Hauck & Xueyan Zhao, 2013. "Patient Safety In Hospitals – A Bayesian Analysis Of Unobservable Hospital And Specialty Level Risk Factors," Health Economics, John Wiley & Sons, Ltd., vol. 22(9), pages 1158-1174, September.
    11. Kim Rose Olsen & Andrew Street, 2008. "The analysis of efficiency among a small number of organisations: How inferences can be improved by exploiting patient‐level data," Health Economics, John Wiley & Sons, Ltd., vol. 17(6), pages 671-681, June.
    12. Honghu Liu & Yan Zheng & Jie Shen, 2008. "Goodness-of-fit measures of R2 for repeated measures mixed effect models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(10), pages 1081-1092.
    13. Gabriel Picone & R. Mark Wilson & Shin‐Yi Chou, 2003. "Analysis of hospital length of stay and discharge destination using hazard functions with unmeasured heterogeneity," Health Economics, John Wiley & Sons, Ltd., vol. 12(12), pages 1021-1034, December.
    14. Yau, Kelvin K. W. & Lee, Andy H. & Ng, Angus S. K., 2003. "Finite mixture regression model with random effects: application to neonatal hospital length of stay," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 359-366, January.
    15. Castelli, Adriana & Jacobs, Rowena & Goddard, Maria & Smith, Peter C., 2013. "Health, policy and geography: Insights from a multi-level modelling approach," Social Science & Medicine, Elsevier, vol. 92(C), pages 61-73.
    16. Alfons Palangkaraya & Jongsay Yong, 2013. "Effects of competition on hospital quality: an examination using hospital administrative data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(3), pages 415-429, June.
    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. Mareike Heimeshoff & Jonas Schreyögg & Oliver Tiemann, 2014. "Employment effects of hospital privatization in Germany," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(7), pages 747-757, September.
    2. Mark Stabile & Sarah Thomson, 2014. "The Changing Role of Government in Financing Health Care: An International Perspective," Journal of Economic Literature, American Economic Association, vol. 52(2), pages 480-518, June.
    3. Lan Nguyen & Andrew C. Worthington, 2023. "Moral hazard in Australian private health insurance: the case of dental care services and extras cover," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(1), pages 157-176, January.
    4. Ha Trong Nguyen & Huong Thu Le & Luke Connelly & Francis Mitrou, 2023. "Accuracy of self‐reported private health insurance coverage," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2709-2729, December.
    5. repec:hal:spmain:info:hdl:2441/3ihldo33ik9ee94procjtfki5f is not listed on IDEAS
    6. Murphy, Aileen & Bourke, Jane & Turner, Brian, 2020. "A two-tiered public-private health system: Who stays in (private) hospitals in Ireland?," Health Policy, Elsevier, vol. 124(7), pages 765-771.
    7. Clifford Afoakwah & Joshua Byrnes & Paul Scuffham & Son Nghiem, 2023. "Testing for selection bias and moral hazard in private health insurance: Evidence from a mixed public‐private health system," Health Economics, John Wiley & Sons, Ltd., vol. 32(1), pages 3-24, January.
    8. Thanassoulis, Emmanuel & Silva Portela, Maria & Graveney, Mike, 2016. "Identifying the scope for savings at inpatient episode level: An illustration applying DEA to chronic obstructive pulmonary disease," European Journal of Operational Research, Elsevier, vol. 255(2), pages 570-582.
    9. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    10. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    11. Jensen, Mark J. & Maheu, John M., 2010. "Bayesian semiparametric stochastic volatility modeling," Journal of Econometrics, Elsevier, vol. 157(2), pages 306-316, August.
    12. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    13. Daiki Maki, 2015. "Wild bootstrap tests for unit root in ESTAR models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(3), pages 475-490, September.
    14. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
    15. Wen Xu, 2016. "Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters," Econometrics, MDPI, vol. 4(4), pages 1-13, October.
    16. Yang Liu & Mariano Croce & Ivan Shaliastovich & Ric Colacito, 2016. "Volatility Risk Pass-Through," 2016 Meeting Papers 135, Society for Economic Dynamics.
    17. Davide Pettenuzzo & Francesco Ravazzolo, 2016. "Optimal Portfolio Choice Under Decision‐Based Model Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
    18. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.
    19. Donelli, Nicola & Peluso, Stefano & Mira, Antonietta, 2021. "A Bayesian semiparametric vector Multiplicative Error Model," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    20. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    21. Lombardi, Marco J. & Calzolari, Giorgio, 2009. "Indirect estimation of [alpha]-stable stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2298-2308, April.

    More about this item

    Keywords

    Gibbs sampler; hierarchical random coefficients; length of stay; hospital ranking.;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

    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:msh:ebswps:2017-20. 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: Professor Xibin Zhang (email available below). General contact details of provider: https://edirc.repec.org/data/dxmonau.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.