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Hospital readmission rates: Signal of failure or success?

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  • Laudicella, Mauro
  • Li Donni, Paolo
  • Smith, Peter C.

Abstract

Hospital readmission rates are increasingly used as signals of hospital performance and a basis for hospital reimbursement. However, their interpretation may be complicated by differential patient survival rates. If patient characteristics are not perfectly observable and hospitals differ in their mortality rates, then hospitals with low mortality rates are likely to have a larger share of un-observably sicker patients at risk of a readmission. Their performance on readmissions will then be underestimated. We examine hospitals’ performance relaxing the assumption of independence between mortality and readmissions implicitly adopted in many empirical applications. We use data from the Hospital Episode Statistics on emergency admissions for fractured hip in 290,000 patients aged 65 and over from 2003 to 2008 in England. We find evidence of sample selection bias that affects inference from traditional models. We use a bivariate sample selection model to allow for the selection process and the dichotomous nature of the outcome variables.

Suggested Citation

  • Laudicella, Mauro & Li Donni, Paolo & Smith, Peter C., 2013. "Hospital readmission rates: Signal of failure or success?," Journal of Health Economics, Elsevier, vol. 32(5), pages 909-921.
  • Handle: RePEc:eee:jhecon:v:32:y:2013:i:5:p:909-921
    DOI: 10.1016/j.jhealeco.2013.06.004
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Sam Watson’s journal round-up for 21st August 2017
      by Sam Watson in The Academic Health Economists' Blog on 2017-08-21 16:00:35

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    Cited by:

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    2. Lobo, Mariana F & Azzone, Vanessa & Lopes, Fernando & Freitas, Alberto & Costa-Pereira, Altamiro & Normand, Sharon-Lise & Teixeira-Pinto, Armando, 2020. "Understanding the large heterogeneity in hospital readmissions and mortality for acute myocardial infarction," Health Policy, Elsevier, vol. 124(7), pages 684-694.
    3. Moscone, Francesco & Siciliani, Luigi & Tosetti, Elisa & Vittadini, Giorgio, 2020. "Do public and private hospitals differ in quality? Evidence from Italy," Regional Science and Urban Economics, Elsevier, vol. 83(C).
    4. Moscelli, Giuseppe & Siciliani, Luigi & Tonei, Valentina, 2016. "Do waiting times affect health outcomes? Evidence from coronary bypass," Social Science & Medicine, Elsevier, vol. 161(C), pages 151-159.
    5. Moscelli, Giuseppe & Gravelle, Hugh & Siciliani, Luigi & Santos, Rita, 2018. "Heterogeneous effects of patient choice and hospital competition on mortality," Social Science & Medicine, Elsevier, vol. 216(C), pages 50-58.
    6. Damien Bricard & Zeynep Or, 2019. "Impact of early primary care follow-up after discharge on hospital readmissions," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(4), pages 611-623, June.
    7. Irene Papanicolas & Alistair McGuire, 2017. "Measuring and forecasting quality in English hospitals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 409-432, February.
    8. Nan Jiang & Gail Pacheco, 2014. "Demand in New Zealand hospitals: expect the unexpected?," Applied Economics, Taylor & Francis Journals, vol. 46(36), pages 4475-4489, December.
    9. Kuhlmey, Florian & Minke, Matthias, 2018. "Estimating Survival Times Using Swiss Hospital Data," Working papers 2018/14, Faculty of Business and Economics - University of Basel.
    10. Laudicella, Mauro & Di Donni, Paolo & Rose Olsen, Kim & Gyrd-Hansen, Dorte, 2020. "Age, morbidity, or something else? A residual approach using microdata to measure the impact of technological progress on health care expenditure," DaCHE discussion papers 2020:4, University of Southern Denmark, Dache - Danish Centre for Health Economics.
    11. Rowena Jacobs & Martin Chalkley & María José Aragón & Jan R. Böhnke & Mike Clark & Valerie Moran & Simon Gilbody, 2016. "Funding of mental health services: Do available data support episodic payment?," Working Papers 137cherp, Centre for Health Economics, University of York.
    12. Guccio, C. & Lisi, D. & Martorana, M.F. & Pignataro, G., 2020. "Incorporating quality in the efficiency assessment of hospitals using a generalized directional distance function approach," Health, Econometrics and Data Group (HEDG) Working Papers 20/17, HEDG, c/o Department of Economics, University of York.
    13. Stephen Martin & Andrew Street & Lu Han & John Hutton, 2014. "The impact of hospital financing on the quality of inpatient care in England," Working Papers 105cherp, Centre for Health Economics, University of York.

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    More about this item

    Keywords

    Hospital performance; Mortality rates; Readmission rates; Sample selection; Hip fractures;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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