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Hospital Variation in Patient-Reported Outcomes at the Level of EQ-5D Dimensions

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  • Nils Gutacker
  • Chris Bojke
  • Silvio Daidone
  • Nancy Devlin
  • Andrew Street

Abstract

Background . The English Department of Health has introduced routine collection of patient-reported outcome data for selected surgical procedures to facilitate patient choice and increase hospital accountability. However, using aggregate health outcome scores, such as EQ-5D utilities, for performance assessment purposes causes information loss and raises statistical and normative concerns. Objectives . For hip replacement surgery, we explore a) the change in patient-reported outcomes between baseline and follow-up on 5 health dimensions (EQ-5D), b) the extent to which treatment impact varies across hospitals, and c) the extent to which hospital performance on EQ-5D dimensions is correlated with performance on the EQ-5D utility index. Methods . We combine information on pre- and postoperative EQ-5D outcomes with routine inpatient data for the financial year 2009–2010. The sample consists of 21,000 patients in 153 hospitals. We employ hierarchical ordered probit risk-adjustment models that recognize the multilevel nature of the data and the response distributions. The treatment impact is modeled as a random coefficient that varies at the hospital level. We obtain hospital-specific empirical Bayes (EB) estimates of this coefficient. We estimate separate models for each EQ-5D dimension and the EQ-5D utility index and analyze correlations of EB estimates across these. Results . Hospital treatment is associated with improvements in all EQ-5D dimensions. Variability in treatment impact is most pronounced on the mobility and usual activities dimensions. Conversely, only pain/discomfort and anxiety/depression correlate well with performance measures based on utilities. This leads to different assessments of hospital performance across metrics. Conclusions . Our results indicate which hospitals are better than others in improving health across particular EQ-5D dimensions. We demonstrate the importance of evaluating dimensions of the EQ-5D separately for the purposes of hospital performance assessment.

Suggested Citation

  • Nils Gutacker & Chris Bojke & Silvio Daidone & Nancy Devlin & Andrew Street, 2013. "Hospital Variation in Patient-Reported Outcomes at the Level of EQ-5D Dimensions," Medical Decision Making, , vol. 33(6), pages 804-818, August.
    • Handle: RePEc:sae:medema:v:33:y:2013:i:6:p:804-818
    DOI: 10.1177/0272989X13482523
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    References listed on IDEAS

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    Cited by:

    1. Matthew Skellern, 2017. "The hospital as a multi-product firm: the effect of hospital competition on value-added indicators of clinical quality," CEP Discussion Papers dp1484, Centre for Economic Performance, LSE.
    2. Henry Bailey & Mathieu F Janssen & Althea La Foucade & Paul Kind, 2019. "EQ-5D-5L population norms and health inequalities for Trinidad and Tobago," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-14, April.
    3. McCarthy, Ian M., 2016. "Eliminating composite bias in treatment effects estimates: Applications to quality of life assessment," Journal of Health Economics, Elsevier, vol. 50(C), pages 47-58.
    4. Luigi Siciliani & James Gaughan & Nils Gutacker & Hugh Gravelle & Martin Chalkley, 2021. "Paying for health gains," Working Papers 183cherp, Centre for Health Economics, University of York.
    5. Nils Gutacker & Andrew Street, 2015. "Multidimensional performance assessment using dominance criteria," Working Papers 115cherp, Centre for Health Economics, University of York.
    6. Gutacker, Nils & Bloor, Karen & Bojke, Chris & Walshe, Kieran, 2018. "Should interventions to reduce variation in care quality target doctors or hospitals?," Health Policy, Elsevier, vol. 122(6), pages 660-666.
    7. Gutacker, Nils & Siciliani, Luigi & Moscelli, Giuseppe & Gravelle, Hugh, 2016. "Choice of hospital: Which type of quality matters?," Journal of Health Economics, Elsevier, vol. 50(C), pages 230-246.
    8. Nils Gutacker & Thomas Patton & Koonal Shah & David Parkin, 2020. "Using EQ-5D Data to Measure Hospital Performance: Are General Population Values Distorting Patients’ Choices?," Medical Decision Making, , vol. 40(4), pages 511-521, May.

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