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Commissioned analysis of surgical performance using routine data: lessons from the Bristol inquiry

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  • David J. Spiegelhalter
  • Paul Aylin
  • Nicola G. Best
  • Stephen J. W. Evans
  • Gordon D. Murray

Abstract

The public inquiry into paediatric cardiac surgery at the Bristol Royal Infirmary commissioned the authors to design and conduct analyses of routine data sources to compare surgical outcomes between centres. Such analyses are necessarily complex in this context but were further hampered by the inherent inconsistencies and mediocre quality of the various sources of data. Three levels of analysis of increasing sophistication were carried out. The reasonable consistency of the results arising from different sources of data, together with a number of sensitivity analyses, led us to conclude that there had been excess mortality in Bristol in open heart operations on children under 1 year of age. We consider criticisms of our analysis and discuss the role of statisticians in this inquiry and their contribution to the final report of the inquiry. The potential statistical role in future programmes for monitoring clinical performance is highlighted.

Suggested Citation

  • David J. Spiegelhalter & Paul Aylin & Nicola G. Best & Stephen J. W. Evans & Gordon D. Murray, 2002. "Commissioned analysis of surgical performance using routine data: lessons from the Bristol inquiry," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(2), pages 191-221, June.
    • Handle: RePEc:bla:jorssa:v:165:y:2002:i:2:p:191-221
    DOI: 10.1111/1467-985X.02021
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    References listed on IDEAS

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    1. John F. Y. Brookfield, 2001. "Predicting the future," Nature, Nature, vol. 411(6841), pages 999-999, June.
    2. Burgess Jr., James F. & Christiansen, Cindy L. & Michalak, Sarah E. & Morris, Carl N., 2000. "Medical profiling: improving standards and risk adjustments using hierarchical models," Journal of Health Economics, Elsevier, vol. 19(3), pages 291-309, May.
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    Cited by:

    1. David I. Ohlssen & Linda D. Sharples & David J. Spiegelhalter, 2007. "A hierarchical modelling framework for identifying unusual performance in health care providers," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 865-890, October.
    2. Trevor C. Bailey & Paul J. Hewson, 2004. "Simultaneous modelling of multiple traffic safety performance indicators by using a multivariate generalized linear mixed model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(3), pages 501-517, August.
    3. Sheila M. Bird & Cox Sir David & Vern T. Farewell & Goldstein Harvey & Holt Tim & Smith Peter C., 2005. "Performance indicators: good, bad, and ugly," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 1-27, January.
    4. Coolen, F.P.A. & Coolen-Schrijner, P., 2006. "Nonparametric predictive subset selection for proportions," Statistics & Probability Letters, Elsevier, vol. 76(15), pages 1675-1684, September.
    5. Nicholas Longford & D. B. Rubin, 2006. "Performance assessment and league tables. Comparing like with like," Economics Working Papers 994, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Sylvia Richardson, 2022. "Statistics in times of increasing uncertainty," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1471-1496, October.
    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. Clare Marshall & Nicky Best & Alex Bottle & Paul Aylin, 2004. "Statistical issues in the prospective monitoring of health outcomes across multiple units," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(3), pages 541-559, August.

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