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Statistical issues in the prospective monitoring of health outcomes across multiple units

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  • Clare Marshall
  • Nicky Best
  • Alex Bottle
  • Paul Aylin

Abstract

Summary. Following several recent inquiries in the UK into medical malpractice and failures to deliver appropriate standards of health care, there is pressure to introduce formal monitoring of performance outcomes routinely throughout the National Health Service. Statistical process control (SPC) charts have been widely used to monitor medical outcomes in a variety of contexts and have been specifically advocated for use in clinical governance. However, previous applications of SPC charts in medical monitoring have focused on surveillance of a single process over time. We consider some of the methodological and practical aspects that surround the routine surveillance of health outcomes and, in particular, we focus on two important methodological issues that arise when attempting to extend SPC charts to monitor outcomes at more than one unit simultaneously (where a unit could be, for example, a surgeon, general practitioner or hospital): the need to acknowledge the inevitable between‐unit variation in ‘acceptable’ performance outcomes due to the net effect of many small unmeasured sources of variation (e.g. unmeasured case mix and data errors) and the problem of multiple testing over units as well as time. We address the former by using quasi‐likelihood estimates of overdispersion, and the latter by using recently developed methods based on estimation of false discovery rates. We present an application of our approach to annual monitoring ‘all‐cause’ mortality data between 1995 and 2000 from 169 National Health Service hospital trusts in England and Wales.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:jorssa:v:167:y:2004:i:3:p:541-559
    DOI: 10.1111/j.1467-985X.2004.apm10.x
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    References listed on IDEAS

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    1. Christian Sonesson & David Bock, 2003. "A review and discussion of prospective statistical surveillance in public health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(1), pages 5-21, February.
    2. 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.
    3. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
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    Citations

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    Cited by:

    1. Marianne Frisén, 2014. "Spatial outbreak detection based on inference principles for multivariate surveillance," IISE Transactions, Taylor & Francis Journals, vol. 46(8), pages 759-769, August.
    2. Du, Lilun & Wen, Mengtao, 2023. "False discovery rate approach to dynamic change detection," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
    3. Frisén, Marianne, 2011. "On multivariate control charts," Research Reports 2011:2, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    4. Frisén, Marianne, 2008. "Introduction to financial surveillance," Research Reports 2008:1, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    5. Frisén, Marianne, 2011. "Inference Principles For Multivariate Surveillance," Research Reports 2011:5, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    6. Marianne Frisen & Eva Andersson & Linus Schioler, 2010. "Evaluation of multivariate surveillance," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(12), pages 2089-2100.
    7. Willem Albers, 2011. "Control charts for health care monitoring under overdispersion," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 74(1), pages 67-83, July.
    8. 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.
    9. O. A. Grigg & D. J. Spiegelhalter & H. E. Jones, 2009. "Local and marginal control charts applied to methicillin resistant Staphylococcus aureus bacteraemia reports in UK acute National Health Service trusts," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 49-66, January.
    10. Frisén, Marianne, 2011. "Methods and evaluations for surveillance in industry, business, finance, and public health," Research Reports 2011:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    11. Frisén, Marianne & Andersson, Eva, 2008. "Semiparametric surveillance of outbreaks," Research Reports 2007:11, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.

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