Journal of Hospital Infection
Volume 76, Issue 2 , Pages 114-118, October 2010

Sequential analysis of uncommon adverse outcomes

  • A. Morton

      Affiliations

    • Infection Management Services, Princess Alexandra Hospital, Brisbane, Queensland, Australia
    • School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
    • Corresponding Author InformationCorresponding author. Address: 40 Garioch St, Tarragindi 4121, Australia. Tel.: +61 7 33974651; fax: +61 7 38473480.
  • ,
  • K. Mengersen

      Affiliations

    • School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
  • ,
  • M. Waterhouse

      Affiliations

    • School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
    • St Andrew’s Medical Institute, Brisbane, Queensland, Australia
  • ,
  • S. Steiner

      Affiliations

    • Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada
  • ,
  • D. Looke

      Affiliations

    • Infection Management Services, Princess Alexandra Hospital, Brisbane, Queensland, Australia

Received 24 November 2009; accepted 30 April 2010. published online 26 July 2010.

Summary 

Sequential analysis of uncommon adverse outcomes (AEs) such as surgical site infections (SSIs) is desirable. Short postoperative lengths of stay (LOS) result in many SSIs occurring after discharge and they are often superficial. Deep and organ space (complex) SSIs occur less frequently but are detected more reliably and are suitable for monitoring wound care. Those occurring post-discharge usually require readmissison and can be counted accurately. Sequential analysis of meticillin-resistant Staphylococcus aureus bacteraemia is also needed. The key to prevention is to implement systems based on evidence, e.g. using ‘bundles’ and checklists. Regular mortality and morbidity audit meetings are required and these may need to be followed by independent audits. Sequential statistical analysis is desirable for data presentation, to detect changes, and to discourage tampering with processes when occasional AEs occur in a reliable system. Tabulations and cumulative observed minus expected (OE) charts and funnel plots are valuable, supplemented in the presence of apparent ‘runs’ of AEs by cumulative sum analysis. Used prospectively, they may enable staff to visualise and detect patterns or shifts in rates and counts that might not otherwise be apparent.

Keywords: Uncommon adverse events, Complex surgical site infections, MRSA bacteraemias, Statistical process control, Evidence-based systems

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PII: S0195-6701(10)00229-X

doi:10.1016/j.jhin.2010.04.022

Journal of Hospital Infection
Volume 76, Issue 2 , Pages 114-118, October 2010