Article Text

Download PDFPDF

Cutting edge methodology
P1-61 Can routine hospital activity data be utilised to provide reliable information about hospital incidence of cases of severe sepsis?
  1. P Warner1,
  2. T Walsh2,
  3. L Williams1,
  4. A Hay3,
  5. E Carduff1,
  6. S Mackenzie3,
  7. M Bain4,
  8. R Prescott1
  1. 1Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK
  2. 2Queen's Medical Research Institute, The University of Edinburgh, Edinburgh, UK
  3. 3Royal Infirmary, Edinburgh, UK
  4. 4NHS National Services Scotland, Edinburgh, UK


Introduction “Severe sepsis”, defined as sepsis plus organ failure, is a heterogeneous and complex condition which occurs across all specialities, causes significant morbidity and mortality (case fatality rate about 30%), and consumes substantial healthcare resources. Yet the diagnostic coding schemes commonly in use do not have a code for this prognostically-important diagnosis, and epidemiological data are hence scarce. Our study aimed to develop an algorithm to ascertain cases of severe sepsis from routine hospital data.

Method The algorithm was developed iteratively, utilising Scottish hospital activity data (n=133 597 selected admissions ie, having an infection code and/or hospital death), secondary analysis of national prospectively-collected critical care research data (n=2687) and expert clinical judgement, followed by validation against case note review (n=1058).

Results The algorithm developed had sensitivity 74% (95% CI 69% to 78%) and estimated specificity was 94%. Applied to all Scottish hospital activity data for 2005 (n=883 K), the algorithm gave an estimate of annual incidence of severe sepsis (2.7%) and case mortality (34%). Analyses were undertaken of factors associated with severe sepsis and outcomes. For example, it was found that in those with severe sepsis, critical care admission was less common in females and those aged over 70 years.

Conclusion Internationally, this is the first rigorously-validated algorithm to detect severe sepsis, and performance is impressive given the complex nature of the condition. Application of the algorithm to provide reliable hospital-wide case rates will allow monitoring of incidence and outcomes, and better-informed planning of intensive care services.

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.