Sepsis surveillance from administrative data in the absence of a perfect verification

S. Reza Jafarzadeh, Benjamin S. Thomas, Jeff Gill, Victoria J. Fraser, Jonas Marschall, David K. Warren

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Purpose Past studies of sepsis epidemiology did not address misclassification bias due to imperfect verification of sepsis detection methods to estimate the true prevalence. Methods We examined 273,126 hospitalizations from 2008 to 2012 at a tertiary-care center to develop surveillance-aimed sepsis detection criteria, based on the presence of the sepsis-explicit International Classification of Diseases, Ninth Revision, Clinical Modification codes (995.92 or 785.52), blood culture orders, and antibiotics administration. We used Bayesian multinomial latent class models to estimate the true prevalence of sepsis, while adjusting for the imperfect sensitivity and specificity and the conditional dependence among the individual criteria. Results The apparent annual prevalence of sepsis hospitalizations based on explicit International Classification of Diseases, Ninth Revision, Clinical Modification codes were 1.5%, 1.4%, 1.6%, 2.2%, and 2.5% for the years 2008 to 2012. Bayesian posterior estimates for the true prevalence of sepsis suggested that it remained stable from 2008, 19.2% (95% credible interval [CI]: 17.9%, 22.9%), to 2012, 17.8% (95% CI: 16.8%, 20.2%). The sensitivity of sepsis-explicit codes, however, increased from 7.6% (95% CI: 6.4%, 8.4%) in 2008 to 13.8% (95% CI: 12.2%, 14.9%) in 2012. Conclusions The true prevalence of sepsis remained high, but stable despite an increase in the sensitivity of sepsis-explicit codes in administrative data.

Original languageEnglish
Pages (from-to)717-722.e1
JournalAnnals of Epidemiology
Volume26
Issue number10
DOIs
StatePublished - Oct 1 2016

Keywords

  • Bayesian estimation
  • No reference standard
  • Prevalence
  • Sensitivity
  • Sepsis
  • Specificity
  • Surveillance

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