Sepsis surveillance from administrative data in the absence of a perfect verification.
Past studies of sepsis epidemiology did not address misclassification bias due to imperfect verification of sepsis detection methods to estimate the true prevalence.



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.



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.



The true prevalence of sepsis remained high, but stable despite an increase in the sensitivity of sepsis-explicit codes in administrative data.
Department of Medicine, Washington University School of Medicine, St. Louis, MO. Electronic address: srjafarz@bu.edu.
S Reza
SR
Jafarzadeh
Department of Medicine, Washington University School of Medicine, St. Louis, MO; Department of Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu.
Benjamin S
BS
Thomas
Division of Biostatistics, Washington University School of Medicine, St. Louis, MO; Division of Public Health Sciences, Washington University School of Medicine, St. Louis, MO.
Jeff
J
Gill
Department of Medicine, Washington University School of Medicine, St. Louis, MO.
Victoria J
VJ
Fraser
Department of Medicine, Washington University School of Medicine, St. Louis, MO; Department of Infectious Diseases, Bern University Hospital and University of Bern, Bern, Switzerland.
Jonas
J
Marschall
Department of Medicine, Washington University School of Medicine, St. Louis, MO.
David K
DK
Warren
D001499:Bayes Theorem; D016208:Databases, Factual; D005260:Female; D006306:Health Surveys; D017052:Hospital Mortality; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D015995:Prevalence; D011634:Public Health; D012189:Retrospective Studies; D018570:Risk Assessment; D018805:Sepsis / Q000145:classification* / Q000453:epidemiology* / Q000503:physiopathology; D016019:Survival Analysis; D014481:United States / Q000453:epidemiology
Bayesian estimation; No reference standard; Prevalence; Sensitivity; Sepsis; Specificity; Surveillance