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

Jafarzadeh, S Reza; Thomas, Benjamin S; Gill, Jeff; Fraser, Victoria J; Marschall, Jonas; Warren, David K (2016). Sepsis surveillance from administrative data in the absence of a perfect verification. Annals of epidemiology, 26(10), 717-722.e1. Elsevier 10.1016/j.annepidem.2016.08.002

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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.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Infectiology

UniBE Contributor:

Marschall, Jonas

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1873-2585

Publisher:

Elsevier

Language:

English

Submitter:

Annelies Luginbühl

Date Deposited:

15 Nov 2016 08:21

Last Modified:

15 Nov 2016 08:21

Publisher DOI:

10.1016/j.annepidem.2016.08.002

PubMed ID:

27600804

Uncontrolled Keywords:

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

BORIS DOI:

10.7892/boris.89049

URI:

https://boris.unibe.ch/id/eprint/89049

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