Sepsis as 2 problems: Identifying sepsis at admission and predicting onset in the hospital using an electronic medical record-based acuity score

Michael Rothman, Mitchell Levy, R Philip Dellinger, Stephen L Jones, Robert L Fogerty, Kirk G Voelker, Barry Gross, Albert Marchetti, Joseph Beals

Research output: Contribution to journalArticle

21 Scopus citations

Abstract

PURPOSE: Early identification and treatment improve outcomes for patients with sepsis. Current screening tools are limited. We present a new approach, recognizing that sepsis patients comprise 2 distinct and unequal populations: patients with sepsis present on admission (85%) and patients who develop sepsis in the hospital (15%) with mortality rates of 12% and 35%, respectively.

METHODS: Models are developed and tested based on 258 836 adult inpatient records from 4 hospitals. A "present on admission" model identifies patients admitted to a hospital with sepsis, and a "not present on admission" model predicts postadmission onset. Inputs include common clinical measurements and the Rothman Index. Sepsis was determined using International Classification of Diseases, Ninth Revision, codes.

RESULTS: For sepsis present on admission, area under the curves ranged from 0.87 to 0.91. Operating points chosen to yield 75% and 50% sensitivity achieve positive predictive values of 17% to 25% and 29% to 40%, respectively. For sepsis not present on admission, at 65% sensitivity, positive predictive values ranged from 10% to 20% across hospitals.

CONCLUSIONS: This approach yields good to excellent discriminatory performance among adult inpatients for predicting sepsis present on admission or developed within the hospital and may aid in the timely delivery of care.

Original languageEnglish (US)
Pages (from-to)237-244
Number of pages8
JournalJournal of Critical Care
Volume38
DOIs
StatePublished - Dec 3 2016

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