• Critical care medicine · Dec 2024

    Adjudication of Codes for Identifying Sepsis in Hospital Administrative Data by Expert Consensus.

    • Allan Garland, Na Li, Wendy Sligl, Alana Lane, Kednapa Thavorn, M Elizabeth Wilcox, Bram Rochwerg, Sean Keenan, Thomas J Marrie, Anand Kumar, Emily Curley, Jennifer Ziegler, Peter Dodek, Osama Loubani, Alain Gervais, Srinivas Murthy, Gina Neto, Hallie C Prescott, and Sepsis Canada Network.
    • Department of Medicine, University of Manitoba, Winnipeg, MB, Canada.
    • Crit. Care Med. 2024 Dec 1; 52 (12): 184518551845-1855.

    ObjectivesRefine the administrative data definition of sepsis in hospitalized patients, including less severe cases.Design And SettingFor each of 1928 infection and 108 organ dysfunction codes used in Canadian hospital abstracts, experts reached consensus on the likelihood that it could relate to sepsis. We developed a new algorithm, called AlgorithmL, that requires at least one infection and one organ dysfunction code adjudicated as likely or very likely to be related to sepsis. AlgorithmL was compared with four previously described algorithms, regarding included codes, population-based incidence, and hospital mortality rates-separately for ICU and non-ICU cohorts in a large Canadian city. We also compared sepsis identification from these code-based algorithms with the Centers for Disease Control's Adult Sepsis Event (ASE) definition.SubjectsAmong Calgary's adult population of 1.033 million there were 61,632 eligible hospitalizations.InterventionsNone.Measurements And Main ResultsAlgorithmL includes 720 infection codes and 50 organ dysfunction codes. Comparison algorithms varied from 42-941 infection codes to 2-36 organ codes. There was substantial nonoverlap of codes in AlgorithmL vs. the comparators. Annual sepsis incidence rates (per 100,000 population) based on AlgorithmL were 91 in the ICU and 291 in the non-ICU cohort. Incidences based on comparators ranged from 28-77 for ICU to 11-266 for non-ICU cohorts. Hospital sepsis mortality rates based on AlgorithmL were 24% in ICU and 17% in non-ICU cohorts; based on comparators, they ranged 27-38% in the ICU cohort and 18-47% for the non-ICU cohort. Of AlgorithmL-identified cases, 41% met the ASE criteria, compared with 42-82% for the comparator algorithms.ConclusionsCompared with other code-based algorithms, AlgorithmL includes more infection and organ dysfunction codes. AlgorithmL incidence rates are higher; hospital mortality rates are lower. AlgorithmL may more fully encompass the full range of sepsis severity.Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine and Wolters Kluwer Health, Inc.

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