Defining Posttraumatic Sepsis for Population-Level Research

Abstract

ImportanceMultiple classification methods are used to identify sepsis from existing data. In the trauma population, it is unknown how administrative methods compare with clinical criteria for sepsis classification.ObjectivesTo characterize the agreement between 3 approaches to sepsis classification among critically ill patients with trauma and compare the sepsis-associated risk of adverse outcomes when each method was used to define sepsis.Design, Setting, and ParticipantsThis retrospective cohort study used data collected between January 1, 2012, and December 31, 2020, from patients aged 16 years or older with traumatic injury, admitted to the intensive care unit of a single-institution level 1 trauma center and requiring invasive mechanical ventilation for at least 3 days. Statistical analysis was conducted from August 1, 2021, to March 31, 2022.ExposureHospital-acquired sepsis, as classified by 3 methods: a novel automated clinical method based on data from the electronic health record, the National Trauma Data Bank (NTDB), and explicit and implicit medical billing codes.Main Outcomes and MeasuresThe primary outcomes were chronic critical illness and in-hospital mortality. Secondary outcomes included number of days in an intensive care unit, number of days receiving mechanical ventilation, discharge to a skilled nursing or long-term care facility, and discharge to home without assistance.ResultsOf 3194 patients meeting inclusion criteria, the median age was 49 years (IQR, 31-64 years), 2380 (74%) were male, and 2826 (88%) sustained severe blunt injury (median Injury Severity Score, 29 [IQR, 21-38]). Sepsis was identified in 747 patients (23%) meeting automated clinical criteria, 118 (4%) meeting NTDB criteria, and 529 (17%) using medical billing codes. The Light κ value for 3-way agreement was 0.16 (95% CI, 0.14-0.19). The adjusted relative risk of chronic critical illness was 9.9 (95% CI, 8.0-12.3) for sepsis identified by automated clinical criteria, 5.0 (95% CI, 3.4-7.3) for sepsis identified by the NTDB, and 4.5 (95% CI, 3.6-5.6) for sepsis identified using medical billing codes. The adjusted relative risk for in-hospital mortality was 1.3 (95% CI, 1.0-1.6) for sepsis identified by automated clinical criteria, 2.7 (95% CI, 1.7-4.3) for sepsis identified by the NTDB, and 1.0 (95% CI, 0.7-1.2) for sepsis identified using medical billing codes.Conclusions and RelevanceIn this cohort study of critically ill patients with trauma, administrative methods misclassified sepsis and underestimated the incidence and severity of sepsis compared with an automated clinical method using data from the electronic health record. This study suggests that an automated approach to sepsis classification consistent with Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) clinical criteria is feasible and may improve existing approaches to health services and population-based research in this population.

Difficulties in Retrospectively Characterizing Sepsis in Patients With Trauma

“…The findings by Stern et al also demonstrate that our reliance on the EMR and large self-reporting electronic databases has become ubiquitous. The dependence on mobile computers and handheld tablets during patient rounds has increased patient data generation to potentially untenable levels.…”

“…Second, analogous to the aforementioned, the retrospective analysis by Stern et al 2 and PROCESS [Protocolized Care for Early Septic Shock]), [5][6][7] which used a similar inclusion criterion and care pathways-EGDT vs standard of care-did not demonstrate a clinical statistical difference between the 2 pathways. This is not surprising.…”

“…By interrogating their institutional electronic medical record (EMR), the National Trauma Data Bank (NTDB), and patients’ International Classification of Diseases ( ICD ) codes, Stern et al investigated 3 methods to identify patients with sepsis. Sepsis was defined by the 2016 Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) consensus guidelines .…”

“…Second, analogous to the aforementioned, the retrospective analysis by Stern et al was contingent on the accuracy of large databases and the translation of clinical information into a coding structure that may not comprehensively capture a patient’s clinical status. This clinical status is best diagnosed by performance of a bedside physical examination.…”

“…Finally, Stern et al performed a retrospective investigation. There are numerous proprietary algorithms that can interrogate an EMR, providing real-time analysis identifying patients who may present with early sepsis.…”