Updated estimates of sepsis hospitalizations at United States academic medical centers - Hei Kit Chan; Swapnil Khose; Summer Chavez; Bela Patel; Henry E. Wang (Journal of the American College of Emergency Physicians Open, 2022)
Abstract Objective Sepsis is a major public health problem. Understanding the epidemiology of sepsis subtypes is important to quantify the magnitude of the problem and identify targets for system wide treatment strategies. We sought to describe the current national epidemiology of community‐acquired (CAS), hospital‐acquired (HAS) and healthcare‐associated sepsis (HCAS) hospitalizations among academic medical centers in the United States using current discharge diagnosis taxonomies. Methods Retrospective analysis of patient discharge data from the Vizient Clinical Data Base/Resource Manager. We identified sepsis hospitalizations using four ICD‐10 coding strategies: (1) “Martin” sepsis codes (21 ICD‐10 codes), (2) “Angus” sepsis codes (ICD‐10 infection + ICD‐10 organ dysfunction), (3) Medicare “SEP‐1” codes (28 ICD‐10 codes), and (4) “explicit sepsis” codes (ICD‐10 R65.20 and R65.21). Using present‐on‐admission flags for each diagnosis, we also distinguished: (1) community‐acquired sepsis (CAS), (2) hospital‐acquired sepsis (HAS), and (3) healthcare associated sepsis (HCAS). Results Among 22,655,240 hospitalizations, the number and incidence of sepsis hospitalizations were: (1) Martin (n = 1,718,257, 75.8 per 1000 hospitalizations), (2) Angus (n = 2,749,163, 121.3 per 1000), (3) SEP‐1 (n = 1,624,909, 71.7 per 1000), and (4) explicit sepsis (n = 655,853, 28.9 per 1000). CAS was the most common sepsis subtype. HAS exhibited higher adjusted mortality than CAS. ICU admission was highest for HAS (Martin, 1.5%; Angus, 1.5%; SEP‐1, 1.6%; Explicit, 1.9%). Conclusions These results illustrate the prevalence of sepsis at US academic medical centers using the most current sepsis classification taxonomies and discharge diagnosis codes. These results highlight important considerations when using hospital discharge data to characterize the epidemiology of sepsis.