ArticleInfection2024
Understanding the biases to sepsis surveillance and quality assurance caused by inaccurate coding in administrative health data.
Article in Infection, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Healthcare pathways and outpatient management prior to community-acquired sepsis hospitalization in Germany, 2016-2019.Infection · 2026Article
- Cancer Patients with Sepsis: Prognostic Insights from a Population-Based Cohort Study in Norway.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
- Think sepsis, write sepsis, code sepsis - patient characteristics associated with sepsis (under-)coding in administrative health data.Infection · 2026Article
- An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study.NPJ digital medicine · 2026Article
- Early time-weighted average PEEP and mortality in sepsis-associated myocardial injury requiring invasive mechanical ventilation: a retrospective cohort study with external validation.Frontiers in cellular and infection microbiology · 2026Article
- Positive and unlabeled learning from hospital administrative data: a novel approach to identify sepsis cases.Health care management science · 2025Article
- Transitional care after hospitalization for sepsis in Germany- results from the population-based AVENIR cohort study.Infection · 2025Article
- Prediction of postoperative infections by strategic data imputation and explainable machine learning.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Article
- Rehospitalizations for ambulatory care sensitive conditions in sepsis survivors- a nationwide cohort study using health claims data 2016-2019.Infection · 2025Article
- Sex differences in sepsis outcomes across the lifespan: a population-based cohort study in Germany.Critical care (London, England) · 2025Article
- Development and validation of an interpretable machine learning model for retrospective identification of suspected infection for sepsis surveillance: a multicentre cohort study.EClinicalMedicine · 2025Article
- Epidemiology and palliative care of in-patient cerebral metastases cases in Germany.Journal of neuro-oncology · 2025Article
- Impacts of the COVID-19 pandemic on sepsis incidence, etiology and hospitalization costs in France: a retrospective observational study.BMC infectious diseases · 2025Observational
- Digital innovation in healthcare: quantifying the impact of digital sepsis screening tools on patient outcomes-a multi-site natural experiment.BMJ health & care informatics · 2025Article
- In-patient neurosurgical tumor treatments for malignant glioma patients in Germany.Journal of neuro-oncology · 2024Article
- Observational
- Article
- Deficits in blood culture collection in the emergency department if sepsis is suspected: results of a retrospective cohort study.Infection · 2024Article
- Article
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32 authors.
Funding
Abstract
purposeTimely and accurate data on the epidemiology of sepsis are essential to inform policy decisions and research priorities. We aimed to investigate the validity of inpatient administrative health data (IAHD) for surveillance and quality assurance of sepsis care.
methodsWe conducted a retrospective validation study in a disproportional stratified random sample of 10,334 inpatient cases of age ≥ 15 years treated in 2015-2017 in ten German hospitals. The accuracy of coding of sepsis and risk factors for mortality in IAHD was assessed compared to reference standard diagnoses obtained by a chart review. Hospital-level risk-adjusted mortality of sepsis as calculated from IAHD information was compared to mortality calculated from chart review information.
resultsICD-coding of sepsis in IAHD showed high positive predictive value (76.9-85.7% depending on sepsis definition), but low sensitivity (26.8-38%), which led to an underestimation of sepsis incidence (1.4% vs. 3.3% for severe sepsis-1). Not naming sepsis in the chart was strongly associated with under-coding of sepsis. The frequency of correctly naming sepsis and ICD-coding of sepsis varied strongly between hospitals (range of sensitivity of naming: 29-71.7%, of ICD-diagnosis: 10.7-58.5%). Risk-adjusted mortality of sepsis per hospital calculated from coding in IAHD showed no substantial correlation to reference standard risk-adjusted mortality (r = 0.09).
conclusionDue to the under-coding of sepsis in IAHD, previous epidemiological studies underestimated the burden of sepsis in Germany. There is a large variability between hospitals in accuracy of diagnosing and coding of sepsis. Therefore, IAHD alone is not suited to assess quality of sepsis care.
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