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Understanding the biases to sepsis surveillance and quality assurance caused by inaccurate coding in administrative health data.
- Source :
- Infection; Apr2024, Vol. 52 Issue 2, p413-427, 15p
- Publication Year :
- 2024
-
Abstract
- Purpose: Timely 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. Methods: We 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. Results: ICD-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). Conclusion: Due 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- PUBLIC health surveillance
RISK assessment
HOSPITAL care
MEDICAL coding software
STATISTICAL sampling
RETROSPECTIVE studies
HOSPITAL mortality
DESCRIPTIVE statistics
GLOBAL burden of disease
SEPSIS
IMPLICIT bias
MEDICAL records
ACQUISITION of data
QUALITY assurance
MANAGEMENT of medical records
COMPARATIVE studies
PREDICTIVE validity
NOSOLOGY
SENSITIVITY & specificity (Statistics)
EVALUATION
Subjects
Details
- Language :
- English
- ISSN :
- 03008126
- Volume :
- 52
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Infection
- Publication Type :
- Academic Journal
- Accession number :
- 176180884
- Full Text :
- https://doi.org/10.1007/s15010-023-02091-y