Use of explicit ICD9-CM codes to identify adult severe sepsis: impacts on epidemiological estimates
Open accessAbstract
BACKGROUND: Severe sepsis is a challenge for healthcare systems, and epidemiological studies are essential to assess its burden and trends. However, there is no consensus on which coding strategy should be used to reliably identify severe sepsis. This study assesses the use of explicit codes to define severe sepsis and the impacts of this on the incidence and in-hospital mortality rates. METHODS: We examined episodes of severe sepsis in adults aged ≥18 years registered in the 2006-2011 national hospital discharge database, identified in an exclusive manner by two ICD-9-CM coding strategies: (1) those assigned explicit ICD-9-CM codes (995.92, 785.52); and (2) those assigned combined ICD-9-CM infection and organ dysfunction codes according to modified Martin criteria. The coding strategies were compared in terms of the populations they defined and their relative implementation. Trends were assessed using Joinpoint regression models and expressed as annual percentage change (APC). RESULTS: Of 222 846 episodes of severe sepsis identified, 138 517 (62.2 %) were assigned explicit codes and 84 329 (37.8 %) combination codes; incidence rates were 60.6 and 36.9 cases per 100 000 inhabitants, respectively. Despite similar demographic characteristics, cases identified by explicit codes involved fewer comorbidities, fewer registered pathogens, greater extent of organ dysfunction (two or more organs affected in 60 % versus 26 % of cases) and higher in-hospital mortality (54.5 % versus 29 %; risk ratio 1.86, 95 % CI 1.83, 1.88). Between 2006 and 2011, explicit codes were increasingly implemented. Standardised incidence rates in this cohort increased over time with an APC of 12.3 % (95 % CI 4.4, 20.8); in the combination code cohort, rates increased by 3.8 % (95 % CI 1.3, 6.3). A decreasing trend in mortality was observed in both cohorts though the APC was -8.1 % (95 % CI -10.4, -5.7) in the combination code cohort and -3.5 % (95 % CI -3.9, -3.2) in the explicit code cohort. CONCLUSIONS: Our findings suggest greater and increasing use of explicit codes for adult severe sepsis in Spain. This trend will have substantial impacts on epidemiological estimates, because these codes capture cases featuring greater organ dysfunction and in-hospital mortality.
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Many studies use ICD coding, which may be an unreliable instrument to identify septic patients.
“Many studies use ICD coding, which may be an unreliable instrument to identify septic patients [44, 45].”
From Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy (2020) · cites this paper as [45]
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- Authors
- Bouza, C., Lopez-Cuadrado, T., & Amate-Blanco, J. M.
- Affiliations
- Instituto de Salud Carlos III (ES)
- Corresponding author
- Bouza, C.
- ORCID
- Bouza, C.
- Venue
- Critical Care
- Published
- 2016-10-03
- Volume
- 20
- Issue
- 1
- Pages
- 313-313
- ISSN
- 1364-8535 (ISSN-L)
- PMC
- PMC5047045
- OpenAlex
- W2524000875
- Cited by
- 47
- References
- 41
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 7 · 2023: 3 · 2022: 6 · 2021: 7 · 2020: 11 · 2019: 4 · 2018: 3 · 2017: 3 · 2016: 1
- FWCI
- 3.44
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Critical Care (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
- Funders
- Instituto de Salud Carlos III (STPY 1346/09)
- Topics
- Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Keywords
- severe sepsis, ICD-9-CM codes, sepsis incidence, in-hospital mortality, hospital discharge data, organ dysfunction, sepsis surveillance, incidence trends, adult sepsis, comorbidities, pathogenic microorganisms, mortality trends, sepsis definitions
- MeSH terms
- Aged, Female, Humans, Male, Middle Aged, Spain, Cohort Studies, Incidence, Epidemiologic Studies, Sepsis, International Classification of Diseases
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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