Performance of hospital administrative data for detection of sepsis in Australia: The sepsis coding and documentation (SECOND) study.
Health Inf Manag
; : 18333583221107713, 2022 Jun 27.
Article
em En
| MEDLINE
| ID: mdl-35676098
ABSTRACT
BACKGROUND:
Sepsis is the world's leading cause of death and its detection from a range of data and coding sources, consistent with consensus clinical definition, is desirable.OBJECTIVE:
To evaluate the performance of three coding definitions (explicit, implicit, and newly proposed synchronous method) for sepsis derived from administrative data compared to a clinical reference standard.METHOD:
Extraction of administrative coded data from Australian metropolitan teaching hospital with 25,000 annual overnight admissions compared to clinical review of medical records; 313 (27.9%) randomly selected adult multi-day stay hospital separations from 1,123 separations with acute infection during July 2019. Estimated prevalence and performance metrics, including positive (PPV) and negative predictive values (NPV), and area under the receiver operator characteristic curve (ROC).RESULTS:
Clinical prevalence of sepsis was estimated at 10.7 (95% CI = 10.3-11.3) per 100 separations, and mortality rate of 11.6 (95% CI = 10.3-13.0) per 100 sepsis separations. Explicit method for case detection had high PPV (93.2%) but low NPV (55.8%) compared to the standard implicit method (74.1 and 66.3%, respectively) and proposed synchronous method (80.4% and 80.0%) compared to a standard clinical case definition. ROC for eachmethod:
0.618 (95% CI = 0.538-0.654), 0.698 (95% CI = 0.648-0.748), and 0.802 (95% CI = 0.757-0.846), respectively.CONCLUSION:
In hospitalised Australian patients with community-onset sepsis, the explicit method for sepsis case detection underestimated prevalence. Implicit methods were consistent with consensus definition for sepsis, and proposed synchronous method had better performance.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Health Inf Manag
Ano de publicação:
2022
Tipo de documento:
Article