Accuracy of ICD-10 Coding System for Identifying Comorbidities and Infectious Conditions Using Data from a Thai University Hospital Administrative Database
Abstract
OBJECTIVE: To determine the accuracy of International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system in identifying comorbidities and infectious conditions using data from a Thai university hospital administrative database.
MATERIAL AND METHOD: A retrospective cross-sectional study was conducted among patients hospitalized in six general medicine wards at Siriraj Hospital. ICD-10 code data was identified and retrieved directly from the hospital administrative database. Patient comorbidities were captured using the ICD-10 coding algorithm for the Charlson comorbidity index. Infectious conditions were captured using the groups of ICD-10 diagnostic codes that were carefully prepared by two independent infectious disease specialists. Accuracy of ICD-10 codes combined with microbiological dataf or diagnosis of urinary tract infection (UTI) and bloodstream infection (BSI) was evaluated. Clinical data gathered from chart review was considered the gold standard in this study.
RESULTS: Between February 1 and May 31, 2013, a chart review of 546 hospitalization records was conducted. The mean age of hospitalized patients was 62.8 ± 17.8 years and 65.9% of patients were female. Median length of stay [range] was 10.0 [1.0-353.0] days and hospital mortality was 21.8%. Conditions with ICD-10 codes that had good sensitivity (90% or higher) were diabetes mellitus and HIV infection. Conditions with ICD-10 codes that had good specificity…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.
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