Accuracy of ICD-10 Coding System for Identifying Comorbidities and Infectious Conditions Using Data from a Thai University Hospital Administrative Database
Pinyo Rattanaumpawan MD, MSCE, PhD*,**, Thanyarak Wongkamhla MD**, Visanu Thamlikitkul MD*,**
Affiliation : * Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand ** Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
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 data for 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 (90% or higher)
were cerebrovascular disease, chronic lung disease, diabetes mellitus, cancer, HIV infection, and all infectious conditions.
By combining ICD-10 codes with microbiological results, sensitivity increased from 49.5 to 66% for UTI and from 78.3 to
92.8% for BSI.
Conclusion : The ICD-10 coding algorithm is reliable only in some selected conditions, including underlying diabetes
mellitus and HIV infection. Combining microbiological results with ICD-10 codes increased sensitivity of ICD-10 codes
for identifying BSI. Future research is needed to improve the accuracy of hospital administrative coding system in Thailand.
Keywords : Comorbidities, ICD-10, Infectious conditions
