RESUMO
OBJECTIVES: Limited screening and delays in diagnosis and linkage-to-care are barriers for hepatitis C virus (HCV) elimination. The LiverTAI study focused on patients tested for HCV using AI technologies to describe their demographic and clinical characteristics and pre-testing patient journeys, reflecting clinical practice in hospitals. PATIENTS AND METHODS: LiverTAI is a retrospective, secondary analysis of electronic health records (EHRs) from 6 tertiary Spanish hospitals, extracting unstructured clinical data using natural language processing (NLP) EHRead® technology. Adult subjects with an HCV testing procedure from January 2014 to December 2018 were grouped according to HCV seropositivity and viremia. RESULTS: From 2,440,358 patients, 16,261 patients were tested for HCV (13,602 [83.6%] HCV seronegative; 2659 [16.4%] seropositive). Active HCV viremia appeared in 37.7% (n=1003) of patients, 18.6% (n=494) had negative viremia, and 43.7% (n=1162) unknown viremia. Patient journeys showed core departments (Gastroenterology, Internal Medicine, and Infectious Disease) and others including Emergency perform ample HCV testing in Spanish hospitals, whereas Medical Oncology lags. Patients were PCR-tested and genotyped significantly faster in core departments (p<.001). CONCLUSIONS: Our results highlight hospital departments responsible for HCV testing. However, further testing was sub-optimal during the study period. Therefore, we underscore the need for HCV screening and reflex testing to accelerate diagnosis and linkage-to-care.