Liver cancer, the fifth most common cancer and second leading cause of cancer-related death among men worldwide, is plagued by not only lack of clinical research, but informatics tools for early detection. Consequently, it presents a major health and cost burden. Among the different types of liver cancer, hepatocellular carcinoma (HCC) is the most common and deadly form, arising from underlying liver disease. Current models for predicting risk of HCC and liver disease are limited to clinical data. A domain analysis of existing research related to screening for HCC and liver disease suggests that metabolic syndrome (MetS) may present oppportunites to detect early signs of liver disease. The purpose of this paper is to (i) provide a domain analysis of the relationship between HCC, liver disease, and metabolic syndrome, (ii) a review of the current disparate sources of data available for MetS diagnosis, and (iii) recommend informatics solutions for the diagnosis of MetS from available administrative (Biometrics, PHA, claims) and laboratory data, towards early prediction of liver disease. Our domain analysis and recommendations incorporate best practices to make meaningful use of available data with the goal of reducing cost associated with liver disease.

Original languageEnglish
Title of host publicationMEDINFO 2015
Subtitle of host publicationeHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics
EditorsAndrew Georgiou, Indra Neil Sarkar, Paulo Mazzoncini de Azevedo Marques
PublisherIOS Press
Number of pages5
ISBN (Electronic)9781614995630
StatePublished - 2015
Event15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 - Sao Paulo, Brazil
Duration: Aug 19 2015Aug 23 2015

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Conference15th World Congress on Health and Biomedical Informatics, MEDINFO 2015
CitySao Paulo


  • Liver cancer
  • economics
  • liver disease
  • metabolic syndrome


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