Identifying cirrhosis, decompensated cirrhosis and hepatocellular carcinoma in health administrative data: A validation study

PLoS One. 2018 Aug 22;13(8):e0201120. doi: 10.1371/journal.pone.0201120. eCollection 2018.


Background: To evaluate screening and treatment strategies, large-scale real-world data on liver disease-related outcomes are needed. We sought to validate health administrative data for identification of cirrhosis, decompensated cirrhosis and hepatocellular carcinoma among patients with known liver disease.

Methods: Primary patient data were abstracted from patients of the Toronto Center for Liver Disease with viral hepatitis (2006-2014), and all patients with liver disease from the Kingston Health Sciences Centre Hepatology Clinic (2013). We linked clinical information to health administrative data and tested a range of coding algorithms against the clinical reference standard.

Results: A total of 6,714 patients had primary chart data abstracted. A single physician visit code for cirrhosis was sensitive (98-99%), and a single hospital diagnostic code for cirrhosis was specific (91-96%). The most sensitive algorithm for decompensated cirrhosis was one cirrhosis code with any of: a hospital diagnostic code, death code, or procedure code for decompensation (range 88-99% across groups). The most specific was one cirrhosis code and one hospital diagnostic code (range 89-98% across groups). Two physician visit codes or a single hospital diagnostic code, death code, or procedure code combined with a code for cirrhosis were sensitive and specific for hepatocellular carcinoma (sensitivity 94-96%, specificity 93-98%).

Conclusion: These sensitive and specific algorithms can be used to define patient cohorts or detect clinical outcomes using health administrative data. Our results will facilitate research into the adequacy of screening and treatment for patients with chronic viral hepatitis or other liver diseases.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Carcinoma, Hepatocellular / diagnosis*
  • Databases, Factual
  • Female
  • Fibrosis / diagnosis
  • Humans
  • Liver Cirrhosis / diagnosis*
  • Liver Neoplasms / diagnosis
  • Male
  • Mass Screening
  • Medical Records
  • Middle Aged
  • Retrospective Studies
  • Sensitivity and Specificity

Grant support

This work was supported by a grant from the Physician Services Incorporated (PSI) Foundation (#14-13) and by the Institute for Clinical Evaluative Sciences (ICES), which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). LLS is supported by a CIHR Fellowship Award. JAF is supported by a Southeastern Ontario New Clinician Scientist Award. JCK is supported by a CIHR New Investigator Award and a University of Toronto Department of Family & Community Medicine Investigator Award. The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources. Parts of this material are based on data and information compiled and provided by the Canadian Institute for Health Information (CIHI) and by Cancer Care Ontario (CCO). However, the analyses, conclusions, opinions, and statement expressed herein are those of the authors, and not necessarily those of CIHI or CCO. No endorsement by ICES, MOHLTC, CIHI, or CCO is intended or should be inferred. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.