Abstract
Administrative datasets are important for cirrhosis research but limited by suboptimal cirrhosis identification. We developed and validated algorithms to accurately identify cirrhosis and its complications in real-world, statewide dataset. From 2017 to 2020 Indiana Patient Care Network data, 15,636 records were grouped by combinations of code and lab criteria (group A: cirrhosis codes, B: FIB-4/APRI criteria, C: cirrhosis complication codes, D: code/lab for liver disease). Diagnoses were confirmed by chart review in 4.5% of 15,636 records. Positive predictive values (PPV) were calculated for various algorithms which were externally validated in hepatology clinic (n = 1,039) and emergency department-based cirrhosis cohorts (n = 2,124). Charts meeting criteria for group A and at least one other group (“AX”, e.g., ABC) had an overall PPV of 86%. Highest PPVs were seen in ACD and ABCD and confirmed during external validation: 88% and 97% (hepatology cohort), 79% and 93% (ED cohort). Without complication codes, ABD showed strong PPVs: 86%(internal), 92%(hepatology), 72%(ED). ICD-10-based definitions alone were suboptimal for complications: ascites (57%), hepatic encephalopathy (HE:55%). PPV for HE was improved with addition of medications but remained < 80%. Taken together, we provide algorithms to identify both compensated and decompensated cirrhosis in real-world data. Using the “AX” algorithm, we created the statewide Indiana Digital Cirrhosis Cohort to support future research across cirrhosis stages.
Data availability
The analytic methods used in this study are detailed in the methods. The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.
References
Xu, J., Murphy, S. L., Kochanek, K. D. & Arias, E. Mortality in the United States, NCHS data brief, 1–8. (2021).
Devarbhavi, H. et al. Global burden of liver disease: 2023 update. J. Hepatol. 79, 516–537. https://doi.org/10.1016/j.jhep.2023.03.017 (2023).
Orman, E. S. et al. Trends in Characteristics, Mortality, and other outcomes of patients with newly diagnosed cirrhosis. JAMA Netw. Open. 2, e196412. https://doi.org/10.1001/jamanetworkopen.2019.6412 (2019).
Hirode, G., Saab, S. & Wong, R. J. Trends in the burden of chronic liver disease among hospitalized US adults. JAMA Netw. Open. 3, e201997. https://doi.org/10.1001/jamanetworkopen.2020.1997 (2020).
Desai, A. P. et al. Increasing economic burden in hospitalized patients with cirrhosis: analysis of a National database. Clin. Translational Gastroenterol. 10, e00062. https://doi.org/10.14309/ctg.0000000000000062 (2019).
Optum Claims Data. https://business.optum.com/en/data-analytics/life-sciences/real-world-data/claims-data.html.
NIS Database Documentation. NIS Database Documentation. https://www.hcup-us.ahrq.gov/db/nation/nis/nisdbdocumentation.jsp.
Wang, X. Q. et al. Veterans affairs patient database (VAPD 2014–2017): Building nationwide granular data for clinical discovery. BMC Med. Res. Methodol. 19, 94. https://doi.org/10.1186/s12874-019-0740-x (2019).
ICD-10. international statistical classification of diseases and related health problems : tenth revision, 2nd ed.
Garrido-Trevino, L. et al. Diagnosis of Acute-on-Chronic liver failure in critically ill patients with cirrhosis using administrative data. Am. J. Gastroenterol. https://doi.org/10.14309/ajg.0000000000003422 (2025).
Louissaint, J., Murphy, S. L., Sonnenday, C. J., Lok, A. S. & Tapper, E. B. Applying administrative Data-Based coding algorithms for frailty in patients with cirrhosis. Liver Transpl. 27, 1401–1411. https://doi.org/10.1002/lt.26078 (2021).
Simon, T. G. et al. Comparative effectiveness and safety of Apixaban, Rivaroxaban, and warfarin in patients with cirrhosis and atrial fibrillation: A nationwide cohort study. Ann. Intern. Med. 177, 1028–1038. https://doi.org/10.7326/M23-3067 (2024).
Desai, A. P., Mohan, P., Roubal, A. M., Bettencourt, R. & Loomba, R. Geographic variability in liver Disease-Related mortality rates in the united States. Am. J. Med. 131, 728–734. https://doi.org/10.1016/j.amjmed.2018.01.047 (2018).
Hayward, K. L. et al. ICD-10-AM codes for cirrhosis and related complications: key performance considerations for population and healthcare studies. BMJ Open. Gastroenterol. 7, e000485. https://doi.org/10.1136/bmjgast-2020-000485 (2020).
Khalifa, A., Obeid, J. S., Gregoski, M. J. & Rockey, D. C. Accurate identification of patients with cirrhosis and its complications in the electronic health record. Dig. Dis. Sci. 68, 2360–2369. https://doi.org/10.1007/s10620-023-07876-7 (2023).
Ramrakhiani, N. S. et al. Validity of international classification of Diseases, tenth Revision, codes for cirrhosis. Dig. Dis. 39, 243–246. https://doi.org/10.1159/000510981 (2021).
Shearer, J. E. et al. Systematic review: development of a consensus code set to identify cirrhosis in electronic health records. Aliment. Pharmacol. Ther. 55, 645–657. https://doi.org/10.1111/apt.16806 (2022).
Monaghan, T. F. et al. Foundational statistical principles in medical research: Sensitivity, Specificity, positive predictive value, and negative predictive value. Medicina 57, 503. https://doi.org/10.3390/medicina57050503 (2021).
Tapper, E. B. et al. Identifying patients with hepatic encephalopathy using administrative data in the ICD-10 era. Clin. Gastroenterol. Hepatol. 19, 604–606e601. https://doi.org/10.1016/j.cgh.2019.12.017 (2021).
Nehra, M. S. et al. Use of administrative claims data for identifying patients with cirrhosis. J. Clin. Gastroenterol. 47, e50–e54. https://doi.org/10.1097/MCG.0b013e3182688d2f (2013).
McDonald, C. J. et al. The Indiana network for patient care: A working local health information infrastructure. Health Aff. 24, 1214–1220. https://doi.org/10.1377/hlthaff.24.5.1214 (2005).
Regenstrief Institute Data Services: Data Sources. https://www.regenstrief.org/rds/data/.
American Community Survey. https://factfinder.census.gov/.
Parvataneni, S. et al. A comprehensive evaluation of emergency department utilization by patients with cirrhosis. Am. J. Gastroenterol. 119, 2444–2454. https://doi.org/10.14309/ajg.0000000000002905 (2024).
Roh, Y. H., Kang, B. K., Jun, D. W., Lee, C. & Kim, M. Role of FIB-4 for reassessment of hepatic fibrosis burden in referral center. Sci. Rep. 11, 13616. https://doi.org/10.1038/s41598-021-93038-6 (2021).
El-Kassas, M. et al. Comparison of different noninvasive scores for assessing hepatic fibrosis in a cohort of chronic hepatitis C patients. Sci. Rep. 14, 29544. https://doi.org/10.1038/s41598-024-79826-w (2024).
Montrose, J. A. et al. Medication burden and anticholinergic use are associated with overt HE in individuals with cirrhosis. Hepatol. Commun. 8 https://doi.org/10.1097/HC9.0000000000000460 (2024).
Goldberg, D., Lewis, J., Halpern, S. & Weiner, M. Lo Re, V. Validation of three coding algorithms to identify patients with end-stage liver disease in an administrative database. Pharmacoepidemiol. Drug. 21, 765–769. https://doi.org/10.1002/pds.3290 (2012).
Bengtsson, B., Askling, J., Ludvigsson, J. F. & Hagström, H. Validity of administrative codes associated with cirrhosis in Sweden. Scand. J. Gastroenterol. 55, 1205–1210. https://doi.org/10.1080/00365521.2020.1820566 (2020).
Dahiya, M. et al. International classification of diseases codes are useful in identifying cirrhosis in administrative databases. Dig. Dis. Sci. 67, 2107–2122. https://doi.org/10.1007/s10620-021-07076-1 (2022).
Re, V. L. et al. Validity of diagnostic codes and liver-related laboratory abnormalities to identify hepatic decompensation events in the veterans aging cohort study. Pharmacoepidemiol. Drug. 20, 689–699. https://doi.org/10.1002/pds.2148 (2011).
Chang, E. K. et al. Defining a patient population with cirrhosis: an automated algorithm with natural Language processing. J. Clin. Gastroenterol. 50, 889–894. https://doi.org/10.1097/MCG.0000000000000583 (2016).
Bonacini, M., Hadi, G., Govindarajan, S. & Lindsay, K. L. Utility of a discriminant score for diagnosing advanced fibrosis or cirrhosis in patients with chronic hepatitis C virus infection. Am. J. Gastroenterol. 92, 1302–1304 (1997).
Obeid, J. S., Khalifa, A., Xavier, B., Bou-Daher, H. & Rockey, D. C. An AI approach for identifying patients with cirrhosis. J. Clin. Gastroenterol. 57, 82–88. https://doi.org/10.1097/MCG.0000000000001586 (2023).
Ozturk, N. B., Jamil, L. H. & Tapper, E. B. Diagnostic performance of the ICD-10 code K76.82 for hepatic encephalopathy in patients with cirrhosis. Am. J. Gastroenterol. 119, 364–366. https://doi.org/10.14309/ajg.0000000000002560 (2024).
Arif, M. S. et al. Su1669: Characterizing Cirrhosis: A comparative Analysis Across Black and White Populations. Digestive Diseases Week 2024. Gastroenterology 169(S1), S1744–1745. https://doi.org/10.1016/S0016-5085%2825%2904876-0 (2025).
Arif, M. S. et al. Contemporary Natural History of Compensated Cirrhosis: Results from the Population-Based Indiana Cirrhosis Cohort. The Liver Meeting: 2025 Abstracts. Hepatology 82(S1), S1–S2308. https://doi.org/10.1097/HEP.0000000000001493 (2025).
Gawrieh, S. et al. Alcohol Use Disorder, Liver Decompensation, and Mortality Risk Across Cirrhosis Etiologies: A Population-based Study. The Liver Meeting: 2025 Abstracts. Hepatology 82(S1), S1–S2308. https://doi.org/10.1097/HEP.0000000000001493 (2025).
Acknowledgements
We thank Swetha Parvataneni, MD; Joe Ma, MD; Nadia Blessing, PA; Lindsay Yoder, PA; Haleigh Rodgers, PA; and Kavish Patidar, DO for manual review of medical records which served as the gold standard for definition of cirrhosis and its complications.
Funding
APD is funded by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award number R03DK139283 and, previously, by award number K23DK123408.
Author information
Authors and Affiliations
Contributions
Study Concept and Design: Eric Orman, Naga Chalasani, Archita DesaiData Analysis: Hani Shamseddeen, Lauren Lembcke, Sui Lui Hui, Eric Orman, Archita DesaiManuscript Preparation: Hani Shamseddeen, Archita DesaiCritical Manuscript Review: All authors.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Desai, A.P., Shamseddeen, H., Lembcke, L. et al. Accurately identifying cirrhosis and its complications to create the novel statewide Indiana digital cirrhosis registry. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39585-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-39585-2
