International Classification of Diseases Codes are Useful in Identifying Cirrhosis in Administrative Databases

• Published in: Digestive diseases and sciences Vol. 67; no. 6; pp. 2107 - 2122
• Main Authors: Dahiya, Monica, Eboreime, Ejemai, Hyde, Ashley, Rahman, Sholeh, Sebastianski, Meghan, Carbonneau, Michelle, Tapper, Elliot B., Tandon, Puneeta
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2022; Springer; Springer Nature B.V
• Subjects: Algorithms; Ascites; Biochemistry; Classification; Codes; Comparative analysis; Data Collection; Databases, Factual; Gastroenterology; Hepatitis; Hepatology; Hospitals; Humans; International Classification of Diseases; Liver; Liver cirrhosis; Liver Cirrhosis - complications; Liver Cirrhosis - diagnosis; Liver Cirrhosis - epidemiology; Liver diseases; Medical care; Medical research; Medicine; Medicine & Public Health; Medicine, Experimental; Oncology; Original Article; Patients; Predictive Value of Tests; Quality management; Science; Systematic review; Transplant Surgery; Validity; Validation; Cirrhosis; Administrative; Identification; ICD
• ISSN: 0163-2116; 1573-2568; 1573-2568
• DOI: 10.1007/s10620-021-07076-1

Background Health administrative databases are essential to define patient populations, make socioeconomic predictions, and facilitate medical research and healthcare planning. The accuracy of this data is dependent on valid codes/coding algorithms. Aims The aim of this study was to systematically identify and summarize the validity of International Classification of Diseases (ICD) codes for identifying patients with cirrhosis in administrative data. Methods Electronic databases, MEDLINE (via Ovid), EMBASE (via Ovid), the Web of Science, and CINAHL (via EBSCOhost), were searched for validation studies which compared ICD codes related to cirrhosis to a clinical reference standard, and reported statistical measures of performance. Results Fourteen studies were included in the review. There was a large variation in the algorithms used to validate ICD codes to diagnose cirrhosis. Despite the variation, the positive predictive value (PPV) was greater than 84% and the specificity was greater than 75% in the majority of the studies. The negative predictive value (NPV) was lower, but still was associated with values greater than 70% in the majority of studies. Sensitivity data varied significantly with values ranging from 0.27 to 99%. Conclusions Evaluated ICD codes for cirrhosis, including codes for chronic liver disease, cirrhosis-specific codes, and cirrhosis-related complications, have demonstrated variable sensitivity and reasonable specificity for the identification of cirrhosis. Additional research is needed to maximize the identification of persons with cirrhosis to avoid underestimating the burden of disease.