Identifying patients with diagnosed cirrhosis in administrative health databases: a validation study.

Abstract

Objectives: Case ascertainment algorithms were developed and validated to identify people living with cirrhosis in administrative health data in Manitoba, Canada using primary care electronic medical records (EMR) to define the reference standards.

Methods: We linked provincial administrative health data to primary care EMR data. The validation cohort included 116,675 Manitobans aged >18 years with at least one primary care visit between April 1998 and March 2015. Hospital records, physician billing claims, vital statistics, and prescription drug data were used to develop and test 93 case-finding algorithms. A validated case definition for primary care EMR data was the reference standard. We estimated sensitivity, specificity, positive and negative predictive values (PPV, NPV), Youden's index, area under the receiver operative curve, and their 95% confidence intervals (CIs).

Results: A total of 116,675 people were in the validation cohort. The prevalence of cirrhosis was 1.4% (n = 1593). Algorithm sensitivity estimates ranged from 32.5% (95% CI 32.2-32.8) to 68.3% (95% CI 68.0-68.9) and PPV from 17.4% (95% CI 17.1-17.6) to 23.4% (95% CI 23.1-23.6). Specificity (95.5-98.2) and NPV (approximately 99%) were high for all algorithms. The algorithms had slightly higher sensitivity estimates among men compared with women, and individuals aged ≥45 years compared to those aged 18-44 years.

Conclusion: Cirrhosis algorithms applied to administrative health data had moderate validity when a validated case definition for primary care EMRs was the reference standard. This study provides algorithms for identifying diagnosed cirrhosis cases for population-based research and surveillance studies.