Abstract
Background:
Since hepatitis C virus therapy is typically prioritized for patients with more advanced disease, predicting which patients will progress could help direct scarce resources to those likely to benefit most. This study aims to identify demographics and clinical characteristics associated with high healthcare resource utilization (HRU) and liver disease progression among CHC patients.
Methods:
Using health insurance claims (January 2001–March 2013), adult patients with ≥2 CHC claims (ICD-9-CM: 070.44 or 070.54), and ≥6 months of continuous insurance coverage before and ≥36 months after the first CHC diagnosis were included. Patients with human immunodeficiency virus were excluded. Generalized estimating equations were used to identify the demographic and clinical characteristics of being in the 20% of patients with the highest HRU. Factors predicting liver disease progression were also identified.
Results:
In the study population (n = 4898), liver disease severity and both CHC- and non–CHC-related comorbidities and conditions were strong predictors of high healthcare costs, with odds ratios (ORs; 95% confidence interval [CI]) for ≥2 CHC-related and ≥2 non-CHC-related comorbidities/conditions of 2.78 (2.48–3.12) and 2.19 (1.76–2.72), respectively. CHC- and non-CHC-related comorbidities and conditions were also strong predictors of liver disease progression with ORs (95% CI) for ≥2 CHC-related and ≥2 non-CHC-related comorbidities and conditions of 2.18 (1.83–2.60) and 1.50 (1.14–1.97), respectively.
Limitations:
Potential inaccuracies in claims data, information or classification bias, and findings based on a privately insured population.
Conclusion:
This study suggests that CHC patients with high healthcare resource utilization have a high level of comorbidity at baseline and also that non-CHC comorbidities and conditions are strong predictors of high HRU. Non-cirrhotic CHC patients with one or more comorbidities are at high risk of progressing to cirrhosis or end-stage liver disease.
Transparency
Declaration of funding
The research was funded by Janssen Scientific Affairs, LLC, in Titusville, NJ.
Declaration of financial/other relationship
FL, GG, DP, and PL are employees of Analysis Group, Inc., a consulting company that has received research grants from Janssen Scientific Affairs. JL, NT, and AP are employees of Janssen Scientific Affairs. JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Acknowledgment
Technical editorial assistance was provided by Shannon O’Sullivan, ELS, of MedErgy, and was funded by Janssen Scientific Affairs, LLC.