Our algorithm cannot be directly applied to other populations directly because clinical backgrounds differ among countries. However, we think that our study is applicable on a global scale because it has clearly shown that a combination of viral and host factors is effective for predicting the respo
Predictors of treatment in patients with chronic hepatitis C infection—Role of patient versus nonpatient factors
✍ Scribed by Fasiha Kanwal; Tuyen Hoang; Brennan M.R. Spiegel; Seth Eisen; Jason A. Dominitz; Allen Gifford; Mathew Goetz; Steven M. Asch
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 298 KB
- Volume
- 46
- Category
- Article
- ISSN
- 0270-9139
No coin nor oath required. For personal study only.
✦ Synopsis
Treatment with interferon and ribavirin is effective in patients with chronic infection with hepatitis C virus (HCV). Previous data indicate that treatment rates are suboptimal. We sought to identify patient and provider-level predictors of treatment receipt in HCV by conducting a retrospective cohort study of 5701 HCV patients in a large regional Veteran's Administration (VA) healthcare network. We also determined the degree of variation in treatment rates attributable to patient, provider, and facility factors. Three thousand seven hundred forty-three patients (65%) were seen by a specialist and 894 (15.7%) received treatment. Treatment rates varied from 6% to 29% across the 5 facilities included in the analysis. Patients were less likely to receive treatment if they were older [RR, 0.55; 95% CI, 0.45, 0.67), single (RR, 0.77; 95%CI, 0.67, 0.88), had hepatic dysfunction (RR, 0.73; 95%CI, 0.66, 0.89), had normal alanine aminotransferase (ALT) (RR, 0.73; 95%CI, 0.59, 0.89), had HCV genotype 1 (RR, 0.78; 95%CI, 0.71, 0.86), were African American with genotype 1 (RR, 0.78; 95% CI, 0.71, 0.86), or were anemic (RR, 0.70; CI, 0.60, 0.89). In addition, patients evaluated by less experienced providers were 77% less likely to receive treatment than those evaluated by more experienced providers. The patient, provider, and facility factors explained 23%, 25%, and 7% of variation in treatment rates, respectively.
Conclusion:
These data suggest that although patient characteristics are important predictors of treatment in hcv, a significant proportion of variation in treatment rates is explained by provider factors. these potentially modifiable provider-level factors may serve as high-yield targets for future quality improvement initiatives in hcv.
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