Hepatitis C Assistance
Predictive models can be applied to electronic health information as it moves through a Health Information Network (HIN) to identify and predict appropriate treatment for Hepatitis C in some cases.
Use Case Summary, Implementation Guide and Supporting Documents
Hepatitis C Assistance Use Case Summary
About this Use Case
It is estimated that 2.7-3.9 million people in the United States have chronic Hepatitis C. Hepatitis C is fatal for one in five people. This translates to 780,000 deaths related to Hepatis C. Liver cancer and cirrhosis are common causes of death resulting from chronic Hepatitis C infection.
Direct-acting antiviral agents (DAAs) have dramatically increased cure rates for Hepatitis C virus (HCV). However, patients who have other diseases in addition to Hepatitis C (referred to as co-morbidities), or certain medical histories may not respond well to DAAs, and may require a different approach.
Clinical research has been used to create a computer model to predict the most appropriate use of DAAs based on presence of co-morbidities or specific patient histories.
