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Author Spotlight: Advancements and Challenges in Hepatitis B Virus Detection
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Comparative effectiveness research of chronic hepatitis B and C cohort study (CHeCS): improving data collection and

Mei Lu1, Loralee B Rupp, Anne C Moorman

  • 1Departments of Public Health Sciences, Center for Health Services Research, and Gastroenterology, Henry Ford Health System, One Ford Place, 3E, Detroit, MI, 48202, USA, mlu1@hfhs.org.

Digestive Diseases and Sciences
|July 18, 2014
PubMed

Insights

The Chronic Hepatitis Cohort Study (CHeCS) used electronic health records and adaptive methods to efficiently identify patients with chronic hepatitis B (HBV) and C (HCV). This approach significantly improved the accuracy of cohort selection for comparative effectiveness research.

Area of Science:

  • Comparative effectiveness research
  • Health informatics
  • Longitudinal cohort studies

Background:

  • The Chronic Hepatitis Cohort Study (CHeCS) is a longitudinal observational study focused on chronic hepatitis B (HBV) and C (HCV) infections.
  • Investigated risks and benefits of treatments and care in patients across four US health systems.

Purpose of the Study:

  • To evaluate the effectiveness of comparative effectiveness methods for cohort selection.
  • Hypothesized that centralized data management and adaptive cohort selection would improve efficiency, data quality, and reduce costs.

Main Methods:

  • Utilized electronic health records (EHR) for primary data collection and chart abstraction for case confirmation.
  • Employed a centralized data management system with parallel data sources (direct EHR and electronic data capture).
  • An adaptive Classification and Regression Tree (CART) model was used to optimize electronic variable selection for improved case ascertainment.

Main Results:

  • Collected over 16 million patient records from 2006-2008, with 99.2% data from EHR.
  • Initial electronic criteria identified 12,144 patients; chart abstraction confirmed 10,098 with positive predictive values (PPV) of 79% for HBV and 83% for HCV.
  • CART-optimized models significantly enhanced PPV to 88% for HBV and 95% for HCV.

Conclusions:

  • CHeCS successfully leveraged electronic data and adaptive cohort identification for efficient comparative effectiveness research.
  • The adaptive CART model substantially improved the positive predictive value for cohort identification, enhancing study efficiency.
Abstract

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