i
Comparative Effectiveness Research of Chronic Hepatitis B and C Cohort Study (CHeCS): Improving Data Collection and Cohort Identification
-
Jul 17 2014
Source: Dig Dis Sci. 59(12):3053-3061.
Details:
-
Alternative Title:Dig Dis Sci
-
Personal Author:
-
Description:Background and Aims
The Chronic Hepatitis Cohort Study (CHeCS) is a longitudinal observational study of risks and benefits of treatments and care in patients with chronic hepatitis B (HBV) and C (HCV) infection from four US health systems. We hypothesized that comparative effectiveness methods—including a centralized data management system and an adaptive approach for cohort selection—would improve cohort selection while controlling data quality and reducing the cost.
Methods
Cohort selection and data collection were performed primarily via the electronic health record (EHR); cases were confirmed via chart abstraction. Two parallel sources fed data to a centralized data management system: direct EHR data collection with common data elements, and chart abstraction via electronic data capture. An adaptive Classification and Regression Tree (CART) identified a set of electronic variables to improve case ascertainment accuracy.
Results
Over 16 million patient records were collected on 23 case report forms in 2006–2008. The vast majority of data (99.2 %) were collected electronically from EHR; only 0.8 % was collected via chart abstraction. Initial electronic criteria identified 12,144 chronic hepatitis patients; 10,098 were confirmed via chart abstraction with positive predictive values (PPV) 79 and 83 % for HBV and HCV, respectively. CART-optimized models significantly increased PPV to 88 for HBV and 95 % for HCV.
Conclusions
CHeCS is a comparative effectiveness research project that leverages electronic centralized data collection and adaptive cohort identification approaches to enhance study efficiency. The adaptive CART model significantly improved the positive predictive value of cohort identification methods.
-
Subjects:
-
Source:
-
Pubmed ID:25030940
-
Pubmed Central ID:PMC5719869
-
Document Type:
-
Collection(s):
-
Main Document Checksum:
-
Download URL:
-
File Type:
Supporting Files
-
xml gif jpeg gif jpeg gif jpeg
More +