title: Semantic ETL into i2b2 with Eureka!
abstract: Clinical phenotyping is an emerging research information systems capability. Research uses of electronic health record (EHR) data may require the ability to identify clinical co-morbidities and complications. Such phenotypes may not be represented directly as discrete data elements, but rather as frequency, sequential and temporal patterns in billing and clinical data. These patterns' complexity suggests the need for a robust yet flexible extract, transform and load (ETL) process that can compute them. This capability should be accessible to investigators with limited ability to engage an IT department in data management. We have developed such a system, Eureka! Clinical Analytics. It extracts data from an Excel spreadsheet, computes a broad set of phenotypes of common interest, and loads both raw and computed data into an i2b2 project. A web-based user interface allows executing and monitoring ETL processes. Eureka! is deployed at our institution and is available for deployment in the cloud.
authors.affiliation: Center for Comprehensive Informatics, Emory University, Atlanta, GA.
authors.forename: Andrew R
authors.initials: AR
authors.lastname: Post
authors.forename: Tahsin
authors.initials: T
authors.lastname: Krc
authors.forename: Himanshu
authors.initials: H
authors.lastname: Rathod
authors.forename: Sanjay
authors.initials: S
authors.lastname: Agravat
authors.forename: Michel
authors.initials: M
authors.lastname: Mansour
authors.forename: William
authors.initials: W
authors.lastname: Torian
authors.forename: Joel H
authors.initials: JH
authors.lastname: Saltz