Paper Info
Title
The Analytic Information Warehouse (AIW): A platform for analytics using electronic health record data.
Abstract
To create an analytics platform for specifying and detecting clinical phenotypes and other derived variables in electronic health record (EHR) data for quality improvement investigations.We have developed an architecture for an Analytic Information Warehouse (AIW). It supports transforming data represented in different physical schemas into a common data model, specifying derived variables in terms of the common model to enable their reuse, computing derived variables while enforcing invariants and ensuring correctness and consistency of data transformations, long-term curation of derived data, and export of derived data into standard analysis tools. It includes software that implements these features and a computing environment that enables secure high-performance access to and processing of large datasets extracted from EHRs.We have implemented and deployed the architecture in production locally. The software is available as open source. We have used it as part of hospital operations in a project to reduce rates of hospital readmission within 30days. The project examined the association of over 100 derived variables representing disease and co-morbidity phenotypes with readmissions in 5years of data from our institution's clinical data warehouse and the UHC Clinical Database (CDB). The CDB contains administrative data from over 200 hospitals that are in academic medical centers or affiliated with such centers.A widely available platform for managing and detecting phenotypes in EHR data could accelerate the use of such data in quality improvement and comparative effectiveness studies.
Year
DOI
Venue
2013
10.1016/j.jbi.2013.01.005
Journal of Biomedical Informatics
Keywords
Field
DocType
Healthcare analytics,Clinical data warehousing,Temporal abstraction,Quality improvement,Comparative effectiveness
Data warehouse,Data science,Data mining,Data transformation (statistics),Reuse,Computer science,Correctness,Software,Analytics,Data model,Database,Quality management
Journal
Volume
Issue
ISSN
46
3
1532-0464
Citations 
PageRank 
References 
11
0.77
33
Authors
10
Name
Order
Citations
PageRank
Andrew R. Post1628.35
Tahsin M. Kurç21423149.77
Sharath R. Cholleti318312.67
Jingjing Gao4969.73
Xia Lin5110.77
William Bornstein6212.17
Dedra Cantrell7212.17
David Levine8110.77
Sam Hohmann9110.77
Joel H. Saltz104046569.91