Using i2b2 to bootstrap rural health analytics and learning networks

Abstract

We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites.

Using closure tables to enable cross-querying of ontologies in database-driven applications

“…In particular, we wish to explore how closure tables can help overcome the shortcomings of rural networks [7] and assist in boostrapping i2b2 for rural health analytics and learning networks [6]. We have shown that closure tables are an effective and efficient data structure for developing database-driven applications that leverage ontologies and that require cross-querying between multiple ontologies.…”

“…i2b2 is reported to be used by over half of all institutions receiving a Clinical and Translational Science Award (CTSA), over 60 academic medical centers, and over 10 international medical centers [5]. We have demonstrated that i2b2 can bootstrap rural health analytics and learning networks [6] and quickly give infrastructure to institutions that otherwise lack the resources to support clinical and health informatics research [7]. …”