Design and Implementation of a Multipurpose Information System for Hematopoietic Stem-Cell Transplantation on the...

An important obstacle to cancer research is that nearly all academic cancer centers maintain substantial collections of highly duplicative, poorly quality-assured, nonintercommunicating, difficult-to-access data repositories. It is inherently clear that this state of affairs increases costs and reduces quality and productivity of both research and nonresearch activities. We hypothesized that designing and implementing a multipurpose cancer information system on the basis of the Biomedical Research Integrated Domain (BRIDG) model developed by the National Cancer Institute and its collaborators might lessen the duplication of effort inherent in capturing, quality-assuring, and accessing data located in multiple single-purpose systems, and thereby increases productivity while reducing costs.

We designed and implemented a core data structure on the basis of the BRIDG model and incorporated multiple entities, attributes, and functionalities to support the multipurpose functionality of the system. We used the resultant model as a foundation upon which to design and implement modules for importing preexisting data, capturing data prospectively, quality-assuring data, exporting data to analytic files, and analyzing the quality-assured data to support multiple functionalities simultaneously. To our knowledge, our system, which we refer to as the Cancer Informatics Data System, is the first multipurpose, BRIDG-harmonized cancer research information system implemented at an academic cancer center.

We describe the BRIDG-harmonized system that simultaneously supports patient care, teaching, research, clinical decision making, administrative decision making, mandated volume-and-outcomes reporting, clinical quality assurance, data quality assurance, and many other functionalities.

Implementation of a highly quality-assured, multipurpose cancer information system on the basis of the BRIDG model at an academic center is feasible and can increase access to accurate data to support research integrity and productivity as well as nonresearch activities.