Abstract
BackgroundSelecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research. We describe the evaluation of a free and open source cohort selection tool from the Informatics for Integrating Biology and the Bedside (i2b2) group: the i2b2 hive.MethodsOur evaluation included the usability and functionality of the i2b2 hive using several real world examples of research data requests received electronically at the University of Utah Health Sciences Center between 2006 - 2008. The hive server component and the visual query tool application were evaluated for their suitability as a cohort selection tool on the basis of the types of data elements requested, as well as the effort required to fulfill each research data request using the i2b2 hive alone.ResultsWe found the i2b2 hive to be suitable for obtaining estimates of cohort sizes and generating research cohorts based on simple inclusion/exclusion criteria, which consisted of about 44% of the clinical research data requests sampled at our institution. Data requests that relied on post-coordinated clinical concepts, aggregate values of clinical findings, or temporal conditions in their inclusion/exclusion criteria could not be fulfilled using the i2b2 hive alone, and required one or more intermediate data steps in the form of pre- or post-processing, modifications to the hive metadata, etc.ConclusionThe i2b2 hive was found to be a useful cohort-selection tool for fulfilling common types of requests for research data, and especially in the estimation of initial cohort sizes. For another institution that might want to use the i2b2 hive for clinical research, we recommend that the institution would need to have structured, coded clinical data and metadata available that can be transformed to fit the logical data models of the i2b2 hive, strategies for extracting relevant clinical data from source systems, and the ability to perform substantial pre- and post-processing of these data.
Highlights
Selecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research
The i2b2 center focuses on developing a new informatics framework to bridge clinical research data with basic sciences research data, and on driving biology projects that serve as test beds for the framework
Among the data requests that could not be fulfilled with the i2b2 workbench without significant modifications (Table 2), 26% (7) had one or more institution-specific criteria, and 48% (13) had one or more temporal criteria that could not be faithfully reproduced using the graphical interface of the i2b2 workbench alone
Summary
Selecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research. We describe the evaluation of a free and open source cohort selection tool from the Informatics for Integrating Biology and the Bedside (i2b2) group: the i2b2 hive. Informatics for Integrating Biology and the Bedside (i2b2) [5] is one of the seven National Centers for Biomedical Computing funded by the National Institutes of Health, and is based at the Brigham and Women's Hospital (Boston, MA) [6]. One of the most visible components of the i2b2 informatics framework is an open source patient cohort selection tool called the i2b2 workbench, which is a modular, userfriendly tool that allows graphical querying and visualizing of clinical data. The latest version of the i2b2 hive (1.3) includes a web client that is functionally similar to the Java client
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