Characterizing Data Discovery and End-User Computing Needs in Clinical Translational Science

In this paper, the authors present the results of a qualitative case-study seeking to characterize data discovery needs and barriers of principal investigators and research support staff in clinical translational science. Several implications for designing and implementing translational research systems have emerged through the authors' analysis. The results also illustrate the benefits of forming early partnerships with scientists to better understand their workflow processes and end-user computing practices in accessing data for research. The authors use this user-centered, iterative development approach to guide the implementation and extension of i2b2, a system they have adapted to support cross-institutional aggregate anonymized clinical data querying. With ongoing evaluation, the goal is to maximize the utility and extension of this system and develop an interface that appropriately fits the swiftly evolving needs of clinical translational scientists.