The winding road of requesting healthcare data for analytics purposes: using the one-interview mental model method for improving services of health data governance and big data request processes

Abstract

ABSTRACT Medical schools store large sets of patient data. The data is important for the analysis of trends and patterns in healthcare practice. However, obtaining access to the data can be problematic due to the data protection mechanisms. In this study, we investigate the current practices from the lens of both the data requester and the data provider. Results reveal discrepancies between how the provider organises the data governance process, how the process is presented to the data requester, and the data requester’s perception of satisfactory user experience. This study provides a simple one interview mental model method approach for data governance services to reveal potential problems in the process. This is a quick and effective method for data providers to help uncover the challenges and to provide foundations for future fully automated (human out of the loop) systems for data accessibility in healthcare organisations.