Improving big data governance in healthcare institutions: user experience research for honest broker based application to access healthcare big data

ABSTRACT

Data users (researchers, scientists) in healthcare institutions need access to integrated healthcare data to conduct timely analysis of diseases to serve the right population at the right time. However, preserving patient privacy and timely access to quality healthcare data is a critical challenge. Current healthcare data governance systems are largely manual. Besides, processing process data requests is extremely slow, often taking months. To address this gap, we designed an honest-broker-based healthcare application to support data users in accessing healthcare data securely and to design a comprehendible process of data governance for data users. This study applied two iterations of a user experience (UX) evaluation of an honest broker prototype. Results show that participants found the new system promising for their research prospects. Implications suggest that technological knowledge should not be a requirement for using healthcare applications to promote broader adoption in the community. This study highlights the necessity of a process to balance the control of access to sensitive data between data providers and users as well as to educate data users on data privacy. Iterative UX studies can be a fruitful approach in gradually uncovering problems and improving the design of complex systems.

KEYWORDS:

• Data governance
• requesting patient data
• user experience
• usability
• cyberinfrastructure
• healthcare

Acknowledgements

We are thankful to the participants for taking the time to participate in this study. We are also grateful to Fan Yu, Soumya Purohit, Naga Ramya Bhamidipati for participating in the software development and evaluation study of the healthcare application.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partially supported by the National Science Foundation [award number OAC-1827177]. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.