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Designing user interface requirement patterns for a genomically enabled clinical decision support system using frailty assessment as a prototypical example

University of British Columbia

At present, the pervasive integration of genomics and other big data into routine clinical care has not been realized, particularly in primary care. One of the critical problems of personalized medicine is an effective and efficient presentation of large genomic data and evolving knowledge in a generalist clinical encounter setting. To address this issue, this study aimed to design and evaluate a user interface for a genomic clinical decision support system intended for primary care physicians. This was a serial, multiple-methods study. This study focused on frailty and the clinically actionable aspects of the frailty lifecycle, such as risk assessment. In phase one of this research, the Lead User method for the participatory design was used for the design of the user interface for genomically-enabled decision support. The concept ideation phase was followed by the design synthesis process in phase two. Phase two generated a set of system-agnostic and evidence-based requirement patterns and an integrated user interface design based on the patterns. In phase three, the integrated design was validated with Representative Users, and the patterns were refined. The key novel contributions of this work were user interface requirement patterns for genomically-enabled clinical decision support and a requirement integration method that supported the pattern development. The nineteen novel and validated requirement patterns are geared towards primary care providers as clinical users. The produced patterns addressed the presentation of CDSS notifications at the point-of-care and the display of detailed personalized risk information, including the risk factors and suggested interventions to address risk. These patterns are technology-agnostic and provide information to future implementers of clinical information systems. Producing theoretically-grounded and user-validated design patterns for presenting large evolving clinical data and knowledge, rather than a particular implementation, allows for this work to be relevant in various software-intensive clinical systems and contexts. Methodologically, the study contributed by developing a requirement integration method that is practical, reproducible, and applicable to a wide variety of design problems where it is necessary to synthesize multiple design perspectives. The method ensures traceability of requirement origin and evolution. It supports theory-informed design and triangulation of evidence.

Text

2020-07-16

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/75182

Experimental Medicine

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/