Genomics in nephrology: identifying informatics opportunities to improve diagnosis of genetic kidney disorders using a human-centered design approach

Author:

Romagnoli Katrina M1,Salvati Zachary M2,Johnson Darren K2,Ramey Heather M2,Chang Alexander R13,Williams Marc S2

Affiliation:

1. Department of Population Health Sciences, Geisinger Clinic , Danville, PA 17822, United States

2. Department of Genomic Health, Geisinger , Danville, PA 17822, United States

3. Department of Nephrology, Geisinger , Danville, PA 17822, United States

Abstract

Abstract Background Genomic kidney conditions often have a long lag between onset of symptoms and diagnosis. To design a real time genetic diagnosis process that meets the needs of nephrologists, we need to understand the current state, barriers, and facilitators nephrologists and other clinicians who treat kidney conditions experience, and identify areas of opportunity for improvement and innovation. Methods Qualitative in-depth interviews were conducted with nephrologists and internists from 7 health systems. Rapid analysis identified themes in the interviews. These were used to develop service blueprints and process maps depicting the current state of genetic diagnosis of kidney disease. Results Themes from the interviews included the importance of trustworthy resources, guidance on how to order tests, and clarity on what to do with results. Barriers included lack of knowledge, lack of access, and complexity surrounding the case and disease. Facilitators included good user experience, straightforward diagnoses, and support from colleagues. Discussion The current state of diagnosis of kidney diseases with genetic etiology is suboptimal, with information gaps, complexity of genetic testing processes, and heterogeneity of disease impeding efficiency and leading to poor outcomes. This study highlights opportunities for improvement and innovation to address these barriers and empower nephrologists and other clinicians who treat kidney conditions to access and use real time genetic information.

Funder

National Human Genome Research Institute

National Institutes of Health

Publisher

Oxford University Press (OUP)

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