The Development of an Infrastructure to Facilitate the Use of Whole Genome Sequencing for Population Health
Nephi Walton, Brent Hafen, Sara Graceffo, Nykole Sutherland, Melanie Emmerson, Rachel Palmquist, Christine M. Formea, Maricel Purcell, Bret S.E. Heale, Matthew A. Brown, Christopher J. Danford, Sumathi I. Rachamadugu, Thomas N. Person, Katherine Shortt, G. Bryce Christensen, Jared M. Evans, Sharanya Raghunath, Christopher P. Johnson, Stacey Knight, Viet T. Le, Jeffrey L. Anderson, Margaret Van Meter, Teresa Reading, Derrick S. Haslem, Ivy C. Hansen, Betsey Batcher, Tyler Barker, Travis J. Sheffield, Bhaskara Yandava, David P. Taylor, Pallavi Ranade-Kharkar, Christopher Giauque, Kenneth R. Eyring, Jesse W. Breinholt, Mickey Miller, Payton R. Carter, Jason Gillman, Andrew W. Gunn, Kirk U. Knowlton, Joshua L. Bonkowsky, Kāri Stefánsson, Lincoln Nadauld, Howard L. McLeod
Abstract
The clinical use of genomic analysis has expanded rapidly resulting in an increased availability and utility of genomic information in clinical care. We have developed an infrastructure utilizing informatics tools and clinical processes to facilitate the use of whole genome sequencing data for population health management across the healthcare system. Our resulting framework scaled well to multiple clinical domains in both pediatric and adult care, although there were domain specific challenges that arose. Our infrastructure was complementary to existing clinical processes and well-received by care providers and patients. Informatics solutions were critical to the successful deployment and scaling of this program. Implementation of genomics at the scale of population health utilizes complicated technologies and processes that for many health systems are not supported by current information systems or in existing clinical workflows. To scale such a system requires a substantial clinical framework backed by informatics tools to facilitate the flow and management of data. Our work represents an early model that has been successful in scaling to 29 different genes with associated genetic conditions in four clinical domains. Work is ongoing to optimize informatics tools; and to identify best practices for translation to smaller healthcare systems.