The Development of an Infrastructure to Facilitate the Use of Whole Genome Sequencing for Population Health.

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.

Universal Germline Testing of Unselected Cancer Patients Detects Pathogenic Variants Missed by Standard Guidelines without Increasing Healthcare Costs.

PURPOSE: To accurately ascertain the frequency of pathogenic germline variants (PGVs) in a pan-cancer patient population with universal genetic testing and to assess the economic impact of receiving genetic testing on healthcare costs. METHODS: In this prospective study, germline genetic testing using a 105-gene panel was administered to an unselected pan-cancer patient population irrespective of eligibility by current guidelines. Financial records of subjects were analyzed to assess the effect of PGV detection on cost of care one year from the date of testing. RESULTS: A total of 284 patients participated in this study, of which 44 patients (15%) tested positive for a PGV in 14 different cancer types. Of the patients with PGVs, 23 patients (52%) were ineligible for testing by current guidelines. Identification of a PGV did not increase cost of care. CONCLUSION: Implementation of universal genetic testing for cancer patients in the clinic, beyond that specified by current guidelines, is necessary to accurately assess and treat hereditary cancer syndromes and does not increase healthcare costs.