Impact of integrating genomic data into the electronic health record on genetics care delivery.

PURPOSE: Integrating genomic data into the electronic health record (EHR) is key for optimally delivering genomic medicine. METHODS: The PennChart Genomics Initiative (PGI) at the University of Pennsylvania is a multidisciplinary collaborative that has successfully linked orders and results from genetic testing laboratories with discrete genetic data in the EHR. We quantified the use of the genomic data within the EHR, performed a time study with genetic counselors, and conducted key informant interviews with PGI members to evaluate the effect of the PGI's efforts on genetics care delivery. RESULTS: The PGI has interfaced with 4 genetic testing laboratories, resulting in the creation of 420 unique computerized genetic testing orders that have been used 4073 times to date. In a time study of 96 genetic testing activities, EHR use was associated with significant reductions in time spent ordering (2 vs 8 minutes, P < .001) and managing (1 vs 5 minutes, P < .001) genetic results compared with the use of online laboratory-specific portals. In key informant interviews, multidisciplinary collaboration and institutional buy-in were identified as key ingredients for the PGI's success. CONCLUSION: The PGI's efforts to integrate genomic medicine into the EHR have substantially streamlined the delivery of genomic medicine.

Case report: 68 yo Chinese-American woman with high HDL-C and ischemic stroke attributed to intracranial atherosclerotic stenosis.

Atherosclerotic cardiovascular disease (ASCVD) events are the most common cause of death in the United States and for most individuals who experience these events, may be predicted by risk identification tools. ASCVD risk calculators enable a clinician-patient discussion and the presence of risk-enhancing factors may further inform decision-making with respect to preventive pharmacotherapy, especially statin prescription. In cases where the decision of whether to treat with medicine is unclear, coronary artery calcium scoring by computed tomography offers enhanced risk stratification and may allow both clinicians and patients to feel more at ease with the decision to withhold statin therapy. Despite this thoughtful approach, individual risk may still be underestimated. We present a case of a woman whose family history suggested increased short- and long-term ASCVD risk due to intracranial atherosclerosis, but whose tests suggested a more equivocal indication for treatment. Neither she nor her clinician appreciated the presence of significant enough risk to persevere through minor statin side effects for primary prevention, but she was lucky to have survived without appreciable harm from an acute cerebrovascular event and is now able to pursue an appropriate secondary preventive strategy. We discuss how exceptional characteristics may mislead clinicians, including misperception about lower risk due to gender, East Asian predisposition to intracranial more than coronary atherosclerosis, high levels of high density lipoprotein cholesterol (HDL-C), and CACS = 0.