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

Authors :
Kelsey S. Lau-Min
Danielle McKenna
Stephanie Byers Asher
Tanya Bardakjian
Colin Wollack
Joseph Bleznuck
Daniel Biros
Arravinth Anantharajah
Dana F. Clark
Courtney Condit
Jessica E. Ebrahimzadeh
Jessica M. Long
Jacquelyn Powers
Anna Raper
Anna Schoenbaum
Michael Feldman
Lauren Steinfeld
Sony Tuteja
Christine VanZandbergen
Susan M. Domchek
Marylyn D. Ritchie
Jeffrey Landgraf
Jessica Chen
Katherine L. Nathanson
Source :
Genetics in Medicine. 24:2338-2350
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

Integrating genomic data into the electronic health record (EHR) is key for optimally delivering genomic medicine.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.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.The PGI's efforts to integrate genomic medicine into the EHR have substantially streamlined the delivery of genomic medicine.

Details

ISSN :
10983600
Volume :
24
Database :
OpenAIRE
Journal :
Genetics in Medicine
Accession number :
edsair.doi.dedup.....220196df29df1e5836b4173cbac6eec9