CC BY 4.0 · ACI Open 2020; 04(02): e162-e166
DOI: 10.1055/s-0040-1721490
Case Report

Pilot Implementation of Clinical Genomic Data into the Native Electronic Health Record: Challenges of Scalability

Nephi A. Walton
1  Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, United States
2  Intermountain Precision Genomics, Intermountain Healthcare, St. George, Utah, United States
,
Darren K. Johnson
1  Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, United States
,
Thomas N. Person
1  Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, United States
,
Jonathon C. Reynolds
1  Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, United States
,
Marc S. Williams
1  Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, United States
› Author Affiliations
Funding This study was funded by National Human Genome Research Institute, grant: U01HG8679-01.

Abstract

Background Recently, electronic health record (EHR) vendors have allowed for the storage of discrete genomic data within the EHR. With this new capability there remain many challenges related to adoption and implementation. Geisinger has genomic data available for approximately 145,000 patients. With the goal of integrating genetic data into the EHR for the entire sequenced population, we performed a pilot study on a subpopulation to assess the plausibility of large-scale deployment.

Objectives

  1. Import genetic results into the EHR for seven pharmacogenes, Center for Disease Control tier one conditions, and hereditary hemochromatosis.

  2. Build decision support and information resources for each condition.

  3. Identify barriers to scaling the deployment.

  4. Identify short-term and long-term solutions to overcome identified barriers.

Methods Discrete genomic variants were imported into the EHR. Maintenance guidelines and information resources were developed for each genetic condition and best practice alerts were built for pharmacogenomic variants. Weekly calls were held to address barriers to implementation. A list of challenges was maintained throughout the process. Solutions were proposed and categorized into short-term and long-term solutions.

Results Challenges were identified and solutions proposed for five discrete areas:

  1. Transmitting data from the laboratory to the EHR.

  2. Maintenance of information and decision support.

  3. Disparate implementation needs of geneticists versus primary care.

  4. Differing perceptions/uses of discrete genomic data versus a PDF report.

  5. Classification and reclassification of variants.

Conclusion Scaling the use of genomic data in the EHR requires the engagement of hospitals, open standards communities, laboratories, EHR vendors, and genomic information resources.

Protection of Human and Animal Subjects

All research activities reported in this publication were reviewed and approved by the Geisinger Institutional Review Board.




Publication History

Received: 15 April 2020

Accepted: 04 November 2020

Publication Date:
31 December 2020 (online)

© 2020. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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