Workforce readiness for pharmacogenomics and key elements for sustainment within the Veterans Health Administration.
Date
2024-02
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Citation Stats
Abstract
Aim: Understanding barriers and facilitators to pharmacogenomics (PGx) implementation and how to structure a clinical program with the Veterans Health Administration (VA). Materials & methods: Healthcare provider (HCP) survey at 20 VA facilities assessing PGx knowledge/acceptance and qualitative interviews to understand how best to design and sustain a national program. Results: 186 (12% response rate) surveyed believed PGx informs drug efficacy (74.7%) and adverse events (71.0%). Low confidence in knowledge (43.0%) and ability to implement (35.4-43.5%). 23 (60.5% response rate) interviewees supported a nationally program to oversee VA education, consultation and IT resources. Prescribing HCPs should be directing local activities. Conclusion: HCPs recognize PGx value but are not prepared to implement. Healthcare systems should build system-wide programs for implementation education and support.
Type
Department
Description
Provenance
Citation
Permalink
Published Version (Please cite this version)
Publication Info
Wu, Rebekah Ryanne, Richelle Benevent, Nina R Sperber, Jill S Bates, Daniel Villa, Dilhan Weeraratne, Timothy A Burrell, Deepak Voora, et al. (2024). Workforce readiness for pharmacogenomics and key elements for sustainment within the Veterans Health Administration. Pharmacogenomics, 25(3). pp. 133–145. 10.2217/pgs-2023-0193 Retrieved from https://hdl.handle.net/10161/30456.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Collections
Scholars@Duke

Rebekah Ryanne Wu
Dr. Wu is an internal medicine physician and health services researcher. Her main research interest is studying the implementation of precision medicine applications to improve clinical care. She is involved in projects currently looking at a patient-facing family history risk assessment tool, MeTree, which provides individualized risk stratification and clinical decision support recommendations to clinicians and patients. In addition she is also involved in a large scale sequencing program in Singapore looking at the intersection of family health history and genomics to better understand how these data elements can complement one another and create more precise risk predictions. She is a member of NHGRI's IGNITE network as a co-investigator on a multi-site pragmatic clinical trial of the impact of pharmacogenetic testing on management of depression and acute, and chronic pain. She is the implementation science advisor for the VA's Pharmacogenomic Testing for Veterans (PHASER) program, which is working to complete preemptive PGx testing on up to 250,000 Veterans by 2024.

Nina Sperber
My research career has centered on understanding how to improve delivery of new evidence-based practices in health care systems. I create study designs that integrate qualitative and quantitative methods (mixed-methods) and apply Implementation Science and System Science approaches. I currently have a developing body of academic work that uses participatory system dynamics modeling as a strategy to identify system level factors that affect development and implementation of equitable AI tools. For the VA health care system, I direct a cross-functional team that conducts rapid turnaround projects for high priority needs by VHA national, regional, and facility leaders.

Deepak Voora
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.