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Kneifati-Hayek JZ, Zachariah T, Ahn W, Khan A, Kiryluk K, Mohan S, Weng C, Gharavi AG, Nestor JG. Bridging the Gap in Genomic Implementation: Identifying User Needs for Precision Nephrology. Kidney Int Rep 2024; 9:2420-2431. [PMID: 39156149 PMCID: PMC11328575 DOI: 10.1016/j.ekir.2024.05.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 05/22/2024] [Accepted: 05/27/2024] [Indexed: 08/20/2024] Open
Abstract
Introduction Genomic medicine holds transformative potential for personalized nephrology care; however, its clinical integration poses challenges. Automated clinical decision support (CDS) systems in the electronic health record (EHR) offer a promising solution but have shown limited impact. This study aims to glean practical insights into nephrologists' challenges using genomic resources, informing precision nephrology decision support tools. Methods We conducted an anonymous electronic survey among US nephrologists from January 19, 2021 to May 19, 2021, guided by the Consolidated Framework for Implementation Research. It assessed practice characteristics, genomic resource utilization, attitudes, perceived knowledge, self-efficacy, and factors influencing genetic testing decisions. Survey links were primarily shared with National Kidney Foundation members. Results We analyzed 319 surveys, with most respondents specializing in adult nephrology. Although respondents generally acknowledged the clinical use of genomic resources, varying levels of perceived knowledge and self-efficacy were evident regarding precision nephrology workflows. Barriers to genetic testing included cost/insurance coverage and limited genomics experience. Conclusion The study illuminates specific hurdles nephrologists face using genomic resources. The findings are a valuable contribution to genomic implementation research, highlighting the significance of developing tailored interventions to support clinicians in using genomic resources effectively. These findings can guide the future development of CDS systems in the EHR. Addressing unmet informational and workflow support needs can enhance the integration of genomics into clinical practice, advancing personalized nephrology care and improving kidney disease outcomes. Further research should focus on interventions promoting seamless precision nephrology care integration.
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Affiliation(s)
| | - Teena Zachariah
- Division of Nephrology, Department of Medicine, Columbia University, New York, USA
| | - Wooin Ahn
- Division of Nephrology, Department of Medicine, Columbia University, New York, USA
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Columbia University, New York, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Columbia University, New York, USA
| | - Sumit Mohan
- Division of Nephrology, Department of Medicine, Columbia University, New York, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, USA
| | - Ali G. Gharavi
- Division of Nephrology, Department of Medicine, Columbia University, New York, USA
- Institute for Genomic Medicine, Columbia University, Hammer Health Sciences, New York, USA
| | - Jordan G. Nestor
- Division of Nephrology, Department of Medicine, Columbia University, New York, USA
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Lingaratnam S, Shah M, Nicolazzo J, Michael M, Seymour JF, James P, Lazarakis S, Loi S, Kirkpatrick CMJ. A systematic review and meta-analysis of the impacts of germline pharmacogenomics on severe toxicity and symptom burden in adult patients with cancer. Clin Transl Sci 2024; 17:e13781. [PMID: 38700261 PMCID: PMC11067509 DOI: 10.1111/cts.13781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 02/12/2024] [Accepted: 03/14/2024] [Indexed: 05/05/2024] Open
Abstract
The clinical application of Pharmacogenomics (PGx) has improved patient safety. However, comprehensive PGx testing has not been widely adopted in clinical practice, and significant opportunities exist to further optimize PGx in cancer care. This systematic review and meta-analysis aim to evaluate the safety outcomes of reported PGx-guided strategies (Analysis 1) and identify well-studied emerging pharmacogenomic variants that predict severe toxicity and symptom burden (Analysis 2) in patients with cancer. We searched MEDLINE, EMBASE, CENTRAL, clinicaltrials.gov, and International Clinical Trials Registry Platform from inception to January 2023 for clinical trials or comparative studies evaluating PGx strategies or unconfirmed pharmacogenomic variants. The primary outcomes were severe adverse events (SAE; ≥ grade 3) or symptom burden with pain and vomiting as defined by trial protocols and assessed by trial investigators. We calculated pooled overall relative risk (RR) and 95% confidence interval (95%CI) using random effects models. PROSPERO, registration number CRD42023421277. Of 6811 records screened, six studies were included for Analysis 1, 55 studies for Analysis 2. Meta-analysis 1 (five trials, 1892 participants) showed a lower absolute incidence of SAEs with PGx-guided strategies compared to usual therapy, 16.1% versus 34.0% (RR = 0.72, 95%CI 0.57-0.91, p = 0.006, I2 = 34%). Meta-analyses 2 identified nine medicine(class)-variant pairs of interest across the TYMS, ABCB1, UGT1A1, HLA-DRB1, and OPRM1 genes. Application of PGx significantly reduced rates of SAEs in patients with cancer. Emergent medicine-variant pairs herald further research into the expansion and optimization of PGx to improve systemic anti-cancer and supportive care medicine safety and efficacy.
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Affiliation(s)
- Senthil Lingaratnam
- Pharmacy DepartmentPeter MacCallum Cancer CentreMelbourneVictoriaAustralia
- Sir Peter MacCallum Department of OncologyUniversity of MelbourneMelbourneVictoriaAustralia
- Monash Institute of Pharmaceutical Sciences, Monash UniversityMelbourneVictoriaAustralia
| | - Mahek Shah
- Faculty of Pharmacy and Pharmaceutical SciencesMonash UniversityMelbourneVictoriaAustralia
| | - Joseph Nicolazzo
- Monash Institute of Pharmaceutical Sciences, Monash UniversityMelbourneVictoriaAustralia
| | - Michael Michael
- Sir Peter MacCallum Department of OncologyUniversity of MelbourneMelbourneVictoriaAustralia
- Department of Medical OncologyPeter MacCallum Cancer CentreMelbourneVictoriaAustralia
| | - John F. Seymour
- Sir Peter MacCallum Department of OncologyUniversity of MelbourneMelbourneVictoriaAustralia
- Department of Clinical HaematologyPeter MacCallum Cancer Centre and Royal Melbourne HospitalMelbourneVictoriaAustralia
| | - Paul James
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre and Royal Melbourne HospitalMelbourneVictoriaAustralia
| | - Smaro Lazarakis
- Health Sciences LibraryRoyal Melbourne HospitalMelbourneVictoriaAustralia
| | - Sherene Loi
- Sir Peter MacCallum Department of OncologyUniversity of MelbourneMelbourneVictoriaAustralia
- Division of Cancer ResearchPeter MacCallum Cancer CentreMelbourneVictoriaAustralia
| | - Carl M. J. Kirkpatrick
- Monash Institute of Pharmaceutical Sciences, Monash UniversityMelbourneVictoriaAustralia
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Tokutomi T, Yoshida A, Fukushima A, Yamamoto K, Ishigaki Y, Kawame H, Fuse N, Nagami F, Suzuki Y, Sakurai-Yageta M, Uruno A, Suzuki K, Tanno K, Ohmomo H, Shimizu A, Yamamoto M, Sasaki M. The Health History of First-Degree Relatives' Dyslipidemia Can Affect Preferences and Intentions following the Return of Genomic Results for Monogenic Familial Hypercholesterolemia. Genes (Basel) 2024; 15:384. [PMID: 38540442 PMCID: PMC10970353 DOI: 10.3390/genes15030384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 03/14/2024] [Accepted: 03/19/2024] [Indexed: 06/14/2024] Open
Abstract
Genetic testing is key in modern healthcare, particularly for monogenic disorders such as familial hypercholesterolemia. This Tohoku Medical Megabank Project study explored the impact of first-degree relatives' dyslipidemia history on individual responses to familial hypercholesterolemia genomic results. Involving 214 participants and using Japan's 3.5KJPN genome reference panel, the study assessed preferences and intentions regarding familial hypercholesterolemia genetic testing results. The data revealed a significant inclination among participants with a family history of dyslipidemia to share their genetic test results, with more than 80% of participants intending to share positive results with their partners and children and 98.1% acknowledging the usefulness of positive results for personal health management. The study underscores the importance of family health history in genetic-testing perceptions, highlighting the need for family-centered approaches in genetic counseling and healthcare. Notable study limitations include the regional scope and reliance on questionnaire data. The study results emphasize the association between family health history and genetic-testing attitudes and decisions.
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Affiliation(s)
- Tomoharu Tokutomi
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa 020-3694, Japan; (A.Y.)
- Department of Clinical Genetics, School of Medicine, Iwate Medical University, Morioka 020-8505, Japan
| | - Akiko Yoshida
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa 020-3694, Japan; (A.Y.)
- Department of Clinical Genetics, School of Medicine, Iwate Medical University, Morioka 020-8505, Japan
| | - Akimune Fukushima
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa 020-3694, Japan; (A.Y.)
- Department of Clinical Genetics, School of Medicine, Iwate Medical University, Morioka 020-8505, Japan
| | - Kayono Yamamoto
- Department of Clinical Genetics, School of Medicine, Iwate Medical University, Morioka 020-8505, Japan
| | - Yasushi Ishigaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa 020-3694, Japan; (A.Y.)
| | - Hiroshi Kawame
- Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan
| | - Fuji Nagami
- Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan
| | - Yoichi Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan
| | - Mika Sakurai-Yageta
- Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan
| | - Akira Uruno
- Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan
| | - Kichiya Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan
| | - Kozo Tanno
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa 020-3694, Japan; (A.Y.)
| | - Hideki Ohmomo
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa 020-3694, Japan; (A.Y.)
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa 020-3694, Japan; (A.Y.)
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa 020-3694, Japan; (A.Y.)
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Bastaki K, Velayutham D, Irfan A, Adnan M, Mohammed S, Mbarek H, Qoronfleh MW, Jithesh PV. Forging the path to precision medicine in Qatar: a public health perspective on pharmacogenomics initiatives. Front Public Health 2024; 12:1364221. [PMID: 38550311 PMCID: PMC10977610 DOI: 10.3389/fpubh.2024.1364221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Accepted: 02/20/2024] [Indexed: 04/02/2024] Open
Abstract
Pharmacogenomics (PGx) is an important component of precision medicine that promises tailored treatment approaches based on an individual's genetic information. Exploring the initiatives in research that help to integrate PGx test into clinical setting, identifying the potential barriers and challenges as well as planning the future directions, are all important for fruitful PGx implementation in any population. Qatar serves as an exemplar case study for the Middle East, having a small native population compared to a diverse immigrant population, advanced healthcare system, national genome program, and several educational initiatives on PGx and precision medicine. This paper attempts to outline the current state of PGx research and implementation in Qatar within the global context, emphasizing ongoing initiatives and educational efforts. The inclusion of PGx in university curricula and healthcare provider training, alongside precision medicine conferences, showcase Qatar's commitment to advancing this field. However, challenges persist, including the requirement for population specific implementation strategies, complex genetic data interpretation, lack of standardization, and limited awareness. The review suggests policy development for future directions in continued research investment, conducting clinical trials for the feasibility of PGx implementation, ethical considerations, technological advancements, and global collaborations to overcome these barriers.
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Affiliation(s)
- Kholoud Bastaki
- Clinical and Pharmacy Practice Department, College of Pharmacy, QU Health, Qatar University, Doha, Qatar
| | - Dinesh Velayutham
- College of Health & Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
| | - Areeba Irfan
- College of Health & Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
| | - Mohd Adnan
- College of Health & Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
| | - Sawsan Mohammed
- College of Medicine, Pre-Clinical Education Department, QU Health, Qatar University, Doha, Qatar
| | | | - M. Waild Qoronfleh
- Q3 Research Institute (QRI), Research & Policy Division, Ann Arbor, MI, United States
| | - Puthen Veettil Jithesh
- College of Health & Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
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Kamga KK, Fonkam MP, Nguefack S, Wonkam A. Navigating the Genetic Frontier for the Integration of Genetic Services into African Healthcare Systems: A scoping review. RESEARCH SQUARE 2024:rs.3.rs-3978686. [PMID: 38464219 PMCID: PMC10925396 DOI: 10.21203/rs.3.rs-3978686/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Background The integration of genetic services into African healthcare systems is a multifaceted endeavor marked by both obstacles and prospects. This study aims to furnish evidence-based recommendations for policymakers and healthcare entities to facilitate the effective assimilation of genetic services within African healthcare systems. Methods Employing a scoping review methodology, we scrutinized peer-reviewed studies spanning from 2003 to 2023, sourced from PubMed, Scopus, and Africa-wide databases. Our analysis drew upon eight pertinent research studies conducted between 2016 and 2023, encompassing diverse genetic topics across six African nations, namely Cameroon, Kenya, Nigeria, Rwanda, South Africa, and Tanzania. Results The reviewed studies underscored numerous challenges hindering the implementation of genetic services in African healthcare systems. These obstacles encompassed deficiencies in disease awareness and education, impediments to genetic testing, resource scarcities, ethical quandaries, and issues related to follow-up and retention. Nevertheless, the authors also identified opportunities and strategies conducive to successful integration, emphasizing proactive measures such as community engagement, advocacy, and the fostering of supportive networks. Conclusion The integration of genetic services in Africa holds promise for enhancing healthcare outcomes but also poses challenges and opportunities for healthcare and biotechnology enterprises. To address gaps in disease awareness, we advocate for healthcare providers to invest in educational initiatives, forge partnerships with local institutions, and leverage digital platforms. Furthermore, we urge businesses to innovate and devise cost-effective genetic testing models while establishing online forums to promote dialogue and contribute positively to African healthcare.
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Buzatu I, Tache DE, Manea Carneluti EV, Zlatian O. ELTD1 Review: New Regulator of Angiogenesis in Glioma. CURRENT HEALTH SCIENCES JOURNAL 2023; 49:495-502. [PMID: 38559823 PMCID: PMC10976199 DOI: 10.12865/chsj.49.04.03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 10/11/2023] [Indexed: 04/04/2024]
Abstract
Glioblastoma (GBM) is a severe brain cancer in which angiogenesis is controlled by G protein-coupled receptors (GPCRs), such as Epidermal Growth Factor Latrophilin and seven transmembrane domain-containing protein 1 (ELTD1), which are crucial for tumor progression. ELTD1 is an understudied GPCR with a broad expression profile in various tissues, including the human brain, especially in the cerebral cortex. It plays a significant role in angiogenesis and tumorigenesis and is regulated by interconnected VEGF and DLL4/Notch pathways. ELTD1 also modulates the JAK/STAT3/HIF-1α signaling axis, affecting the response of cells to low-oxygen conditions and promoting cell proliferation. However, their specific ligands and functional mechanisms remain unclear. ELTD1 expression is associated with different outcomes in various cancers. For example, in GBM, higher ELTD1 levels are linked to more mature and less leaky blood vessels, potentially enhancing drug delivery and therapeutic success. It also has divergent prognostic implications in renal, ovarian, and colorectal cancer. Additionally, ELTD1 overexpression in central nervous system endothelial cells suggests that it is a potential biomarker for multiple sclerosis. Therapeutically, blocking ELTD1 inhibits vessel formation, possibly slowing tumor growth. Initial therapies used polyclonal antibodies, but the shift has been towards more targeted monoclonal antibodies, particularly in preclinical glioma models. This review aimed to translate these insights into effective clinical treatments. However, several gaps remain in our knowledge regarding ELTD1 ligands and their potential involvement in other physiological or pathological processes that future research can address to elucidate the role of ELTD1 in cancer, through angiogenesis and other intracellular pathways.
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Affiliation(s)
| | - Daniela Elise Tache
- Department of Biochemistry, Faculty of Medicine, University of Medicine and Pharmacy of Craiova, Romania
| | | | - Ovidiu Zlatian
- Department of Microbiology, Faculty of Medicine, University of Medicine and Pharmacy of Craiova, Romania
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Oni-Orisan A, Tuteja S, Hoffecker G, Smith DM, Castrichini M, Crews KR, Murphy WA, Nguyen NHK, Huang Y, Lteif C, Friede KA, Tantisira K, Aminkeng F, Voora D, Cavallari LH, Whirl-Carrillo M, Duarte JD, Luzum JA. An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers. Clin Pharmacol Ther 2023; 114:275-287. [PMID: 37303270 PMCID: PMC10406163 DOI: 10.1002/cpt.2957] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/17/2023] [Indexed: 06/13/2023]
Abstract
Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.
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Affiliation(s)
- Akinyemi Oni-Orisan
- Department of Clinical Pharmacy, University of California San Francisco, San Francisco, California, USA
| | - Sony Tuteja
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Glenda Hoffecker
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - D. Max Smith
- MedStar Health, Columbia, Maryland, USA
- Department of Oncology, Georgetown University Medical Center, Washington, DC, USA
| | - Matteo Castrichini
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Kristine R. Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - William A. Murphy
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nam H. K. Nguyen
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Yimei Huang
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Christelle Lteif
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Kevin A. Friede
- Division of Cardiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Kelan Tantisira
- Division of Respiratory Medicine, Department of Pediatrics, University of California San Diego, San Diego, California, USA
| | - Folefac Aminkeng
- Departments of Medicine and Biomedical Informatics (DBMI), Yong Loo Lin School of Medicine, National University of Singapore, Singapore City, Singapore
- Centre for Precision Health (CPH), National University Health System (NUHS), Singapore City, Singapore
| | - Deepak Voora
- Precision Medicine Program, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Julio D. Duarte
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Jasmine A. Luzum
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, Michigan, USA
- Center for Individualized and Genomic Medicine Research, Henry Ford Health System, Detroit, Michigan, USA
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Milko LV, Berg JS. Age-Based Genomic Screening during Childhood: Ethical and Practical Considerations in Public Health Genomics Implementation. Int J Neonatal Screen 2023; 9:36. [PMID: 37489489 PMCID: PMC10366892 DOI: 10.3390/ijns9030036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 06/07/2023] [Accepted: 06/21/2023] [Indexed: 07/26/2023] Open
Abstract
Genomic sequencing offers an unprecedented opportunity to detect inherited variants that are implicated in rare Mendelian disorders, yet there are many challenges to overcome before this technology can routinely be applied in the healthy population. The age-based genomic screening (ABGS) approach is a novel alternative to genome-scale sequencing at birth that aims to provide highly actionable genetic information to parents over the course of their child's routine health care. ABGS utilizes an established metric to identify conditions with high clinical actionability and incorporates information about the age of onset and age of intervention to determine the optimal time to screen for any given condition. Ongoing partnerships with parents and providers are instrumental to the co-creation of educational resources and strategies to address potential implementation barriers. Implementation science frameworks and informative empirical data are used to evaluate strategies to establish this unique clinical application of targeted genomic sequencing. Ultimately, a pilot project conducted in primary care pediatrics clinics will assess patient and implementation outcomes, parent and provider perspectives, and the feasibility of ABGS. A validated, stakeholder-informed, and practical ABGS program will include hundreds of conditions that are actionable during infancy and childhood, setting the stage for a longitudinal implementation that can assess clinical and health economic outcomes.
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Affiliation(s)
- Laura V. Milko
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Rd., Chapel Hill, NC 27599-7264, USA;
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Ellis SD, Brooks JV, Birken SA, Morrow E, Hilbig ZS, Wulff-Burchfield E, Kinney AY, Ellerbeck EF. Determinants of targeted cancer therapy use in community oncology practice: a qualitative study using the Theoretical Domains Framework and Rummler-Brache process mapping. Implement Sci Commun 2023; 4:66. [PMID: 37308981 PMCID: PMC10259814 DOI: 10.1186/s43058-023-00441-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 05/25/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Precision medicine holds enormous potential to improve outcomes for cancer patients, offering improved rates of cancer control and quality of life. Not all patients who could benefit from targeted cancer therapy receive it, and some who may not benefit do receive targeted therapy. We sought to comprehensively identify determinants of targeted therapy use among community oncology programs, where most cancer patients receive their care. METHODS Guided by the Theoretical Domains Framework, we conducted semi-structured interviews with 24 community cancer care providers and mapped targeted therapy delivery across 11 cancer care delivery teams using a Rummler-Brache diagram. Transcripts were coded to the framework using template analysis, and inductive coding was used to identify key behaviors. Coding was revised until a consensus was reached. RESULTS Intention to deliver precision medicine was high across all participants interviewed, who also reported untenable knowledge demands. We identified distinctly different teams, processes, and determinants for (1) genomic test ordering and (2) delivery of targeted therapies. A key determinant of molecular testing was role alignment. The dominant expectation for oncologists to order and interpret genomic tests is at odds with their role as treatment decision-makers' and pathologists' typical role to stage tumors. Programs in which pathologists considered genomic test ordering as part of their staging responsibilities reported high and timely testing rates. Determinants of treatment delivery were contingent on resources and ability to offset delivery costs, which low- volume programs could not do. Rural programs faced additional treatment delivery challenges. CONCLUSIONS We identified novel determinants of targeted therapy delivery that potentially could be addressed through role re-alignment. Standardized, pathology-initiated genomic testing may prove fruitful in ensuring patients eligible for targeted therapy are identified, even if the care they need cannot be delivered at small and rural sites which may have distinct challenges in treatment delivery. Incorporating behavior specification and Rummler-Brache process mapping with determinant analysis may extend its usefulness beyond the identification of the need for contextual adaptation.
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Affiliation(s)
- Shellie D. Ellis
- University of Kansas School of Medicine, 3901 Rainbow Blvd., Kansas City, KS 66610 USA
| | - Joanna Veazey Brooks
- University of Kansas School of Medicine, 3901 Rainbow Blvd., Kansas City, KS 66610 USA
| | - Sarah A. Birken
- Wake Forest University School of Medicine, 525 Vine Street, Winston-Salem, NC 27101 USA
| | - Emily Morrow
- Kansas City Kansas Community College, 7250 State Ave., Kansas City, KS 66112 USA
| | - Zachary S. Hilbig
- University of Kansas School of Medicine, 3901 Rainbow Blvd., Kansas City, KS 66610 USA
| | | | - Anita Y. Kinney
- Rutgers Cancer Institute of New Jersey, Rutgers University, 195 Little Albany St., New Brunswick, NJ 08901 USA
| | - Edward F. Ellerbeck
- University of Kansas School of Medicine, 3901 Rainbow Blvd., Kansas City, KS 66610 USA
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Wu RR, Myers RA, Neuner J, McCarty C, Haller IV, Harry M, Fulda KG, Dimmock D, Rakhra-Burris T, Buchanan A, Ginsburg GS, Orlando LA. Implementation-effectiveness trial of systematic family health history based risk assessment and impact on clinical disease prevention and surveillance activities. BMC Health Serv Res 2022; 22:1486. [PMID: 36474257 PMCID: PMC9727967 DOI: 10.1186/s12913-022-08879-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 11/23/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Systematically assessing disease risk can improve population health by identifying those eligible for enhanced prevention/screening strategies. This study aims to determine the clinical impact of a systematic risk assessment in diverse primary care populations. METHODS Hybrid implementation-effectiveness trial of a family health history-based health risk assessment (HRA) tied to risk-based guideline recommendations enrolling from 2014-2017 with 12 months of post-intervention survey data and 24 months of electronic medical record (EMR) data capture. SETTING 19 primary care clinics at four geographically and culturally diverse U.S. healthcare systems. PARTICIPANTS any English or Spanish-speaking adult with an upcoming appointment at an enrolling clinic. METHODS A personal and family health history based HRA with integrated guideline-based clinical decision support (CDS) was completed by each participant prior to their appointment. Risk reports were provided to patients and providers to discuss at their clinical encounter. OUTCOMES provider and patient discussion and provider uptake (i.e. ordering) and patient uptake (i.e. recommendation completion) of CDS recommendations. MEASURES patient and provider surveys and EMR data. RESULTS One thousand eight hundred twenty nine participants (mean age 56.2 [SD13.9], 69.6% female) completed the HRA and had EMR data available for analysis. 762 (41.6%) received a recommendation (29.7% for genetic counseling (GC); 15.2% for enhanced breast/colon cancer screening). Those with recommendations frequently discussed disease risk with their provider (8.7%-38.2% varied by recommendation, p-values ≤ 0.004). In the GC subgroup, provider discussions increased referrals to counseling (44.4% with vs. 5.9% without, P < 0.001). Recommendation uptake was highest for colon cancer screening (provider = 67.9%; patient = 86.8%) and lowest for breast cancer chemoprevention (0%). CONCLUSIONS Systematic health risk assessment revealed that almost half the population were at increased disease risk based on guidelines. Risk identification resulted in shared discussions between participants and providers but variable clinical action uptake depending upon the recommendation. Understanding the barriers and facilitators to uptake by both patients and providers will be essential for optimizing HRA tools and achieving their promise of improving population health. TRIAL REGISTRATION Clinicaltrials.gov number NCT01956773 , registered 10/8/2013.
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Affiliation(s)
- R Ryanne Wu
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
- Duke-NUS Medical School, Programme in Health Services and Systems Research, Singapore, Singapore.
| | - Rachel A Myers
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Joan Neuner
- Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA
- Center for Patient Care and Outcomes Research, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Catherine McCarty
- University of Minnesota Medical School, Duluth Campus, Duluth, MN, USA
| | | | | | - Kimberly G Fulda
- The North Texas Primary Care Practice-Based Research Network and Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - David Dimmock
- Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
| | - Tejinder Rakhra-Burris
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Adam Buchanan
- Genomic Medicine Institute, Geisinger, Geisinger, PA, USA
| | - Geoffrey S Ginsburg
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Lori A Orlando
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
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11
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Cavallari LH, Pratt VM. Building Evidence for Clinical Use of Pharmacogenomics and Reimbursement for Testing. Clin Lab Med 2022; 42:533-546. [PMID: 36368780 PMCID: PMC9896522 DOI: 10.1016/j.cll.2022.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, PO Box 100486, Gainesville, FL 32610-0486, USA.
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12
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Truong TM, Apfelbaum JL, Danahey K, Schierer E, Ludwig J, George D, House L, Karrison T, Shahul S, Anitescu M, Choksi A, Hartman S, Knoebel RW, van Wijk XM, Yeo KTJ, Meltzer D, Ratain MJ, O’Donnell PH. Pilot Findings of Pharmacogenomics in Perioperative Care: Initial Results From the First Phase of the ImPreSS Trial. Anesth Analg 2022; 135:929-940. [PMID: 35213469 PMCID: PMC9402808 DOI: 10.1213/ane.0000000000005951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
BACKGROUND Pharmacogenomics, which offers a potential means by which to inform prescribing and avoid adverse drug reactions, has gained increasing consideration in other medical settings but has not been broadly evaluated during perioperative care. METHODS The Implementation of Pharmacogenomic Decision Support in Surgery (ImPreSS) Trial is a prospective, single-center study consisting of a prerandomization pilot and a subsequent randomized phase. We describe findings from the pilot period. Patients planning elective surgeries were genotyped with pharmacogenomic results, and decision support was made available to anesthesia providers in advance of surgery. Pharmacogenomic result access and prescribing records were analyzed. Surveys (Likert-scale) were administered to providers to understand utilization barriers. RESULTS Of eligible anesthesiology providers, 166 of 211 (79%) enrolled. A total of 71 patients underwent genotyping and surgery (median, 62 years; 55% female; average American Society of Anesthesiologists (ASA) score, 2.6; 58 inpatients and 13 ambulatories). No patients required postoperative intensive care or pain consultations. At least 1 provider accessed pharmacogenomic results before or during 41 of 71 surgeries (58%). Faculty were more likely to access results (78%) compared to house staff (41%; P = .003) and midlevel practitioners (15%) ( P < .0001). Notably, all administered intraoperative medications had favorable genomic results with the exception of succinylcholine administration to 1 patient with genomically increased risk for prolonged apnea (without adverse outcome). Considering composite prescribing in preoperative, recovery, throughout hospitalization, and at discharge, each patient was prescribed a median of 35 (range 15-83) total medications, 7 (range 1-22) of which had annotated pharmacogenomic results. Of 2371 prescribing events, 5 genomically high-risk medications were administered (all tramadol or omeprazole; with 2 of 5 pharmacogenomic results accessed), and 100 genomically cautionary mediations were administered (hydralazine, oxycodone, and pantoprazole; 61% rate of accessing results). Providers reported that although results were generally easy to access and understand, the most common reason for not considering results was because remembering to access pharmacogenomic information was not yet a part of their normal clinical workflow. CONCLUSIONS Our pilot data for result access rates suggest interest in pharmacogenomics by anesthesia providers, even if opportunities to alter prescribing in response to high-risk genotypes were infrequent. This pilot phase has also uncovered unique considerations for implementing pharmacogenomic information in the perioperative care setting, and new strategies including adding the involvement of surgery teams, targeting patients likely to need intensive care and dedicated pain care, and embedding pharmacists within rounding models will be incorporated in the follow-on randomized phase to increase engagement and likelihood of affecting prescribing decisions and clinical outcomes.
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Affiliation(s)
- Tien M. Truong
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
| | - Jeffrey L. Apfelbaum
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Keith Danahey
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Center for Research Informatics, University of Chicago, Chicago, IL, USA
| | - Emily Schierer
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - Jenna Ludwig
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - David George
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Larry House
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Theodore Karrison
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Sajid Shahul
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Magdalena Anitescu
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Anish Choksi
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Seth Hartman
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Randall W. Knoebel
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Xander M.R. van Wijk
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Kiang-Teck J. Yeo
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - David Meltzer
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Mark J. Ratain
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
| | - Peter H. O’Donnell
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
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13
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Public Attitudes toward Pharmacogenomic Testing and Establishing a Statewide Pharmacogenomics Database in the State of Minnesota. J Pers Med 2022; 12:jpm12101615. [PMID: 36294754 PMCID: PMC9604616 DOI: 10.3390/jpm12101615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 09/18/2022] [Accepted: 09/19/2022] [Indexed: 11/07/2022] Open
Abstract
The clinical adoption and implementation of pharmacogenomics (PGx) beyond academic medical centers remains slow, restricting the general population from benefitting from this important component of personalized medicine. As an initial step in the statewide initiative of PGx implementation in Minnesota, we engaged community members and assessed attitudes towards PGx testing and acceptability of establishing a secure statewide PGx database for clinical and research use among Minnesota residents. Data was collected from 808 adult attendees at the 2021 Minnesota State Fair through an electronic survey. Eighty-four percent of respondents felt comfortable getting a PGx test for clinical care. Most respondents trusted health professionals (78.2%) and researchers (73.0%) to keep their PGx data private. The majority expressed their support and interest in participating in a statewide PGx database for clinical and research use (64–72%). Higher acceptability of the statewide PGx database was associated with younger age, higher education, higher health literacy, having health insurance, and prior genetic testing. The study sample representing Minnesota residents expressed high acceptability of receiving PGx testing and willingness to participate in PGx data sharing for clinical and research use. Community support and engagement are needed to advance PGx implementation and research on the state scale.
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14
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Zhang H, Kleinberger JW, Maloney KA, Guan Y, Mathias TJ, Bisordi K, Streeten EA, Blessing K, Snyder MN, Bromberger LA, Goehringer J, Kimball A, Damcott CM, Taylor CO, Nicholson M, Nwaba D, Palmer K, Sewell D, Ambulos N, Jeng LJB, Shuldiner AR, Levin P, Carey DJ, Pollin TI. Model for Integration of Monogenic Diabetes Diagnosis Into Routine Care: The Personalized Diabetes Medicine Program. Diabetes Care 2022; 45:1799-1806. [PMID: 35763601 PMCID: PMC9346978 DOI: 10.2337/dc21-1975] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 05/03/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To implement, disseminate, and evaluate a sustainable method for identifying, diagnosing, and promoting individualized therapy for monogenic diabetes. RESEARCH DESIGN AND METHODS Patients were recruited into the implementation study through a screening questionnaire completed in the waiting room or through the patient portal, physician recognition, or self-referral. Patients suspected of having monogenic diabetes based on the processing of their questionnaire and other data through an algorithm underwent next-generation sequencing for 40 genes implicated in monogenic diabetes and related conditions. RESULTS Three hundred thirteen probands with suspected monogenic diabetes (but most diagnosed with type 2 diabetes) were enrolled from October 2014 to January 2019. Sequencing identified 38 individuals with monogenic diabetes, with most variants found in GCK or HNF1A. Positivity rates for ascertainment methods were 3.1% for clinic screening, 5.3% for electronic health record portal screening, 16.5% for physician recognition, and 32.4% for self-referral. The algorithmic criterion of non-type 1 diabetes before age 30 years had an overall positivity rate of 15.0%. CONCLUSIONS We successfully modeled the efficient incorporation of monogenic diabetes diagnosis into the diabetes care setting, using multiple strategies to screen and identify a subpopulation with a 12.1% prevalence of monogenic diabetes by molecular testing. Self-referral was particularly efficient (32% prevalence), suggesting that educating the lay public in addition to clinicians may be the most effective way to increase the diagnosis rate in monogenic diabetes. Scaling up this model will assure access to diagnosis and customized treatment among those with monogenic diabetes and, more broadly, access to personalized medicine across disease areas.
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Affiliation(s)
- Haichen Zhang
- Department of Endocrinology, Peking Union Medical College Hospital, Beijing, China.,Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Jeffrey W Kleinberger
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Kristin A Maloney
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Yue Guan
- Rollins School of Public Health, Emory University, Atlanta, GA
| | - Trevor J Mathias
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Katharine Bisordi
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Elizabeth A Streeten
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | | | | | - Lee A Bromberger
- Metabolism, Osteoporosis/Obesity, Diabetes, Endocrinology and Lipids (MODEL) Clinical Research, Research Division of Bay Endocrinology Associates, Baltimore, MD
| | | | - Amy Kimball
- Harvey Institute for Human Genetics, Greater Baltimore Medical Center, Baltimore, MD
| | - Coleen M Damcott
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Casey O Taylor
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Michaela Nicholson
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Devon Nwaba
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Kathleen Palmer
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Danielle Sewell
- University of Maryland Marlene and Stewart Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD
| | - Nicholas Ambulos
- University of Maryland Marlene and Stewart Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD
| | - Linda J B Jeng
- Division of Rare Diseases and Medical Genetics, US Food and Drug Administration, Silver Spring, MD
| | - Alan R Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Philip Levin
- Bay West Endocrinology Associates, Baltimore, MD
| | | | - Toni I Pollin
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
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15
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Blagec K, Swen JJ, Koopmann R, Cheung KC, Crommentuijn-van Rhenen M, Holsappel I, Konta L, Ott S, Steinberger D, Xu H, Cecchin E, Dolžan V, Dávila-Fajardo CL, Patrinos GP, Sunder-Plassmann G, Turner RM, Pirmohamed M, Guchelaar HJ, Samwald M. Pharmacogenomics decision support in the U-PGx project: Results and advice from clinical implementation across seven European countries. PLoS One 2022; 17:e0268534. [PMID: 35675343 PMCID: PMC9176797 DOI: 10.1371/journal.pone.0268534] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 04/26/2022] [Indexed: 12/18/2022] Open
Abstract
Background The clinical implementation of pharmacogenomics (PGx) could be one of the first milestones towards realizing personalized medicine in routine care. However, its widespread adoption requires the availability of suitable clinical decision support (CDS) systems, which is often impeded by the fragmentation or absence of adequate health IT infrastructures. We report results of CDS implementation in the large-scale European research project Ubiquitous Pharmacogenomics (U-PGx), in which PGx CDS was rolled out and evaluated across more than 15 clinical sites in the Netherlands, Spain, Slovenia, Italy, Greece, United Kingdom and Austria, covering a wide variety of healthcare settings. Methods We evaluated the CDS implementation process through qualitative and quantitative process indicators. Quantitative indicators included statistics on generated PGx reports, median time from sampled upload until report delivery and statistics on report retrievals via the mobile-based CDS tool. Adoption of different CDS tools, uptake and usability were further investigated through a user survey among healthcare providers. Results of a risk assessment conducted prior to the implementation process were retrospectively analyzed and compared to actual encountered difficulties and their impact. Results As of March 2021, personalized PGx reports were produced from 6884 genotyped samples with a median delivery time of twenty minutes. Out of 131 invited healthcare providers, 65 completed the questionnaire (response rate: 49.6%). Overall satisfaction rates with the different CDS tools varied between 63.6% and 85.2% per tool. Delays in implementation were caused by challenges including institutional factors and complexities in the development of required tools and reference data resources, such as genotype-phenotype mappings. Conclusions We demonstrated the feasibility of implementing a standardized PGx decision support solution in a multinational, multi-language and multi-center setting. Remaining challenges for future wide-scale roll-out include the harmonization of existing PGx information in guidelines and drug labels, the need for strategies to lower the barrier of PGx CDS adoption for healthcare institutions and providers, and easier compliance with regulatory and legal frameworks.
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Affiliation(s)
- Kathrin Blagec
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Jesse J Swen
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Rudolf Koopmann
- Diagnosticum Center for Human Genetics, Frankfurt am Main, Germany.,Institute for Human Genetics, Justus Liebig University, Giessen, Germany
| | - Ka-Chun Cheung
- Medicines Information Centre, Royal Dutch Pharmacists Association (KNMP), The Hague, The Netherlands
| | | | - Inge Holsappel
- Medicines Information Centre, Royal Dutch Pharmacists Association (KNMP), The Hague, The Netherlands
| | - Lidija Konta
- Diagnosticum Center for Human Genetics, Frankfurt am Main, Germany
| | - Simon Ott
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Daniela Steinberger
- Diagnosticum Center for Human Genetics, Frankfurt am Main, Germany.,Institute for Human Genetics, Justus Liebig University, Giessen, Germany
| | - Hong Xu
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Erika Cecchin
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy
| | - Vita Dolžan
- Faculty of Medicine, Institute of Biochemistry and Molecular Genetics, Pharmacogenetics Laboratory, University of Ljubljana, Ljubljana, Slovenia
| | - Cristina Lucía Dávila-Fajardo
- Clinical Pharmacy Department, Hospital Universitario Virgen de las Nieves, Instituto de Investigación Biosanitaria Granada (Ibs.Granada), Granada, Spain
| | - George P Patrinos
- Department of Pharmacy, Laboratory of Pharmacogenomics and Individualized Therapy, University of Patras School of Health Sciences, Patras, Greece
| | - Gere Sunder-Plassmann
- Division of Nephrology and Dialysis, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Richard M Turner
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- Department of Molecular and Clinical Pharmacology, Royal Liverpool University Hospital and University of Liverpool, Liverpool, United Kingdom
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthias Samwald
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
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16
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Madden JA, Brothers KK, Williams JL, Myers MF, Leppig KA, Clayton EW, Wiesner GL, Holm IA. Impact of returning unsolicited genomic results to nongenetic health care providers in the eMERGE III Network. Genet Med 2022; 24:1297-1305. [PMID: 35341654 PMCID: PMC9940614 DOI: 10.1016/j.gim.2022.02.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 02/22/2022] [Accepted: 02/28/2022] [Indexed: 10/18/2022] Open
Abstract
PURPOSE As genomic sequencing becomes more common, medically actionable secondary findings will increasingly be returned to health care providers (HCPs), who will be faced with managing the resulting patient care. These findings are generally unsolicited, ie, unrelated to the sequencing indication and/or ordered by another clinician. METHODS To understand the impact of receiving unsolicited results, we interviewed HCPs who received genomic results for patients enrolled in the Electronic Medical Records and Genomics (eMERGE) Phase III Network, which returned results on >100 actionable genes to eMERGE participants and HCPs. RESULTS In total, 16 HCPs across 3 eMERGE sites were interviewed about their experience of receiving a positive (likely pathogenic or pathogenic), negative, or variant of uncertain significance result for a patient enrolled in eMERGE Phase III and about managing their patient on the basis of the result. Although unsolicited, HCPs felt responsible for managing the patient's resulting medical care. HCPs indicated that clinical utility depended on the actionability of results, and whereas comfort levels varied, confidence was improved by the availability of subspecialist consults. HCPs were concerned about patient anxiety, insurability, and missing an actionable result in the electronic health record. CONCLUSION Our findings help inform best practices for return of unsolicited genomic screening findings in the future.
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Affiliation(s)
- Jill A. Madden
- Division of Genetics & Genomics and the Manton Center for Orphan Disease Research, Boston Children’s Hospital, Boston, MA
| | - Kyle K. Brothers
- Department of Pediatrics, School of Medicine, University of Louisville, Louisville, KY
| | | | - Melanie F. Myers
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, and College of Medicine, University of Cincinnati, Cincinnati, OH
| | | | - Ellen Wright Clayton
- Center for Biomedical Ethics and Society and Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
| | - Georgia L. Wiesner
- Division of Genetic Medicine, Department of Medicine, and Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Ingrid A. Holm
- Division of Genetics & Genomics and the Manton Center for Orphan Disease Research, Boston Children’s Hospital, Boston, MA,Department of Pediatrics, Harvard Medical School, Boston, MA,Correspondence and requests for materials should be addressed to Ingrid A. Holm, Division of Genetics and Genomics and the Manton Center for Orphan Disease Research, Boston Children’s Hospital, Boston, MA.
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17
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Salloum RG, Bishop JR, Elchynski AL, Smith DM, Rowe E, Blake KV, Limdi NA, Aquilante CL, Bates J, Beitelshees AL, Cipriani A, Duong BQ, Empey PE, Formea CM, Hicks JK, Mroz P, Oslin D, Pasternak AL, Petry N, Ramsey LB, Schlichte A, Swain SM, Ward KM, Wiisanen K, Skaar TC, Van Driest SL, Cavallari LH, Tuteja S. Best-worst scaling methodology to evaluate constructs of the Consolidated Framework for Implementation Research: application to the implementation of pharmacogenetic testing for antidepressant therapy. Implement Sci Commun 2022; 3:52. [PMID: 35568931 PMCID: PMC9107643 DOI: 10.1186/s43058-022-00300-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 04/25/2022] [Indexed: 11/10/2022] Open
Abstract
Background Despite the increased demand for pharmacogenetic (PGx) testing to guide antidepressant use, little is known about how to implement testing in clinical practice. Best–worst scaling (BWS) is a stated preferences technique for determining the relative importance of alternative scenarios and is increasingly being used as a healthcare assessment tool, with potential applications in implementation research. We conducted a BWS experiment to evaluate the relative importance of implementation factors for PGx testing to guide antidepressant use. Methods We surveyed 17 healthcare organizations that either had implemented or were in the process of implementing PGx testing for antidepressants. The survey included a BWS experiment to evaluate the relative importance of Consolidated Framework for Implementation Research (CFIR) constructs from the perspective of implementing sites. Results Participating sites varied on their PGx testing platform and methods for returning recommendations to providers and patients, but they were consistent in ranking several CFIR constructs as most important for implementation: patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and identification of champions. Conclusions This study demonstrates the feasibility of using choice experiments to systematically evaluate the relative importance of implementation determinants from the perspective of implementing organizations. BWS findings can inform other organizations interested in implementing PGx testing for mental health. Further, this study demonstrates the application of BWS to PGx, the findings of which may be used by other organizations to inform implementation of PGx testing for mental health disorders. Supplementary Information The online version contains supplementary material available at 10.1186/s43058-022-00300-7.
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Affiliation(s)
- Ramzi G Salloum
- University of Florida Clinical and Translational Science Institute, Gainesville, FL, USA.,University of Florida College of Medicine, Gainesville, FL, USA
| | - Jeffrey R Bishop
- University of Minnesota Medical School, Minneapolis, MN, USA.,University of Minnesota College of Pharmacy, Minneapolis, MN, USA
| | | | - D Max Smith
- MedStar Health, Georgetown University Medical Center, Washington, DC, USA
| | - Elizabeth Rowe
- Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Nita A Limdi
- University of Alabama Heersink School of Medicine, Birmingham, AL, USA
| | | | - Jill Bates
- Durham VA Healthcare System, Durham, NC, USA
| | | | - Amber Cipriani
- University of North Carolina Medical Center, Chapel Hill, NC, USA
| | | | - Philip E Empey
- University of Pittsburgh School of Pharmacy, Pittsburgh, PA, USA
| | | | | | - Pawel Mroz
- University of Minnesota Medical School, Minneapolis, MN, USA
| | - David Oslin
- Corporal Michael J. Cresenz VA Medical Center, Philadelphia, PA, USA
| | - Amy L Pasternak
- University of Michigan College of Pharmacy, Ann Arbor, MI, USA
| | - Natasha Petry
- North Dakota State University/Sanford Health, Fargo, ND, USA
| | - Laura B Ramsey
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | | | - Sandra M Swain
- MedStar Health, Georgetown University Medical Center, Washington, DC, USA
| | - Kristen M Ward
- University of Michigan College of Pharmacy, Ann Arbor, MI, USA
| | | | - Todd C Skaar
- Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Larisa H Cavallari
- University of Florida Clinical and Translational Science Institute, Gainesville, FL, USA.,University of Florida College of Pharmacy, Gainesville, FL, USA
| | - Sony Tuteja
- University of Pennsylvania Perelman School of Medicine, Smilow Center for Translational Research, 3400 Civic Center Boulevard, Bldg. 421 11th Floor, Room 143, Philadelphia, PA, 19104-5158, USA.
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18
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Wildin RS, Giummo CA, Reiter AW, Peterson TC, Leonard DGB. Primary Care Implementation of Genomic Population Health Screening Using a Large Gene Sequencing Panel. Front Genet 2022; 13:867334. [PMID: 35547253 PMCID: PMC9081681 DOI: 10.3389/fgene.2022.867334] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 03/21/2022] [Indexed: 11/17/2022] Open
Abstract
To realize the promise of genomic medicine, harness the power of genomic technologies, and capitalize on the extraordinary pace of research linking genomic variation to disease risks, healthcare systems must embrace and integrate genomics into routine healthcare. We have implemented an innovative pilot program for genomic population health screening for any-health-status adults within the largest health system in Vermont, United States. This program draws on key research and technological advances to safely extract clinical value for genomics in routine health care. The program offers no-cost, non-research DNA sequencing to patients by their primary care providers as a preventive health tool. We partnered with a commercial clinical testing company for two next generation sequencing gene panels comprising 431 genes related to both high and low-penetrance common health risks and carrier status for recessive disorders. Only pathogenic or likely pathogenic variants are reported. Routine written clinical consultation is provided with a concise, clinical “action plan” that presents core messages for primary care provider and patient use and supports clinical management and health education beyond the testing laboratory’s reports. Access to genetic counseling is free in most cases. Predefined care pathways and access to genetics experts facilitates the appropriate use of results. This pilot tests the feasibility of routine, ethical, and scalable use of population genomic screening in healthcare despite generally imperfect genomic competency among both the public and health care providers. This article describes the program design, implementation process, guiding philosophies, and insights from 2 years of experience offering testing and returning results in primary care settings. To aid others planning similar programs, we review our barriers, solutions, and perceived gaps in the context of an implementation research framework.
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Affiliation(s)
- Robert S Wildin
- Department of Pathology & Laboratory Medicine, University of Vermont Health Network and Robert Larner M.D. College of Medicine at the University of Vermont, Burlington, VT, United States.,Department of Pediatrics, University of Vermont Health Network and Robert Larner M.D. College of Medicine at the University of Vermont, Burlington, VT, United States
| | - Christine A Giummo
- Department of Pathology & Laboratory Medicine, University of Vermont Health Network and Robert Larner M.D. College of Medicine at the University of Vermont, Burlington, VT, United States.,Department of Pediatrics, University of Vermont Health Network and Robert Larner M.D. College of Medicine at the University of Vermont, Burlington, VT, United States
| | - Aaron W Reiter
- Department of Family Medicine, University of Vermont Health Network and Robert Larner M.D. College of Medicine at the University of Vermont, Burlington, VT, United States
| | - Thomas C Peterson
- Department of Family Medicine, University of Vermont Health Network and Robert Larner M.D. College of Medicine at the University of Vermont, Burlington, VT, United States
| | - Debra G B Leonard
- Department of Pathology & Laboratory Medicine, University of Vermont Health Network and Robert Larner M.D. College of Medicine at the University of Vermont, Burlington, VT, United States
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19
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Receiving results of uncertain clinical relevance from population genetic screening: systematic review & meta-synthesis of qualitative research. Eur J Hum Genet 2022; 30:520-531. [PMID: 35256770 PMCID: PMC9090782 DOI: 10.1038/s41431-022-01054-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 01/11/2022] [Accepted: 01/18/2022] [Indexed: 01/01/2023] Open
Abstract
Genetic screening can be hugely beneficial, yet its expansion poses clinical and ethical challenges due to results of uncertain clinical relevance (such as ‘cystic fibrosis screen positive, inconclusive diagnosis’/CFSPID). This review systematically identifies, appraises, and synthesises the qualitative research on experiences of receiving results of uncertain clinical relevance from population genetic screening. Eight databases were systematically searched for original qualitative research using the SPIDER framework, and checked against inclusion criteria by the research team and an independent researcher. Nine papers were included (from USA, Canada, UK, New Zealand). PRISMA, ENTREQ, and EMERGE guidance were used to report. Quality was appraised using criteria for qualitative research. All papers focused on parental responses to uncertain results from newborn screening. Data were synthesised using meta-ethnography and first- and second-order constructs. Findings suggest that results of uncertain clinical relevance are often experienced in the same way as a ‘full-blown’ diagnosis. This has significant emotional and behavioural impact, for example adoption of lifestyle-altering disease-focused behaviours. Analysis suggests this may be due to the results not fitting a common medical model, leading recipients to interpret the significance of the result maladaptively. Findings suggest scope for professionals to negotiate and reframe uncertain screening results. Clearer initial communication is needed to reassure recipients there is no immediate severe health risk from these types of results. Public understanding of an appropriate medical model, that accounts for uncertain genetic screening results in a non-threatening way, may be key to maximising the benefits of genomic medicine and minimising potential psychological harm.
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20
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The reckoning: The return of genomic results to 1444 participants across the eMERGE3 Network. Genet Med 2022; 24:1130-1138. [PMID: 35216901 PMCID: PMC10074557 DOI: 10.1016/j.gim.2022.01.015] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 02/05/2023] Open
Abstract
PURPOSE The goal of Electronic Medical Records and Genomics (eMERGE) Phase III Network was to return actionable sequence variants to 25,084 consenting participants from 10 different health care institutions across the United States. The purpose of this study was to evaluate system-based issues relating to the return of results (RoR) disclosure process for clinical grade research genomic tests to eMERGE3 participants. METHODS RoR processes were developed and approved by each eMERGE institution's internal review board. Investigators at each eMERGE3 site were surveyed for RoR processes related to the participant's disclosure of pathogenic or likely pathogenic variants and engagement with genetic counseling. Standard statistical analysis was performed. RESULTS Of the 25,084 eMERGE participants, 1444 had a pathogenic or likely pathogenic variant identified on the eMERGEseq panel of 67 genes and 14 single nucleotide variants. Of these, 1077 (74.6%) participants had results disclosed, with 562 (38.9%) participants provided with variant-specific genetic counseling. Site-specific processes that either offered or required genetic counseling in their RoR process had an effect on whether a participant ultimately engaged with genetic counseling (P = .0052). CONCLUSION The real-life experience of the multiarm eMERGE3 RoR study for returning actionable genomic results to consented research participants showed the impact of consent, method of disclosure, and genetic counseling on RoR.
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21
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Hertz DL, McShane LM, Hayes DF. Defining Clinical Utility of Germline Indicators of Toxicity Risk: A Perspective. J Clin Oncol 2022; 40:1721-1731. [PMID: 35324346 PMCID: PMC9148690 DOI: 10.1200/jco.21.02209] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Affiliation(s)
- Daniel L Hertz
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Daniel F Hayes
- Stuart B. Padnos Professor of Breast Cancer Research, University of Michigan Rogel Cancer Center, Ann Arbor, MI
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22
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Schwartz TS, Christensen KD, Uveges MK, Waisbren SE, McGuire AL, Pereira S, Robinson JO, Beggs AH, Green RC, Bachmann GA, Rabson AB, Holm IA. Effects of participation in a U.S. trial of newborn genomic sequencing on parents at risk for depression. J Genet Couns 2022; 31:218-229. [PMID: 34309124 PMCID: PMC8789951 DOI: 10.1002/jgc4.1475] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 06/15/2021] [Accepted: 06/27/2021] [Indexed: 02/03/2023]
Abstract
Much emphasis has been placed on participant's psychological safety within genomic research studies; however, few studies have addressed parental psychological health effects associated with their child's participation in genomic studies, particularly when parents meet the threshold for clinical concern for depression. We aimed to determine if parents' depressive symptoms were associated with their child's participation in a randomized-controlled trial of newborn exome sequencing. Parents completed the Edinburgh Postnatal Depression Scale (EPDS) at baseline, immediately post-disclosure, and 3 months post-disclosure. Mothers and fathers scoring at or above thresholds for clinical concern on the EPDS, 12 and 10, respectively, indicating possible Major Depressive Disorder with Peripartum Onset, were contacted by study staff for mental health screening. Parental concerns identified in follow-up conversations were coded for themes. Forty-five parents had EPDS scores above the clinical threshold at baseline, which decreased by an average of 2.9 points immediately post-disclosure and another 1.1 points 3 months post-disclosure (both p ≤ .014). For 28 parents, EPDS scores were below the threshold for clinical concern at baseline, increased by an average of 4.7 points into the elevated range immediately post-disclosure, and decreased by 3.8 points at 3 months post-disclosure (both p < .001). Nine parents scored above thresholds only at 3 months post-disclosure after increasing an average of 5.7 points from immediately post-disclosure (p < .001). Of the 82 parents who scored above the threshold at any time point, 43 (52.4%) were reached and 30 (69.7%) of these 43 parents attributed their elevated scores to parenting stress, balancing work and family responsibilities, and/or child health concerns. Only three parents (7.0%) raised concerns about their participation in the trial, particularly their randomization to the control arm. Elevated scores on the EPDS were typically transient and parents attributed their symptomatology to life stressors in the postpartum period rather than participation in a trial of newborn exome sequencing.
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Affiliation(s)
- Talia S Schwartz
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, Massachusetts, USA.,Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey, USA
| | - Kurt D Christensen
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.,The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Melissa K Uveges
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Connell School of Nursing, Boston College, Chestnut Hill, Massachusetts, USA
| | - Susan E Waisbren
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Amy L McGuire
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas, USA
| | - Stacey Pereira
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas, USA
| | - Jill O Robinson
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas, USA
| | - Alan H Beggs
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Robert C Green
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA.,Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | | | - Gloria A Bachmann
- Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey, USA
| | - Arnold B Rabson
- Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey, USA
| | - Ingrid A Holm
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
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23
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Lajonchere C, Naeim A, Dry S, Wenger N, Elashoff D, Vangala S, Petruse A, Ariannejad M, Magyar C, Johansen L, Werre G, Kroloff M, Geschwind D. An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study. J Med Internet Res 2021; 23:e31121. [PMID: 34889741 PMCID: PMC8701720 DOI: 10.2196/31121] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 08/23/2021] [Accepted: 09/18/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Obtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine. OBJECTIVE We aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system. METHODS The University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected. RESULTS The consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; P<.001). Patients with higher medical acuity were more likely to opt in. The multivariate analyses showed that African American (odds ratio [OR] 0.53, 95% CI 0.49-0.58; P<.001), Asian (OR 0.72, 95% CI 0.68-0.77; P<.001), and multiple-race populations (OR 0.73, 95% CI 0.69-0.77; P<.001) were less likely to participate than White individuals. CONCLUSIONS This is one of the few large-scale, electronic video-based consent implementation programs that reports a 65.5% (26,314/40,144) average overall opt-in rate across a large academic health system. This rate is higher than those previously reported for email (3.6%) and electronic biobank (50%) informed consent rates. This study demonstrates a scalable recruitment approach for population health research.
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Affiliation(s)
- Clara Lajonchere
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Arash Naeim
- Center for SMART Health, Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Sarah Dry
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Neil Wenger
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - David Elashoff
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Sitaram Vangala
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Antonia Petruse
- Embedded Clinical Research and Innovation Unit, Clinical and Translational Science Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Maryam Ariannejad
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Clara Magyar
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Liliana Johansen
- Embedded Clinical Research and Innovation Unit, Clinical and Translational Science Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Gabriela Werre
- Embedded Clinical Research and Innovation Unit, Clinical and Translational Science Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Maxwell Kroloff
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Daniel Geschwind
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
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24
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David SP, Singh L, Pruitt J, Hensing A, Hulick P, Meltzer DO, O’Donnell PH, Dunnenberger HM. The Contribution of Pharmacogenetic Drug Interactions to 90-Day Hospital Readmissions: Preliminary Results from a Real-World Healthcare System. J Pers Med 2021; 11:jpm11121242. [PMID: 34945714 PMCID: PMC8705172 DOI: 10.3390/jpm11121242] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 11/21/2021] [Accepted: 11/21/2021] [Indexed: 01/09/2023] Open
Abstract
Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines exist for many medications commonly prescribed prior to hospital discharge, yet there are limited data regarding the contribution of gene-x-drug interactions to hospital readmissions. The present study evaluated the relationship between prescription of CPIC medications prescribed within 30 days of hospital admission and 90-day hospital readmission from 2010 to 2020 in a study population (N = 10,104) who underwent sequencing with a 14-gene pharmacogenetic panel. The presence of at least one pharmacogenetic indicator for a medication prescribed within 30 days of hospital admission was considered a gene-x-drug interaction. Multivariable logistic regression analyzed the association between one or more gene-x-drug interactions with 90-day readmission. There were 2211/2354 (93.9%) admitted patients who were prescribed at least one CPIC medication. Univariate analyses indicated that the presence of at least one identified gene-x-drug interaction increased the risk of 90-day readmission by more than 40% (OR = 1.42, 95% confidence interval (CI) 1.09–1.84) (p = 0.01). A multivariable model adjusting for age, race, sex, employment status, body mass index, and medical conditions slightly attenuated the effect (OR = 1.32, 95% CI 1.02–1.73) (p = 0.04). Our results suggest that the presence of one or more CPIC gene-x-drug interactions increases the risk of 90-day hospital readmission, even after adjustment for demographic and clinical risk factors.
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Affiliation(s)
- Sean P. David
- Department of Family Medicine, NorthShore University Health System, Evanston, IL 60201, USA;
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA; (P.H.); (D.O.M.); (P.H.O.)
- Correspondence:
| | - Lavisha Singh
- Department of Statistics, NorthShore University Health System, Evanston, IL 60201, USA;
| | - Jaclyn Pruitt
- Department of Surgery, NorthShore University Health System, Evanston, IL 60201, USA;
- Outcomes Research Network, NorthShore University Health System, Evanston, IL 60201, USA;
| | - Andrew Hensing
- Outcomes Research Network, NorthShore University Health System, Evanston, IL 60201, USA;
| | - Peter Hulick
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA; (P.H.); (D.O.M.); (P.H.O.)
- Center for Personalized Medicine, NorthShore University Health System, Evanston, IL 60201, USA
| | - David O. Meltzer
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA; (P.H.); (D.O.M.); (P.H.O.)
| | - Peter H. O’Donnell
- Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA; (P.H.); (D.O.M.); (P.H.O.)
| | - Henry M. Dunnenberger
- Department of Family Medicine, NorthShore University Health System, Evanston, IL 60201, USA;
- Outcomes Research Network, NorthShore University Health System, Evanston, IL 60201, USA;
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25
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Mroz P, Michel S, Allen JD, Meyer T, McGonagle EJ, Carpentier R, Vecchia A, Schlichte A, Bishop JR, Dunnenberger HM, Yohe S, Thyagarajan B, Jacobson PA, Johnson SG. Development and Implementation of In-House Pharmacogenomic Testing Program at a Major Academic Health System. Front Genet 2021; 12:712602. [PMID: 34745204 PMCID: PMC8564018 DOI: 10.3389/fgene.2021.712602] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/16/2021] [Indexed: 12/26/2022] Open
Abstract
Pharmacogenomics (PGx) studies how a person's genes affect the response to medications and is quickly becoming a significant part of precision medicine. The clinical application of PGx principles has consistently been cited as a major opportunity for improving therapeutic outcomes. Several recent studies have demonstrated that most individuals (> 90%) harbor PGx variants that would be clinically actionable if prescribed a medication relevant to that gene. In multiple well-conducted studies, the results of PGx testing have been shown to guide therapy choice and dosing modifications which improve treatment efficacy and reduce the incidence of adverse drug reactions (ADRs). Although the value of PGx testing is evident, its successful implementation in a clinical setting presents a number of challenges to molecular diagnostic laboratories, healthcare systems, providers and patients. Different molecular methods can be applied to identify PGx variants and the design of the assay is therefore extremely important. Once the genotyping results are available the biggest technical challenge lies in turning this complex genetic information into phenotypes and actionable recommendations that a busy clinician can effectively utilize to provide better medical care, in a cost-effective, efficient and reliable manner. In this paper we describe a successful and highly collaborative implementation of the PGx testing program at the University of Minnesota and MHealth Fairview Molecular Diagnostic Laboratory and selected Pharmacies and Clinics. We offer detailed descriptions of the necessary components of the pharmacogenomic testing implementation, the development and technical validation of the in-house SNP based multiplex PCR based assay targeting 20 genes and 48 SNPs as well as a separate CYP2D6 copy number assay along with the process of PGx report design, results of the provider and pharmacists usability studies, and the development of the software tool for genotype-phenotype translation and gene-phenotype-drug CPIC-based recommendations. Finally, we outline the process of developing the clinical workflow that connects the providers with the PGx experts within the Molecular Diagnostic Laboratory and the Pharmacy.
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Affiliation(s)
- Pawel Mroz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Stephen Michel
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Josiah D Allen
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | - Tim Meyer
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States
| | - Erin J McGonagle
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | | | | | | | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States.,Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Henry M Dunnenberger
- Mark R Neaman Center for Personalized Medicine Center, NorthShore University HealthSystem, Evanston, IL, United States
| | - Sophia Yohe
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Pamala A Jacobson
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States
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26
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Dong OM, Roberts MC, Wu RR, Voils CI, Sperber N, Gavin KL, Bates J, Chanfreau-Coffinier C, Naglich M, Kelley MJ, Vassy JL, Sriram P, Heise CW, Rivas S, Ribeiro M, Chapman JG, Voora D. Evaluation of the Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program at initial test sites. Pharmacogenomics 2021; 22:1121-1133. [PMID: 34704830 DOI: 10.2217/pgs-2021-0089] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: The first Plan-Do-Study-Act cycle for the Veterans Affairs Pharmacogenomic Testing for Veterans pharmacogenomic clinical testing program is described. Materials & methods: Surveys evaluating implementation resources and processes were distributed to implementation teams, providers, laboratory and health informatics staff. Survey responses were mapped to the Consolidated Framework for Implementation Research constructs to identify implementation barriers. The Expert Recommendation for Implementing Change strategies were used to address implementation barriers. Results: Survey response rate was 23-73% across personnel groups at six Veterans Affairs sites. Nine Consolidated Framework for Implementation Research constructs were most salient implementation barriers. Program revisions addressed these barriers using the Expert Recommendation for Implementing Change strategies related to three domains. Conclusion: Beyond providing free pharmacogenomic testing, additional implementation barriers need to be addressed for improved program uptake.
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Affiliation(s)
- Olivia M Dong
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
| | - Megan C Roberts
- Division of Pharmaceutical Outcomes & Policy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - R Ryanne Wu
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
| | - Corrine I Voils
- William S Middleton Memorial Veterans Hospital, Madison, WI 53705, USA.,Department of Surgery, University of Wisconsin School of Medicine & Public Health, Madison, WI 53792, USA
| | - Nina Sperber
- Duke Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27701, USA
| | - Kara L Gavin
- William S Middleton Memorial Veterans Hospital, Madison, WI 53705, USA.,Department of Surgery, University of Wisconsin School of Medicine & Public Health, Madison, WI 53792, USA
| | - Jill Bates
- Durham VA Health Care System, Durham, NC 27705, USA.,Division of Practice Advancement & Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Catherine Chanfreau-Coffinier
- VA Informatics & Computing Infrastructure (VINCI), Salt Lake City VA Health Care System, Salt Lake City, UT 84148, USA
| | - Michael Naglich
- Institute for Medical Research, Durham VA Medical Center, Durham, NC 27705, USA
| | - Michael J Kelley
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke University Medical Center, Durham, NC 27708, USA.,National Oncology Program Office, Office of Specialty Care, Department of Veterans Affairs, Durham, NC 27705, USA
| | - Jason L Vassy
- VA Boston Healthcare System, Boston, MA 02130, USA.,Harvard Medical School, Boston, MA 02115, USA
| | - Peruvemba Sriram
- North Florida/South Georgia Veterans Health System, Gainesville, FL 32608, USA
| | - C William Heise
- Phoenix VA Health Care System, Phoenix, AZ 85012, USA.,The University of Arizona College of Medicine - Phoenix, Phoenix, AZ 85004, USA
| | - Salvador Rivas
- Phoenix VA Health Care System, Phoenix, AZ 85012, USA.,The University of Arizona College of Medicine - Phoenix, Phoenix, AZ 85004, USA
| | - Maria Ribeiro
- Atlanta VA Medical Center, Atlanta, GA 30033, USA.,Department of Hematology & Medical Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jennifer G Chapman
- Institute for Medical Research, Durham VA Medical Center, Durham, NC 27705, USA
| | - Deepak Voora
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
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27
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Petry NJ, Curtis B, Feldhege E, Khan S, Leedahl DD, Breidenbach JL, Hines L. Impact of Automated Best Practice Advisories on Provider Response to CYP2C19 Genotyping Results for Patients on Clopidogrel. J Pharm Pract 2021; 36:487-493. [PMID: 34622701 DOI: 10.1177/08971900211049589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
ObjectiveThe study objective was to examine provider acceptance and genotyping responses to a best practice advisory (BPA) concerning clopidogrel and CYP2C19 intermediate and poor metabolizers within the context of a new pharmacogenomics program at a Midwestern health system. Other secondary objectives analyzed included appropriate BPA firing, the distribution of alleles in study population, indications for clopidogrel use, and impact of indication on therapy change. Methods: In this study, the progress of this program was assessed by quantifying how providers respond to BPAs generated in the electronic medical record (EMR), in the context of a single representative gene-drug-outcome relationship. Patient data was pulled via reports yielding patients with genotyped information in the EMR and cross-referenced with a report evaluating BPA firing occurrences. Results: By capturing antiplatelet therapy changes in response to CYP2C19 genotyping results, 37 patients were found that had 73 BPAs fire. Nine of those patients had alternative antiplatelet therapy ordered. Of these, 6 alternative antiplatelet therapies were ordered from the BPA. Conclusion: Providers utilized BPAs, but responded differently based on individual knowledge of genotypes and indications. Information obtained from this study can be used for provider education and as reference for future design and wording of BPAs.
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Affiliation(s)
- Natasha J Petry
- Department of Pharmacy Practice, School of Pharmacy, College of Health Professions, 3323North Dakota State University, Fargo, ND, USA.,Imagenetics, 24195Sanford Health, Sioux Falls, SD, USA
| | - Breanna Curtis
- Department of Pharmacy, 24195Sanford Health, Fargo, ND, USA
| | - Erica Feldhege
- Department of Pharmacy Practice, School of Pharmacy, College of Health Professions, 3323North Dakota State University, Fargo, ND, USA
| | - Shahjahan Khan
- Department of Internal Medicine, Sanford School of Medicine, 8191University of South Dakota, Sioux Falls, SD, USA
| | | | | | - Lindsay Hines
- Department of Neuropsychology, 24195Sanford Health, Fargo, ND, USA
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28
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Clinical implementation of drug metabolizing gene-based therapeutic interventions worldwide. Hum Genet 2021; 141:1137-1157. [PMID: 34599365 DOI: 10.1007/s00439-021-02369-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/09/2021] [Indexed: 02/05/2023]
Abstract
Over the last few years, the field of pharmacogenomics has gained considerable momentum. The advances of new genomics and bioinformatics technologies propelled pharmacogenomics towards its implementation in the clinical setting. Since 2007, and especially the last-5 years, many studies have focused on the clinical implementation of pharmacogenomics while identifying obstacles and proposed strategies and approaches for overcoming them in the real world of primary care as well as outpatients and inpatients clinics. Here, we outline the recent pharmacogenomics clinical implementation projects and provide details of the study designs, including the most predominant and innovative, as well as clinical studies worldwide that focus on outpatients and inpatient clinics, and primary care. According to these studies, pharmacogenomics holds promise for improving patients' health in terms of efficacy and toxicity, as well as in their overall quality of life, while simultaneously can contribute to the minimization of healthcare expenditure.
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29
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Eric V, Yi V, Murdock D, Kalla SE, Wu TJ, Sabo A, Li S, Meng Q, Tian X, Murugan M, Cohen M, Kovar C, Wei WQ, Chung WK, Weng C, Wiesner GL, Jarvik GP, Muzny D, Gibbs RA. Neptune: an environment for the delivery of genomic medicine. Genet Med 2021; 23:1838-1846. [PMID: 34257418 PMCID: PMC8487966 DOI: 10.1038/s41436-021-01230-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 05/13/2021] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. METHODS We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. RESULTS Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. CONCLUSION Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .
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Affiliation(s)
- Venner Eric
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
| | - Victoria Yi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - David Murdock
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Sara E Kalla
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Tsung-Jung Wu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Aniko Sabo
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Shoudong Li
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Qingchang Meng
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Xia Tian
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Mullai Murugan
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Michelle Cohen
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Christie Kovar
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, New York, NY, USA
| | - Georgia L Wiesner
- Division of Genetic Medicine, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gail P Jarvik
- Department of Medicine (Medical Genetics), University of Washington School of Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Donna Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
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30
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Tuteja S, Salloum RG, Elchynski AL, Smith DM, Rowe E, Blake KV, Limdi NA, Aquilante CL, Bates J, Beitelshees AL, Cipriani A, Duong BQ, Empey PE, Formea CM, Hicks JK, Mroz P, Oslin D, Pasternak AL, Petry N, Ramsey LB, Schlichte A, Swain SM, Ward KM, Wiisanen K, Skaar TC, Van Driest SL, Cavallari LH, Bishop JR. Multisite evaluation of institutional processes and implementation determinants for pharmacogenetic testing to guide antidepressant therapy. Clin Transl Sci 2021; 15:371-383. [PMID: 34562070 PMCID: PMC8841452 DOI: 10.1111/cts.13154] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 08/11/2021] [Accepted: 08/16/2021] [Indexed: 12/11/2022] Open
Abstract
There is growing interest in utilizing pharmacogenetic (PGx) testing to guide antidepressant use, but there is lack of clarity on how to implement testing into clinical practice. We administered two surveys at 17 sites that had implemented or were in the process of implementing PGx testing for antidepressants. Survey 1 collected data on the process and logistics of testing. Survey 2 asked sites to rank the importance of Consolidated Framework for Implementation Research (CFIR) constructs using best‐worst scaling choice experiments. Of the 17 sites, 13 had implemented testing and four were in the planning stage. Thirteen offered testing in the outpatient setting, and nine in both outpatient/inpatient settings. PGx tests were mainly ordered by psychiatry (92%) and primary care (69%) providers. CYP2C19 and CYP2D6 were the most commonly tested genes. The justification for antidepressants selected for PGx guidance was based on Clinical Pharmacogenetics Implementation Consortium guidelines (94%) and US Food and Drug Administration (FDA; 75.6%) guidance. Both institutional (53%) and commercial laboratories (53%) were used for testing. Sites varied on the methods for returning results to providers and patients. Sites were consistent in ranking CFIR constructs and identified patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and the identification of champions as most important for implementation. Sites deployed similar implementation strategies and measured similar outcomes. The process of implementing PGx testing to guide antidepressant therapy varied across sites, but key drivers for successful implementation were similar and may help guide other institutions interested in providing PGx‐guided pharmacotherapy for antidepressant management.
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Affiliation(s)
- Sony Tuteja
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ramzi G Salloum
- University of Florida College of Medicine, Gainesville, Florida, USA
| | | | - D Max Smith
- MedStar Health, Georgetown University Medical Center, Washington, DC, USA
| | - Elizabeth Rowe
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Nita A Limdi
- University of Alabama School of Medicine, Birmingham, Alabama, USA
| | | | - Jill Bates
- Durham VA Healthcare System, Durham, North Carolina, USA
| | | | - Amber Cipriani
- University of North Carolina Medical Center, Chapel Hill, North Carolina, USA
| | | | - Philip E Empey
- University of Pittsburgh School of Pharmacy, Pittsburgh, Pennsylvania, USA
| | | | | | - Pawel Mroz
- University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - David Oslin
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.,Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA
| | - Amy L Pasternak
- University of Michigan College of Pharmacy, Ann Arbor, Michigan, USA
| | - Natasha Petry
- North Dakota State University/Sanford Health, Fargo, North Dakota, USA
| | - Laura B Ramsey
- Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | | | - Sandra M Swain
- MedStar Health, Georgetown University Medical Center, Washington, DC, USA
| | - Kristen M Ward
- University of Michigan College of Pharmacy, Ann Arbor, Michigan, USA
| | - Kristin Wiisanen
- University of Florida College of Pharmacy, Gainesville, Florida, USA
| | - Todd C Skaar
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | | | - Jeffrey R Bishop
- University of Minnesota Medical School, Minneapolis, Minnesota, USA.,University of Minnesota College of Pharmacy, Minneapolis, Minnesota, USA
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31
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Wake DT, Smith DM, Kazi S, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision. Clin Pharmacol Ther 2021; 112:44-57. [PMID: 34365648 PMCID: PMC9291515 DOI: 10.1002/cpt.2387] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 07/28/2021] [Indexed: 02/06/2023]
Abstract
Clinical decision support (CDS) is an essential part of any pharmacogenomics (PGx) implementation. Increasingly, institutions have implemented CDS tools in the clinical setting to bring PGx data into patient care, and several have published their experiences with these implementations. However, barriers remain that limit the ability of some programs to create CDS tools to fit their PGx needs. Therefore, the purpose of this review is to summarize the types, functions, and limitations of PGx CDS currently in practice. Then, we provide an approachable step‐by‐step how‐to guide with a case example to help implementers bring PGx to the front lines of care regardless of their setting. Particular focus is paid to the five “rights” of CDS as a core around designing PGx CDS tools. Finally, we conclude with a discussion of opportunities and areas of growth for PGx CDS.
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Affiliation(s)
- Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, DC, USA
| | - Sadaf Kazi
- Georgetown University Medical Center, Washington, DC, USA.,National Center for Human Factors in Healthcare, MedStar Health Research Institute Washington, Washington, DC, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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32
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McDonough CW. Pharmacogenomics in Cardiovascular Diseases. Curr Protoc 2021; 1:e189. [PMID: 34232575 DOI: 10.1002/cpz1.189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Cardiovascular pharmacogenomics is the study and identification of genomic markers that are associated with variability in cardiovascular drug response, cardiovascular drug-related outcomes, or cardiovascular drug-related adverse events. This overview presents an introduction and historical background to cardiovascular pharmacogenomics, and a protocol for designing a cardiovascular pharmacogenomics study. Important considerations are also included for constructing a cardiovascular pharmacogenomics phenotype, designing the replication or validation strategy, common statistical approaches, and how to put the results in context with the cardiovascular drug or cardiovascular disease under investigation. © 2021 Wiley Periodicals LLC. Basic Protocol: Designing a cardiovascular pharmacogenomics study.
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Affiliation(s)
- Caitrin W McDonough
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida
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33
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Sperber NR, Dong OM, Roberts MC, Dexter P, Elsey AR, Ginsburg GS, Horowitz CR, Johnson JA, Levy KD, Ong H, Peterson JF, Pollin TI, Rakhra-Burris T, Ramos MA, Skaar T, Orlando LA. Strategies to Integrate Genomic Medicine into Clinical Care: Evidence from the IGNITE Network. J Pers Med 2021; 11:647. [PMID: 34357114 PMCID: PMC8306482 DOI: 10.3390/jpm11070647] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 06/29/2021] [Accepted: 07/02/2021] [Indexed: 11/16/2022] Open
Abstract
The complexity of genomic medicine can be streamlined by implementing some form of clinical decision support (CDS) to guide clinicians in how to use and interpret personalized data; however, it is not yet clear which strategies are best suited for this purpose. In this study, we used implementation science to identify common strategies for applying provider-based CDS interventions across six genomic medicine clinical research projects funded by an NIH consortium. Each project's strategies were elicited via a structured survey derived from a typology of implementation strategies, the Expert Recommendations for Implementing Change (ERIC), and follow-up interviews guided by both implementation strategy reporting criteria and a planning framework, RE-AIM, to obtain more detail about implementation strategies and desired outcomes. We found that, on average, the three pharmacogenomics implementation projects used more strategies than the disease-focused projects. Overall, projects had four implementation strategies in common; however, operationalization of each differed in accordance with each study's implementation outcomes. These four common strategies may be important for precision medicine program implementation, and pharmacogenomics may require more integration into clinical care. Understanding how and why these strategies were successfully employed could be useful for others implementing genomic or precision medicine programs in different contexts.
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Affiliation(s)
- Nina R. Sperber
- Duke Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27701, USA
- Durham VA Health Care System, Durham, NC 27705, USA
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA; (O.M.D.); (G.S.G.); (T.R.-B.); (L.A.O.)
| | - Olivia M. Dong
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA; (O.M.D.); (G.S.G.); (T.R.-B.); (L.A.O.)
| | - Megan C. Roberts
- Division of Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA;
| | - Paul Dexter
- Regenstrief Institute, Indianapolis, Indiana University School of Medicine and Clem McDonald Center for Biomedical Informatics, Indianapolis, IN 46202, USA;
| | - Amanda R. Elsey
- Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL 32610, USA; (A.R.E.); (J.A.J.)
| | - Geoffrey S. Ginsburg
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA; (O.M.D.); (G.S.G.); (T.R.-B.); (L.A.O.)
| | - Carol R. Horowitz
- Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Julie A. Johnson
- Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL 32610, USA; (A.R.E.); (J.A.J.)
| | - Kenneth D. Levy
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, 950 W. Walnut Street, Indianapolis, IN 46202, USA; (K.D.L.); (T.S.)
| | - Henry Ong
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (H.O.); (J.F.P.)
| | - Josh F. Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (H.O.); (J.F.P.)
| | - Toni I. Pollin
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA;
| | - Tejinder Rakhra-Burris
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA; (O.M.D.); (G.S.G.); (T.R.-B.); (L.A.O.)
| | - Michelle A. Ramos
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Todd Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, 950 W. Walnut Street, Indianapolis, IN 46202, USA; (K.D.L.); (T.S.)
| | - Lori A. Orlando
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA; (O.M.D.); (G.S.G.); (T.R.-B.); (L.A.O.)
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34
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Hicks JK, El Rouby N, Ong HH, Schildcrout JS, Ramsey LB, Shi Y, Tang LA, Aquilante CL, Beitelshees AL, Blake KV, Cimino JJ, Davis BH, Empey PE, Kao DP, Lemkin DL, Limdi NA, Lipori GP, Rosenman MB, Skaar TC, Teal E, Tuteja S, Wiley LK, Williams H, Winterstein AG, Van Driest SL, Cavallari LH, Peterson JF. Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems. Clin Pharmacol Ther 2021; 110:179-188. [PMID: 33428770 PMCID: PMC8217370 DOI: 10.1002/cpt.2161] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 12/24/2020] [Indexed: 12/11/2022]
Abstract
The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.
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Affiliation(s)
- J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Nihal El Rouby
- Department of Pharmacotherapy & Translational Research, University of Florida, Gainesville, FL
- James Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH
| | - Henry H. Ong
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | | | - Laura B. Ramsey
- Department of Pediatrics, College of Medicine, University of Cincinnati, Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Leigh Anne Tang
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Christina L. Aquilante
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO
| | | | | | - James J. Cimino
- Informatics Institute, University of Alabama at Birmingham, Birmingham, AL
| | - Brittney H. Davis
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Philip E. Empey
- Department of Pharmacy & Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA
| | - David P. Kao
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | | | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Gloria P. Lipori
- University of Florida Health and University of Florida Health Sciences Center, Gainesville, FL
| | - Marc B. Rosenman
- Indiana University School of Medicine, Indianapolis, IN
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL
| | - Todd C. Skaar
- Indiana University School of Medicine, Indianapolis, IN
| | | | - Sony Tuteja
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Laura K. Wiley
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | | | - Almut G. Winterstein
- Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL
| | - Sara L. Van Driest
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Larisa H. Cavallari
- Department of Pharmacotherapy & Translational Research, University of Florida, Gainesville, FL
| | - Josh F. Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
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35
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Carress H, Lawson DJ, Elhaik E. Population genetic considerations for using biobanks as international resources in the pandemic era and beyond. BMC Genomics 2021; 22:351. [PMID: 34001009 PMCID: PMC8127217 DOI: 10.1186/s12864-021-07618-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 04/14/2021] [Indexed: 12/11/2022] Open
Abstract
The past years have seen the rise of genomic biobanks and mega-scale meta-analysis of genomic data, which promises to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limits the global understanding of disease risk but also inhibits viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable and computable and to operate without access to raw data due to privacy concerns. Comparability is key both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of the most common genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks (locally and internationally), increase the accuracy of association analyses and inform developmental efforts.
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Affiliation(s)
- Hannah Carress
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK
| | - Daniel John Lawson
- School of Mathematics and Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Eran Elhaik
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK. .,Department of Biology, Lund University, Lund, Sweden.
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Luczak T, Brown SJ, Armbruster D, Hundertmark M, Brown J, Stenehjem D. Strategies and settings of clinical pharmacogenetic implementation: a scoping review of pharmacogenetics programs. Pharmacogenomics 2021; 22:345-364. [PMID: 33829852 DOI: 10.2217/pgs-2020-0181] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Pharmacogenetic (PGx) literature has shown beneficial outcomes in safety, efficacy and cost when evidence-based gene-drug decision making is incorporated into clinical practice. PGx programs with successfully implemented clinical services have been published in a variety of settings including academic health centers and community practice. The primary objective was to systematically scope the literature to characterize the current trends, extent, range and nature of clinical PGx programs. Forty articles representing 19 clinical PGx programs were included in analysis. Most programs are in urban, academic institutions. Education, governance and workflow were commonly described while billing/reimbursement and consent were not. This review provides an overview of current PGx models that can be used as a reference for institutions beginning the implementation process.
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Affiliation(s)
- Tiana Luczak
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA.,Essentia Health, Duluth, MN 55805, USA
| | - Sarah Jane Brown
- Health Sciences Libraries, University of Minnesota, MN 55455, USA
| | - Danielle Armbruster
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Megan Hundertmark
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Jacob Brown
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - David Stenehjem
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
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37
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Fredrikson KM, Fasolino T. Pharmacogenetic testing: Clinical integration and application for chronic pain management. Nurse Pract 2021; 46:12-19. [PMID: 33739321 DOI: 10.1097/01.npr.0000737180.73290.1f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT NPs commonly prescribe pharmaceutical therapies such as opiates, antidepressants, and/or other analgesics to improve the health and well-being of patients experiencing chronic pain. This article provides NPs with pharmacogenetic testing knowledge, such as readiness for clinical implementation, considerations for choosing a testing service, and testing costs for chronic pain management.
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Ginsburg GS, Cavallari LH, Chakraborty H, Cooper-DeHoff RM, Dexter PR, Eadon MT, Ferket BS, Horowitz CR, Johnson JA, Kannry J, Kucher N, Madden EB, Orlando LA, Parker W, Peterson J, Pratt VM, Rakhra-Burris TK, Ramos MA, Skaar TC, Sperber N, Steen-Burrell KA, Van Driest SL, Voora D, Wiisanen K, Winterstein AG, Volpi S. Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network. Genet Med 2021; 23:1185-1191. [PMID: 33782552 PMCID: PMC8263480 DOI: 10.1038/s41436-021-01118-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 12/20/2022] Open
Abstract
PURPOSE A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. METHODS The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. RESULTS Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. CONCLUSION IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers.
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Affiliation(s)
- Geoffrey S Ginsburg
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA.
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | | | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Paul R Dexter
- School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Michael T Eadon
- Division of Clinical Pharmacology, Indiana University, Indianapolis, IN, USA
| | - Bart S Ferket
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Carol R Horowitz
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Joseph Kannry
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Natalie Kucher
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - Ebony B Madden
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - Lori A Orlando
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA
| | - Wanda Parker
- Duke Clinical Research Institute, Duke University, Durham, NC, USA
| | - Josh Peterson
- Department of Biomedical Informatics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Victoria M Pratt
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA
| | | | - Michelle A Ramos
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Todd C Skaar
- Division of Clinical Pharmacology, Indiana University, Indianapolis, IN, USA
| | - Nina Sperber
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA.,Department of Population Health Sciences, Duke Margolis Center for Health Policy, Durham VA Health Services Research & Development Service, Duke Center for Applied Genomics & Precision Medicine, Durham, NC, USA
| | | | - Sara L Van Driest
- Department of Pediatrics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Deepak Voora
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Almut G Winterstein
- Department of Pharmaceutical Outcomes and Policy, Center for Drug Evaluation and Safety, University of Florida, Gainesville, FL, USA
| | - Simona Volpi
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
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Nestor JG, Fedotov A, Fasel D, Marasa M, Milo-Rasouly H, Wynn J, Chung WK, Gharavi A, Hripcsak G, Bakken S, Sengupta S, Weng C. An electronic health record (EHR) log analysis shows limited clinician engagement with unsolicited genetic test results. JAMIA Open 2021; 4:ooab014. [PMID: 33709066 PMCID: PMC7935499 DOI: 10.1093/jamiaopen/ooab014] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 01/21/2021] [Accepted: 02/12/2021] [Indexed: 11/14/2022] Open
Abstract
How clinicians utilize medically actionable genomic information, displayed in the electronic health record (EHR), in medical decision-making remains unknown. Participating sites of the Electronic Medical Records and Genomics (eMERGE) Network have invested resources into EHR integration efforts to enable the display of genetic testing data across heterogeneous EHR systems. To assess clinicians’ engagement with unsolicited EHR-integrated genetic test results of eMERGE participants within a large tertiary care academic medical center, we analyzed automatically generated EHR access log data. We found that clinicians viewed only 1% of all the eMERGE genetic test results integrated in the EHR. Using a cluster analysis, we also identified different user traits associated with varying degrees of engagement with the EHR-integrated genomic data. These data contribute important empirical knowledge about clinicians limited and brief engagements with unsolicited EHR-integrated genetic test results of eMERGE participants. Appreciation for user-specific roles provide additional context for why certain users were more or less engaged with the unsolicited results. This study highlights opportunities to use EHR log data as a performance metric to more precisely inform ongoing EHR-integration efforts and decisions about the allocation of informatics resources in genomic research.
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Affiliation(s)
- Jordan G Nestor
- Department of Medicine, Division of Nephrology, Columbia University, New York, New York, USA
| | - Alexander Fedotov
- The Irving Institute for Clinical and Translational Research, Columbia University, New York, New York, USA
| | - David Fasel
- Department of Medicine, Center for Precision Medicine and Genomics, Columbia University, New York, New York, USA
| | - Maddalena Marasa
- Department of Medicine, Division of Nephrology, Columbia University, New York, New York, USA.,Department of Medicine, Center for Precision Medicine and Genomics, Columbia University, New York, New York, USA
| | - Hila Milo-Rasouly
- Department of Medicine, Division of Nephrology, Columbia University, New York, New York, USA.,Department of Medicine, Center for Precision Medicine and Genomics, Columbia University, New York, New York, USA
| | - Julia Wynn
- Department of Pediatrics, Columbia University, New York, New York, USA
| | - Wendy K Chung
- Departments of Pediatric and Medicine, Columbia University, New York, New York, USA
| | - Ali Gharavi
- Department of Medicine, Division of Nephrology, Columbia University, New York, New York, USA.,Department of Medicine, Center for Precision Medicine and Genomics, Columbia University, New York, New York, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Suzanne Bakken
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Soumitra Sengupta
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
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40
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A Quantitative Framework for Measuring Personalized Medicine Integration into US Healthcare Delivery Organizations. J Pers Med 2021; 11:jpm11030196. [PMID: 33809012 PMCID: PMC8000405 DOI: 10.3390/jpm11030196] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 02/26/2021] [Accepted: 03/07/2021] [Indexed: 11/23/2022] Open
Abstract
Personalized medicine (PM) approaches have revolutionized healthcare delivery by offering new insights that enable healthcare providers to select the optimal treatment approach for their patients. However, despite the consensus that these approaches have significant value, implementation across the US is highly variable. In order to address barriers to widespread PM adoption, a comprehensive and methodical approach to assessing the current level of PM integration within a given organization and the broader healthcare system is needed. A quantitative framework encompassing a multifactorial approach to assessing PM adoption has been developed and used to generate a rating of PM integration in 153 organizations across the US. The results suggest significant heterogeneity in adoption levels but also some consistent themes in what defines a high-performing organization, including the sophistication of data collected, data sharing practices, and the level of internal funding committed to supporting PM initiatives. A longitudinal approach to data collection will be valuable to track continued progress and adapt to new challenges and barriers to PM adoption as they arise.
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41
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Roosan D, Hwang A, Roosan MR. Pharmacogenomics cascade testing (PhaCT): a novel approach for preemptive pharmacogenomics testing to optimize medication therapy. THE PHARMACOGENOMICS JOURNAL 2021; 21:1-7. [PMID: 32843688 PMCID: PMC7840503 DOI: 10.1038/s41397-020-00182-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Revised: 06/18/2020] [Accepted: 08/12/2020] [Indexed: 11/08/2022]
Abstract
The implementation of pharmacogenomics (PGx) has come a long way since the dawn of utilizing pharmacogenomic data in clinical patient care. However, the potential benefits of sharing PGx results have yet to be explored. In this paper, we explore the willingness of patients to share PGx results, as well as the inclusion of family medication history in identifying potential family members for pharmacogenomics cascade testing (PhaCT). The genetic similarities in families allow for identifying potential gene variants prior to official preemptive testing. Once a candidate patient is determined, PhaCT can be initiated. PhaCT recognizes that further cascade testing throughout a family can serve to improve precision medicine. In order to make PhaCT feasible, we propose a novel shareable HIPAA-compliant informatics platform that will enable patients to manage not only their own test results and medications but also those of their family members. The informatics platform will be an external genomics system with capabilities to integrate with patients' electronic health records. Patients will be given the tools to provide information to and work with clinicians in identifying family members for PhaCT through this platform. Offering patients the tools to share PGx results with their family members for preemptive testing could be the key to empowering patients. Clinicians can utilize PhaCT to potentially improve medication adherence, which may consequently help to distribute the burden of health management between patients, family members, providers, and payers.
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Affiliation(s)
- Don Roosan
- Department of Pharmacy Practice and Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA, USA.
| | - Angela Hwang
- Department of Pharmacy Practice and Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA, USA
| | - Moom R Roosan
- Department of Pharmacy Practice, School of Pharmacy, Chapman University, School of Pharmacy, Irvine, CA, USA.
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42
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Ding X, Schimenti JC. Strategies to Identify Genetic Variants Causing Infertility. Trends Mol Med 2021; 27:792-806. [PMID: 33431240 DOI: 10.1016/j.molmed.2020.12.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 11/26/2020] [Accepted: 12/11/2020] [Indexed: 12/19/2022]
Abstract
Genetic causes are thought to underlie about half of infertility cases, but understanding the genetic bases has been a major challenge. Modern genomics tools allow more sophisticated exploration of genetic causes of infertility through population, family-based, and individual studies. Nevertheless, potential therapies based on genetic diagnostics will be limited until there is certainty regarding the causality of genetic variants identified in an individual. Genome modulation and editing technologies have revolutionized our ability to functionally test such variants, and also provide a potential means for clinical correction of infertility variants. This review addresses strategies being used to identify causative variants of infertility.
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Affiliation(s)
- Xinbao Ding
- Cornell University, College of Veterinary Medicine, Department of Biomedical Sciences, Ithaca, NY 14853, USA
| | - John C Schimenti
- Cornell University, College of Veterinary Medicine, Department of Biomedical Sciences, Ithaca, NY 14853, USA.
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43
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Dong OM, Bates J, Chanfreau-Coffinier C, Naglich M, Kelley MJ, Meyer LJ, Icardi M, Vassy JL, Sriram P, Heise CW, Rivas S, Ribeiro M, Jacobitz R, Rozelle S, Chapman JG, Voora D. Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program. Pharmacogenomics 2021; 22:137-144. [PMID: 33403869 DOI: 10.2217/pgs-2020-0173] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
In 2019, the Veterans Affairs (VA), the largest integrated US healthcare system, started the Pharmacogenomic Testing for Veterans (PHASER) clinical program that provides multi-gene pharmacogenomic (PGx) testing for up to 250,000 veterans at approximately 50 sites. PHASER is staggering program initiation at sites over a 5-year period from 2019 to 2023, as opposed to simultaneous initiation at all sites, to facilitate iterative program quality improvements through Plan-Do-Study-Act cycles. Current resources in the PGx field have not focused on multisite, remote implementation of panel-based PGx testing. In addition to bringing large scale PGx testing to veterans, the PHASER program is developing a roadmap to maximize uptake and optimize the use of PGx to improve drug response outcomes.
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Affiliation(s)
- Olivia M Dong
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
| | - Jill Bates
- Durham VA Health Care System, Durham, NC 27705, USA.,Division of Practice Advancement & Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - Michael Naglich
- Institute for Medical Research, Durham VA Medical Center, Durham, NC 27705, USA
| | - Michael J Kelley
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke University Medical Center, Durham, NC 27708, USA.,Department of Veterans Affairs, National Oncology Program Office, Office of Specialty Care, Durham, NC 27705, USA
| | - Laurence J Meyer
- Department of Veterans Affairs, Washington, DC 20571, USA.,Department of Dermatology, University of Utah, UT 84112, USA
| | - Michael Icardi
- Department of Veterans Affairs, Washington, DC 20571, USA
| | - Jason L Vassy
- VA Boston Healthcare System, Boston, MA 02130, USA.,Harvard Medical School, Boston, MA 02115, USA
| | - Peruvemba Sriram
- North Florida/South Georgia Veterans Health System, Gainesville, FL 32608, USA
| | - Craig William Heise
- Phoenix VA Health Care System, Phoenix, AZ 85012, USA.,The University of Arizona College of Medicine - Phoenix, Phoenix, AZ 85004, USA
| | | | - Maria Ribeiro
- Atlanta VA Medical Center, Atlanta, GA 30033, USA.,Department of Hematology & Medical Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Russell Jacobitz
- North Florida/South Georgia Veterans Health System, Gainesville, FL 32608, USA
| | - Susan Rozelle
- North Florida/South Georgia Veterans Health System, Gainesville, FL 32608, USA
| | - Jennifer G Chapman
- Institute for Medical Research, Durham VA Medical Center, Durham, NC 27705, USA
| | - Deepak Voora
- Durham VA Health Care System, Durham, NC 27705, USA.,Department of Medicine, Duke Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, Durham, NC 27708, USA
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44
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Implementation Science to Increase Adoption of Genomic Medicine: An Urgent Need. J Pers Med 2020; 11:jpm11010019. [PMID: 33383675 PMCID: PMC7824626 DOI: 10.3390/jpm11010019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 12/24/2020] [Indexed: 12/17/2022] Open
Abstract
Advances in genomics have the potential to improve human health [...].
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45
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Design of a study to implement population-based risk assessment for hereditary cancer genetic testing in primary care. Contemp Clin Trials 2020; 101:106257. [PMID: 33373667 DOI: 10.1016/j.cct.2020.106257] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 12/18/2020] [Accepted: 12/21/2020] [Indexed: 11/24/2022]
Abstract
Identifying patients with high genetic risk for cancer has important clinical ramifications, but hereditary cancer risk is often not identified because of testing barriers at both the provider and patient level. It is unknown how to best implement appropriate genetic testing and follow-up care into an operating primary care clinic. Implementation studies to date have been conducted in high resourced facilities under optimal conditions, often not at the clinic level. This study aims to compare and evaluate two population-wide engagement strategies for identifying members of a primary care clinic's population with a family or personal history of cancer and offering high-risk individuals genetic testing for cancer susceptibility mutations. The two engagement strategies are: 1) point of care screening (POC), conducted when a patient is scheduled for an appointment and 2) direct patient engagement (DPE), where outreach provides the patient an opportunity to complete screening online on their own time. The study will identify changes, problems, and inefficiencies in clinical flow during and after the implementation of risk assessment and genomic testing for cancer risk across primary care clinics. It will also evaluate the effects of the two engagement strategies on patient, provider, and clinic leader outcomes, including perceptions of benefits, harms, and satisfaction with the engagement strategy and process of cancer risk assessment and genetic testing, across gender, racial/ethnic, socioeconomic, and genetic literacy divides. Finally, the study will evaluate the cost-effectiveness and budget impact of each engagement strategy.
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46
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Brown JT, Ramsey LB, Van Driest SL, Aka I, Colace SI. Characterizing Pharmacogenetic Testing Among Children's Hospitals. Clin Transl Sci 2020; 14:692-701. [PMID: 33325650 PMCID: PMC7993279 DOI: 10.1111/cts.12931] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 10/12/2020] [Indexed: 12/27/2022] Open
Abstract
Although pharmacogenetic testing is becoming increasingly common across medical subspecialties, a broad range of utilization and implementation exists across pediatric centers. Large pediatric institutions that routinely use pharmacogenetics in their patient care have published their practices and experiences; however, minimal data exist regarding the full spectrum of pharmacogenetic implementation among children’s hospitals. The primary objective of this nationwide survey was to characterize the availability, concerns, and barriers to pharmacogenetic testing in children’s hospitals in the Children’s Hospital Association. Initial responses identifying a contact person were received from 18 institutions. Of those 18 institutions, 14 responses (11 complete and 3 partial) to a more detailed survey regarding pharmacogenetic practices were received. The majority of respondents were from urban institutions (72%) and held a Doctor of Pharmacy degree (67%). Among all respondents, the three primary barriers to implementing pharmacogenetic testing identified were test reimbursement, test cost, and money. Conversely, the three least concerning barriers were potential for genetic discrimination, sharing results with family members, and availability of tests in certified laboratories. Low‐use sites rated several barriers significantly higher than the high‐use sites, including knowledge of pharmacogenetics (P = 0.03), pharmacogenetic interpretations (P = 0.04), and pharmacogenetic‐based changes to therapy (P = 0.03). In spite of decreasing costs of pharmacogenetic testing, financial barriers are one of the main barriers perceived by pediatric institutions attempting clinical implementation. Low‐use sites may also benefit from education/outreach in order to reduce perceived barriers to implementation.
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Affiliation(s)
- Jacob T Brown
- Department of Pharmacy Practice and Pharmaceutical Sciences, College of Pharmacy, University of Minnesota Duluth, Duluth, Minnesota, USA
| | - Laura B Ramsey
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.,Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Sara L Van Driest
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ida Aka
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Susan I Colace
- Department of Pediatrics, Nationwide Children's Hospital, Columbus, Ohio, USA
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47
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Snir M, Nazareth S, Simmons E, Hayward L, Ashcraft K, Bristow SL, Esplin ED, Aradhya S. Democratizing genomics: Leveraging software to make genetics an integral part of routine care. AMERICAN JOURNAL OF MEDICAL GENETICS. PART C, SEMINARS IN MEDICAL GENETICS 2020; 187:14-27. [PMID: 33296144 DOI: 10.1002/ajmg.c.31866] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 11/16/2020] [Accepted: 11/17/2020] [Indexed: 12/25/2022]
Abstract
Genetic testing can provide definitive molecular diagnoses and guide clinical management decisions from preconception through adulthood. Innovative solutions for scaling clinical genomics services are necessary if they are to transition from a niche specialty to a routine part of patient care. The expertise of specialists, like genetic counselors and medical geneticists, has traditionally been relied upon to facilitate testing and follow-up, and while ideal, this approach is limited in its ability to integrate genetics into primary care. As individuals, payors, and providers increasingly realize the value of genetics in mainstream medicine, several implementation challenges need to be overcome. These include electronic health record integration, patient and provider education, tools to stay abreast of guidelines, and simplification of the test ordering process. Currently, no single platform offers a holistic view of genetic testing that streamlines the entire process across specialties that begins with identifying at-risk patients in mainstream care settings, providing pretest education, facilitating consent and test ordering, and following up as a "genetic companion" for ongoing management. We describe our vision for using software that includes clinical-grade chatbots and decision support tools, with direct access to genetic counselors and pharmacists within a modular, integrated, end-to-end testing journey.
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48
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Ramsey LB, Ong HH, Schildcrout JS, Shi Y, Tang LA, Hicks JK, El Rouby N, Cavallari LH, Tuteja S, Aquilante CL, Beitelshees AL, Lemkin DL, Blake KV, Williams H, Cimino JJ, Davis BH, Limdi NA, Empey PE, Horvat CM, Kao DP, Lipori GP, Rosenman MB, Skaar TC, Teal E, Winterstein AG, Owusu Obeng A, Salyakina D, Gupta A, Gruber J, McCafferty-Fernandez J, Bishop JR, Rivers Z, Benner A, Tamraz B, Long-Boyle J, Peterson JF, Van Driest SL. Prescribing Prevalence of Medications With Potential Genotype-Guided Dosing in Pediatric Patients. JAMA Netw Open 2020; 3:e2029411. [PMID: 33315113 PMCID: PMC7737091 DOI: 10.1001/jamanetworkopen.2020.29411] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 09/28/2020] [Indexed: 12/17/2022] Open
Abstract
Importance Genotype-guided prescribing in pediatrics could prevent adverse drug reactions and improve therapeutic response. Clinical pharmacogenetic implementation guidelines are available for many medications commonly prescribed to children. Frequencies of medication prescription and actionable genotypes (genotypes where a prescribing change may be indicated) inform the potential value of pharmacogenetic implementation. Objective To assess potential opportunities for genotype-guided prescribing in pediatric populations among multiple health systems by examining the prevalence of prescriptions for each drug with the highest level of evidence (Clinical Pharmacogenetics Implementation Consortium level A) and estimating the prevalence of potential actionable prescribing decisions. Design, Setting, and Participants This serial cross-sectional study of prescribing prevalences in 16 health systems included electronic health records data from pediatric inpatient and outpatient encounters from January 1, 2011, to December 31, 2017. The health systems included academic medical centers with free-standing children's hospitals and community hospitals that were part of an adult health care system. Participants included approximately 2.9 million patients younger than 21 years observed per year. Data were analyzed from June 5, 2018, to April 14, 2020. Exposures Prescription of 38 level A medications based on electronic health records. Main Outcomes and Measures Annual prevalence of level A medication prescribing and estimated actionable exposures, calculated by combining estimated site-year prevalences across sites with each site weighted equally. Results Data from approximately 2.9 million pediatric patients (median age, 8 [interquartile range, 2-16] years; 50.7% female, 62.3% White) were analyzed for a typical calendar year. The annual prescribing prevalence of at least 1 level A drug ranged from 7987 to 10 629 per 100 000 patients with increasing trends from 2011 to 2014. The most prescribed level A drug was the antiemetic ondansetron (annual prevalence of exposure, 8107 [95% CI, 8077-8137] per 100 000 children). Among commonly prescribed opioids, annual prevalence per 100 000 patients was 295 (95% CI, 273-317) for tramadol, 571 (95% CI, 557-586) for codeine, and 2116 (95% CI, 2097-2135) for oxycodone. The antidepressants citalopram, escitalopram, and amitriptyline were also commonly prescribed (annual prevalence, approximately 250 per 100 000 patients for each). Estimated prevalences of actionable exposures were highest for oxycodone and ondansetron (>300 per 100 000 patients annually). CYP2D6 and CYP2C19 substrates were more frequently prescribed than medications influenced by other genes. Conclusions and Relevance These findings suggest that opportunities for pharmacogenetic implementation among pediatric patients in the US are abundant. As expected, the greatest opportunity exists with implementing CYP2D6 and CYP2C19 pharmacogenetic guidance for commonly prescribed antiemetics, analgesics, and antidepressants.
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Affiliation(s)
- Laura B. Ramsey
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio
- Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
| | - Henry H. Ong
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Leigh Anne Tang
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Nihal El Rouby
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville
- James Winkle College of Pharmacy, University of Cincinnati, Cincinnati, Ohio
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville
| | - Sony Tuteja
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | | | - Daniel L. Lemkin
- Department of Emergency Medicine, University of Maryland, Baltimore
| | - Kathryn V. Blake
- Center for Pharmacogenomics and Translational Research, Nemours Children’s Health System, Jacksonville, Florida
| | - Helen Williams
- Nemours Research Institute, Nemours Children’s Health System, Jacksonville, Florida
| | | | | | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham
| | - Philip E. Empey
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Christopher M. Horvat
- Department of Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David P. Kao
- Department of Medicine, School of Medicine, University of Colorado, Aurora
| | - Gloria P. Lipori
- University of Florida Health and University of Florida Health Sciences Center, Gainesville
| | - Marc B. Rosenman
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis
- Department of Pediatrics, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois
| | - Todd C. Skaar
- Department of Medicine, Indiana University School of Medicine, Indianapolis
| | | | - Almut G. Winterstein
- Department of Pharmaceutical Outcomes and Policy and Center for Drug Evaluation and Safety, University of Florida, Gainesville
| | - Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine, Departments of Medicine and Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Daria Salyakina
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | - Apeksha Gupta
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | - Joshua Gruber
- Personalized Medicine Initiative, Nicklaus Children’s Health System, Miami, Florida
| | | | - Jeffrey R. Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis
| | - Zach Rivers
- Department of Pharmaceutical Care and Health Systems, University of Minnesota College of Pharmacy, Minneapolis
| | - Ashley Benner
- Clinical and Translational Science Institute, University of Minnesota, Minneapolis
| | - Bani Tamraz
- School of Pharmacy, University of California, San Francisco
| | | | - Josh F. Peterson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
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49
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Orlando LA, Wu RR, Myers RA, Neuner J, McCarty C, Haller IV, Harry M, Fulda KG, Dimmock D, Rakhra-Burris T, Buchanan A, Ginsburg GS. At the intersection of precision medicine and population health: an implementation-effectiveness study of family health history based systematic risk assessment in primary care. BMC Health Serv Res 2020; 20:1015. [PMID: 33160339 PMCID: PMC7648301 DOI: 10.1186/s12913-020-05868-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 10/27/2020] [Indexed: 01/27/2023] Open
Abstract
Background Risk assessment is a precision medicine technique that can be used to enhance population health when applied to prevention. Several barriers limit the uptake of risk assessment in health care systems; and little is known about the potential impact that adoption of systematic risk assessment for screening and prevention in the primary care population might have. Here we present results of a first of its kind multi-institutional study of a precision medicine tool for systematic risk assessment. Methods We undertook an implementation-effectiveness trial of systematic risk assessment of primary care patients in 19 primary care clinics at four geographically and culturally diverse healthcare systems. All adult English or Spanish speaking patients were invited to enter personal and family health history data into MeTree, a patient-facing family health history driven risk assessment program, for 27 medical conditions. Risk assessment recommendations followed evidence-based guidelines for identifying and managing those at increased disease risk. Results One thousand eight hundred eighty-nine participants completed MeTree, entering information on N = 25,967 individuals. Mean relatives entered = 13.7 (SD 7.9), range 7–74. N = 1443 (76.4%) participants received increased risk recommendations: 597 (31.6%) for monogenic hereditary conditions, 508 (26.9%) for familial-level risk, and 1056 (56.1%) for risk of a common chronic disease. There were 6617 recommendations given across the 1443 participants. In multivariate analysis, only the total number of relatives entered was significantly associated with receiving a recommendation. Conclusions A significant percentage of the general primary care population meet criteria for more intensive risk management. In particular 46% for monogenic hereditary and familial level disease risk. Adopting strategies to facilitate systematic risk assessment in primary care could have a significant impact on populations within the U.S. and even beyond. Trial registration Clinicaltrials.gov number NCT01956773, registered 10/8/2013.
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Affiliation(s)
- Lori A Orlando
- Department of Medicine, Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, USA.
| | - R Ryanne Wu
- Department of Medicine, Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, USA.,Programme in Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Rachel A Myers
- Department of Medicine, Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, USA
| | - Joan Neuner
- Department of Medicine, Medical College of Wisconsin, Milwaukee, USA.,Center for Patient Care and Outcomes Research, Medical College of Wisconsin, Milwaukee, USA
| | | | | | | | - Kimberly G Fulda
- The North Texas Primary care Practice-Based Research Network and Family Medicine, University of North Texas Health Science Center, Fort Worth, USA
| | - David Dimmock
- Rady Children's Institute for Genomic Medicine, San Diego, USA
| | - Teji Rakhra-Burris
- Department of Medicine, Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, USA
| | - Adam Buchanan
- Genomic Medicine Institute, Geisinger, Geisinger, USA
| | - Geoffrey S Ginsburg
- Department of Medicine, Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, USA
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50
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Roosan D, Hwang A, Law AV, Chok J, Roosan MR. The inclusion of health data standards in the implementation of pharmacogenomics systems: a scoping review. Pharmacogenomics 2020; 21:1191-1202. [PMID: 33124487 DOI: 10.2217/pgs-2020-0066] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Background: Despite potential benefits, the practice of incorporating pharmacogenomics (PGx) results in clinical decisions has yet to diffuse widely. In this study, we conducted a review of recent discussions on data standards and interoperability with a focus on sharing PGx test results among health systems. Materials & methods: We conducted a literature search for PGx clinical decision support systems between 1 January 2012 and 31 January 2020. Thirty-two out of 727 articles were included for the final review. Results: Nine of the 32 articles mentioned data standards and only four of the 32 articles provided solutions for the lack of interoperability. Discussions: Although PGx interoperability is essential for widespread implementation, a lack of focus on standardized data creates a formidable challenge for health information exchange. Conclusion: Standardization of PGx data is essential to improve health information exchange and the sharing of PGx results between disparate systems. However, PGx data standards and interoperability are often not addressed in the system-level implementation.
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Affiliation(s)
- Don Roosan
- Assistant Professor, Department of Pharmacy Practice & Administration, College of Pharmacy, Western University of Health Sciences, 309 E 2nd street, Pomona, CA 91766, USA
| | - Angela Hwang
- Research Assistant, Department of Pharmacy Practice & Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Anandi V Law
- Professor, Department of Pharmacy Practice & Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Jay Chok
- Associate Professor, School of Applied Life Sciences, Keck Graduate Institute, Claremont Colleges, Pomona, CA 91711, USA
| | - Moom R Roosan
- Assistant Professor, School of Pharmacy, Department of Pharmacy Practice, Chapman University, Irvine, CA 92618, USA
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