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Clayton EW, Smith ME, Anderson KC, Chung WK, Connolly JJ, Fullerton SM, McGowan ML, Peterson JF, Prows CA, Sabatello M, Holm IA. Studying the impact of translational genomic research: Lessons from eMERGE. Am J Hum Genet 2023; 110:1021-1033. [PMID: 37343562 PMCID: PMC10357472 DOI: 10.1016/j.ajhg.2023.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/23/2023] Open
Abstract
Two major goals of the Electronic Medical Record and Genomics (eMERGE) Network are to learn how best to return research results to patient/participants and the clinicians who care for them and also to assess the impact of placing these results in clinical care. Yet since its inception, the Network has confronted a host of challenges in achieving these goals, many of which had ethical, legal, or social implications (ELSIs) that required consideration. Here, we share impediments we encountered in recruiting participants, returning results, and assessing their impact, all of which affected our ability to achieve the goals of eMERGE, as well as the steps we took to attempt to address these obstacles. We divide the domains in which we experienced challenges into four broad categories: (1) study design, including recruitment of more diverse groups; (2) consent; (3) returning results to participants and their health care providers (HCPs); and (4) assessment of follow-up care of participants and measuring the impact of research on participants and their families. Since most phases of eMERGE have included children as well as adults, we also address the particular ELSI posed by including pediatric populations in this research. We make specific suggestions for improving translational genomic research to ensure that future projects can effectively return results and assess their impact on patient/participants and providers if the goals of genomic-informed medicine are to be achieved.
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Affiliation(s)
- Ellen Wright Clayton
- Center for Biomedical Ethics and Society, Departments of Pediatrics and Health Policy, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
| | - Maureen E Smith
- Department of Medicine, Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Katherine C Anderson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY 10032, USA
| | - John J Connolly
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Stephanie M Fullerton
- Department of Bioethics & Humanities, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Michelle L McGowan
- Biomedical Ethics Research Program, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA; Department of Women's, Gender, and Sexuality Studies, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Josh F Peterson
- Center for Precision Medicine, Department of Biomedical Informatics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Cynthia A Prows
- Divisions of Human Genetics and Patient Services, Cincinnati Children's Hospital, Cincinnati, OH 45229, USA
| | - Maya Sabatello
- Center for Precision Medicine & Genomics, Department of Medicine, and Division of Ethics, Department of Medical Humanities & Ethics Columbia University Vagelos College of Physicians and Surgeons, NY, NY 10032, USA
| | - Ingrid A Holm
- Division of Genetics and Genomics, Boston Children's Hospital; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
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Rasmussen LV, Agrawal AH, Botsford P, Powers A, Schnoebelen J, Xinos S, Harper G, Thanner J, McCabe S, Moore S, Wicklund CA, Duquette D, Gordon EJ. Challenges of Integrating APOL1 Genetic Test Results into the Electronic Health Record. Appl Clin Inform 2023; 14:321-325. [PMID: 37186083 PMCID: PMC10132929 DOI: 10.1055/s-0043-1767680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 02/12/2023] [Indexed: 05/17/2023] Open
Abstract
OBJECTIVES Integrating genetic test results into the electronic health record (EHR) is essential for integrating genetic testing into clinical practice. This article describes the organizational challenges of integrating discrete apolipoprotein L1 (APOL1) genetic test results into the EHR for a research study on culturally sensitive genetic counseling for living kidney donors. METHODS We convened a multidisciplinary team across three institutions (Northwestern University, Northwestern Memorial HealthCare [NMHC], and OHSU Knight Diagnostic Laboratories [KDL]), including researchers, physicians, clinical information technology, and project management. Through a series of meetings over a year between the team and the genetic testing laboratory, we explored and adjusted our EHR integration plan based on regulatory and budgetary constraints. RESULTS Our original proposal was to transmit results from KDL to NMHC as structured data sent via Health Level Seven (HL7) v2 message. This was ultimately deemed infeasible given the time and resources required to establish the interface, and the low number of samples to be processed for the study (n = 316). We next explored the use of Epic's Care Everywhere interoperability platform, but learned it was not possible as a laboratory test ordered for a research study; even though our intent was to study the APOL1 genetic test result's clinical use and impact, test results were still considered "research results." Faced with two remaining options-downloading a PDF from the KDL laboratory portal or scanning a faxed result from KDL-only a PDF of the APOL1 test result could be integrated into the EHR, reinforcing the status quo. CONCLUSION Even with early and ongoing stakeholder engagement, dedicated project management, and funding, unanticipated implementation challenges-especially for research projects-can result in drastic design tradeoffs.
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Affiliation(s)
- Luke V. Rasmussen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Akansha H. Agrawal
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Paul Botsford
- Information Services, Digital Solutions, Northwestern Medicine, Chicago, Illinois, United States
| | - Andrew Powers
- Information Services, Clinical Applications, Northwestern Medicine, Chicago, Illinois, United States
| | - Jeffrey Schnoebelen
- Information Services, Business Relationship Management, Northwestern Medicine, Chicago, Illinois, United States
| | - Stavroula Xinos
- Information Services, Digital Administration, Northwestern Medicine, Chicago, Illinois, United States
| | - Gail Harper
- Business Development and Strategic Outreach, Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, Oregon, United States
| | - Jane Thanner
- Information Technology Group, Oregon Health & Science University, Portland, Oregon, United States
| | - Sarah McCabe
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, Oregon, United States
| | - Stephen Moore
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, Oregon, United States
| | - Catherine A. Wicklund
- Department of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Debra Duquette
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Elisa J. Gordon
- Department of Surgery, Section of Surgical Sciences, and Center for Biomedical Ethics and Society, Vanderbilt University Medical Center, Nashville, Tennessee, United States
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Bartos MN, Scott SA, Jabs EW, Naik H. Attitudes on pharmacogenomic results as secondary findings among medical geneticists. Pharmacogenet Genomics 2022; 32:273-280. [PMID: 35916546 DOI: 10.1097/fpc.0000000000000479] [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: 10/16/2022]
Abstract
OBJECTIVES As evidence mounts supporting the utility of pharmacogenomic-guided medication management, incorporating pharmacogenomic genes into secondary finding results from sequencing panels is increasingly under consideration. We studied medical geneticists' attitudes on receiving pharmacogenomic results as secondary finding. METHODS Four focus groups with 16 medical geneticists total were conducted followed by thematic analysis. RESULTS All participants ordered genetic sequencing tests; however, the majority had rarely or never ordered pharmacogenomic tests (10/16) or prescribed medications with established response variability (11/16). In total 81.3% expressed low comfort interpreting pharmacogenomic results without appropriate clinical resources (13/16). The positives of receiving pharmacogenomic results as secondary finding included prevention of adverse drug reactions in adults, grateful information-seeking patients, the ability to rapidly prescribe more effective treatments and appreciation of the recent advances in both pharmacogenomic knowledge and available guidelines. Negatives included laboratory reporting issues, exclusivity of pharmacogenomic results to certain populations, lengthy reports concealing pharmacogenomic results in patient charts and laboratories marketing to individuals without prior pharmacogenomic knowledge or targeting inappropriate populations. The most desirable pharmacogenomic resources included a universal electronic health record clinical decision support tool to assist identifying and implementing pharmacogenomic results, a specialized pharmacist as part of the care team, additional pharmacogenomic training during medical/graduate school, and a succinct interpretation of pharmacogenomic results included on laboratory reports. CONCLUSIONS The majority of participants agreed that adding certain actionable pharmacogenomic genes to the American College of Medical Genetics and Genomics SF list is reasonable; however, this was qualified with a need for additional resources to support implementation.
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Affiliation(s)
- Meghan N Bartos
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
- Department of Genetics, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama
| | - Stuart A Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
- Department of Pathology, Stanford University, Stanford
- Clinical Genomics Laboratory, Stanford Health Care, Palo Alto, California, USA
| | - Ethylin Wang Jabs
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
| | - Hetanshi Naik
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York
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Haidar CE, Crews KR, Hoffman JM, Relling MV, Caudle KE. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing. Annu Rev Genomics Hum Genet 2022; 23:449-473. [PMID: 35537468 PMCID: PMC9483991 DOI: 10.1146/annurev-genom-111621-102737] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.
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Affiliation(s)
- Cyrine E Haidar
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kristine R Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - James M Hoffman
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
- Office of Quality and Safety, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Mary V Relling
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kelly E Caudle
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
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Qin W, Lu X, Shu Q, Duan H, Li H. Building an information system to facilitate pharmacogenomics clinical translation with clinical decision support. Pharmacogenomics 2021; 23:35-48. [PMID: 34787504 DOI: 10.2217/pgs-2021-0110] [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: 12/14/2022] Open
Abstract
Pharmacogenomics clinical decision support (PGx-CDS) is an important tool to incorporate PGx information into existing clinical workflows and facilitate PGx clinical translation. However, due to the lack of a computable formalization to represent the primary PGx knowledge, the complexity of genomics information and the lag of current commercial electronic health record (EHR) system for precision medicine, it is difficult to develop computerized PGx-CDS. Therefore, we explored a novel approach to build an information system, named the Pharmacogenomics Clinical Translation Platform (PCTP), for PGx clinical implementation. The PCTP can represent, store, and manage the primary PGx knowledge in a structured and computable format. Moreover, it has the potential to provide various PGx-CDS services and simplify the integration of PGx-CDS into EHRs.
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Affiliation(s)
- Weifeng Qin
- The Children's Hospital, Zhejiang University School of Medicine & National Clinical Research Center for Child Health, Hangzhou 310052, PR China.,College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Xudong Lu
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Qiang Shu
- The Children's Hospital, Zhejiang University School of Medicine & National Clinical Research Center for Child Health, Hangzhou 310052, PR China
| | - Huilong Duan
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Haomin Li
- The Children's Hospital, Zhejiang University School of Medicine & National Clinical Research Center for Child Health, Hangzhou 310052, PR China
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Challenges and practical solutions for managing secondary genomic findings in primary care. Eur J Med Genet 2021; 65:104384. [PMID: 34768014 DOI: 10.1016/j.ejmg.2021.104384] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 07/25/2021] [Accepted: 11/07/2021] [Indexed: 11/22/2022]
Abstract
Primary care providers will increasingly be tasked with managing most secondary findings from genomic sequencing, but literature exploring their capacity to manage findings beyond conventional genetic testing is limited. This study aimed to explore primary care providers' challenges and potential solutions for managing secondary findings. Providers were recruited in two groups. Group 1 providers had a patient in their practice who received secondary findings and all potential group 1 providers were invited to participate. Group 2 providers were provided with the secondary findings of a hypothetical patient and were purposefully sampled for maximal variation in sex, practice setting, and geographic location. Providers were interviewed about their challenges and solutions managing secondary findings from a patient in their practice or a hypothetical patient. Using interpretive description methodology, transcripts were analysed thematically complemented by constant comparison. Out of the fifty-five providers invited, 15 family physicians participated across community and academic settings in Ontario, Canada (range 6-40 years in practice; 10/15 female). Providers described a responsibility to manage secondary findings, but limited capacity for this, describing practice, knowledge, and technical challenges. Providers expressed concern that compared to other incidental findings, secondary genomic findings might be reported directly to patients and result in longer-term anxiety. Potential solutions were a structured letter with categorized results and summary tables highlighting key secondary findings with follow-up recommendations and resources, as well as electronic medical records (EMRs) that store and integrate genomic information for prescribing or referrals. These solutions were deemed essential to address knowledge and technical challenges faced by primary care physicians and ultimately promote clinical utility of secondary findings.
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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: 7] [Impact Index Per Article: 2.3] [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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8
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Taylor CO, Rasmussen LV, Rasmussen-Torvik LJ, Prows CA, Dorr DA, Samal L, Aronson S. Facilitating Genetics Aware Clinical Decision Support: Putting the eMERGE Infrastructure into Practice. ACI OPEN 2021; 5:e54-e58. [PMID: 37920232 PMCID: PMC10621326 DOI: 10.1055/s-0041-1729981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/04/2023]
Abstract
This editorial provides context for a series of published case reports in ACI Open by summarizing activities and outputs of joint electronic health record integration and pharmacogenomics workgroups in the NIH-funded electronic Medical Records and Genomics (eMERGE) Network. A case report is a useful tool to describe the range of capabilities that an IT infrastructure or a particular technology must support. The activities we describe have informed infrastructure requirements used during eMERGE phase III, provided a venue to share experiences and ask questions among other eMERGE sites, summarized potential hazards that might be encountered for specific clinical decision support (CDS) implementation scenarios, and provided a simple framework that captured progress toward implementing CDS at eMERGE sites in a consistent format.
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Affiliation(s)
- Casey Overby Taylor
- Departments of Medicine and Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Geisinger Health System, Genomic Medicine Institute, Danville, Pennsylvania, United States
| | - Luke V Rasmussen
- Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States
| | | | - Cynthia A Prows
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States
| | - David A Dorr
- Departments of Medical Informatics and Clinical Epidemiology and Medicine, Oregon Health & Science University, Portland, Oregon, United States
| | - Lipika Samal
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
| | - Samuel Aronson
- Partners Personalized Medicine, Partners HealthCare, Cambridge, Massachusetts, United States
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Roberts MC, Fohner AE, Landry L, Olstad DL, Smit AK, Turbitt E, Allen CG. Advancing precision public health using human genomics: examples from the field and future research opportunities. Genome Med 2021; 13:97. [PMID: 34074326 PMCID: PMC8168000 DOI: 10.1186/s13073-021-00911-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 05/17/2021] [Indexed: 01/21/2023] Open
Abstract
Precision public health is a relatively new field that integrates components of precision medicine, such as human genomics research, with public health concepts to help improve population health. Despite interest in advancing precision public health initiatives using human genomics research, current and future opportunities in this emerging field remain largely undescribed. To that end, we provide examples of promising opportunities and current applications of genomics research within precision public health and outline future directions within five major domains of public health: biostatistics, environmental health, epidemiology, health policy and health services, and social and behavioral science. To further extend applications of genomics within precision public health research, three key cross-cutting challenges will need to be addressed: developing policies that implement precision public health initiatives at multiple levels, improving data integration and developing more rigorous methodologies, and incorporating initiatives that address health equity. Realizing the potential to better integrate human genomics within precision public health will require transdisciplinary efforts that leverage the strengths of both precision medicine and public health.
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Affiliation(s)
- Megan C. Roberts
- Division of Pharmaceutical Outcomes and Policy, University of North Carolina Eshelman School of Pharmacy, 301 Pharmacy Lane, Chapel Hill, NC 27599 USA
| | - Alison E. Fohner
- Department of Epidemiology and Institute of Public Health Genetics, University of Washington, 1959 NE Pacific Ave, Seattle, WA 98195 USA
| | - Latrice Landry
- Harvard Medical School, Harvard T.H. Chan School of Public Health, Brigham and Women’s Hospital &The Division of Population Sciences in Dana Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215-5450 USA
| | - Dana Lee Olstad
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB T2N 4Z6 Canada
| | - Amelia K. Smit
- Cancer Epidemiology and Prevention Research, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, 119-143 Missenden Road, Camperdown, NSW 2050 Australia
| | - Erin Turbitt
- Discipline of Genetic Counselling, The University of Technology Sydney, 100 Broadway, Ultimo, NSW 2008 Australia
| | - Caitlin G. Allen
- Department of Behavioral Social and Health Education Sciences, Rollins School of Public Health, Emory University, 1518 Clifton Road, Atlanta, GA 30322 USA
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Lubin IM, Lockhart ER, Frank J, See VY, Vashist S, Greene C. Challenges and opportunities for integrating genetic testing into a diagnostic workflow: heritable long QT syndrome as a model. Diagnosis (Berl) 2021; 8:17-26. [PMID: 31287796 DOI: 10.1515/dx-2019-0018] [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: 03/04/2019] [Accepted: 06/18/2019] [Indexed: 11/15/2022]
Abstract
BACKGROUND An increasing number of diagnostic evaluations incorporate genetic testing to facilitate accurate and timely diagnoses. The increasing number and complexity of genetic tests continue to pose challenges in deciding when to test, selecting the correct test(s), and using results to inform medical diagnoses, especially for medical professionals lacking genetic expertise. Careful consideration of a diagnostic workflow can be helpful in understanding the appropriate uses of genetic testing within a broader diagnostic workup. CONTENT The diagnosis of long QT syndrome (LQTS), a life-threatening cardiac arrhythmia, provides an example for this approach. Electrocardiography is the preferred means for diagnosing LQTS but can be uninformative for some patients due to the variable presentation of the condition. Family history and genetic testing can augment physiological testing to inform a diagnosis and subsequent therapy. Clinical and laboratory professionals informed by peer- reviewed literature and professional recommendations constructed a generalized LQTS diagnostic workflow. This workflow served to explore decisions regarding the use of genetic testing for diagnosing LQTS. SUMMARY AND OUTLOOK Understanding the complexities and approaches to integrating genetic testing into a broader diagnostic evaluation is anticipated to support appropriate test utilization, optimize diagnostic evaluation, and facilitate a multidisciplinary approach essential for achieving accurate and timely diagnoses.
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Affiliation(s)
- Ira M Lubin
- Division of Laboratory Systems, Centers for Disease Control and Prevention, Atlanta, USA
| | - Edward R Lockhart
- Division of Laboratory Systems, Centers for Disease Control and Prevention, Atlanta, USA
| | - Julie Frank
- Division of Genetics and Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Vincent Y See
- Cardiovascular Medicine Division and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Sudhir Vashist
- Division of Cardiology and Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Carol Greene
- Division of Genetics and Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, USA
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Meagher KM, Curtis SH, Borucki S, Beck A, Srinivasan T, Cheema A, Sharp RR. Communicating unexpected pharmacogenomic results to biobank contributors: A focus group study. PATIENT EDUCATION AND COUNSELING 2021; 104:242-249. [PMID: 32919825 DOI: 10.1016/j.pec.2020.08.023] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 07/08/2020] [Accepted: 08/19/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVES The goals of this study were to explore 1) the impact of returning unexpected pharmacogenomic (PGx) results to biobank contributors, and 2) participant views about improving communication. METHODS We conducted a qualitative focus group study with biobank participants (N = 54) who were notified by mail of an individual research result indicating increased risk for adverse events associated with the common cancer drug 5-fluorouracil (5-FU). We employed a framework approach for analysis. RESULTS Our results revealed three themes illustrating participants' questions and uncertainty, especially regarding how to share results with health providers and family members, and remember them over time. Participants valued results for themselves and others, and for the future of medicine. Risk perception was framed by health identity. "Toxicity narratives," or familiarity with another's adverse reaction to chemotherapy, increased the sense of importance participants reported. CONCLUSION These focus group results highlight research participant remaining questions and high valuation of PGx results, even when unexpected. PRACTICE IMPLICATIONS We identify PGx research participants' needs for clear clinical translation messaging that attends to health identity, pragmatics of sharing information with family members, and patient perceptions of barriers to transferring research results to a clinical context.
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Affiliation(s)
- Karen M Meagher
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, USA
| | - Susan H Curtis
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, USA
| | | | - Annika Beck
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, USA
| | | | - Amal Cheema
- Geisel School of Medicine, Dartmouth College, Hanover, USA
| | - Richard R Sharp
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, USA.
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Hoffman JM, Flynn AJ, Juskewitch JE, Freimuth RR. Biomedical Data Science and Informatics Challenges to Implementing Pharmacogenomics with Electronic Health Records. Annu Rev Biomed Data Sci 2020. [DOI: 10.1146/annurev-biodatasci-020320-093614] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic information must be incorporated into electronic health records (EHRs) with clinical decision support in order to fully realize its potential to improve drug therapy. Supported by various clinical knowledge resources, pharmacogenomic workflows have been implemented in several healthcare systems. Little standardization exists across these efforts, however, which limits scalability both within and across clinical sites. Limitations in information standards, knowledge management, and the capabilities of modern EHRs remain challenges for the widespread use of pharmacogenomics in the clinic, but ongoing efforts are addressing these challenges. Although much work remains to use pharmacogenomic information more effectively within clinical systems, the experiences of pioneering sites and lessons learned from those programs may be instructive for other clinical areas beyond genomics. We present a vision of what can be achieved as informatics and data science converge to enable further adoption of pharmacogenomics in the clinic.
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Affiliation(s)
- James M. Hoffman
- Department of Pharmaceutical Sciences and the Office of Quality and Patient Care, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Allen J. Flynn
- Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Justin E. Juskewitch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Robert R. Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Center for Individualized Medicine, and Information and Knowledge Management, Mayo Clinic, Rochester, Minnesota 55905, USA
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14
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Williams MS, Taylor CO, Walton NA, Goehringer SR, Aronson S, Freimuth RR, Rasmussen LV, Hall ES, Prows CA, Chung WK, Fedotov A, Nestor J, Weng C, Rowley RK, Wiesner GL, Jarvik GP, Del Fiol G. Genomic Information for Clinicians in the Electronic Health Record: Lessons Learned From the Clinical Genome Resource Project and the Electronic Medical Records and Genomics Network. Front Genet 2019; 10:1059. [PMID: 31737042 PMCID: PMC6830110 DOI: 10.3389/fgene.2019.01059] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 10/03/2019] [Indexed: 01/05/2023] Open
Abstract
Genomic knowledge is being translated into clinical care. To fully realize the value, it is critical to place credible information in the hands of clinicians in time to support clinical decision making. The electronic health record is an essential component of clinician workflow. Utilizing the electronic health record to present information to support the use of genomic medicine in clinical care to improve outcomes represents a tremendous opportunity. However, there are numerous barriers that prevent the effective use of the electronic health record for this purpose. The electronic health record working groups of the Electronic Medical Records and Genomics (eMERGE) Network and the Clinical Genome Resource (ClinGen) project, along with other groups, have been defining these barriers, to allow the development of solutions that can be tested using implementation pilots. In this paper, we present “lessons learned” from these efforts to inform future efforts leading to the development of effective and sustainable solutions that will support the realization of genomic medicine.
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Affiliation(s)
- Marc S Williams
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | - Casey Overby Taylor
- Genomic Medicine Institute, Geisinger, Danville, PA, United States.,Department of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Nephi A Walton
- Genomic Medicine Institute, Geisinger, Danville, PA, United States
| | | | | | - Robert R Freimuth
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States
| | - Luke V Rasmussen
- Department of Preventive Medicine, Northwestern University, Chicago, IL, United States
| | - Eric S Hall
- Department of Pediatrics, University of Cincinnati College of Medicine, and Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Cynthia A Prows
- Divisions of Human Genetics and Patient Services, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY, United States
| | - Alexander Fedotov
- Irving Institute for Clinical and Translational Research, Columbia University, New York, NY, United States
| | - Jordan Nestor
- Department of Medicine, Division of Nephrology, Columbia University, New York, NY, United States
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | - Robb K Rowley
- National Human Genome Research Institute, Bethesda, MD, United States
| | - Georgia L Wiesner
- Division of Genetic Medicine, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, United States
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States
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15
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Haga SB. Managing Increased Accessibility to Pharmacogenomic Data. Clin Pharmacol Ther 2019; 106:922-924. [PMID: 31482575 DOI: 10.1002/cpt.1602] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 07/12/2019] [Indexed: 01/07/2023]
Affiliation(s)
- Susanne B Haga
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina, USA
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