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The Implementation Chasm Hindering Genome-informed Health Care

Published online by Cambridge University Press:  01 January 2021

Kevin B. Johnson ,
Ellen Wright Clayton ,
Justin Starren  and
Josh Peterson
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Abstract

The promises of precision medicine are often heralded in the medical and lay literature, but routine integration of genomics in clinical practice is still limited. While the “last mile” infrastructure to bring genomics to the bedside has been demonstrated in some healthcare settings, a number of challenges remain — both in the receptivity of today's health system and in its technical and educational readiness to respond to this evolution in care. To improve the impact of genomics on health and disease management, we will need to integrate both new knowledge and new care processes into existing workflows. This change will be onerous and time-consuming, but hopefully valuable to the provision of high quality, economically feasible care worldwide.

Type
Symposium Articles
Information
Journal of Law, Medicine & Ethics , Volume 48 , Issue 1: LawSeq: Building a Sound Legal Foundation for Translating Genomics into Clinical Application , Spring 2020 , pp. 119 - 125
Copyright
Copyright © American Society of Law, Medicine and Ethics 2020

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References

Splinter, K., et al., “Effect of Genetic Diagnosis on Patients with Previously Undiagnosed Disease,” New England Journal of Medicine 379, no. 22 (2018): 2131–2139; Wise, A.L., et al., “Genomic Medicine for Undiagnosed Diseases,” Lancet 394, no. 10197 (2019): 533–540.CrossRefGoogle Scholar
Pulley, J. M., et al., “Operational Implementation of Prospective Genotyping for Personalized Medicine: The Design of the Vanderbilt PREDICT Project,” Clinical Pharmacology and Therapeutics 92, no. 1 (2012): 87–95; Peterson, J. F., et al., “Physician Response to Implementation of Genotype-Tailored Antiplatelet Therapy,” Clinical Pharmacology and Therapeutics 100, no. 1 (2016): 67–74; Peterson, J. F., et al., “Electronic Health Record Design and Implementation for Pharmacogenomics: A Local Perspective,” Genetics in Medicine 15, no. 10 (2013): 833–841.CrossRefGoogle Scholar
van El, C. G., et al., “Whole-Genome Sequencing in Health Care: Recommendations of the European Society of Human Genetics,” European Journal of Human Genetics 21, no. 6 (2013): 580–584; Boycott, K., et al., “The Clinical Application of Genome-Wide Sequencing for Monogenic Diseases in Canada: Position Statement of the Canadian College of Medical Geneticists,” Journal of Medical Genetics 52, no. 7 (2015): 431–437; ACMG Board of Directors, “ACMG Policy Statement: Updated Recommendations Regarding Analysis and Reporting of Secondary Findings in Clinical Genome-Scale Sequencing,” Genetics in Medicine 17, no. 1 (2015): 68–69.Google Scholar
Roberts, J. S., et al., “Returning Individual Research Results: Development of a Cancer Genetics Education and Risk Communication Protocol,” Journal of Empirical Research in Human Research Ethics 5, no. 3 (2010): 17–30.Google Scholar
Rasmussen, L. V., et al., “Practical Considerations for Implementing Genomic Information Resources. Experiences from eMERGE and CSER,” Applied Clinical Informatics 7, no. 3 (2016): 870–882; Kullo, I. J., et al., “Return of Results in the Genomic Medicine Projects of the eMERGE Network,” Frontiers in Genetics 5 (2014): 50; Shaibi, G. Q., et al., “Developing a Process for Returning Medically Actionable Genomic Variants to Latino Patients in a Federally Qualified Health Center,” Public Health Genomics 21, no. 1-2 (2018): 77–84.Google Scholar
Myers, C. T. and Mefford, H. C., “Advancing Epilepsy Genetics in the Genomic Era,” Genome Medicine 7 (2015): 91.CrossRefGoogle Scholar
U. S. Preventive Services Task Force, Owens, D. K., et al., “Risk Assessment, Genetic Counseling, and Genetic Testing for BRCA-Related Cancer: US Preventive Services Task Force Recommendation Statement,” JAMA 322, no. 7 (2019): 652–665.Google Scholar
Reinsel, D., Gantz, J., and Rydning, J., “The Digitization of the World from Edge to Core,” available at <https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf> (last visited January 31, 2020).+(last+visited+January+31,+2020).>Google Scholar
Balas, E. A. and Boren, S. A., “Managing Clinical Knowledge for Health Care Improvement,” in Bemmel, J. and McCray, A. T., eds., Yearbook of Medical Informatics 2000: Patient-Centered Systems (Stuttgart, Germany: Schattauer Verlagsgesellschaft mbH, 2000): 65–70.Google Scholar
Anthonisen, N. R., Skeans, M. A., Wise, R. A., Manfreda, J., Kanner, R. E., Connett, J. E., and Group Lung Health Study Research, “The Effects of a Smoking Cessation Intervention on 14.5-Year Mortality: A Randomized Clinical Trial,” Annals of Internal Medicine 142, no. 4 (2005): 233–239.CrossRefGoogle Scholar
Park, E. R., et al., “Primary Care Provider-Delivered Smoking Cessation Interventions and Smoking Cessation among Participants in the National Lung Screening Trial,” JAMA Internal Medicine 175, no. 9 (2015): 1509–1516.CrossRefGoogle Scholar
Timbie, J. W., et al., “Five Reasons That Many Comparative Effectiveness Studies Fail to Change Patient Care and Clinical Practice,” Health Affairs 31, no. 10 (2012): 2168–2175.CrossRefGoogle Scholar
Ioannidis, J. P., “Why Most Published Research Findings Are False,” PLoS Medicine 2, no. 8 (2005): e124.CrossRefGoogle Scholar
Donabedian, A., “The Quality of Care. How Can It Be Assessed?” JAMA 260, no. 12 (1988): 1743–1748.CrossRefGoogle Scholar
Kohn, L. T., Corrigan, J., and Donaldson, M. S., To Err Is Human : Building a Safer Health System (Washington, D.C.: National Academy Press, 2000).Google Scholar
Marcotte, L., et al., “Achieving Meaningful Use of Health Information Technology: A Guide for Physicians to the EHR Incentive Programs,” Archives of Internal Medicine 172, no. 9 (2012): 731–736; Blumenthal, D. and Tavenner, M., “The ‘Meaningful Use’ Regulation for Electronic Health Records,” New England Journal of Medicine 363, no. 6 (2010): 501–504.Google Scholar
Williams, D. C., et al., “Physician Use of Electronic Health Records: Survey Study Assessing Factors Associated with Provider Reported Satisfaction and Perceived Patient Impact,” Journal of Medical Internet Research Medical Informatics 7, no. 2 (2019): e10949; Eberts, M. and Capurro, D., “Patient and Physician Perceptions of the Impact of Electronic Health Records on the Patient-Physician Relationship,” Applied Clinical Informatics 10, no. 4 (2019): 729–734; Marmor, R. A., et al., “The Impact of Physician EHR Usage on Patient Satisfaction,” Applied Clinical Informatics 9, no. 1 (2018): 11–14.Google Scholar
Berwick, D. M., “Era 3 for Medicine and Health Care,” JAMA 315, no. 13 (2016): 1329–1330.CrossRefGoogle Scholar
Wang, M. D., Khanna, R., and Najafi, N., “Characterizing the Source of Text in Electronic Health Record Progress Notes,” JAMA Internal Medicine 177, no. 8 (2017): 1212–1213.CrossRefGoogle Scholar
Del Carmen, M. G., et al., “Trends and Factors Associated with Physician Burnout at a Multispecialty Academic Faculty Practice Organization,” JAMA Network Open 2, no. 3 (2019): e190554; Dyrbye, L. N., et al., “Association of Clinical Specialty with Symptoms of Burnout and Career Choice Regret among US Resident Physicians,” JAMA 320, no. 11 (2018): 1114–1130.CrossRefGoogle Scholar
Gold, K. J., Sen, A., and Schwenk, T. L., “Details on Suicide among US Physicians: Data from the National Violent Death Reporting System,” General Hospital Psychiatry 35, no. 1 (2013): 45–49.CrossRefGoogle Scholar
Khairat, S., et al., “Perceived Burden of EHRs on Physicians at Different Stages of Their Career,” Applied Clinical Informatics 9, no. 2 (2018): 336–347; Kroth, P. J., et al., “The Electronic Elephant in the Room: Physicians and the Electronic Health Record.” Journal of the American Medical Informatics Association Open 1, no. 1 (2018): 49–56.Google Scholar
Mir, T. H., et al., “Assessing the Quality of the After-Visit Summary (AVS) in a Primary-Care Clinic,” Journal of the American Board of Family Medicine 32, no. 1 (2019): 65–68.CrossRefGoogle Scholar
Shanafelt, T. D. and Noseworthy, J. H., “Executive Leadership and Physician Well-Being: Nine Organizational Strategies to Promote Engagement and Reduce Burnout,” Mayo Clinic Proceedings 92, no. 1 (2017): 129–146.CrossRefGoogle Scholar
Herzlinger, R. E., “Why Innovation in Healthcare Is So Hard,” Harvard Business Review 84, no. 5 (2006): 58–66, 156.Google Scholar
Palfrey, J. G. and Gasser, U., Born Digital: Understanding the First Generation of Digital Natives (New York: Basic Books, 2008).Google Scholar
Abelson, J. S., et al., “Barriers and Benefits to Using Mobile Health Technology after Operation: A Qualitative Study,” Surgery 162, no. 3 (2017): 605–611.CrossRefGoogle Scholar
Thies, K., Anderson, D., and Cramer, B., “Lack of Adoption of a Mobile App to Support Patient Self-Management of Diabetes and Hypertension in a Federally Qualified Health Center: Interview Analysis of Staff and Patients in a Failed Randomized Trial,” Journal of Medical Internet Research Human Factors 4, no. 4 (2017): e24; Rigby, M., et al., “Steps in Moving Evidence-Based Health Informatics from Theory to Practice,” Healthcare Informatics Research 22, no. 4 (2016): 255–260.Google Scholar
Bauer, A. M., et al., “Patient-Oriented Health Technologies: Patients’ Perspectives and Use,” Journal of Mobile Technology in Medicine 6, no. 2 (2017): 1–10.CrossRefGoogle Scholar
The eMERGE Consortium, “Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network,” American Journal of Human Genetics 105, no. 3 (2019): 588–605; Pulley, J. M., et al. “Operational Implementation of Prospective Genotyping for Personalized Medicine: The Design of the Vanderbilt PREDICT Project,” Clinical Pharmacology and Therapeutics 92, no. 1 (2012): 87–95.Google Scholar
Hoffman, J. M., et al., “Developing Knowledge Resources to Support Precision Medicine: Principles from the Clinical Pharmacogenetics Implementation Consortium (CPIC),” Journal of the American Medical Informatics Association 23, no. 4 (2016): 796–801; Masys, D. R., et al., “Technical Desiderata for the Integration of Genomic Data into Electronic Health Records,” Journal of Biomedical Informatics 45, no. 3 (2012): 419–422.CrossRefGoogle Scholar
Berrios, D. C., Beheshti, A., and Costes, S. V., “FAIRness and Usability for Open-Access Omics Data Systems,” American Medical Informatics Association Annual Symposium Proceedings 2018 (2018): 232–241.Google Scholar
Guttmacher, A. E., Porteous, M. E., and McInerney, J. D., “Educating Health-Care Professionals About Genetics and Genomics,” Nature Reviews Genetics 8, no. 2 (2007): 151–157.CrossRefGoogle Scholar
Hurle, B., et al., “What Does It Mean to Be Genomically Literate? National Human Genome Research Institute Meeting Report,” Genetics in Medicine 15, no. 8 (2013): 658–663.CrossRefGoogle Scholar
Roberts, supra note 4.Google Scholar
Anderson, J. L., et al., “Randomized Trial of Genotype-Guided Versus Standard Warfarin Dosing in Patients Initiating Oral Anticoagulation,” Circulation 116, no. 22 (2007): 2563–2570.CrossRefGoogle Scholar
Ramirez, A. H., et al., “Predicting Warfarin Dosage in European-Americans and African-Americans Using DNA Samples Linked to an Electronic Health Record,” Pharmacogenomics 13, no. 4 (2012): 407–418.CrossRefGoogle Scholar
Christensen, K. D., Dukhovny, D., Siebert, U., and Green, R. C., “Assessing the Costs and Cost-Effectiveness of Genomic Sequencing,” Journal of Personalized Medicine 5, no. 4 (2015): 470–486.CrossRefGoogle Scholar
Ammenwerth, E., et al., “Evaluation of Health Information Systems — Problems and Challenges,” International Journal of Medical Informatics 71, no. 2-3 (2003): 125–135.CrossRefGoogle Scholar
Evans, B. J., “HIPAA's Individual Right of Access to Genomic Data: Reconciling Safety and Civil Rights,” American Journal of Human Genetics 102, no. 1 (2018): 5–10.CrossRefGoogle Scholar
Starren, J., Williams, M. S., and Bottinger, E. P., “Crossing the Omic Chasm: A Time for Omic Ancillary Systems,” JAMA 309, no. 12 (2013): 1237–1238.CrossRefGoogle Scholar
Starr, P., The Social Transformation of American Medicine (New York: Basic Books, 2017, updated ed.).Google Scholar
Potts, H. W. and Wyatt, J. C., “Survey of Doctors' Experience of Patients Using the Internet,” Journal of Medical Internet Research 4, no. 1 (2002): e5.CrossRefGoogle Scholar
Clayton, E. W., Evans, B. J., Hazel, J. W., and Rothstein, M. A., “The Law of Genetic Privacy: Applications, Implications, and Limitations,” Journal of Law and the Biosciences (2019): 1–36.CrossRefGoogle Scholar
Roberts, J. S., et al., “Direct-to-Consumer Genetic Testing: User Motivations, Decision Making, and Perceived Utility of Results,” Public Health Genomics 20, no. 1 (2017): 36–45.CrossRefGoogle Scholar
Pet, D. B., et al., “Physicians' Perspectives on Receiving Unsolicited Genomic Results,” Genetics in Medicine 21, no. 2 (2019): 311–318; Haga, S. B., “First Responder to Genomic Information: A Guide for Primary Care Providers,” Molecular Diagnosis & Therapy 23, no. 4 (2019): 459–466.Google Scholar
Hurle, supra note 34.Google Scholar
Overby, C. L., et al., “Opportunities for Genomic Clinical Decision Support Interventions,” Genetics in Medicine 15, no. 10 (2013): 817–823.CrossRefGoogle Scholar
Katsanis, S. J. and Katsanis, N., “Molecular Genetic Testing and the Future of Clinical Genomics,” Nature Reviews Genetics 14, no. 6 (2013): 415–426; Korngiebel, D. M., Fullerton, S. M., and Burke, W., “Patient Safety in Genomic Medicine: An Exploratory Study,” Genetics in Medicine 18, no. 11 (2016): 1136–1142.CrossRefGoogle Scholar
Crowson, C. S., et al., “Primer: Demystifying Risk — Understanding and Communicating Medical Risks,” Nature Clinical Practice Rheumatology 3, no. 3 (2007): 181–187; Lipkus, I. M., Samsa, G., and Rimer, B. K., “General Performance on a Numeracy Scale among Highly Educated Samples,” Medical Decision Making 21, no. 1 (2001): 37–44.CrossRefGoogle Scholar
Schumock, G. T., et al., “Factors That Influence Prescribing Decisions,” Annals of Pharmacotherapy 38, no. 4 (2004): 557–562.CrossRefGoogle Scholar
Bhatti, J. and Redelmeier, D. A., “Angelina Jolie and Medical Decision Science,” Medical Decision Making 35, no. 1 (2015): 4–5.CrossRefGoogle Scholar
Hendricks-Sturrup, R. M. and Lu, C. Y., “Understanding Implementation Challenges to Genetic Testing for Familial Hyper-cholesterolemia in the United States,” Journal of Personalized Medicine 9, no. 1 (2019): doi: 10.3390/jpm9010009; Roden, D. M., et al., “Benefit of Preemptive Pharmacogenetic Information on Clinical Outcome,” Clinical Pharmacology and Therapeutics 103, no. 5 (2018): 787–794.Google Scholar
Chambers, D. A., Feero, W. G., and Khoury, M. J., “Convergence of Implementation Science, Precision Medicine, and the Learning Health Care System: A New Model for Biomedical Research,” JAMA 315, no. 18 (2016): 1941–1942.CrossRefGoogle Scholar
Al Kawam, A., et al., “Understanding the Bioinformatics Challenges of Integrating Genomics into Healthcare,” IEEE Journal of Biomedical Health Informatics 22, no. 5 (2018): 1672–1683.CrossRefGoogle Scholar