Journal of General Internal Medicine

, Volume 33, Issue 6, pp 877–885 | Cite as

How Primary Care Providers Talk to Patients about Genome Sequencing Results: Risk, Rationale, and Recommendation

  • Jason L. VassyEmail author
  • J. Kelly Davis
  • Christine Kirby
  • Ian J. Richardson
  • Robert C. Green
  • Amy L. McGuire
  • Peter A. Ubel



Genomics will play an increasingly prominent role in clinical medicine.


To describe how primary care physicians (PCPs) discuss and make clinical recommendations about genome sequencing results.


Qualitative analysis.


PCPs and their generally healthy patients undergoing genome sequencing.


Patients received clinical genome reports that included four categories of results: monogenic disease risk variants (if present), carrier status, five pharmacogenetics results, and polygenic risk estimates for eight cardiometabolic traits. Patients’ office visits with their PCPs were audio-recorded, and summative content analysis was used to describe how PCPs discussed genomic results.

Key Results

For each genomic result discussed in 48 PCP–patient visits, we identified a “take-home” message (recommendation), categorized as continuing current management, further treatment, further evaluation, behavior change, remembering for future care, or sharing with family members. We analyzed how PCPs came to each recommendation by identifying 1) how they described the risk or importance of the given result and 2) the rationale they gave for translating that risk into a specific recommendation. Quantitative analysis showed that continuing current management was the most commonly coded recommendation across results overall (492/749, 66%) and for each individual result type except monogenic disease risk results. Pharmacogenetics was the most common result type to prompt a recommendation to remember for future care (94/119, 79%); carrier status was the most common type prompting a recommendation to share with family members (45/54, 83%); and polygenic results were the most common type prompting a behavior change recommendation (55/58, 95%). One-fifth of recommendation codes associated with monogenic results were for further evaluation (6/24, 25%). Rationales for these recommendations included patient context, family context, and scientific/clinical limitations of sequencing.


PCPs distinguish substantive differences among categories of genome sequencing results and use clinical judgment to justify continuing current management in generally healthy patients with genomic results.


genome sequencing physician communication medical decision-making 



The authors thank Mary Carol Barks, BA, and Sanjay Advani, MA, for assistance in preparing this manuscript.

Prior Presentations

Parts of this work were presented at the American Society for Human Genetics national meetings in 2014 and 2016.


The MedSeq Project is funded by grant U01-HG006500 from the National Human Genome Research Institute of the National Institutes of Health (NIH). Dr. Vassy is an employee of the VA Boston Healthcare System and received support from NIH grant KL2-TR001100 and Career Development Award IK2-CX001262 from the VA Clinical Sciences Research and Development Service. Dr. Green is also supported by NIH U19-HD077671, U01-HG008685, R03-HG008809, UG3-OD023156, U41-HG006834, U01-AG24904, R01-CA154517, P60-AR047782, R01-AG047866, as well as funding from the Broad Institute and the Department of Defense. This work was conducted with support from Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Research Resources and National Center for Advancing Translational Sciences, NIH grant UL1-TR001102), and financial contributions from Harvard University and its affiliated academic health care centers. The contents do not necessarily represent the views of the U.S. Department of Veterans Affairs (VA), the U.S. government, Harvard Catalyst, Harvard University and its affiliated academic healthcare centers, or the National Institutes of Health.

Compliance with Ethical Standards

Conflict of Interest

Dr. Ubel is a consultant for Humana. Dr. Green receives compensation for speaking or consultation from AIA, GenePeeks, Helix, Illumina, Ohana, Prudential, and Veritas, and is co-founder, advisor, and equity holder in Genome Medical, Inc. The other authors declare that they do not have a conflict of interest.

Supplementary material

11606_2017_4295_MOESM1_ESM.pdf (643 kb)
ESM 1 (PDF 643 kb)


  1. 1.
    Biesecker LG, Green RC. Diagnostic clinical genome and exome sequencing. N Engl J Med. 2014;370(25):2418–25.CrossRefPubMedGoogle Scholar
  2. 2.
    Gagan J, Van Allen EM. Next-generation sequencing to guide cancer therapy. Genome Med. 2015;7(1):80.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Yang Y, Muzny DM, Xia F, et al. Molecular findings among patients referred for clinical whole-exome sequencing. JAMA. 2014;312(18):1870–9.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Cuckle H, Benn P, Pergament E. Cell-free DNA screening for fetal aneuploidy as a clinical service. Clin Biochem. 2015;48(15):932–41.CrossRefPubMedGoogle Scholar
  5. 5.
    Beaudet AL. Using fetal cells for prenatal diagnosis: History and recent progress. Am J Med Genet C Semin Med Genet. 2016;172(2):123–7.CrossRefPubMedGoogle Scholar
  6. 6.
    Brison N, Van Den Bogaert K, Dehaspe L, et al. Accuracy and clinical value of maternal incidental findings during noninvasive prenatal testing for fetal aneuploidies. Genet Med. 2017;19(3):306–13.CrossRefPubMedGoogle Scholar
  7. 7.
    Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics. Genet Med. 2015;17(6):505–7.Google Scholar
  8. 8.
    Grosse SD, Rogowski WH, Ross LF, Cornel MC, Dondorp WJ, Khoury MJ. Population screening for genetic disorders in the 21st century: evidence, economics, and ethics. Public Health Genomics. 2010;13(2):106–15.CrossRefPubMedGoogle Scholar
  9. 9.
    Hampel H. Genetic counseling and cascade genetic testing in Lynch syndrome. Fam. Cancer. 2016;15(3):423–7.CrossRefPubMedGoogle Scholar
  10. 10.
    Linderman MD, Nielsen DE, Green RC. Personal genome sequencing in ostensibly healthy individuals and the peopleSeq consortium. J Pers Med. 2016;6(2):14.Google Scholar
  11. 11.
    Peplow M. The 100,000 Genomes Project. BMJ. 2016;353:i1757.CrossRefPubMedGoogle Scholar
  12. 12.
    Precision Medicine Initiative Working Group. The Precision Medicine Initiative Cohort Program – Building a Research Foundation for 21st Century Medicine. 2015. Accessed December 13, 2017.
  13. 13.
    Carey DJ, Fetterolf SN, Davis FD, et al. The Geisinger MyCode community health initiative: an electronic health record-linked biobank for precision medicine research. Genet. Med. 2016;18(9):906–13.Google Scholar
  14. 14.
    Gaziano JM, Concato J, Brophy M, et al. Million Veteran Program: a mega-biobank to study genetic influences on health and disease. J Clin Epidemiol. 2016;70:214–23.CrossRefPubMedGoogle Scholar
  15. 15.
    Green RC, Goddard KA, Jarvik GP, et al. Clinical sequencing exploratory research consortium: accelerating evidence-based practice of genomic medicine. Am. J. Hum. Genet. 2016.Google Scholar
  16. 16.
    Ball MP, Bobe JR, Chou MF, et al. Harvard Personal Genome Project: lessons from participatory public research. Genome Med. 2014;6(2):10.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Green RC, Berg JS, Grody WW, et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013;15(7):565–74.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Kalia SS, Adelman K, Bale SJ, et al. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2017;19(2):249–55.CrossRefPubMedGoogle Scholar
  19. 19.
    Christensen KD, Vassy JL, Jamal L, et al. Are physicians prepared for whole genome sequencing? A qualitative analysis. Clin Genet. 2016;89(2):228–34.CrossRefPubMedGoogle Scholar
  20. 20.
    Gray SW, Park ER, Najita J, et al. Oncologists’ and cancer patients’ views on whole-exome sequencing and incidental findings: results from the CanSeq study. Genet Med. 2016;18(10):1011–9.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Dobson A, El-Gamil A, Pal S, Heath S, DaVanzo JE. Projecting the Supply and Demand for Certified Genetic Counselors: A Workforce Study. Vienna, VA: Dobson DaVanzo & Associates, September 7, 2016.Google Scholar
  22. 22.
    Zhang H, Yu J, Ming Q, Bao L, Wu B-L, Li P. On the globalization and standardization of medical genetics and genomics as clinical and laboratory specialties. N Am J Med Sci (Boston). 2014;7(4):194–8.Google Scholar
  23. 23.
    Lewis KL, Hooker GW, Connors PD, et al. Participant use and communication of findings from exome sequencing: a mixed-methods study. Genet Med. 2016;18(6):577–83.CrossRefPubMedGoogle Scholar
  24. 24.
    Evans JP, Powell BC, Berg JS. Finding the rare pathogenic variants in a human genome. JAMA. 2017;317(18):1904–5.CrossRefPubMedGoogle Scholar
  25. 25.
    McLaughlin HM, Ceyhan-Birsoy O, Christensen KD, et al. A systematic approach to the reporting of medically relevant findings from whole genome sequencing. BMC Med Genet. 2014;15:134.CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Lek M, Karczewski KJ, Minikel EV, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536(7616):285–91.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Vassy JL, Christensen KD, Schonman EF, et al. The impact of whole-genome sequencing on the primary care and outcomes of healthy adult patients: a pilot randomized trial. Ann Intern Med. 2017;167(3):159–69.CrossRefGoogle Scholar
  28. 28.
    Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405–24.CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Nambot S, Thevenon J, Kuentz P, et al. Clinical whole-exome sequencing for the diagnosis of rare disorders with congenital anomalies and/or intellectual disability: substantial interest of prospective annual reanalysis. Genet Med. 2017 Nov 2.
  30. 30.
    Vassy JL, Korf BR, Green RC. How to know when physicians are ready for genomic medicine. Sci Transl Med. 2015;7(287):287fs19-fs19.CrossRefGoogle Scholar
  31. 31.
    Clark D, Kowal S. Communicating genomic risk in primary health care: challenges and opportunities for providers. Med Care. 2014;52(10):933–4.CrossRefPubMedGoogle Scholar
  32. 32.
    Vassy JL, Lautenbach DM, McLaughlin HM, et al. The MedSeq Project: a randomized trial of integrating whole genome sequencing into clinical medicine. Trials. 2014;15(1):85.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Vassy JL, Christensen KD, Slashinski MJ, et al. “Someday it will be the norm”: Physician perspectives on the utility of genome sequencing for patient care in the MedSeq Project. Per Med. 2015;12(1):23–32.CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Vassy JL, McLaughlin HM, MacRae CA, et al. A one-page summary report of genome sequencing for the healthy adult. Public Health Genomics. 2015;8(2):123–9.CrossRefGoogle Scholar
  35. 35.
    Kong SW, Lee I-H, Leshchiner I, et al. Summarizing polygenic risks for complex diseases in a clinical whole-genome report. Genet Med. 2015;17(7):536–44.CrossRefPubMedGoogle Scholar
  36. 36.
    United States Surgeon General. My Family Health Portrait: A Tool from the Surgeon General. 2009. Accessed December 13, 2017.
  37. 37.
    Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88.CrossRefPubMedGoogle Scholar
  38. 38.
    Carroll JC, Makuwaza T, Manca DP, et al. Primary care providers’ experiences with and perceptions of personalized genomic medicine. Can Fam Phys. 2016;62(10):e626-e35.Google Scholar
  39. 39.
    Selkirk CG, Weissman SM, Anderson A, Hulick PJ. Physicians’ preparedness for integration of genomic and pharmacogenetic testing into practice within a major healthcare system. Genet Test Mol Biomarkers. 2013;17(3):219–25.CrossRefPubMedGoogle Scholar
  40. 40.
    Korf BR. Genomic medicine: educational challenges. Mol Genet Genomic Med. 2013;1(3):119–22.CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Najafzadeh M, Davis JC, Joshi P, Marra C. Barriers for integrating personalized medicine into clinical practice: a qualitative analysis. Am J Med Genet A. 2013;161A(4):758–63.CrossRefPubMedGoogle Scholar
  42. 42.
    Nippert I, Harris HJ, Julian-Reynier C, et al. Confidence of primary care physicians in their ability to carry out basic medical genetic tasks-a European survey in five countries-Part 1. J Commun Genet. 2011;2(1):1–11.CrossRefGoogle Scholar
  43. 43.
    Manolio TA, Murray MF. The growing role of professional societies in educating clinicians in genomics. Genet Med. 2014;16(8):571–2.CrossRefPubMedGoogle Scholar
  44. 44.
    Feero WG, Manolio TA, Khoury MJ. Translational research is a key to nongeneticist physicians’ genomics education. Genet Med. 2014;16(12):871–3.CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Demmer LA, Waggoner DJ. Professional medical education and genomics. Annu Rev Genomics Hum Genet. 2014;15:507–16.CrossRefPubMedGoogle Scholar
  46. 46.
    Blazer KR, Christie C, Uman G, Weitzel JN. Impact of web-based case conferencing on cancer genetics training outcomes for community-based clinicians. J Cancer Educ. 2012;27(2):217–25.CrossRefPubMedGoogle Scholar
  47. 47.
    Carroll JC, Wilson BJ, Allanson J, et al. GenetiKit: a randomized controlled trial to enhance delivery of genetics services by family physicians. Fam Pract. 2011;28(6):615–23.CrossRefPubMedGoogle Scholar
  48. 48.
    Korf BR, Berry AB, Limson M, et al. Framework for development of physician competencies in genomic medicine: report of the Competencies Working Group of the Inter-Society Coordinating Committee for Physician Education in Genomics. Genet Med. 2014;16(11):804–9.CrossRefPubMedGoogle Scholar
  49. 49.
    Sharp RR, Goldlust ME, Eng C. Addressing gaps in physician education using personal genomic testing. Genet Med. 2011;13(8):750–1.CrossRefPubMedGoogle Scholar
  50. 50.
    NHS Health Education England. Introducing Health Education England’s Genomics Education Programme. Accessed December 13, 2017.
  51. 51.
    Paul J, Metcalfe S, Stirling L, Wilson B, Hodgson J. Analyzing communication in genetic consultations—a systematic review. Patient Educ Couns. 2015;98(1):15–33.CrossRefPubMedGoogle Scholar
  52. 52.
    Arora NS, Davis JK, Kirby C, et al. Communication challenges for non-geneticist physicians relaying clinical genomic results. Pers Med. 2016;14(5):423–431.CrossRefGoogle Scholar
  53. 53.
    Sarangi S. The language of likelihood in genetic-counseling discourse. J Lang Soc Psychol. 2002;21(1):7–31.CrossRefGoogle Scholar
  54. 54.
    O’Doherty K. Risk communication in genetic counselling. Theory Psychol. 2006;16(2):225–56.CrossRefGoogle Scholar
  55. 55.
    O’Doherty KC, Navarro DJ, Crabb SH. A qualitative approach to the study of causal reasoning in natural language. Theory Psychol. 2009;19(4):475–500.CrossRefGoogle Scholar
  56. 56.
    Thomassen G, Sarangi S. Evidence-based familial risk explanations in cancer genetic counselling. Health Risk Soc. 2012;14(7–8):607–26.CrossRefGoogle Scholar
  57. 57.
    Lehtinen E, Kääriäinen H. Doctor’s expertise and managing discrepant information from other sources in genetic counseling: a conversation analytic perspective. J Genet Couns. 2005;14(6):435–51.CrossRefPubMedGoogle Scholar
  58. 58.
    Lehtinen E. Hedging, knowledge and interaction: Doctors’ and clients’ talk about medical information and client experiences in genetic counseling. Patient Educ Couns. 2013;92(1):31–7.CrossRefPubMedGoogle Scholar
  59. 59.
    Scheuner MT, Edelen MO, Hilborne LH, Lubin IM. Effective communication of molecular genetic test results to primary care providers. Genet Med. 2013;15(6):444–9.CrossRefPubMedGoogle Scholar
  60. 60.
    Williams JL, Rahm AK, Stuckey H, et al. Enhancing genomic laboratory reports: a qualitative analysis of provider review. Am J Med Genet A. 2016;170A(5):1134–41.CrossRefPubMedGoogle Scholar
  61. 61.
    Shirts BH, Salama JS, Aronson SJ, et al. CSER and eMERGE: current and potential state of the display of genetic information in the electronic health record. J Am Med Inform Assoc. 2015;22(6):1231–42.PubMedPubMedCentralGoogle Scholar
  62. 62.
    McGuire AL, Burke W. An unwelcome side effect of direct-to-consumer personal genome testing: raiding the medical commons. JAMA. 2008;300(22):2669–71.CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Korngiebel DM, Fullerton SM, Burke W. Patient safety in genomic medicine: an exploratory study. Genet Med. 2016;18(11):1136–42.CrossRefPubMedPubMedCentralGoogle Scholar
  64. 64.
    Deyo RA. Cascade effects of medical technology. Annu Rev Public Health. 2002;23:23–44.CrossRefPubMedGoogle Scholar
  65. 65.
    Vassy JL, Bates DW, Murray MF. Appropriateness: a key to enabling the use of genomics in clinical practice? Am J Med. 2016;129(6):551–3.CrossRefPubMedPubMedCentralGoogle Scholar
  66. 66.
    Overby CL, Kohane I, Kannry JL, et al. Opportunities for genomic clinical decision support interventions. Genet Med. 2013;15(10):817–23.CrossRefPubMedGoogle Scholar

Copyright information

© Society of General Internal Medicine (outside the USA) 2018

Authors and Affiliations

  • Jason L. Vassy
    • 1
    • 2
    • 3
    Email author
  • J. Kelly Davis
    • 4
  • Christine Kirby
    • 4
  • Ian J. Richardson
    • 2
  • Robert C. Green
    • 3
    • 5
    • 6
  • Amy L. McGuire
    • 7
  • Peter A. Ubel
    • 4
    • 8
  1. 1.Section of General Internal MedicineVA Boston Healthcare SystemBostonUSA
  2. 2.Division of General Internal Medicine and Primary CareBrigham and Women’s HospitalBostonUSA
  3. 3.Department of MedicineHarvard Medical SchoolBostonUSA
  4. 4.Margolis Center for Health PolicyDuke UniversityDurhamUSA
  5. 5.Division of GeneticsBrigham and Women’s HospitalBostonUSA
  6. 6.Broad Institute of MIT and HarvardCambridgeUSA
  7. 7.Center for Medical Ethics and Health PolicyBaylor College of MedicineHoustonUSA
  8. 8.Fuqua School of Business, Sanford School of Public Policy, School of MedicineDuke UniversityDurhamUSA

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