Shared decision-making following disclosure of coronary heart disease genetic risk: Results from a randomized clinical trial

Journal of Investigative Medicine

Volumn 65, Issue 3, 2017, Pages 681-688

  Jouni, Hayan ^a   Haddad, Raad A ^a   Marroush, Tariq S ^a   Brown, Sherry Ann ^a   Kruisselbrink, Teresa M ^a   Austin, Erin E ^a   Shameer, Khader ^a   Behnken, Emma M ^a   Chaudhry, Rajeev ^a   Montori, Victor M ^a   Kullo, Iftikhar J ^a  

^a MAYO CLINIC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HIGH DENSITY LIPOPROTEIN CHOLESTEROL; HYDROXYMETHYLGLUTARYL COENZYME A REDUCTASE INHIBITOR; LOW DENSITY LIPOPROTEIN CHOLESTEROL;

ADULT; AGED; ARTICLE; CLINICAL PRACTICE; CONTROLLED STUDY; CORONARY RISK; ELECTRONIC HEALTH RECORD; FEMALE; GENETIC RISK; HUMAN; INTERPERSONAL COMMUNICATION; ISCHEMIC HEART DISEASE; MAJOR CLINICAL STUDY; MALE; PATIENT SATISFACTION; PERCEPTION; RANDOMIZED CONTROLLED TRIAL; RISK FACTOR; SHARED DECISION MAKING; VIDEORECORDING; CORONARY ARTERY DISEASE; DECISION MAKING; GENETIC PREDISPOSITION; GENETICS; HEART INFARCTION; MIDDLE AGED; PHYSICIAN;

CORONARY DISEASE; DECISION MAKING; DISCLOSURE; FEMALE; GENETIC PREDISPOSITION TO DISEASE; HUMANS; MALE; MIDDLE AGED; MYOCARDIAL INFARCTION; PATIENT SATISFACTION; PHYSICIANS; RISK FACTORS;

EID: 85014603931     PISSN: 10815589     EISSN: 17088267     Source Type: Journal    
DOI: 10.1136/jim-2016-000318     Document Type: Article

References (34)

1. Spatz ES, Spertus JA. Shared decision making: a path toward improved patient-centered outcomes. Circ Cardiovasc Qual Outcomes 2012; 5: e75-7. doi:10.1161/CIRCOUTCOMES.112.969717
2. Coylewright M, Branda M, Inselman JW, et al. Impact of sociodemographic patient characteristics on the efficacy of decision AIDS: a patient-level meta-analysis of 7 randomized trials. Circ Cardiovasc Qual Outcomes 2014; 7: 360-7. doi:10.1161/HCQ.0000000000000006
3. Goff DC Jr, Lloyd-Jones DM, Bennett G, et al., American College of Cardiology/American Heart Association Task Force on Practice Guidelines. 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk: a Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation 2014; 129 (Suppl 2): S49-73. doi:10.1161/01.cir.0000437741.48606.98
4. Deloukas P, Kanoni S, Willenborg C, et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet 2013; 45: 25-33. doi:10.1038/ng.2480
5. Paulos JA. Innumeracy: mathematical illeteracy and its consequences. New York: Hill and Wang, 1988.
6. McBride CM, Alford SH, Reid RJ, et al. Putting science over supposition in the arena of personalized genomics. Nat Genet 2008; 40: 939-42. doi:10.1038/ng0808-939
7. Ding K, Bailey KR, Kullo IJ. Genotype-informed estimation of risk of coronary heart disease based on genome-wide association data linked to the electronic medical record. BMC Cardiovasc Disord 2011; 11: 66. doi:10.1186/1471-2261-11-66
8. Gottesman O, Kuivaniemi H, Tromp G, et al. The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future. Genet Med 2013; 15: 761-71. doi:10.1038/gim.2013.72
9. Gigerenzer G, Edwards A. Simple tools for understanding risks: from innumeracy to insight. BMJ 2003; 327: 741-4. doi:10.1136/bmj.327.7417.741
10. O'Doherty K, Suthers GK. Risky communication: pitfalls in counseling about risk, and how to avoid them. J Genet Couns 2007; 16: 409-17. doi:10.1007/s10897-006-9077-9
11. Montori VM, Breslin M, Maleska M, et al. Creating a conversation: insights from the development of a decision aid. PLoS Med 2007; 4: e233. doi:10.1371/journal.pmed.0040233
12. Kullo IJ, Jouni H, Olson JE, et al. Design of a randomized controlled trial of disclosing genomic risk of coronary heart disease: the Myocardial Infarction Genes (MI-GENES) study. BMC Med Genomics 2015; 8: 51. doi:10.1186/s12920-015-0122-0
13. Kullo IJ, Jouni H, Austin EE, et al. Incorporating a genetic risk score into coronary heart disease risk estimates: effect on low-density lipoprotein cholesterol levels (the MI-GENES Clinical Trial). Circulation 2016; 133: 1181-8. doi:10.1161/CIRCULATIONAHA.115.020109
14. Olson JE, Ryu E, Johnson KJ, et al. The Mayo Clinic Biobank: a building block for individualized medicine. Mayo Clin Proc 2013; 88: 952-62. doi:10.1016/j.mayocp.2013.06.006
15. Pocock SJ, Simon R. Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial. Biometrics 1975; 31: 103-15. doi:10.2307/2529712
16. Wilson PW, D'Agostino RB, Levy D, et al. Prediction of coronary heart disease using risk factor categories. Circulation 1998; 97: 1837-47. doi:10.1161/01.CIR.97.18.1837
17. Chaudhry R, Peters SG, Wagholikar K, et al. Innovations in the delivery of primary care services using a software solution: the Mayo Clinic's generic disease management system. Int J Pers Cent Med 2012; 2: 361-7.
18. Mann DM, Ponieman D, Montori VM, et al. The Statin Choice decision aid in primary care: a randomized trial. Patient Educ Couns 2010; 80: 138-40. doi:10.1016/j.pec.2009.10.008
19. Weymiller AJ, Montori VM, Jones LA, et al. Helping patients with type 2 diabetes mellitus make treatment decisions: statin choice randomized trial. Arch Intern Med 2007; 167: 1076-82. doi:10.1001/archinte.167.10.1076
20. Branda ME, LeBlanc A, Shah ND, et al. Shared decision making for patients with type 2 diabetes: a randomized trial in primary care. BMC Health Serv Res 2013; 13: 301. doi:10.1186/1472-6963-13-301
21. Simon D, Schorr G, Wirtz M, et al. Development and first validation of the shared decision-making questionnaire (SDM-Q). Patient Educ Couns 2006; 63: 319-27. doi:10.1016/j.pec.2006.04.012
22. Elwyn G, Tsulukidze M, Edwards A, et al. Using a 'talk' model of shared decision making to propose an observation-based measure: observer OPTION 5 Item. Patient Educ Couns 2013; 93: 265-71. doi:10.1016/j.pec.2013.08.005
23. McInnes DK, Brown JA, Hays RD, et al. Development and evaluation of CAHPS questions to assess the impact of health information technology on patient experiences with ambulatory care. Med Care 2012; 50 (Suppl): S11-19. doi:10.1097/MLR.0b013e3182610a50
24. Guttmacher AE, McGuire AL, Ponder B, et al. Personalized genomic information: preparing for the future of genetic medicine. Nat Rev Genet 2010; 11: 161-5. doi:10.1038/nrg2735
25. Lanie AD, Jayaratne TE, Sheldon JP, et al. Exploring the public understanding of basic genetic concepts. J Genet Couns 2004; 13: 305-20. doi:10.1023/B:JOGC.0000035524.66944.6d
26. McCarthy MI, Abecasis GR, Cardon LR, et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet 2008; 9: 356-69. doi:10.1038/nrg2344
27. Marsolo K, Spooner SA. Clinical genomics in the world of the electronic health record. Genet Med 2013; 15: 786-91. doi:10.1038/gim.2013.88
28. Kullo IJ, Ding K, Jouni H, et al. A genome-wide association study of red blood cell traits using the electronic medical record. PLoS One 2010; 5: pii: e13011. doi:10.1371/journal.pone.0013011
29. Kullo IJ, Ding K, Shameer K, et al. Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate. Am J Hum Genet 2011; 89: 131-8. doi:10.1016/j.ajhg.2011.05.019
30. Kullo IJ, Jarvik GP, Manolio TA, et al. Leveraging the electronic health record to implement genomic medicine. Genet Med 2013; 15: 270-1. doi:10.1038/gim.2012.131
31. Mikat-Stevens NA, Larson IA, Tarini BA. Primary-care providers' perceived barriers to integration of genetics services: a systematic review of the literature. Genet Med 2015; 17: 169-76. doi:10.1038/gim.2014.101
32. Ting HH, Brito JP, Montori VM. Shared decision making: science and action. Circ Cardiovasc Qual Outcomes 2014; 7: 323-7. doi:10.1161/CIRCOUTCOMES.113.000288
33. Wyatt KD, Branda ME, Anderson RT, et al. Peering into the black box: a meta-analysis of how clinicians use decision aids during clinical encounters. Implement Sci 2014; 9: 26. doi:10.1186/1748-5908-9-26
34. Kaphingst KA, McBride CM, Wade C, et al. Patients' understanding of and responses to multiplex genetic susceptibility test results. Genet Med 2012; 14: 681-7. doi:10.1038/gim.2012.22