Advertisement

Disclosing Genetic Risk for Coronary Heart Disease: Attitudes Toward Personal Information in Health Records

Published:January 03, 2017DOI:https://doi.org/10.1016/j.amepre.2016.11.005

      Introduction

      Incorporating genetic risk information in electronic health records (EHRs) will facilitate implementation of genomic medicine in clinical practice. However, little is known about patients’ attitudes toward incorporation of genetic risk information as a component of personal health information in EHRs. This study investigated whether disclosure of a genetic risk score (GRS) for coronary heart disease influences attitudes toward incorporation of personal health information including genetic risk in EHRs.

      Methods

      Participants aged 45–65 years with intermediate 10-year coronary heart disease risk were randomized to receive a conventional risk score (CRS) alone or with a GRS from a genetic counselor, followed by shared decision making with a physician using the same standard presentation and information templates for all study participants. The CRS and GRS were then incorporated into the EHR and made accessible to both patients and physicians. Baseline and post-disclosure surveys were completed to assess whether attitudes differed by GRS disclosure. Data were collected from 2013 to 2015 and analyzed in 2015–2016.

      Results

      GRS and CRS participants reported similar positive attitudes toward incorporation of genetic risk information in the EHR. Compared with CRS participants, participants with high GRS were more concerned about the confidentiality of genetic risk information (OR=3.67, 95% CI=1.29, 12.32, p=0.01). Post-disclosure, frequency of patient portal access was associated with positive attitudes.

      Conclusions

      Participants in this study of coronary heart disease risk disclosure overall had positive attitudes toward incorporation of genetic risk information in EHRs, although those who received genetic risk information had concerns about confidentiality.
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to American Journal of Preventive Medicine
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Collins F.
        • Varmus H.
        A new initiative on precision medicine.
        N Engl J Med. 2015; 372: 793-795https://doi.org/10.1056/NEJMp1500523
        • Kho A.N.
        • Rasmussen L.V.
        • Connolly J.J.
        • et al.
        Practical challenges in integrating genomic data into the electronic health record.
        Genet Med. 2013; 15: 772-778https://doi.org/10.1038/gim.2013.131
        • Fein R.
        Innovate or die!: Genomic data and the electronic health record (EHR).
        Appl Transl Genom. 2014; 3: 130-131https://doi.org/10.1016/j.atg.2014.09.007
        • Ganna A.
        • Magnusson P.K.
        • Pedersen N.L.
        • et al.
        Multilocus genetic risk scores for coronary heart disease prediction.
        Arterioscler Thromb Vasc Biol. 2013; 33: 2267-2272https://doi.org/10.1161/ATVBAHA.113.301218
        • Thanassoulis G.
        • Peloso G.M.
        • Pencina M.J.
        • et al.
        A genetic risk score is associated with incident cardiovascular disease and coronary artery calcium: the Framingham Heart Study.
        Circ Cardiovasc Genet. 2012; 5: 113-121https://doi.org/10.1161/CIRCGENETICS.111.961342
        • Tikkanen E.
        • Havulinna A.S.
        • Palotie A.
        • Salomaa V.
        • Ripatti S.
        Genetic risk prediction and a 2-stage risk screening strategy for coronary heart disease.
        Arterioscler Thromb Vasc Biol. 2013; 33: 2261-2266https://doi.org/10.1161/ATVBAHA.112.301120
        • Ripatti S.
        • Tikkanen E.
        • Orho-Melander M.
        • et al.
        A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses.
        Lancet. 2010; 376: 1393-1400https://doi.org/10.1016/S0140-6736(10)61267-6
        • Brautbar A.
        • Pompeii L.A.
        • Dehghan A.
        • et al.
        A genetic risk score based on direct associations with coronary heart disease improves coronary heart disease risk prediction in the Atherosclerosis Risk in Communities (ARIC), but not in the Rotterdam and Framingham Offspring, Studies.
        Atherosclerosis. 2012; 223: 421-426https://doi.org/10.1016/j.atherosclerosis.2012.05.035
        • Hughes M.F.
        • Saarela O.
        • Stritzke J.
        • et al.
        Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts.
        PLoS One. 2012; 7: e40922https://doi.org/10.1371/journal.pone.0040922
        • Samaan Z.
        • Schulze K.M.
        • Middleton C.
        • et al.
        South Asian Heart Risk Assessment (SAHARA): randomized controlled trial design and pilot study.
        JMIR Res Protoc. 2013; 2: e33https://doi.org/10.2196/resprot.2621
        • Schickedanz A.
        • Huang D.
        • Lopez A.
        • et al.
        Access, interest, and attitudes toward electronic communication for health care among patients in the medical safety net.
        J Gen Intern Med. 2013; 28: 914-920https://doi.org/10.1007/s11606-012-2329-5
        • Dimitropoulous L.
        • Patel V.
        • Scheffler S.A.
        • Posnack S.
        Public attitudes toward health information exchange: perceived benefits and concernss.
        Am J Manag Care. 2011; 17: SP111-SP116
        • Pushpangadan S.
        • Seckman C.
        Consumer perspective on personal health records: a review of the literature.
        Online J Nurs Inform. 2015; 19
      1. Markle Foundation. Attitudes of Americans Regarding Personal Health Records and Nationwide Electronic Health Information Exchange. Key Findings from Two Surveys of Americans Conducted by Public Opinion Strategies. Alexandria, VA. 2015. www.markle.org/sites/default/files/research_release_101105.pdf. Accessed November 22, 2016.

        • Patel V.
        • Hughes P.
        • Savage L.
        • Barker W.
        Individuals’ perceptions of the privacy and security of medical records and the sharing of medical records between health care providers.
        ONC Data Brief. 2015; (;27)
        • Thornewill J.
        • Dowling A.F.
        • Cox B.A.
        • Esterhay R.J.
        Information infrastructure for consumer health: a health information exchange stakeholder study.
        Am J Prev Med. 2011; 40: S123-S133https://doi.org/10.1016/j.amepre.2011.01.010
        • Kullo I.J.
        • Jouni H.
        • Austin E.E.
        • 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: 1181-1188https://doi.org/10.1161/CIRCULATIONAHA.115.020109
        • Wilson P.W.
        • D’Agostino R.B.
        • Levy D.
        • Belanger A.M.
        • Silbershatz H.
        • Kannel W.B.
        Prediction of coronary heart disease using risk factor categories.
        Circulation. 1998; 97: 1837-1847https://doi.org/10.1161/01.CIR.97.18.1837
        • Ding K.
        • Bailey K.R.
        • Kullo I.J.
        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: 66https://doi.org/10.1186/1471-2261-11-66
        • Harris P.A.
        • Taylor R.
        • Thielke R.
        • Payne J.
        • Gonzalez N.
        • Conde J.G.
        Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.
        J Biomed Inform. 2009; 42: 377-381https://doi.org/10.1016/j.jbi.2008.08.010
        • Beckjord E.B.
        • Rechis R.
        • Nutt S.
        • Shulman L.
        • Hesse B.W.
        What do people affected by cancer think about electronic health information exchange? Results from the 2010 LIVESTRONG Electronic Health Information Exchange Survey and the 2008 Health Information National Trends Survey.
        J Oncol Pract. 2011; 7: 237-241https://doi.org/10.1200/JOP.2011.000324
        • Agaku I.T.
        • Adisa A.O.
        • Ayo-Yusuf O.A.
        • Connolly G.N.
        Concern about security and privacy, and perceived control over collection and use of health information are related to withholding of health information from healthcare providers.
        J Am Med Inform Assoc. 2014; 21: 374-378https://doi.org/10.1136/amiajnl-2013-002079
        • Campos-Castillo C.
        • Anthony D.L.
        The double-edged sword of electronic health records: implications for patient disclosure.
        J Am Med Inform Assoc. 2015; 22: e130-e140
        • Wen K.Y.
        • Kreps G.
        • Zhu F.
        • Miller S.
        Consumers׳ perceptions about and use of the internet for personal health records and health information exchange: analysis of the 2007 Health Information National Trends Survey.
        J Med Internet Res. 2010; 12: e73https://doi.org/10.2196/jmir.1668
        • Platt J.
        • Kardia S.
        Public trust in health information sharing: implications for biobanking and electronic health record systems.
        J Pers Med. 2015; 5: 3-21https://doi.org/10.3390/jpm5010003
        • Patel V.N.
        • Dhopeshwarkar R.V.
        • Edwards A.
        • Barron Y.
        • Sparenborg J.
        • Kaushal R.
        Consumer support for health information exchange and personal health records: a regional health information organization survey.
        J Med Syst. 2012; 36: 1043-1052https://doi.org/10.1007/s10916-010-9566-0
        • Vodicka E.
        • Mejilla R.
        • Leveille S.G.
        • et al.
        Online access to doctors’ notes: patient concerns about privacy.
        J Med Internet Res. 2013; 15: e208https://doi.org/10.2196/jmir.2670
        • Brown M.
        • Moyer A.
        Predictors of awareness of clinical trials and feelings about the use of medical information for research in a nationally representative U.S. sample.
        Ethn Health. 2010; 15: 223-236https://doi.org/10.1080/13557851003624281
        • Singer E.
        • Antonucci T.
        • Van Hoewyk J.
        Racial and ethnic variations in knowledge and attitudes about genetic testing.
        Genet Test. 2004; 8: 31-43https://doi.org/10.1089/109065704323016012
        • Bates B.R.
        • Lynch J.A.
        • Bevan J.L.
        • Condit C.M.
        Warranted concerns, warranted outlooks: a focus group study of public understandings of genetic research.
        Soc Sci Med. 2005; 60: 331-344https://doi.org/10.1016/j.socscimed.2004.05.012
        • Paniagua C.
        • Taylor R.
        The cultural lens of genomics.
        Online J Issues Nurs. 2008; 13
        • Jarvik G.P.
        • Amendola L.M.
        • Berg J.S.
        • et al.
        Return of genomic results to research participants: the floor, the ceiling, and the choices in between.
        Am J Hum Genet. 2014; 94: 818-826https://doi.org/10.1016/j.ajhg.2014.04.009
        • Hazin R.
        • Brothers K.B.
        • Malin B.A.
        • et al.
        Ethical, legal, and social implications of incorporating genomic information into electronic health records.
        Genet Med. 2013; 15: 810-816https://doi.org/10.1038/gim.2013.117
        • Kullo I.J.
        • Jarvik G.P.
        • Manolio T.A.
        • Williams M.S.
        • Roden D.M.
        Leveraging the electronic health record to implement genomic medicine.
        Genet Med. 2013; 15: 270-271https://doi.org/10.1038/gim.2012.131
        • Welch B.M.
        • Kawamoto K.
        The need for clinical decision support integrated with the electronic health record for the clinical application of whole genome sequencing information.
        J Pers Med. 2013; 3: 306-325https://doi.org/10.3390/jpm3040306
        • Robinson C.L.
        • Jouni H.
        • Kruisselbrink T.M.
        • et al.
        Disclosing genetic risk for coronary heart disease: effects on perceived personal control and genetic counseling satisfaction.
        Clin Genet. 2016; 89: 251-257https://doi.org/10.1111/cge.12577
        • Hollands G.J.
        • French D.P.
        • Griffin S.J.
        • et al.
        The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis.
        BMJ. 2016; 352: i1102https://doi.org/10.1136/bmj.i1102
        • Ancker J.S.
        • Kern L.M.
        • Edwards A.
        • et al.
        Associations between healthcare quality and use of electronic health record functions in ambulatory care.
        J Am Med Inform Assoc. 2015; 22: 864-871https://doi.org/10.1093/jamia/ocv030
        • Kruse C.S.
        • Bolton K.
        • Freriks G.
        The effect of patient portals on quality outcomes and its implications to meaningful use: a systematic review.
        J Med Internet Res. 2015; 17: e44https://doi.org/10.2196/jmir.3171
        • Jackson S.L.
        • Mejilla R.
        • Darer J.D.
        • et al.
        Patients who share transparent visit notes with others: characteristics, risks, and benefits.
        J Med Internet Res. 2014; 16: e247https://doi.org/10.2196/jmir.3363
        • Ralston J.D.
        • Hirsch I.B.
        • Hoath J.
        • Mullen M.
        • Cheadle A.
        • Goldberg H.I.
        Web-based collaborative care for type 2 diabetes: a pilot randomized trial.
        Diabetes Care. 2009; 32: 234-239https://doi.org/10.2337/dc08-1220
        • Ross S.E.
        • Moore L.A.
        • Earnest M.A.
        • Wittevrongel L.
        • Lin C.T.
        Providing a web-based online medical record with electronic communication capabilities to patients with congestive heart failure: randomized trial.
        J Med Internet Res. 2004; 6: e12https://doi.org/10.2196/jmir.6.2.e12
        • Hood L.
        • Auffray C.
        Participatory medicine: a driving force for revolutionizing healthcare.
        Genome Med. 2013; 5: 110https://doi.org/10.1186/gm514
        • Milani L.
        • Leitsalu L.
        • Metspalu A.
        An epidemiological perspective of personalized medicine: the Estonian experience.
        J Intern Med. 2015; 277: 188-200https://doi.org/10.1111/joim.12320
        • Collins F.S.
        • Hudson K.L.
        • Briggs J.P.
        • Lauer M.S.
        PCORnet: turning a dream into reality.
        J Am Med Inform Assoc. 2014; 21: 576-577https://doi.org/10.1136/amiajnl-2014-002864