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Review article: Biomedical intelligence

Vol. 148 No. 0304 (2018)

Digital health: meeting the ethical and policy challenges

  • Effy Vayena
  • Tobias Haeusermann
  • Afua Adjekum
  • Alessandro Blasimme
DOI
https://doi.org/10.4414/smw.2018.14571
Cite this as:
Swiss Med Wkly. 2018;148:w14571
Published
16.01.2018

Summary

Digital health encompasses a wide range of novel digital technologies related to health and medicine. Such technologies rely on recent advances in the collection and analysis of ever increasing amounts of data from both patients and healthy citizens. Along with new opportunities, however, come new ethical and policy challenges. These range from the need to adapt current evidence-based standards, to issues of privacy, oversight, accountability and public trust as well as national and international data governance and management. This review illustrates key issues and challenges facing the rapidly unfolding digital health paradigm and reflects on the impact of big data in medical research and clinical practice both internationally and in Switzerland. It concludes by emphasising five conditions that will be crucial to fulfil in order to foster innovation and fair benefit sharing in digital health.

References

  1. U.S. Food and Drug Administration. [Internet]. Silver Spring: U.S. Food and Drug Administration; c1995-2017 [cited 2017 May 3]. U.S. Department of Health and Human Services; [about 2 screens]. Available from: https://www.fda.gov/medicaldevices/digitalhealth/#mobileapp.
  2. Adheretech.com. [Internet]. New York: AdhereTech Inc.; c2017 [cited 2017 July 21]. Available from: https://adheretech.com/
  3. Airstrip.com. [Internet]. Texas: Airstrip Technologies; c2017 [cited 2017 July 21]. Available from: http://www.airstrip.com/
  4. Food and Drug Administration. Section 5_510(k) Summary revised v3 [Internet]. Maryland: FDA; 2014 [cited 2017 July 21]. Available from: https://www.accessdata.fda.gov/cdrh_docs/pdf13/k133450.pdf
  5. Alivecor.com. [Internet]. San Francisco: AliveCor Inc.; c2017 [cited 2017 July 21]. Available from: https://www.alivecor.com/
  6. Food and Drug Administration. Section 5_510(k) Summary revised v3 [Internet]. Maryland: FDA; 2014 [cited 2017 July 21]. Available from: https://www.fda.gov/cdrh/510k/k122356.pdf
  7. Bluesparktechnologies.com. [Internet]. Ohio: Blue Spark Technologies Inc.; c2017 [cited 2017 July 21]. Available from: http://bluesparktechnologies.com/index.php/products-and-services/temptraq
  8. Food and Drug Administration. Section 5_510(k) Summary revised v3 [Internet]. Maryland: FDA; 2015 [cited 2017 July 21]. Available from: https://www.accessdata.fda.gov/cdrh_docs/pdf14/k143267.pdf
  9. Natural Cycles.com [Internet]. Stockholm: Natural Cycles [cited 2017 July 21]. Available from: https://www.naturalcycles.com/en
  10. Proteus.com. [Internet]. Redwood City: Proteus Digital Health; c2017 [cited 2017 July 21]. Available from: http://www.proteus.com/.
  11. Food and Drug Administration. Ingestible Event Marker [Internet]. Maryland: FDA; 2014 [cited 2017 July 21]. Available from: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn_template.cfm?id=k133263
  12. Butterflynetinc.com. [Internet]. New York: Butterfly Network Inc. [cited 2017 July 21]. Available from: https://www.butterflynetinc.com/
  13. Fitbit.com. [Internet]. San Francisco: Fitbit; c2017 [cited 2017 July 21]. Available from: https://www.fitbit.com/aria
  14. Happify.com. [Internet]. New York: Happify Inc.; c2017 [cited 2017 July 21]. Available from: https://my.happify.com/public/contact/
  15. Myfitnesspal.com. [Internet]. MyFitnessPal Inc. c2005-2017 [cited 2017 July 21]. Available from: https://www.myfitnesspal.com/.
  16. Elenko E, Speier A, Zohar D. A regulatory framework emerges for digital medicine. Nat Biotechnol. 2015;33(7):697–702. doi:.https://doi.org/10.1038/nbt.3284
  17. Eisenstein M. Miniature wireless sensors presage smart phone medicine. Nat Biotechnol. 2012;30(11):1013–4. doi:.https://doi.org/10.1038/nbt1112-1013
  18. Flahault A, Geissbuhler A, Guessous I, Guérin P, Bolon I, Salathé M, et al. Precision global health in the digital age. Swiss Med Wkly. 2017;147:w14423.
  19. Salathé M, Bengtsson L, Bodnar TJ, Brewer DD, Brownstein JS, Buckee C, et al. Digital epidemiology. PLOS Comput Biol. 2012;8(7):e1002616. doi:.https://doi.org/10.1371/journal.pcbi.1002616
  20. Vayena E, Dzenowagis J. Langfeld M. [Internet]. Geneva: World Health Organization; c1948-2017 [cited 2017 May 3]. U.S. United Nations; [about 1 screen]. Available from: http://www.who.int/ehealth/resources/ecosystem/en/.
  21. Groves P, Kayyali B, Knott D, Van Kuiken S. The ‘big data’revolution in healthcare. New York: McKinsey & Company; 2013.
  22. Weber GM, Mandl KD, Kohane IS. Finding the missing link for big biomedical data. JAMA. 2014;311(24):2479–80. doi:.https://doi.org/10.1001/jama.2014.4228
  23. Blasimme A. Healthcare meets big data: the science and politics of precision medicine. In: Blanchard A, Strand R, editors. Social, ethical and economic aspects of cancer biomarkers. Kokstad: Megaloceros Press; 2017. p. 95-110.
  24. Vayena E, Blasimme A. Biomedical big data: new models of control over access, use and governance. J Bioeth Inq. 2017;14(4):501–13. doi:.https://doi.org/10.1007/s11673-017-9809-6
  25. Vayena E, Gasser U, Wood A, O’Brian DR, Altman M. Elements of a new ethical framework for big data research. Wash Lee Law Rev. 2016;72 (3):420–41. http://lawreview.journals.wlu.io/elements-of-a-new-ethical-framework-for-big-data-research/
  26. US Department of Veterans Affairs [Internet]. Washington DC: The Department; c1930-2017 [cited 2017 Jul 20]. Office of Public and Intergovernmental Affairs; [about 2 screens]. Available from: https://www.va.gov/opa/pressrel/pressrelease.cfm?id=2806
  27. Wojcicki A. Power of One Million. 2015 June 18 [cited 2017 Jul 20]. In: 23andMe. Blog [Internet]. Mountain View: 23andMe, Inc. c2007-2017. [about 2 screens]. Available from: https://blog.23andme.com/news/one-in-a-million/.
  28. Kaiser Permanente [Internet]. Oakland: Kaiser Foundation Health Plan, Inc.; c2017 [cited 2017 Jul 20]. [about 2 screens]. Available from: https://share.kaiserpermanente.org/article/kaiser-permanente-launches-research-biobank-aims-to-transform-health/.
  29. Khoury MJ, Evans JP. A public health perspective on a national precision medicine cohort: balancing long-term knowledge generation with early health benefit. JAMA. 2015;313(21):2117–8. doi:.https://doi.org/10.1001/jama.2015.3382
  30. Blasimme A, Vayena E. “Tailored-to-you” - public engagement and the political legitimation of precision medicine. Perspect Biol Med. 2016;59(2):172–88. doi:.https://doi.org/10.1353/pbm.2017.0002
  31. Khoury MJ, Iademarco MF, Riley WT. Precision public health for the era of precision medicine. Am J Prev Med. 2016;50(3):398–401. doi:.https://doi.org/10.1016/j.amepre.2015.08.031
  32. Rubin R. Precision medicine: the future or simply politics? JAMA. 2015;313(11):1089–91. doi:.https://doi.org/10.1001/jama.2015.0957
  33. Coote JH, Joyner MJ. Is precision medicine the route to a healthy world? Lancet. 2015;385(9978):1617. doi:.https://doi.org/10.1016/S0140-6736(15)60786-3
  34. Jarow JP, LaVange L, Woodcock J. Multidimensional evidence generation and FDA regulatory decision making: defining and using “real-world” data. JAMA. 2017;318(8):703–4. doi:.https://doi.org/10.1001/jama.2017.9991
  35. Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793–5. doi:.https://doi.org/10.1056/NEJMp1500523
  36. Khoury MJ, Evans JP. A public health perspective on a national precision medicine cohort: balancing long-term knowledge generation with early health benefit. JAMA. 2015;313(21):2117–8. doi:.https://doi.org/10.1001/jama.2015.3382
  37. Khoury MJ, Iademarco MF, Riley WT. Precision public health for the era of precision medicine. Am J Prev Med. 2016;50(3):398–401. doi:.https://doi.org/10.1016/j.amepre.2015.08.031
  38. Flahault A, Geissbuhler A, Guessous I, Guérin P, Bolon I, Salathé M, et al. Precision global health in the digital age. Swiss Med Wkly. 2017;147:w14423.
  39. Sankar PL, Parker LS. The Precision Medicine Initiative’s All of Us Research Program: an agenda for research on its ethical, legal, and social issues. Genet Med. 2017;19(7):743–50. doi:.https://doi.org/10.1038/gim.2016.183
  40. Vayena E, Salathé M, Madoff LC, Brownstein JS. Ethical challenges of big data in public health. PLOS Comput Biol. 2015;11(2):e1003904. doi:.https://doi.org/10.1371/journal.pcbi.1003904
  41. Rothwell PM. External validity of randomised controlled trials: “to whom do the results of this trial apply?”. Lancet. 2005;365(9453):82–93. doi:.https://doi.org/10.1016/S0140-6736(04)17670-8
  42. Frueh FW. Back to the future: why randomized controlled trials cannot be the answer to pharmacogenomics and personalized medicine. Pharmacogenomics. 2009;10(7):1077–81. doi:.https://doi.org/10.2217/pgs.09.62
  43. LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521(7553):436–44. doi:.https://doi.org/10.1038/nature14539
  44. Anderson C. The end of theory: the data deluge makes the scientific method obsolete. WIRED [Internet]. 2008 Jun [cited 2017 May 8]; [about 3 p.]. Available from: https://www.wired.com/2008/06/pb-theory/.
  45. Pigliucci M. The end of theory in science? EMBO Rep. 2009;10(6):534. doi:.https://doi.org/10.1038/embor.2009.111
  46. Price WN. Black-Box Medicine. Harv. J. L. & Tech. 2015;28(2):419.
  47. Mazzocchi F. Could Big Data be the end of theory in science? A few remarks on the epistemology of data-driven science. EMBO Rep. 2015;16(10):1250–5. doi:.https://doi.org/10.15252/embr.201541001
  48. Khoury MJ, Ioannidis JPA. Big data meets public health. Science. 2014;346(6213):1054–5. doi:.https://doi.org/10.1126/science.aaa2709
  49. Vayena E, Mastroianni A, Kahn J. Caught in the web: informed consent for online health research. Sci Transl Med. 2013;5(173):173fs6. doi:.https://doi.org/10.1126/scitranslmed.3004798
  50. Gayle D, Topping A, Sample I, Marsh S, Dodd V. NHS seeks to recover from global cyber-attack as security concerns resurface. The Guardian 13 May 2017. Available from https://www.theguardian.com/society/2017/may/12/hospitals-across-england-hit-by-large-scale-cyber-attack
  51. Information Commissioner’s Office [Internet]. London: Information Commissioner’s Office; c2017 [cited 2017 Jul 20]; [about 3 screens]. Available from: https://ico.org.uk/action-weve-taken/data-security-incident-trends/
  52. Tasioulas J, Vayena E. The place of human rights and the common good in global health policy. Theor Med Bioeth. 2016;37(4):365–82. doi:.https://doi.org/10.1007/s11017-016-9372-x
  53. Department of Health. Freeman G [Internet]. London: Gov.UK; c2016 [cited 2017 Jul 20]; Available from: https://www.gov.uk/government/speeches/review-of-health-and-care-data-security-and-consent
  54. Carter P, Laurie GT, Dixon-Woods M. The social licence for research: why care.data ran into trouble. J Med Ethics. 2015;41(5):404–9. doi:.https://doi.org/10.1136/medethics-2014-102374
  55. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005;330(7494):765. doi:.https://doi.org/10.1136/bmj.38398.500764.8F
  56. Hsu W, Markey MK, Wang MD. Biomedical imaging informatics in the era of precision medicine: progress, challenges, and opportunities. J Am Med Inform Assoc. 2013;20(6):1010–3. doi:.https://doi.org/10.1136/amiajnl-2013-002315
  57. Yang GZ, Cambias J, Cleary K, Daimler E, Drake J, Dupont PE, et al. Medical robotics - regulatory, ethical, and legal considerations for increasing levels of autonomy. Sci Robot. 2017;2(4):eaam8638. doi:.https://doi.org/10.1126/scirobotics.aam8638
  58. Elenko E, Underwood L, Zohar D. Defining digital medicine. Nat Biotechnol. 2015;33(5):456–61. doi:.https://doi.org/10.1038/nbt.3222
  59. Elenko E, Speier A, Zohar D. A regulatory framework emerges for digital medicine. Nat Biotechnol. 2015;33(7):697–702. doi:.https://doi.org/10.1038/nbt.3284
  60. World Health Organization. Global diffusion of eHealth: making universal health coverage achievable. Report of the third global survey on eHealth [Internet]. Geneva: WHO Document Production Services; 2016 [cited 2017 Jul 20]. Available from: http://apps.who.int/iris/bitstream/10665/252529/1/9789241511780-eng.pdf?ua=1.
  61. Organization of Economic Cooperation and Development. Recommendations of OECD Council on Health Data Governance [cited 21 July 2017] Available from http://www.oecd.org/health/health-systems/Recommendation-of-OECD-Council-on-Health-Data-Governance-Booklet.pdf
  62. General Data Protection Regulation [Internet]. Brussels: European Union; 2016 [cited 2017 July 21]. Available from: http://ec.europa.eu/justice/data-protection/reform/files/regulation_oj_en.pdf
  63. e-health-suisse.ch. [Internet]. Bern: eHealth Suisse; c2007-2017 [cited 2017 Jun 1]. Kompetenz- und Koordinationsstelle von Bund und Kantonen; [about 2 screens]. Available from: https://www.e-health-suisse.ch/elektronisches-patientendossier.html [available in German, French and Italian only].
  64. Rosemberg A, Schmid A, Plaut O. MonDossierMedical.ch - the personal health record for every Geneva citizen. Stud Health Technol Inform. 2016;225:700–2. doi:.https://doi.org/10.3233/978-1-61499-658-3-700
  65. Gnaegi A, Michelet C. Dossier patient partagé Infomed, qu’en pensent les médecins. Swiss Medical Informatics. 2016;32. doi:.https://doi.org/10.4414/smi.32.361
  66. Lovis C, Looser H, Schmid A, Wagner J, Wyss S. eHealth in Switzerland - building consensus, awareness and architecture. Stud Health Technol Inform. 2011;165:57–62. doi:.https://doi.org/10.3233/978-1-60750-735-2-57
  67. De Pietro C, Camenzind P, Sturny I, Crivelli L, Edwards-Garavoglia S, Spranger A, et al. Switzerland: health system review. Health Syst Transit. 2015;17(4):1–288, xix.
  68. Dossier éIectronique du patient: la Suisse romande avance en ordre disperse [Electronic patient records: Switzerland is moving forward haphazardly]. Rev Med Suisse. 2015;11(499):2411. Article in French.
  69. Gall W, Aly AF, Sojer R, Spahni S, Ammenwerth E. The national e-medication approaches in Germany, Switzerland and Austria: A structured comparison. Int J Med Inform. 2016;93:14–25. doi:.https://doi.org/10.1016/j.ijmedinf.2016.05.009
  70. Grady C, Eckstein L, Berkman B, Brock D, Cook-Deegan R, Fullerton SM, et al. Broad consent for research with biological samples: Workshop conclusions. Am J Bioeth. 2015;15(9):34–42. doi:.https://doi.org/10.1080/15265161.2015.1062162
  71. Helgesson G. In defense of broad consent. Camb Q Healthc Ethics. 2012;21(1):40–50. doi:.https://doi.org/10.1017/S096318011100048X
  72. Hofmann B. Broadening consent--and diluting ethics? J Med Ethics. 2009;35(2):125–9. doi:.https://doi.org/10.1136/jme.2008.024851
  73. Sheehan M. Can broad consent be informed consent? Public Health Ethics. 2011;4(3):226–35. Published online August 3, 2011. doi:.https://doi.org/10.1093/phe/phr020
  74. Vayena E, Gasser U. Between openness and privacy in genomics. PLoS Med. 2016;13(1):e1001937. doi:.https://doi.org/10.1371/journal.pmed.1001937
  75. Swiss Personalized Health Network [Internet]. Bern: Swiss Academy of Medical Sciences (SAMS); c1943-2017 [cited 2017 June 1]. Swiss Academy of Medical Sciences; [about 2 screens]. Available from: http://www.samw.ch/en/Projects/SPHN.html.
  76. Haeusermann T, Greshake B, Blasimme A, Irdam D, Richards M, Vayena E. Open sharing of genomic data: Who does it and why? PLoS One. 2017;12(5):e0177158. doi:.https://doi.org/10.1371/journal.pone.0177158
  77. Blasimme A, Vayena E. Becoming partners, retaining autonomy: ethical considerations on the development of precision medicine. BMC Med Ethics. 2016;17(1):67. doi:.https://doi.org/10.1186/s12910-016-0149-6
  78. Walker DM, Sieck CJ, Menser T, Huerta TR, Scheck McAlearney A. Information technology to support patient engagement: where do we stand and where can we go? J Am Med Inform Assoc. 2017;24(6):1088–94; Epub ahead of print. doi:.https://doi.org/10.1093/jamia/ocx043
  79. Moen A, Hackl WO, Hofdijk J, Van Gemert-Pijnen L, Ammenwerth E, Nykänen P, et al. eHealth in Europe - status and challenges. Yearb Med Inform. 2013;8:59–63.
  80. Patil S, Lu H, Saunders CL, Potoglou D, Robinson N. Public preferences for electronic health data storage, access, and sharing - evidence from a pan-European survey. J Am Med Inform Assoc. 2016;23(6):1096–106. doi:.https://doi.org/10.1093/jamia/ocw012
  81. Leuthold M. Patients as partners for improving safety. World Hosp Health Serv. 2014;50(3):20–2.
  82. Tripathi M, Delano D, Lund B, Rudolph L. Engaging patients for health information exchange. Health Aff (Millwood). 2009;28(2):435–43. doi:.https://doi.org/10.1377/hlthaff.28.2.435
  83. Mantwill S, Monestel-Umaña S, Schulz PJ. The relationship between health literacy and health disparities: a systematic review. PLoS One. 2015;10(12):e0145455. doi:.https://doi.org/10.1371/journal.pone.0145455
  84. Nohr C, Wong MC, Turner P, Almond H, Parv L, Gilstad H, et al. Citizens’ access to their digital health data in eleven countries - a comparative study. Stud Health Technol Inform. 2016;228:685–9. doi:.https://doi.org/10.3233/978-1-61499-678-1-685
  85. Sak G, Rothenfluh F, Schulz PJ. Assessing the predictive power of psychological empowerment and health literacy for older patients’ participation in health care: a cross-sectional population-based study. BMC Geriatr. 2017;17(1):59. doi:.https://doi.org/10.1186/s12877-017-0448-x
  86. Romano MF, Sardella MV, Alboni F, Russo L, Mariotti R, Nicastro I, et al. Is the digital divide an obstacle to e-health? An analysis of the situation in Europe and in Italy. Telemed J E Health. 2015;21(1):24–35. doi:.https://doi.org/10.1089/tmj.2014.0010
  87. Feldman HH, Haas M, Gandy S, Schoepp DD, Cross AJ, Mayeux R, et al.; One Mind for Research and the New York Academy of Sciences. Alzheimer’s disease research and development: a call for a new research roadmap. Ann N Y Acad Sci. 2014;1313(1):1–16. doi:.https://doi.org/10.1111/nyas.12424
  88. Salter H, Holland R. Biomarkers: refining diagnosis and expediting drug development - reality, aspiration and the role of open innovation. J Intern Med. 2014;276(3):215–28. doi:.https://doi.org/10.1111/joim.12234
  89. Leyens L, Reumann M, Malats N, Brand A. Use of big data for drug development and for public and personal health and care. Genet Epidemiol. 2017;41(1):51–60. doi:.https://doi.org/10.1002/gepi.22012
  90. Chataway J, Fry C, Marjanovic S, Yaqub O. Public-private collaborations and partnerships in stratified medicine: making sense of new interactions. N Biotechnol. 2012;29(6):732–40. doi:.https://doi.org/10.1016/j.nbt.2012.03.006
  91. digitalswitzerland.com. [Internet]. Zürich: digitalswitzerland; c2015 [cited 2017 June 1]. Available from: http://digitalswitzerland.com.
  92. opendata.ch. [Internet]. Zurich: Verein Opendata.ch, the Swiss Chapter of the Open Knowledge Foundation; c2012 [cited 2017 June 1]. Available from: https://opendata.ch.
  93. www.midata.coop. [Internet]. Zürich: MIDATA Genossenschaft; c2017 [cited 2017 Jul 20]. Available from: https://www.midata.coop/.
  94. Hafen E, Kossmann D, Brand A. Health data cooperatives - citizen empowerment. Methods Inf Med. 2014;53(2):82–6. doi:.https://doi.org/10.3414/ME13-02-0051
  95. Hafen E. Midata Cooperatives - Citizen-Controlled Use of Health Data Is a Pre-Requiste for Big Data Analysis, Economic Success and a Democratization of the Personal Data Economy. Tropical Medicine & International Health [Internet]. 2015 Sep [cited 2017 July 20]; 20 (Supplement 1):129. [about 1 p.] Available from: https://insights.ovid.com/tropical-medicine-international-health/tmih/2015/09/001/midata-cooperatives-citizen-controlled-use-health/313/00060771.

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