The Ethics and Politics of Infrastructures: Creating the Conditions of Possibility for Big Data in Medicine

Law, Governance and Technology Series

Volumn 29, Issue , 2016, Pages 397-427

  Hogle, Linda F ^a  

^a UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

Author keywords

Health Information Exchange; Health Information Technology; Personal Health Information; Precision Medicine; Protected Health Information

Indexed keywords

EID: 85126015229     PISSN: 23521902     EISSN: 23521910     Source Type: Book Series    
DOI: 10.1007/978-3-319-33525-4_17     Document Type: Chapter

References (64)

1. Adler-Milstein, J. 2013. Operational health information exchanges show substantial growth but funding remains a concern. Health Affairs 32: 1486–1492.
2. Adler-Milstein, J., and A. Jha. 2013. Health care’s “Big Data” challenge. American Journal of Managed Care 19(7): 537–538.
3. Agency for Healthcare Research and Quality. 2014. A Robust Health Data Infrastructure. Report No. 14-0041-EF prepared by JASON. McLean, VA.
4. Avorn, J., and S. Kesselheim. 2015. The 21st C Cures act: Will it take us back in time? New England Journal of Medicine 372: 2473–2475. doi:10.1056/NEJMp1506964.
5. Barocas, S., and H. Nissenbaum. 2014. Big data’s end run around anonymity and informed consent. In Privacy, big data and the public good: Frameworks for engagement, ed. J. Lane, V. Stodden, S. Bender, and H. Nissenbaum, 44–75. New York: Cambridge University Press.
6. Bayer, R., and S. Galea. 2015. Public health in the precision-medicine era. New England Journal of Medicine 373(6): 499–501.
7. Blumenthal, D. 2010. Launching HITECH. New England Journal of Medicine 362(5): 382–385.
8. Brailer, D. 2009. Presidential leadership and health information technology. Health Affairs 28(2): w392–w398.
9. Charles, D., M. Gabriel, and M. Furukawa. 2014. Adoption of electronic health record systems among U.S. non-federal acute care hospitals: 2008–2013 Office of the National Coordinator for Health Information Technology, Data Brief No. 16. Available at http://www.healthit.gov/sites/default/files/oncdatabrief16.pdf
10. Cohen, G., R. Amarasingham, A. Shah, B. Xie, and B. Lo. 2014. The legal and ethical concerns that rise from using complex predictive analytics in health care. Health Affairs 33(7): 1139–1147.
11. Collins, F. 2004. The case for a US prospective cohort study of genes and environment. Nature 429: 475–477.
12. Denny, J., M. Ritchie, D. Crawford, et al. 2010. Identification of genomic predictors of atrioven-tricular conduction: using electronic medical records as a tool for genome science. Circulation 122: 2016–2021.
13. Edwards, P. 2003. Infrastructure and modernity: Force, time, and social organization. In The history of sociotechnical systems. Modernity and technology, ed. T.J. Misa, P. Brey, and A. Feenberg, 185–226. Cambridge, MA: The MIT Press.
14. Edwards, P., G. Bowker, S. Jackson, and R. Williams. 2009. Introduction: an agenda for infrastructure studies. Journal of the Association for Information Systems 10(5): 364–374.
15. Evans, B. 2009. Congress’ new infrastructural model of medical privacy. Notre Dame Law Review 84(3): 586–654.
16. Executive Office of the President. 2014. Big data: Seizing opportunities, preserving values. Available online at https://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_ may_1_2014.pdf
17. Findlay, S. 2015. The FDA’s sentinel initiative. Health Policy Briefs. Available at: http://www.healthaffairs.org/healthpolicybriefs/brief.php?brief_id=139
18. Fredrikson, M., E. Lantz, S. Jha, D. Page, and T. Ristenpart. 2014. Privacy in pharmacogenetics: And end-to-end case study of Warfarin dosing. Proceedings of the 23rd USENIX symposium. Available at https://www.usenix.org/system/files/conference/usenixsecurity14/sec14-paper-fredrikson-privacy.pdf
19. Gottesman, O., H. Kuivaniemi, G. Tromp, W.A. Faucett, et al. 2013. Electronic medical records and genomics network: Past, present and future. Genetics in Medicine 15(10): 761–771.
20. Grossman, C., B. Powers, and J.M. McGinnis (eds.). 2011. Digital infrastructure for the learning healthcare system. Washington, DC: National Academies Press.
21. Gymrek, L., et al. 2013. Identifying personal genomes by surname inference. Science 339: 321– 324.
22. Halamka, J. 2014. Early experiences with big data at an academic medical center. Health Affairs 33(7): 1132–1138.
23. Hoffman, Sharona, and Andy Podgurski. 2013. The use and misuse of biomedical data: Is bigger really better? American Journal of Law & Medicine 39: 497–546.
24. Hogle, L. forthcoming. Big data assemblages in healthcare. BioSocieties 11(3).
25. Hood, L., and S. Friend. 2011. Predictive, personalized, preventive, participatory (P4) cancer medicine. Nature Reviews Clinical Oncology 8(3): 184–187.
26. Jasanoff, S. 2005. Designs on nature: Science and democracy in Europe and the United States. Princeton NJ: Princeton University Press.
27. Kahn, Howie. 2013. Who really owns your personal data? http://www.details.com/culture-trends/critical-eye/201305/sharing-biodata-on-apps-and-devices. Accessed 25 Aug 2013.
28. Kaye, J. 2015. The tension between data sharing and the protection of privacy in genomics research. In Ethics, law and governance of biobanking, ed. D. Mascalzoni. New York: Springer.
29. Kho, A.N., M.G. Hayes, L. Rasmussen-Torvik, et al. 2012. Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study. Journal of the American Medical Informatics Association 19: 212–218.
30. Kitchin, R. 2014. Big data new epistemologies and paradigm shifts. Big Data & Society 1(1): 1–12. doi:10.1177/2053951714528481. Accessed 20 June 2015.
31. Kohane, I. 2011. Using electronic health records to drive discovery in disease genomics. Nature Reviews Genetics 12: 417–428.
32. Law, J., and W. Bijker (eds.). 1992. Shaping technology/building society: Studies in sociotechnical change. Cambridge, MA: MIT Press.
33. Loukides, G., J. Denny, and B. Malin. 2010. The disclosure of diagnosis codes can breach research participants’ privacy. Journal of the American Medical Informatics Association 17: 322–327.
34. Lupton, D. 2014. The commodification of patient opinion: The digital patient experience economy in the age of big data. Sociology of Health and Illness 36(6): 856–869.
35. Lyon, D. 2003. Surveillance as social sorting: Privacy, risk and digital discrimination. New York: Routledge.
36. Malin, B., D. Karp, and R. Scheuermann. 2010. Technical and policy approaches to balancing patient privacy and data sharing in clinical and translational research. Journal of Investigational Medicine 58(1): 11–18.
37. McGuire, A.L., M. Basford, L.G. Dressler, et al. 2011. Ethical and practical challenges of sharing data from genome-wide association studies: The eMERGE Consortium experience. Genome Research 21: 1001–1007.
38. Mittelstadt, B.D., and L. Floridi. 2016. The ethics of big data: Current and foreseeable issues in biomedical contexts. Science and Engineering Ethics 22(2): 303–341. doi:10.1007/s11948-015-9652-2.
39. Mittelstadt, B., N.B. Fairweather, M. Shaw, and N. McBride. 2014. The ethical implications of personal health monitoring. International Journal of Technoethics 5(2): 37–60.
40. Murdoch, T., and A. Detsky. 2013. The inevitable application of big data to health care. Journal of the American Medical Association 309(13): 1351–1352.
41. National Research Council Committee on a Framework for Developing a New Taxonomy of Disease. 2011. Toward precision medicine: Building a knowledge network for biomedical research and a new taxonomy of disease. Washington, DC: National Academies Press.
42. Neff, G. 2013. Why big data won’t cure us. Big Data 1(3): 117–123.
43. November, J. 2012. Biomedical computing: Digitizing life in the United States. Baltimore: Johns Hopkins University Press.
44. Office of the National Coordinator for Health IT. 2014. Report to congress: Update on the adoption of health information technology and related efforts to facilitate the electronic use and exchange of health information. Washington, DC. Available at https://www.healthit.gov/sites/default/files/rtc_adoption_and_exchange9302014.pdf.
45. Office of the National Coordinator for Health IT. 2015a. Connecting health and care for the nation: A shared interoperability roadmap. Available online at http://www.healthit.gov/sites/default/files/nationwide-interoperability-roadmap-draft-version-1.0.pdf
46. Office of the National Coordinator for Health IT. 2015b. Federal Health IT Strategic Plan 2015– 2020. Available online at http://www.healthit.gov/sites/default/files/federal-healthIT-strategic-plan-2014.pdf
47. Pasquale, F., and T. Ragone. 2014. Protecting health privacy in an era of big data processing and cloud computing. Stanford Technology Law Review 17: 595–653.
48. President’s Council of Advisors on Science and Technology (PCAST). 2014. Big data and privacy: A technological perspective. Report to the President (May). Available online at https://www.whitehouse.gov/sites/default/files/microsites/ostp/PCAST/pcast_ big_data_and_privacy_-_may_2014.pdf
49. Ranck, J. 2014. How connected health, public-private cooperation, and big data can revolutionize health care. Forbes. http://www.forbes.com/sites/benkerschberg/2012/07/06/how-connected-health-public-private-cooperation-and-big-data-can-revolutionize-health-care/. Accessed 25 July 2014.
50. Redhead, S. 2009. The Health Information Technology and Economic and Clinical Health (HITECH Act). Congressional Research Service, Report No. R40101.
51. Ricciardi, L., et al. 2013. A national action plan to support consumer engagement via e-health. Health Affairs 32(2): 376–384.
52. Roski, J., G.W. Bo-Linn, and T.A. Andrews. 2014. Creating value in health care through big data: Opportunities and policy implications. Health Affairs 33(7): 1115–1122.
53. Saha, K., and L.F. Hogle. 2014. Allying with donors to link health and medical information with stem cell lines can advance disease modeling while enhancing data access. Cell Stem Cell 14(1): 559–560.
54. Schadt, E. 2012. The changing privacy landscape in the era of big data. Molecular Systems Biology 8(1): 612–617.
55. Singer, N. 2014. When a health plan knows how you shop. New York Times, June 28. Available at http://www.nytimes.com/2014/06/29/technology/when-a-health-plan-knows-how-you-shop.html
56. Star, S.L., and K. Ruhleder. 1996. Steps toward an ecology of infrastructure: Design and access for large information spaces. Information Systems Research 7(1): 111–134.
57. Stevens, H. 2013. Life out of sequence: A data-driven history of bioinformatics. Chicago: University of Chicago Press.
58. Stevens, H. forthcoming. Hadooping the genome: The impact of big data tools on biology. BioSocieties 11(3).
59. Sulzicki, M., D. Atkins, C. Schilling, et al. 2012. A model to predict risk of non-adherence to medications highlighted in CMS star-ratings. Value in Health 15: A164 (PRM30).
60. Terry, N. 2012. Protecting patient privacy in the age of big data. Indiana University Legal Studies Research Paper 2013–04.
61. Thune, J., L. Alexander, P. Roberts, R. Burr, and M. Enzi. 2015. Where is HITECH’s $35 billion dollar investment going? Health Affairs Blog, March 4. Available at: http://healthaffairs.org/blog/2015/03/04/where-is-hitechs-35-billion-dollar-investment-going/. Accessed 20 July 2015.
62. Vaidya, M. 2014. As funds to sync health records dwindle, research could suffer. Nature Biotechnology 20(11): 1225–1226.
63. Weiss, J., S. Natarajan, P. Paissig, C. McCarthy, and D. Page. 2012. Machine learning for personalized medicine: Predicting primary MI from electronic medical records. AI Magazine 33(4): 33–45.
64. Xu, H., et al. 2011. Extracting and integrating data from entire electronic health records for detecting colorectal cancer cases. AMIA Annual Symposium Proceedings 2011: 1564–1572.