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

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The Ethics of Biomedical Big Data

Part of the book series: Law, Governance and Technology Series ((LGTS,volume 29))

Abstract

The vision of creating a more comprehensive understanding of human health and disease calls for collecting ever-greater volumes of information about individuals, in continuous, real-time streams, and from sources outside of the clinic. Such data is heterogenous and high-dimensional, requiring the use of big data analytics. Big data has been granted considerable perceived authority to solve problems in healthcare and biomedicine. At the same time, there is potential for tremendous impact on social and political life more broadly. For this reason, it is important to elucidate less-visible ethical issues related to the infrastructures being built to support big data projects in biomedical science and clinical medicine. The constellation of changes in laws, institutional arrangements, and new forms of expertise being brought together are reordering relations among patients, clinical and family caregivers, researchers and payers, with potentially long-term effects. For example, conventional concepts of autonomy are challenged when data is collected ubiquitously and passively, and notions of expertise are provoked when ‘non-medical’ experts (including patients themselves) participate more directly in processes of defining health, illness, and care. In the process, the distinction between research and clinical activities (which have been conceptually kept apart for decades) becomes blurred, and the definition of ‘research subject’ is confounded.

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Notes

  1. 1.

    The report followed much earlier similar recommendations from NIH chief Frances Collins developed at the turn of the twenty-first century (Collins 2004). Committee members authoring the report included genome scientists, clinician-researchers in academic medicine, and representatives from Pfizer and a former scientist for Bristol-Meyers Squibb.

  2. 2.

    My data comes from field notes and interviews at multiple conferences focusing on big data and biomedicine since 2013, as well as content analyses of policy documents.

  3. 3.

    Recent national initiatives to facilitate such large-scale research include, eMERGE (an NIH-sponsored consortium to link data from DNA biorepositories with electronic medical records) and dbGAP (NIH-sponsored database on genotypes and phenotypes) (McGuire etal. 2011).

  4. 4.

    HIMSS remains a powerful lobbying force and currently has 57,000 individual members internationally, plus more than 615 corporate members and 400 not-for-profit partner organizations.

  5. 5.

    Electronic health records should be distinguished from medical records. The latter is essentially the entirety of what would appear in a patient’s paper chart from a single or primary care provider, including physician notations, tests and treatment history. The former is being used by the ONC and refers to all information from all care providers.

  6. 6.

    Pub.L. 111–5.

  7. 7.

    The formal name is the Patient Protection and Affordable Care Act, PL 111–148 (2010), more commonly referred to as the Affordable Care Act (or colloquially, “Obamacare”). It is important to distinguish that unlike many European countries, Americans are still provided health care insurance through their employers, through private exchanges, rather than being provided to all by the State, with the exception of the elderly, poor, and some children. This Act was an effort to provide more Americans with coverage.

  8. 8.

    Section 3025 of the Affordable Care Act added section 1886(q) to the Social Security Act establishing the Hospital Readmissions Reduction Program.

  9. 9.

    Craig Schilling (developer of Drug Adherence IndexTM Optum) presentation to Medical Information World, Boston, May 2014. As Schilling explained, it is too costly to target all patients for compliance; the algorithm helps to identify which potential problem patients to target. The ACA quality measures are on a star rating, and as Schilling put it in his presentation: “at the end of the day, it’s all about the star rating.”

  10. 10.

    The Office of the National Coordinator and the White House are encouraging IT developers to develop standards for automatically uploading new data, and for stimulating new markets around this activity (ONC 2015a; Ricciardi etal. 2013).

  11. 11.

    The JASON Report cited ineffectiveness of the Federal Advisory Committees created to assist with coordination (the Health IT Policy Committee and the Health IT Standards Committee, which report to the ONC) (Agency for Healthcare Research and Quality 2014). Notably, a proposed new law would replace existing committees with a new entity comprised of industry representatives (see Sect. 7).

  12. 12.

    Health Insurance Portability and Accountability Act of 1996 Public Law 104–191, Sub. F, Sec. 264.

  13. 13.

    Health information is defined as “any information, whether oral or recorded in any form or medium, that (A) is created or received by a health care provider, health plan, public health authority, employer, life insurer, school or university, or health care clearinghouse; and (B) relates to the past, present, or future physical or mental health or condition of an individual, the provision of health care to an individual, or the past, present, or future payment for the provision of health care to an individual.” Personally identifiable information is that which can be directly tied to an individual, including name, geographic information smaller than a state, social security number, birth and death dates, phone and fax numbers, device serial numbers, and biometric identifiers (including voice print and photos) (45.CFR 160.103). “Business Associate” is defined in 45 CFR 160, subpart A and includes an entity which “…claims processing or administration, data analysis, processing or administration, utilization review, quality assurance, patient safety activities, billing, benefit management, practice management and repricing, or provides legal, actuarial, accounting, consulting, data aggregation, management, administrative, accreditation, or financial services to a covered entity or for an organized health care arrangement…" A summary of the privacy rule can be found at http://www.hhs.gov/ocr/privacy/hipaa/understanding/summary/index.html

  14. 14.

    Id at 164.508 ‘uses and disclosures for which an authorization is required.’

  15. 15.

    https://www.cms.gov/Newsroom/MediaReleaseDatabase/Press-releases/2015-Press-releases-items/2015-06-02.html

  16. 16.

    The Common Rule (45 CFR 46) was created to implement uniform regulations across the major federal agencies, including the Department of Veterans Affairs, Environmental Protection Agency, National Science Foundation, Agency for International Development, Department of Defense, Department of Commerce, Department of Education, among others. Researchers funded by these agencies are subject to the Rule. The proposed rule extends the scope to non-federally funded studies as well.

  17. 17.

    The ANPRM and public comments can be found at http://www.hhs.gov/ohrp/humansubjects/anprm2011page.html and in the Federal Register at 76 FR 44512–44531. The NPRM will be available online at http://federalregister.gov/a/2015-21756

  18. 18.

    In the process of conducting research on this topic, I attended a number of medical information technology and precision medicine symposia and workshops, and in each one the desire to change the Common Rule was raised in presentations and audience comments. In informal discussions with participants as well as public presentations sponsored by the White House, it was consistently asserted that this was a top priority, and that it would happen by September.

  19. 19.

    Specimens that have been stripped of identifiers (“de-identified”) are currently not counted as human subjects. Currently, the definition of a “human subject” includes living subjects about whom a researcher obtains data through intervention or interaction with the individual, but also any biospecimen or data derived from a human and for which any individual personal information can be identified.

  20. 20.

    This is based on the assumption that people engaging in activities occurring in a public context would have no reasonable expectation of privacy.

  21. 21.

    Guidance document: Electronic Source Data in Clinical Investigations, available at http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm328691.pdf. The FDA defines an electronic record as any combination of text, graphics, data, audio, pictorial, or other information represented in digital form that is created, modified, maintained, archived, retrieved, or distributed by a computer system (21 CFR 11.3(b)(6)). Source data includes clinical findings, observations, or other activities in a clinical investigation used for reconstructing and evaluating an investigation.

  22. 22.

    Discussion of additional ethical and legal issues related to mobile health devices can be found in Mittelstadt etal. (2014).

  23. 23.

    “Health” software is defined as that which is intended for use by patients for self-management or self-monitoring of a disease or condition, including management of medications; is intended for use to analyze patient-specific information or other medical information for the purpose of providing general information related to the prevention, diagnosis, prognosis, treatment, cure, monitoring, or management of a disease or condition; is intended for administrative or operational support for financial purposes; is intended for use for use aggregation, conversion, storage, management, retrieval, or transmission of data from a device or other thing. See http://assets.fiercemarkets.net/public/healthit/softwareact1-15draft.pdf for a full description of the amended draft bill.

  24. 24.

    The Food and Drug Administration Safety Innovation Act (FDASIA) Workgroup provides expert input on relevant issues as identified by the FDA, the ONC and the Federal Communications Commission (FCC), focusing on safety for mobile medical applications. Members include representatives from Intel, Qualcomm, Roche Diagnostics, Practice Fusion and other (mostly large) corporations involved in developing mobile medical apps.

  25. 25.

    FDA defines relevant regulated entities as whose which match the definition of “device” and that are intended to be used as an accessory to a regulated medical device, or transform a mobile platform into a regulated medical device. Guidance documents can be found at: http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM263366.pdf. Examples of mobile medical applications that may be regulated can be found at: http://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/ConnectedHealth/MobileMedicalApplications/ucm368744.htm

  26. 26.

    An obvious problem is that medical codes used for mining were designed for billing, and would not necessarily reflect events relevant to adverse event surveillance.

  27. 27.

    16 FDAAA § 905(a), 21 U.S.C.A. § 355(k)(3)(C)(i)(III)(aa)–(cc) (West Supp. 2008). Section 164.512 of the Privacy Rule of HIPAA of the Privacy Rule allows “public health” exemptions in which personally identifiable information may be disseminated without consent from the individuals.

  28. 28.

    At the time of this writing, the bill (H.R.6) was overwhelmingly approved by the House of Representatives in a rare bipartisan effort (July 2, 2015), and is likely to pass easily in the Senate. Estimated net costs (costs to implement minus projected savings) are pegged at $8.7 billion over 5 years.

  29. 29.

    Title One, Subtitle G, Part 4. subsection 13442.

  30. 30.

    Title One, Subtitle G, sec. 1124.

  31. 31.

    Subtitle G, Part 4 subsection 13442 states: “(a) Remuneration. The Secretary shall revise or clarify the Rule so that disclosures of protected health information for research purposes are not subject to the limitation on remuneration described in section 164.502(a)(5)(ii)(B)(2)(ii) of part 164.”

  32. 32.

    Sec 2014. The relevant FDCA section is at 21 U.S.C. §§ 351–60.

  33. 33.

    Title Two Subtitle D. Clinical outcome assessments are defined in the Act as “a measurement of a patient’s symptoms, overall mental state, or the effects of a disease or condition on how the patient functions” (section 2021). This includes patient-reported outcomes (e.g., “a measurement based on a report from a patient regarding the status of the patient’s health condition without amendment or interpretation of the patient’s report by a clinician or any other person”).

  34. 34.

    Title Two, Subtitle A, Section 2001.

  35. 35.

    Supporters include powerful industry lobbying groups such as PhRMA (pharmaceutical industry association) and Advomed (medical devices industry association) and CHIME (College of Health Info Management Executives).

  36. 36.

    For example, the bill limits Medicaid payments (health insurance for those with low income) for durable medical equipment (e.g., oxygen tanks, etc.) to states rather than being born by the federal government. So while the Congressional Budget Office estimates that direct spending would be reduced by $11.0 billion (net) from 2016 to 2025, however, the cost to states for Medicaid would be increased $2.6 billion over the same period. Interestingly, funds to pay for the changes would come from the sale of 8 million barrels of oil from the Strategic Petroleum Reserve in each of the fiscal years 2018 to 2025; not surprising since the bill originated in the Energy and Commerce Committee (see http://energycommerce.house.gov/fact-sheet/hr-6-21st-century-cures-act-frequently-asked-questions).

  37. 37.

    See http://www.hhs.gov/sites/default/files/budget/fy2016/fy-2016-budget-in-brief.pdf

  38. 38.

    Additional criticisms of PCORI, however, suggest that funds have been used more for promotional and justificatory activities than meaningful outcomes research, and have been diverted to special interests, including industry lobbying organizations. It is sometimes difficult to tease out criticisms.

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Acknowledgement

Research for this chapter was supported by the University of Wisconsin Graduate School Interdisciplinary Award. I am grateful to Joseph Wszalek for his contributions to research on relevant legislation.

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Correspondence to Linda F. Hogle .

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Hogle, L.F. (2016). The Ethics and Politics of Infrastructures: Creating the Conditions of Possibility for Big Data in Medicine. In: Mittelstadt, B., Floridi, L. (eds) The Ethics of Biomedical Big Data. Law, Governance and Technology Series, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-319-33525-4_17

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