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Frontiers of Health Policy: Digital Data and Personalized Medicine

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  • Amalia R. Miller
  • Catherine Tucker

Abstract

This paper argues that due to two unstoppable mechanisms, some of the most pressing future questions in health policy will relate to the use of digital technologies to analyze data concerning patient health. The first mechanism is the shift away from a system where patient data was essentially temporary and not intended to be reused or easily accessed again, to a new digital world where patient data is easily transferred and accessed repeatedly. The second mechanism is a fundamental deepening of the nature of patient data that enables increased personalization of health care for each individual patient, based on not only their detailed medical history, but also their likely future medical history that can be projected for their genetic makeup. We summarize our research investigating the potential consequences of policies in this new world where patient data is virtually costless to store, share, and individualize. We emphasize that issues of data management and privacy are now at the forefront of health policy considerations.Digital data and digital technologies have the potential to transform medicine through two mechanisms. First, digital patient data is far easier to share and access than traditional paper records. This has many potential upsides, but also raises the question of how the potential benefits of sharing patient data are moderated by privacy concerns. Second, the advent of digital storage has now made it possible to store, virtually costlessly, vast swathes of data about any one individual patient. Such individualized data also enables a patient-centric approach to medicine, often referred to as “personalized” or “precision” medicine, based on that individual patient’s genetic makeup.This article discusses the potential benefits and possible policy consequences of this digital shift. It emphasizes that the benefits of digital technologies are found when data is actually transferred and repeatedly accessed. This emphasizes that policies that wish to encourage the potential upside of digital technologies should emphasize easy data transfer. Empirical evidence suggests that health-care providers may not individually have the right incentives to share data, and therefore if a policy aims to encourage data transfer it needs to not only subsidize the adoption of digital technologies, but also make sure that there are the right incentives to use these technologies to share data. Often, well-meaning policies toward data security and data privacy can hamper this process. This article also suggests that there are distinct concerns related to the deepening and individualizing of data that is associated with personalized medicine, and that while there is potentially a large upside in terms of medical outcomes, the risks associated with this data are unusual. If policymakers seek to encourage personalized medicine, they might be especially successful to employ an approach to data management that gives control of the use of the data to the patient.

Suggested Citation

  • Amalia R. Miller & Catherine Tucker, 2017. "Frontiers of Health Policy: Digital Data and Personalized Medicine," Innovation Policy and the Economy, University of Chicago Press, vol. 17(1), pages 49-75.
  • Handle: RePEc:ucp:ipolec:doi:10.1086/688844
    DOI: 10.1086/688844
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    1. Emily Oster & Ira Shoulson & E. Ray Dorsey, 2013. "Optimal Expectations and Limited Medical Testing: Evidence from Huntington Disease," American Economic Review, American Economic Association, vol. 103(2), pages 804-830, April.
    2. Oster, Emily & Shoulson, Ira & Quaid, Kimberly & Dorsey, E. Ray, 2010. "Genetic adverse selection: Evidence from long-term care insurance and Huntington disease," Journal of Public Economics, Elsevier, vol. 94(11-12), pages 1041-1050, December.
    3. Avi Goldfarb & Catherine Tucker, 2012. "Privacy and Innovation," NBER Chapters, in: Innovation Policy and the Economy, Volume 12, pages 65-89, National Bureau of Economic Research, Inc.
    4. Avi Goldfarb & Catherine E. Tucker, 2011. "Privacy Regulation and Online Advertising," Management Science, INFORMS, vol. 57(1), pages 57-71, January.
    5. David Dranove & Chris Forman & Avi Goldfarb & Shane Greenstein, 2014. "The Trillion Dollar Conundrum: Complementarities and Health Information Technology," American Economic Journal: Economic Policy, American Economic Association, vol. 6(4), pages 239-270, November.
    6. Melnick, Glenn & Keeler, Emmett, 2007. "The effects of multi-hospital systems on hospital prices," Journal of Health Economics, Elsevier, vol. 26(2), pages 400-413, March.
    7. Seth Freedman & Haizhen Lin & Jeffrey T. Prince, 2014. "Information Technology and Patient Health: An Expanded Analysis of Outcomes, Populations, and Mechanisms," Working Papers 2014-02, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    8. Amalia R. Miller & Catherine Tucker, 2009. "Privacy Protection and Technology Diffusion: The Case of Electronic Medical Records," Management Science, INFORMS, vol. 55(7), pages 1077-1093, July.
    9. Gautam Gowrisankaran & Joanna Stavins, 2004. "Network Externalities and Technology Adoption: Lessons from Electronic Payments," RAND Journal of Economics, The RAND Corporation, vol. 35(2), pages 260-276, Summer.
    10. Sasha Romanosky & Rahul Telang & Alessandro Acquisti, 2011. "Do data breach disclosure laws reduce identity theft?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 30(2), pages 256-286, March.
    11. Agha, Leila, 2014. "The effects of health information technology on the costs and quality of medical care," Journal of Health Economics, Elsevier, vol. 34(C), pages 19-30.
    12. Amalia R. Miller & Catherine E. Tucker, 2011. "Can Health Care Information Technology Save Babies?," Journal of Political Economy, University of Chicago Press, vol. 119(2), pages 289-324.
    13. Tatiana Komarova & Denis Nekipelov & Evgeny Yakovlev, 2015. "Estimation of Treatment Effects from Combined Data: Identification versus Data Security," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 279-308, National Bureau of Economic Research, Inc.
    14. Jeffrey S. McCullough & Stephen T. Parente & Robert Town, 2013. "Health Information Technology and Patient Outcomes: The Role of Organizational and Informational Complementarities," NBER Working Papers 18684, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Bleier, Alexander & Goldfarb, Avi & Tucker, Catherine, 2020. "Consumer privacy and the future of data-based innovation and marketing," International Journal of Research in Marketing, Elsevier, vol. 37(3), pages 466-480.

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