HEC Forum

, Volume 31, Issue 4, pp 261–282 | Cite as

Transformation of the Doctor–Patient Relationship: Big Data, Accountable Care, and Predictive Health Analytics

  • Seuli Bose BrillEmail author
  • Karen O. Moss
  • Laura Prater


The medical profession is steeped in traditions that guide its practice. These traditions were developed to preserve the well-being of patients. Transformations in science, technology, and society, while maintaining a self-governance structure that drives the goal of care provision, have remained hallmarks of the profession. The purpose of this paper is to examine ethical challenges in health care as it relates to Big Data, Accountable Care Organizations, and Health Care Predictive Analytics using the principles of biomedical ethics laid out by Beauchamp and Childress (autonomy, beneficence, non-maleficence, and justice). Among these are the use of Electronic Health Records within stipulations of the Health Insurance Portability and Accountability Act. Clinicians are well-positioned to impact health policy development to address ethical issues associated with the use of Big Data, Accountable Care, and Health Care Predictive Analytics as we work to transform the doctor–patient relationship towards improving population health outcomes and creating a healthier society.


Doctor–patient relationship Health care ethics Health analytics Big Data Accountable Care Organizations 



The authors would like to thank Matthew Vest, Ph.D, MA for valuable feedback and insights on this paper.


  1. Amarasingham, R., Audet, A.-M. J., Bates, D. W., Cohen, I. G., Entwistle, M., Escobar, G. J., et al. (2016). Consensus statement on electronic health predictive analytics: A guiding framework to address challenges. EGEMs (Generating Evidence & Methods to Improve Patient Outcomes), 4(1), 1163. Scholar
  2. Amarasingham, R., Patzer, R. E., Huesch, M., Nguyen, N. Q., & Xie, B. (2014). Implementing electronic health care predictive analytics: Considerations and challenges. Health Affairs, 33(7), 1148–1154. Scholar
  3. American Medical Association. (1848). Code of medical ethics. New York: Ludwig & Company.Google Scholar
  4. Annas, G. J. (2003). HIPAA regulations—A new era of medical-record privacy? New England Journal of Medicine, 348(15), 1486–1490. Scholar
  5. Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big data in health care: Using analytics to identify and manage high-risk and high-cost patients. Health Affairs, 33(7), 1123–1131. Scholar
  6. Beach, M. C., Meredith, L. S., Halpern, J., Wells, K. B., & Ford, D. E. (2005). Physician conceptions of responsibility to individual patients and distributive justice in health care. Annals of Family Medicine, 3(1), 53–59. Scholar
  7. Berger, M. L., Mamdani, M., Atkins, D., & Johnson, M. L. (2009). Good research practices for comparative effectiveness research: Defining, reporting and interpreting nonrandomized studies of treatment effects using secondary data sources: The ISPOR good research practices for retrospective database analysis task force report—Part I. Value in Health, 12(8), 1044–1052. Scholar
  8. Berwick, D. M. (2011). Launching accountable care organizations—The proposed rule for the Medicare Shared Savings Program. New England Journal of Medicine, 364(16), e32. Scholar
  9. Berwick, D. M., & Hackbarth, A. D. (2012). Eliminating waste in US health care. JAMA, Journal of the American Medical Association,307(14), 1513–1516.CrossRefGoogle Scholar
  10. Berwick, D. M., Nolan, T. W., & Whittington, J. (2008). The triple aim: Care, health, and cost. Health Affairs,27(3), 759–769.CrossRefGoogle Scholar
  11. Bisognano, M., & Kenney, C. (2012). Pursuing the triple aim: Seven innovators show the way to better care, better health, and lower costs. San Francisco: Jossey-Bass Publishers.Google Scholar
  12. Blendon, R. J., Benson, J. M., & Hero, J. O. (2014). Public trust in physicians—U.S. medicine in international perspective. New England Journal of Medicine, 371(17), 1570–1572. Scholar
  13. Blumenthal, D. (2010). Launching HITECH. New England Journal of Medicine, 362(5), 382–385. Scholar
  14. Centers for Disease Control and Prevention. (2003). HIPAA privacy rule and public health. Guidance from CDC and the U.S. Department of Health and Human Services. MMWR Supplements,52, 2–12.Google Scholar
  15. Centers for Medicare & Medicaid Services (CMS). (2019). Accountable Care Organizations (ACOs): General Information. Accessed 15 June 2019.
  16. Chaudhuri, A. (2016). Internet of things data protection and privacy in the era of the General Data Protection Regulation. Journal of Data Protection & Privacy,1(1), 64–75.Google Scholar
  17. Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on big data. Information Sciences,275, 314–347.CrossRefGoogle Scholar
  18. Childress, T., & Beauchamp, J. (2001). Principles of biomedical ethics. New York: Oxford University Press.Google Scholar
  19. Clay, M. (2005). Ethics consultation: From theory to practice. Psychiatric Services,56(3), 367–368.CrossRefGoogle Scholar
  20. Cohen, I. G., Amarasingham, R., Shah, A., Xie, B., & Lo, B. (2014). The legal and ethical concerns that arise from using complex predictive analytics in health care. Health Affairs, 33(7), 1139–1147. Scholar
  21. Cookson, R., & Dolan, P. (2000). Principles of justice in health care rationing. Journal of Medical Ethics, 26(5), 323–329. Scholar
  22. Cushman, R., Froomkin, A. M., Cava, A., Abril, P., & Goodman, K. W. (2010). Ethical, legal and social issues for personal health records and applications. Journal of Biomedical Informatics, 43(5 Suppl): S51–S55. Scholar
  23. Davenport, T. H., & Dyché, J. (2013). Big data in big companies. SAS Institute Inc. Accessed 7 June 2019.
  24. Delmonico, F. L., Arnold, R., Scheper-Hughes, N., Siminoff, L. A., Kahn, J., & Youngner, S. J. (2002). Ethical incentives—Not payment—For organ donation. New England Journal of Medicine, 346(25), 2002–2005. Scholar
  25. Department of Health & Human Services. (2016). Examining oversight of the privacy and security of health data collected by entities not regulated by HIPAA. Washington DC: U.S. Department of Health and Human Services.Google Scholar
  26. Fisher, E. S., & Shortell, S. M. (2010). Accountable care organizations: Accountable for what, to whom, and how. JAMA, Journal of the American Medical Association, 304(15), 1715–1716. Scholar
  27. Fisher, E. S., Staiger, D. O., Bynum, J. P. W., & Gottlieb, D. J. (2007). Creating accountable care organizations: The extended hospital medical staff. Health Affairs, 26(1), w44–w57. Scholar
  28. Fleming, N. S., Becker, E. R., Culler, S. D., Cheng, D., McCorkle, R., Da Graca, B., et al. (2014). The impact of electronic health records on workflow and financial measures in primary care practices. Health Services Research, 49(1 Pt 2), 405–420. Scholar
  29. Frank, L., Basch, E., & Selby, J. V. (2014). The PCORI perspective on patient-centered outcomes research. JAMA, Journal of the American Medical Association, 312(15), 1513–1514. Scholar
  30. Frieden, T. R., & Berwick, D. M. (2011). The “Million Hearts” Initiative—Preventing heart attacks and strokes. New England Journal of Medicine, 365(13), e27. Scholar
  31. Fuentes, M. R. (2017). Cybercrime and other threats faced by the healthcare industry. TrendsLabs Research. [Online].
  32. Fuks, A., Brawer, J., & Boudreau, J. D. (2012). The foundation of physicianship. Perspectives in Biology and Medicine55(1), 114–126. Scholar
  33. Gibson, J. L., Martin, D. K., & Singer, P. A. (2004). Setting priorities in health care organizations: Criteria, processes, and parameters of success. BMC Health Services Research, 4(1), 25. Scholar
  34. Hodson, H. (2016). Revealed: Google AI has access to huge haul of NHS patient data. New Scientist. [Online].
  35. Institute of Medicine. (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academy Press.Google Scholar
  36. Jones, S. (1997). The failure of the NHS-distributive justice and health care in Britain. In J. Craughan & R. Fisher (Eds.), UCL Jurisprudence Review (Vol. 7, pp. 163–182). London: Faculty of Laws, University College London.Google Scholar
  37. Kenny, N. P., Mann, K. V., & MacLeod, H. (2003). Role modeling in physicians’ professional formation: Reconsidering an essential but untapped educational strategy. Academic Medicine, 78(12), 1203–1210. Scholar
  38. Kim, K. K., Joseph, J. G., & Ohno-Machado, L. (2015). Comparison of consumers’ views on electronic data sharing for healthcare and research. Journal of the American Medical Informatics Association, 22(4), 821–830. Scholar
  39. King, L. S. (1983). The social transformation of American medicine. JAMA, The Journal of the American Medical Association,249(16), 2237.CrossRefGoogle Scholar
  40. King, L. S. (1991). Transformations in American medicine: From Benjamin Rush to William Osler. Baltimore: The Johns Hopkins University Press.Google Scholar
  41. Kluge, E. H. W. (2004). Informed consent and the security of the electronic health record (EHR): Some policy considerations. International Journal of Medical Informatics, 73(3), 229–234. Scholar
  42. Laiteerapong, N., & Huang, E. S. (2015). The pace of change in medical practice and health policy: Collision or coexistence? Journal of General Internal Medicine,30(6), 848–852.CrossRefGoogle Scholar
  43. Levin, Rep. S. M. [D-M.-17]. (1990). Patient Self Determination Act of 1990. Retrieved from
  44. Martinez-Inigo, D., & Totterdell, P. (2016). The mediating role of distributive justice perceptions in the relationship between emotion regulation and emotional exhaustion in healthcare workers. Work and Stress,30(1), 26–45.CrossRefGoogle Scholar
  45. Martinez-Losas, P., Higueras, J., & Gomez-Polo, J. C. (2017). The computerized interpretation of the electrocardiogram: A double-edged sword? Enfermeria Clinica (English Edition),27(2), 136–137.CrossRefGoogle Scholar
  46. Mcgraw, D., Rosati, K., & Evans, B. (2012). A policy framework for public health uses of electronic health data. Pharmacoepidemiology and Drug Safety, 21(Suppl 1), 18–22. Scholar
  47. McNamara, A. R. (2015). The accountable care paradigm shift: New ethical considerations. AMA Journal of Ethics,17(7), 622–629.CrossRefGoogle Scholar
  48. McWilliams, J. M., Landon, B. E., Chernew, M. E., & Zaslavsky, A. M. (2014). Changes in patients’ experiences in Medicare Accountable Care Organizations. New England Journal of Medicine, 371(18), 1715–1724. Scholar
  49. Mennemeyer, S. T., Menachemi, N., Rahurkar, S., & Ford, E. W. (2016). Impact of the HITECH act on physicians’ adoption of electronic health records. Journal of the American Medical Informatics Association, 23(2), 375–379. Scholar
  50. Minelli, M., Chambers, M., & Dhiraj, A. (2013). Big data, big analytics: Emerging business intelligence and analytic trends for today’s businesses. Hoboken: John Wiley & Sons.CrossRefGoogle Scholar
  51. Muhlestein, D. B., & Smith, N. J. (2016). Physician consolidation: Rapid movement from small to large group practices, 2013–15. Health Affairs, 35(9), 1638–1642. Scholar
  52. Murphy, S. N., & Chueh, H. C. (2002). A security architecture for query tools used to access large biomedical databases. In Proceedings of the AMIA symposium (pp. 552–556).Google Scholar
  53. Office for Human Research Protections. (2016). Federal policy for the protection of human subjects (‘common rule’). [Online].
  54. Orr, R. D., Pang, N., Pellegrino, E. D., & Siegler, M. (1997). Use of the hippocratic oath: A review of twentieth century practice and a content analysis of oaths administered in medical schools in the U.S. and Canada in 1993. Journal of Clinical Ethics,8(4), 377–388.Google Scholar
  55. Parikh, R. B., Kakad, M., & Bates, D. W. (2016). Integrating predictive analytics into high-value care. JAMA, The Journal of the American Medical Association, 315(7), 651–652. Scholar
  56. Pellegrino, E. D. (1993). The metamorphosis of medical ethics. JAMA, The Journal of the American Medical Association,269(9), 1158–1162.CrossRefGoogle Scholar
  57. Pellegrino, E. D. (1994). Allocation of resources at the bedside: The intersections of economics, law, and ethics. Kennedy Institute of Ethics Journal,4(4), 309–317.CrossRefGoogle Scholar
  58. Pellegrino, E. D. (1995). Interests, obligations, and justice: Some notes toward an ethic of managed care. The Journal of Clinical Ethics,6(12), 312–317.Google Scholar
  59. Pellegrino, E. D. (1997). Managed care at the bedside: How do we look in the moral mirror? Kennedy Institute of Ethics Journal, 7(4), 321–330. Scholar
  60. Pellegrino, E. D. (2001). The internal morality of clinical medicine: A paradigm for the ethics of the helping and healing professions. The Journal of Medicine and Philosophy, 26(6), 559–579. Scholar
  61. Phillips, K. A., Ann Sakowski, J., Trosman, J., Douglas, M. P., Liang, S. Y., & Neumann, P. (2014). The economic value of personalized medicine tests: What we know and what we need to know. Genetics in Medicine, 16(3), 251–257. Scholar
  62. Poissant, L., Pereira, J., Tamblyn, R., & Kawasumi, Y. (2005). The impact of electronic health records on time efficiency of physicians and nurses: A systematic review. Journal of the American Medical Informatics Association, 12(5), 505–516. Scholar
  63. Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: Promise and potential. Health Information Science and Systems. Scholar
  64. Rawls, J. (1971). A theory of justice. Cambridge: Harvard University Press.Google Scholar
  65. Reuzel, R. P. B., van der Wilt, G. J., ten Have, H. A. M. J., & de Vries Robbe, P. F. (2001). Interactive technology assessment and wide reflective equilibrium. The Journal of Medicine and Philosophy, 26(2), 245–261. Scholar
  66. Saarni, S. I., Hofmann, B., Lampe, K., Lühmann, D., Mäkelä, M., Velasco-Garrido, M., et al. (2008). Ethical analysis to improve decision-making on health technologies. Bulletin of the World Health Organization, 86(8), 617–623. Scholar
  67. Self, R., & Coffin, J. (2017). Advanced alternative payment models. The Journal of Medical Practice Management: MPM,32(6), 399.Google Scholar
  68. Shabani, M., Vears, D., & Borry, P. (2018). Raw genomic data: Storage, access, and sharing. Trends in Genetics, 34(1), 8–10. Scholar
  69. Shams, I., Ajorlou, S., & Yang, K. (2015). A predictive analytics approach to reducing 30-day avoidable readmissions among patients with heart failure, acute myocardial infarction, pneumonia, or COPD. Health Care Management Science, 18(1), 19–34. Scholar
  70. Spencer, K., Sanders, C., Whitley, E. A., Lund, D., Kaye, J., & Dixon, W. G. (2016). Patient perspectives on sharing anonymized personal health data using a digital system for dynamic consent and research feedback: A qualitative study. Journal of Medical Internet Research, 18(4), e66. Scholar
  71. Stark, P. (2010). Congressional intent for the HITECH Act. The American Journal of Managed Care,16(12 Suppl HIT), SP24–SP28.Google Scholar
  72. Starr, P. (1982). The social transformation of American medicine: The rise of a sovereign profession and the making of a vast industry. New York: Basic Books.Google Scholar
  73. Sweeney, L. (2000). Simple demographics often identify people uniquely. Carnegie Mellon University, Data Privacy Working Paper 3. Pittsburgh 2000. [Online].
  74. van Biesen, T., & Weisbrod, J. (2017). Doctors feel excluded from health care value efforts. Harvard Business Review. [Online].
  75. Vydra, T. P., Cuaresma, E., Kretovics, M., & Bose-Brill, S., Vydra Pressler, T., Cuaresma, E., et al. (2015). Diffusion and use of tethered personal health records in primary care. Perspectives in Health Information Management, 12(Spring), 1c.Google Scholar
  76. Whittington, J. W., Nolan, K., Lewis, N., & Torres, T. (2015). Pursuing the triple aim: The first 7 years. Milbank Quarterly, 93(2), 263–300. Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.The Division of General Internal Medicine at The Ohio State University Wexner Medical CenterColumbusUSA
  2. 2.The Ohio State University College of NursingColumbusUSA

Personalised recommendations