Social Justice, Equality and Primary Care: (How) Can ‘Big Data’ Help?
A growing body of research emphasises the role of ‘social determinants of health’ in generating inequalities in health outcomes. How, if at all, should primary care providers respond? In this paper, I want to shed light on this issue by focusing on the role that ‘big data’ might play in allowing primary care providers to respond to the social determinants that affect individual patients’ health. The general idea has been proposed and endorsed by the Institute of Medicine, and the idea has been developed in more detail by Bazemore et al. (2016). In Bazemore et al.’s proposal, patients’ addresses are used to generate information about the patients’ neighbourhood; this information is then included in patients’ health care records and made available to providers. This allows primary care providers to take this information into account when interacting with, and providing care to, patients. I explore three issues arising from this proposal. First, while questions of privacy have been central to discussions about big data, Bazemore et al.’s proposal also allows us to see that there might be costs to not making certain information available. Second, I consider some of the questions arising for primary care from the influence of social factors on health outcomes: given that we know these factors to be significant contributors to social inequalities in health, what precisely should be done about this in the primary care context? Finally, I address problems arising from the use of population level data when dealing with individuals.
KeywordsEquality Equity Health inequality Social determinants of health Big data
This paper was written while I was a Senior Researcher at the Ethox Centre, University of Oxford. An earlier version of this paper was presented at the Brocher Foundation workshop, ‘Ethical Risk Assessment in Biomedical Big Data’, March 2016; I am grateful to the audience for their comments and suggestions. I would also like to thank two anonymous reviewers of this journal for their input.
- Bazemore, A. W., Cottrell, E. K., Gold, R., Hughes, L. S., Phillips, R. L., Angier, H., Burdick, T. E., Carrozza, M. A., et al. (2016). “Community vital signs”: incorporating geocoded social determinants into electronic records to promote patient and population health. Journal of the American Medical Informatics Association: JAMIA, 23(2), 407–412.CrossRefGoogle Scholar
- FitzGerald, C., & Hurst, S. (2017). Implicit bias in healthcare professionals: a systematic review. BMC Medical Ethics, 18(19), 71.Google Scholar
- Institute of Medicine. (2015a). Capturing social and behavioral domains in electronic health records: Phase 1. Washington, D.C.: National Academies Press.Google Scholar
- Institute of Medicine. (2015b). Capturing social and behavioral domains and measures in electronic health records: Phase 2. Washington, D.C.: National Academies Press.Google Scholar
- Nuffield Council on Bioethics. (2015). The collection, linking and use of data in biomedical research and health care: ethical issues. London: Nuffield Council on Bioethics.Google Scholar
- Shedd, C. (2015). Unequal City. New York: Russell Sage Foundation.Google Scholar
- Sreenivasan, G. (2014). Justice, inequality, and health. In E. Zalta (Ed.), The Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/archives/fall2014/entries/justice-inequality-health/.
- Stevens, G. D. (2014). Addressing social determinants of health using big data. In K. Marconi & H. Lehmann (Eds.), Big data and health analytics (pp. 105–126). Boca Raton: Taylor & Francis.Google Scholar
- Voigt, K., Nicholls, S. G., & Williams, G. (2014). Childhood obesity: ethical and policy issues. New York: Oxford University Press.Google Scholar
- World Health Organization. (2008). Closing the gap in a generation: Hhealth equity through action on the social determinants of health. Geneva: World Health Organization.Google Scholar