Big Data Neglects Populations Most in Need of Medical and Public Health Research and Interventions

Abstract

Big data should be extremely useful to medical and public health professionals attempting to engage in research, intervention, and precision medicine. The use of big data in these areas, however, has the potential to ignore a large portion of the population, because the sources of much of the data – social media, wearables, electronic health records, and insurance claims – are not utilized by that subset. These omitted populations, such as minorities and low-income individuals, are at a greater risk for health disparities and are the very populations that could most benefit from research and intervention. This paper argues that the scope of big data and the subsequent health uses of the information gathered needs to be broadened to increase the diversity of the data, especially by including those most vulnerable to diminished health outcomes. Building on existing government measures such as the Lifeline program to provide internet access to the underprivileged and NHS guidelines for the inclusion of minorities in research, we propose monetary, programmatic, and regulatory recommendations as means of addressing, and ultimately remedying, this problem.

Keywords: Big Data, Precision Medicine, Health, Poverty, Race, Health Disparities, Interventions