Data Collection, EHRs, and Poverty Determinations

Abstract

Today, patients emanate increasing quantities of health information. However, not all health data are created equal. Questions regarding technology and innovation have been well explored when it comes to certain kinds of medical data. Genetic data have received the most attention. Less prominent, but nonetheless commonly analyzed, are the more typical kinds of biometric data that are already present in electronic health records (EHRs). These data include the bread and butter of medical practice — heart rate, blood pressure, and the like. When scholars write about clinical and non-clinical technologies that capture health information and deploy it for research and treatment, they usually are considering this kind of data. Work that focuses on deploying data relating to social determinants of health is rarer.

Social determinants of health are environmental factors that help determine health outcomes in individuals and populations. Research suggests that on average, these factors are more determinative of health outcomes than medical interventions. It is therefore important to collect data both to understand how these determinants affect health, and to figure out how to prevent these effects — either by curing the health conditions, or by changing the underlying social conditions. However, because these determinants lie beyond the control of the healthcare system, and often, the expertise of medical professionals, information about them is lacking.

As part of the Medicalization of Poverty Symposium, this article is a first step in considering how data that relates to social determinants of health can be collected and analyzed by focusing on the collection, analysis, and deployment of poverty-related data to provide better rounded healthcare. There are benefits to considering poverty as an entry point to understanding other social determinants of health. First, there is already research on how poverty should be measured that takes into account parameters that are both financial and non-financial. I lay out some of those below.

More importantly, what exactly a social determinant of health is remains unclear. Many aspects of human activity have some bearing on health. But without data on those determinants, it is unclear how serious their effects are. Poverty escapes this classic chicken and egg problem because we know that poverty affects health in clear and plausible ways, some of which have already been researched. Creating a template for collecting information about poverty can then be used as a spring board for data collection regarding other determinants.

Finally, poverty is a useful place to begin precisely because it is connected to or comprises so many other social determinants of health. To understand a given individual’s poverty, we must have some information regarding his or her employment, family structure, housing situation, and welfare status. All of these are key candidates for social determinant status. Collecting data regarding poverty is a good starting point for determining where to go next. And collection and analysis of poverty data raises many of the same challenges and questions as data regarding other determinants.

The article is divided into two parts. The first examines questions of data collection, and considers the kind of data needed, sources of such data, and how to incentivize collection. It also considers privacy objections. The second considers how the data can be used for research to achieve interventions at both the individual and system-wide levels.

Keywords: EHR, economic inequality, health privacy, data regulation