Big Bad Data: Law, Public Health, and Biomedical Databases

Abstract

The accelerating adoption of electronic health record (EHR) systems will have profound impacts on clinical care. It will also have far-reaching implications for public health research and surveillance, which in turn could lead to changes in public policy, statutes, and regulations. The public health benefits of EHR use can be significant. However, researchers and analysts who rely on EHR data must proceed with caution and understand the potential limitations of EHRs.

Much has been written about the risk of EHR privacy breaches. This paper focuses on a different set of concerns, those relating to data quality. EHR data can be erroneous, miscoded, fragmented, and incomplete. In addition, if causation is at issue, analysts must grapple with the complexities of causal inference. Public health findings can be tainted by the problems of selection bias, confounding bias, and measurement bias. These and other obstacles can easily lead to invalid conclusions and unsound public health policies.

The paper will highlight the public health uses of EHRs. It will also probe the shortcomings of EHR information and the challenges of collecting and analyzing it. Finally, we outline several regulatory and other interventions to address data analysis difficulties.

Keywords: electronic health records, public health, biomedical databases, health care informatics, clinical care, public health emergencies, causal inference, data infrastructure, data integrity, interoperability, data collection, data storage, data analysis

JEL Classification: K32