title: Big bad data: law, public health, and biomedical databases.
abstract: The accelerating adoption of electronic health record (EHR) systems will 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. Because of clinicians' workloads, poor user-interface design, and other factors, EHR data can be erroneous, miscoded, fragmented, and incomplete. In addition, public health findings can be tainted by the problems of selection bias, confounding bias, and measurement bias. These flaws may become all the more troubling and important in an era of electronic "big data," in which a massive amount of information is processed automatically, without human checks. Thus, we conclude the paper by outlining several regulatory and other interventions to address data analysis difficulties that could result in invalid conclusions and unsound public health policies.
authors.affiliation: Law-Medicine Center at Case Western Reserve University School of Law.
authors.forename: Sharona
authors.initials: S
authors.lastname: Hoffman
authors.forename: Andy
authors.initials: A
authors.lastname: Podgurski
mesh_terms: D015984:Causality; D003627:Data Interpretation, Statistical; D057286:Electronic Health Records / Q000331:legislation & jurisprudence; D015981:Epidemiologic Factors; D016021:Epidemiologic Studies; D033161:Government Regulation; D006801:Humans; D016247:Information Storage and Retrieval; D011159:Population Surveillance; D011634:Public Health / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data*; D015980:Public Health Practice / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data*; D011786:Quality Control; D014481:United States