Title |
Big Bad Data: Law, Public Health, and Biomedical Databases
|
---|---|
Published in |
The Journal of Law, Medicine & Ethics, January 2021
|
DOI | 10.1111/jlme.12040 |
Pubmed ID | |
Authors |
Sharona Hoffman, Andy Podgurski |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 3 | 2% |
United Kingdom | 2 | 1% |
Canada | 2 | 1% |
Finland | 1 | <1% |
Netherlands | 1 | <1% |
United States | 1 | <1% |
Unknown | 160 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 32 | 19% |
Student > Master | 32 | 19% |
Researcher | 31 | 18% |
Student > Postgraduate | 10 | 6% |
Student > Doctoral Student | 8 | 5% |
Other | 28 | 16% |
Unknown | 29 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 31 | 18% |
Computer Science | 30 | 18% |
Social Sciences | 16 | 9% |
Business, Management and Accounting | 11 | 6% |
Nursing and Health Professions | 10 | 6% |
Other | 33 | 19% |
Unknown | 39 | 23% |