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Big Bad Data: Law, Public Health, and Biomedical Databases
in
Adoption of innovations
/ Biomedicine
/ Breaches
/ Clinical research
/ Clinical trials
/ Data quality
/ Electronic health records
/ Errors
/ Handwriting
/ Health research
/ Health services
/ Human-computer interaction
/ Medical records
/ Policy making
/ Privacy
/ Public health
/ Public policy
/ Regulation
/ Statutes
/ Surveillance
/ Workloads
2013
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Big Bad Data: Law, Public Health, and Biomedical Databases
by
in
Adoption of innovations
/ Biomedicine
/ Breaches
/ Clinical research
/ Clinical trials
/ Data quality
/ Electronic health records
/ Errors
/ Handwriting
/ Health research
/ Health services
/ Human-computer interaction
/ Medical records
/ Policy making
/ Privacy
/ Public health
/ Public policy
/ Regulation
/ Statutes
/ Surveillance
/ Workloads
2013
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Do you wish to request the book?
Big Bad Data: Law, Public Health, and Biomedical Databases
in
Adoption of innovations
/ Biomedicine
/ Breaches
/ Clinical research
/ Clinical trials
/ Data quality
/ Electronic health records
/ Errors
/ Handwriting
/ Health research
/ Health services
/ Human-computer interaction
/ Medical records
/ Policy making
/ Privacy
/ Public health
/ Public policy
/ Regulation
/ Statutes
/ Surveillance
/ Workloads
2013
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Big Bad Data: Law, Public Health, and Biomedical Databases
Journal Article
Big Bad Data: Law, Public Health, and Biomedical Databases
2013
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Overview
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. Unlike clinical trial data, EHR data is not recorded primarily to meet the needs of researchers. Because of clinicians’ workloads, poor user-interface design, and other factors, EHR data is surprisingly likely to be erroneous, miscoded, fragmented, and incomplete. Although EHRs eliminate the problem of cryptic handwriting, other kinds of errors are more common with EHRs than with paper records.
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