Understanding de-identification of healthcare big data

Maureen S. Van Devender, Ryan Benton, William Bradley Glisson, George Grispos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


In society’s increasingly computerized world, the intensification of electronic data collection is resulting in large volumes of new data (known as big data). This is creating new opportunities for secondary uses of this data, particularly in the healthcare sector. The opportunities for secondary uses of healthcare data include constructive studies, research, policy assessment and other endeavors that could produce beneficial results such as improved healthcare quality and finding cures for diseases. However, protecting the privacy of individuals represented in data presents a challenge to the secondary utility of healthcare data. De-identifying data by removing any information that could be used to uniquely identify individuals is a potential solution to the challenge of protecting individual privacy. Hence, this research identifies a practical process for applying anonymizing techniques through a process model designed to handle requests for healthcare data.

Original languageEnglish (US)
Title of host publicationAMCIS 2017 - America's Conference on Information Systems
Subtitle of host publicationA Tradition of Innovation
PublisherAmericas Conference on Information Systems
ISBN (Electronic)9780996683142
StatePublished - 2017
Externally publishedYes
EventAmerica�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017 - Boston, United States
Duration: Aug 10 2017Aug 12 2017

Publication series

NameAMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation


OtherAmerica�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017
CountryUnited States


  • Big data opportunities
  • De-identification
  • Healthcare
  • Privacy preserving techniques

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Understanding de-identification of healthcare big data'. Together they form a unique fingerprint.

Cite this