Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity.
This handbook covers Electronic Medical Record (EMR) systems, which enable the storage, management, and sharing of massive amounts of demographic, diagnosis, medication, and genomic information.
This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.
... data to a service provider and want to control how their data is used. Among ... Data Anonymisation The HIPAA Privacy Rule [19] establishes three means for ... data, with specific obligations for the receiving party for excluding any ...
Academics and other research scientists will also find the book invaluable.
... data related to individual or organization. In this paper, we deal with the problem of anonymizing mixed data (continuous and categorical data) to preserve its privacy and perform the data anonymization in such a way that that we get a ...
... anonymized social network for various application fields. – Formally analyze ... Data Mining (2004) 6. Ciriani, V., Vimercati, S.C., Foresti, S., Samarati, P ... HIPAA. Health Insurance Portability and Accountability Act (2002), http ...
... data . “ But in the face of criticism , the final FTC Report changed course ... data anonymization as a means to protect privacy , contending that wealth of ... HIPAA Privacy Rule's " minimum necessary " standard and on de ...
... data an mHealth app generates necessitates cloud data storage. Cloud computing allows for cost savings, storage management ... anonymise or de-identify per HIPAA requirements, if even covered by HIPAA (Schwartz and Solove 2011). mHealth.
The current social and economic context increasingly demands open data to improve scientific research and decision making.