13,377 research outputs found
Challenges of web-based personal genomic data sharing
In order to study the relationship between genes and diseases, the increasing availability and sharing of phenotypic and genotypic data have been promoted as an imperative within the scientific community. In parallel with data sharing practices by clinicians and researchers, recent initiatives have been observed in which individuals are sharing personal genomic data. The involvement of individuals in such initiatives is facilitated by the increased accessibility of personal genomic data, offered by private test providers along with availability of online networks. Personal webpages and on-line data sharing platforms such as Consent to Research (Portable Legal Consent), Free the Data, and Genomes Unzipped are being utilized to host and share genotypes, electronic health records and family history uploaded by individuals. Although personal genomic data sharing initiatives vary in nature, the emphasis on the individuals’ control on their data in order to benefit research and ultimately health care has seen as a key theme across these initiatives. In line with the growing practice of personal genomic data sharing, this paper aims to shed light on the potential challenges surrounding these initiatives. As in the course of these initiatives individuals are solicited to individually balance the risks and benefits of sharing their genomic data, their awareness of the implications of personal genomic data sharing for themselves and their family members is a necessity. Furthermore, given the sensitivity of genomic data and the controversies around their complete de-identifiability, potential privacy risks and harms originating from unintended uses of data have to be taken into consideration
Security and confidentiality approach for the Clinical E-Science Framework (CLEF)
CLEF is an MRC sponsored project in the E-Science programme that aims to
establish policies and infrastructure for the next generation of integrated clinical and
bioscience research. One of the major goals of the project is to provide a
pseudonymised repository of histories of cancer patients that can be accessed by
researchers. Robust mechanisms and policies are needed to ensure that patient
privacy and confidentiality are preserved while delivering a repository of such
medically rich information for the purposes of scientific research. This paper
summarises the overall approach adopted by CLEF to meet data protection
requirements, including the data flows and pseudonymisation mechanisms that are
currently being developed. Intended constraints and monitoring policies that will
apply to research interrogation of the repository are also outlined. Once evaluated, it
is hoped that the CLEF approach can serve as a model for other distributed
electronic health record repositories to be accessed for research
Routes for breaching and protecting genetic privacy
We are entering the era of ubiquitous genetic information for research,
clinical care, and personal curiosity. Sharing these datasets is vital for
rapid progress in understanding the genetic basis of human diseases. However,
one growing concern is the ability to protect the genetic privacy of the data
originators. Here, we technically map threats to genetic privacy and discuss
potential mitigation strategies for privacy-preserving dissemination of genetic
data.Comment: Draft for comment
Multiple imputation for sharing precise geographies in public use data
When releasing data to the public, data stewards are ethically and often
legally obligated to protect the confidentiality of data subjects' identities
and sensitive attributes. They also strive to release data that are informative
for a wide range of secondary analyses. Achieving both objectives is
particularly challenging when data stewards seek to release highly resolved
geographical information. We present an approach for protecting the
confidentiality of data with geographic identifiers based on multiple
imputation. The basic idea is to convert geography to latitude and longitude,
estimate a bivariate response model conditional on attributes, and simulate new
latitude and longitude values from these models. We illustrate the proposed
methods using data describing causes of death in Durham, North Carolina. In the
context of the application, we present a straightforward tool for generating
simulated geographies and attributes based on regression trees, and we present
methods for assessing disclosure risks with such simulated data.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS506 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Security and confidentiality approach for the Clinical E-Science Framework (CLEF)
Objectives: CLEF is an MRC sponsored project in the E-Science programme that aims to establish methodologies and a technical infrastructure for the next generation of integrated clinical and bioscience research. Methods: The heart of the CLEF approach to this challenge is to design and develop a pseudonymised repository of histories of cancer patients that can be accessed by researchers. Robust mechanisms and policies have been developed to ensure that patient privacy and confidentiality are preserved while delivering a repository of such medically rich information for the purposes of scientific research. Results: This paper summarises the overall approach adopted by CLEF to meet data protection requirements, including the data flows, pseudonymisation measures and additional monitoring policies that are currently being developed. Conclusion: Once evaluated, it is hoped that the CLEF approach can serve as a model for other distributed electronic health record repositories to be accessed for research
- …