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| Author | : Acar Tamersoy |
| Publisher | : |
| Total Pages | : 44 |
| Release | : 2011 |
| Genre | : Electronic dissertations |
| ISBN | : |
| Author | : Khaled El Emam |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 252 |
| Release | : 2013-12-11 |
| Genre | : Computers |
| ISBN | : 1449363032 |
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. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets. Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others. Understand different methods for working with cross-sectional and longitudinal datasets Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy Use methods to anonymize unstructured free-form text data Minimize the risks inherent in geospatial data, without omitting critical location-based health information Look at ways to anonymize coding information in health data Learn the challenge of anonymously linking related datasets
| Author | : Institute of Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 236 |
| Release | : 2015-04-20 |
| Genre | : Medical |
| ISBN | : 0309316324 |
Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. 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.
| Author | : Karl-Heinz Schriever |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 210 |
| Release | : 2014-10-02 |
| Genre | : Medical |
| ISBN | : 311028328X |
Establishing ethical and privacy protection aspects in scientific research, especially in medical research, has a long history. Medical data are usually more sensible than other personal data and require therefore an even higher degree of protection than other personal data. In recent research projects genetic evaluations become more and more important and trigger thereby new and continuing activities in the context of data protection. Genetic data as a subset of medical data are the most sensible category of personal data and require therefore the highest degree of data protection. The book provides a systematic and itemized approach to data protection in clinical research including the handling of genetic material, genetic samples as well as derived genetic data and the subsequent secure storage of them. The set up of different kinds of clinical trials having in addition a genetic part, the concept of a genetic informed consent as well as collection schemes of samples are described in detail. Technical requirements and aspects of data protection including pseudonymization and anonymization procedures taking into account ethics committees requirements as well as the underlying legal framework are also presented. Without any exception, all principles and methods presented are best practices, repeatedly applied in different clinical environments and by no means theoretical considerations.
| Author | : Aris Gkoulalas-Divanis |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 87 |
| Release | : 2012-10-13 |
| Genre | : Medical |
| ISBN | : 1461456681 |
Anonymization of Electronic Medical Records to Support Clinical Analysis closely examines the privacy threats that may arise from medical data sharing, and surveys the state-of-the-art methods developed to safeguard data against these threats. To motivate the need for computational methods, the book first explores the main challenges facing the privacy-protection of medical data using the existing policies, practices and regulations. Then, it takes an in-depth look at the popular computational privacy-preserving methods that have been developed for demographic, clinical and genomic data sharing, and closely analyzes the privacy principles behind these methods, as well as the optimization and algorithmic strategies that they employ. Finally, through a series of in-depth case studies that highlight data from the US Census as well as the Vanderbilt University Medical Center, the book outlines a new, innovative class of privacy-preserving methods designed to ensure the integrity of transferred medical data for subsequent analysis, such as discovering or validating associations between clinical and genomic information. Anonymization of Electronic Medical Records to Support Clinical Analysis is intended for professionals as a reference guide for safeguarding the privacy and data integrity of sensitive medical records. Academics and other research scientists will also find the book invaluable.
| Author | : |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2006 |
| Genre | : |
| ISBN | : |
For example, if I. is performing a survey on the web and does not collect identifying information in the on-line questionnaire, does not retain the IP addresses of the client machines in the log files, nor use cookies, then one can make the case that data is being collected anonymously. [...] There are a number of situations where permanent anonymization of data in the research database would create practical difficulties, for example: • If each S. needs to come back to the study site for multiple visits, then it is important to match the S. with their record in the research database at each visit. [...] A code is attached to the research database and the same code is used to link with the identifying database. [...] This is most suitable if a third party will hold the linking database to ensure that the records in the research database cannot be re-identified by any of the participants in the study. [...] It should be noted that in none of the cases that were covered during the interviews was it reported that the data was encrypted in the research database.
| Author | : |
| Publisher | : ScholarlyEditions |
| Total Pages | : 555 |
| Release | : 2013-05-01 |
| Genre | : Computers |
| ISBN | : 1490107274 |
Issues in Information Science—Informatics / 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Industrial Informatics. The editors have built Issues in Information Science—Informatics: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Industrial Informatics in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Information Science—Informatics: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
| Author | : Nataraj Venkataramanan |
| Publisher | : CRC Press |
| Total Pages | : 206 |
| Release | : 2016-10-03 |
| Genre | : Computers |
| ISBN | : 1315353768 |
The book covers data privacy in depth with respect to data mining, test data management, synthetic data generation etc. It formalizes principles of data privacy that are essential for good anonymization design based on the data format and discipline. The principles outline best practices and reflect on the conflicting relationship between privacy and utility. From a practice standpoint, it provides practitioners and researchers with a definitive guide to approach anonymization of various data formats, including multidimensional, longitudinal, time-series, transaction, and graph data. In addition to helping CIOs protect confidential data, it also offers a guideline as to how this can be implemented for a wide range of data at the enterprise level.
| Author | : Agency for Healthcare Research and Quality/AHRQ |
| Publisher | : Government Printing Office |
| Total Pages | : 396 |
| Release | : 2014-04-01 |
| Genre | : Medical |
| ISBN | : 1587634333 |
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
| Author | : Khaled El Emam |
| Publisher | : |
| Total Pages | : 15 |
| Release | : 2006 |
| Genre | : Confidential communications |
| ISBN | : |
