iDASH: integrating data for analysis, anonymization, and sharing
- Lucila Ohno-Machado1,
- Vineet Bafna2,
- Aziz A Boxwala1,
- Brian E Chapman1,
- Wendy W Chapman1,
- Kamalika Chaudhuri2,
- Michele E Day1,3,
- Claudiu Farcas4,
- Nathaniel D Heintzman1,
- Xiaoqian Jiang1,
- Hyeoneui Kim1,
- Jihoon Kim1,
- Michael E Matheny5,6,
- Frederic S Resnic7,
- Staal A Vinterbo1,
- and the iDASH team
- 1Division of Biomedical Informatics, University of California San Diego, La Jolla, California, USA
- 2Department of Computer Science, University of California San Diego, La Jolla, California, USA
- 3San Diego Supercomputer Center, University of California San Diego, La Jolla, California, USA
- 4California Institute for Telecommunications and Information Technology (Calit2), University of California San Diego, La Jolla, California, USA
- 5Research & Development Service, VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
- 6Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA
- 7Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Correspondence to Dr Lucila Ohno-Machado, Division of Biomedical Informatics, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA; machado{at}ucsd.edu
- Received 11 August 2011
- Accepted 15 August 2011
- Published Online First 10 November 2011
Abstract
iDASH (integrating data for analysis, anonymization, and sharing) is the newest National Center for Biomedical Computing funded by the NIH. It focuses on algorithms and tools for sharing data in a privacy-preserving manner. Foundational privacy technology research performed within iDASH is coupled with innovative engineering for collaborative tool development and data-sharing capabilities in a private Health Insurance Portability and Accountability Act (HIPAA)-certified cloud. Driving Biological Projects, which span different biological levels (from molecules to individuals to populations) and focus on various health conditions, help guide research and development within this Center. Furthermore, training and dissemination efforts connect the Center with its stakeholders and educate data owners and data consumers on how to share and use clinical and biological data. Through these various mechanisms, iDASH implements its goal of providing biomedical and behavioral researchers with access to data, software, and a high-performance computing environment, thus enabling them to generate and test new hypotheses.
- Privacy technology
- cloud computing
- electronic health records
- genomics
- natural language processing
- informatics
- machine learning
- predictive modeling
- statistical learning
- knowledge bases
- translational research—application of biological knowledge to clinical care
- developing/using clinical decision support (other than diagnostic) and guideline systems
- knowledge acquisition and knowledge management
- privacy technology
- cloud computing
- data mining
- detecting disease outbreaks and biological threats
- statistical analysis of large datasets
- discovery
- and text and data mining methods
- automated learning
- measuring/improving patient safety and reducing medical errors
- monitoring the health of populations
