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Data Management and Mining
The Data storage, management, integration and mining services of CHIBI fully enable and/or contribute to the design, implementation, and management of a far-reaching strategic institutional vision that is jointly formulated and dynamically evolving by many participants including: the academic leadership, CHIBI, IT, the Research IT committee, the CTSI/CTSA, several researcher labs/units, the Biorepository facilities, the various high throughput molecular assay cores directors, and others.
This complex data management landscape covers all aspects of:
- Capture and storage of clinical and operational transactional data (e.g., EMR data)
- Data warehousing
- Data annotation
- Research protocol data management
- Biorepository specimen and meta data management
- High-throughput assay core data management and integration
- Advanced data analytics of stored data
Individual activities/projects to date include:
Use of the new Electronic Medical Record for research purposes
Design, acquisition and deployment of a Federated Data Warehouse
Clinical trial and other clinical research protocol-supporting data management systems and Database management services:
The NYU-HHC Clinical and Translational Science Institute (CTSI) and CHIBI recently announced the establishment of the Clinical and Research Informatics Data Management Unit led by Jim Robinson. This unit will act as an interface among investigators and the recently acquired eVelos system for management of clinical trials and other research protocol data. The unit also works with IT to ensure smooth implementation and interfacing of eVelos with legacy systems. In addition to hands on management, the Data Management Unit will provide educational services so that small projects can be executed directly by the investigators’ labs with minimal costs.
Biorepository specimen and data management and integration:
Currently NYULMC has several biorepositories specimens in which are being managed by the Freezerworks system. A recently-instituted working group will assess the future needs for biorepository specimen management and evaluate various open source and vendor provided systems.
