Clinical Research Information Technology & Informatics
Our data scientists and informaticians provide informational technology and informatics services in support of investigators conducting clinical research.
DataCore is an integrated service providing enterprise-level support in the areas of electronic data capture and storage, management and integrity, and extraction and sharing. For more information, contact Alexander Bragat at firstname.lastname@example.org.
Institute for Computational Medicine
At the Institute for Computational Medicine at NYU Langone Health, data scientists and informaticians use computer models to better understand human disease, transforming the way doctors diagnose and treat patients.
Our experts focus on the fields of cancer biology, host–pathogen interactions, adaptive immune systems, and population health. These disciplines require expertise to analyze big data sets and apply principles of developmental and evolutionary systems. For more information, contact Itai Yanai, PhD, director, at email@example.com.
Online Information Technology and Informatics Systems and Databases
In addition to DataCore and the Institute for Computational Medicine, the following systems and databases are available to investigators, who may access these resources by logging in using a Kerberos ID. To obtain a Kerberos ID, contact information technology at 212-263-6868.
Data Catalog contains numerous large datasets from, for instance, the U.S. Census Bureau, the New York State Department of Health’s Statewide Planning and Research Cooperative System, and UnitedHealthcare. Investigators can browse existing datasets as well as add their own to the catalog.
Epic Electronic Health Records
Integration between the electronic medical record system, Epic, and the Clinical Research Management System allows physicians to receive up-to-date information on patients of theirs who are participating in a clinical trial. It also helps researchers track study subjects and maintain billing compliance.
Short for “Informatics for Integrating Biology and the Bedside,” i2b2 was developed at Partners HealthCare and supported by the National Institutes of Health as an open-source cohort discovery and identification tool that enables quick study feasibility determinations.
Supported by NYU Grossman School of Medicine’s DataCore, our current installation of i2b2 contains deidentified demographic, diagnosis, encounter, lab, vitals, procedure, and medication data from nearly all patients whose records are in Epic. i2b2 provides a self-service, drag-and-drop interface to build queries for exploring our data, using your specific inclusion or exclusion criteria, to identify sets of patients for protocol feasibility, cohort identification, or other purposes. Using generic data—not that of real patients—you can try out i2b2 in the Internet Explorer browser by entering the username “demo” and the password “demouser.” If you are interested in obtaining an account, please contact Alexander Bragat, firstname.lastname@example.org.
Laboratory Information Management System
The Laboratory Information Management System (LIMS) is a software-based laboratory and information management system used to support laboratory operations, as well as to submit requests for cores services. Please note that you must request access to LIMS in order to use the system.
REDCap is a secure web application for building and managing online surveys and databases. It provides automated export procedures for seamless data downloads to Excel as well as common statistical packages such as SPSS, SAS, Stata, and R. REDCap is available for both internal and external users.
Research Navigator is a single sign-on portal for managing your NYU Grossman School of Medicine research portfolio. This online resource assists investigators in submitting research protocols and managing information related to current clinical trials and research studies. In order to use Research Navigator, you must first complete the Research Navigator training, available through iDevelop, where you can also download user’s guides. Login requires a Kerberos ID.
Velos is a web-based, Health Insurance Portability and Accountability Act–compliant database system that can be used for data collection and management. Velos is capable of handling very large datasets, complicated form structures, and large numbers of patients. Differences between REDCap and Velos are outlined on the MCIT Research intranet page (Kerberos ID required for login).