The Office of Chief Research Informatics Officer (CRIO) oversees the Mount Sinai IT needs related to research infrastructure, data science and informatics education, taking advantage of the unique data assets, diverse patient population and informatics resources of the entire Mount Sinai Health System. The CRIO provides critical support to the School’s precision medicine initiative by bridging academic research needs with Mount Sinai’s clinical information systems and expanding IT infrastructure supporting clinical and translational research including e-consenting capabilities integrated with institution-wide biobanking efforts.

Leadership
Joseph Finkelstein, MD, PhD
Chief Research Informatics Officer (CRIO)
Senior Associate Dean for Information Technology at ISMMS

Contact Information
Venus Velez, MBA
Project Coordinator
venus.velez@mssm.edu
212-659-9686

Services

Projects

  • Multipurpose Scalable Electronic Informed Consent Platform
  • Universal Consent for Mount Sinai Biorepository
    • Collect and store identified leftover specimens
    • Link specimens to Electronic Health Records
    • Share samples and information with qualified researchers
  • Comprehensive Research Data Integration Trust (CReDIT) for Electronic Biorepository Phenotyping
    • Integrating disparate data sources
    • Creation of unified query tool/reporting
    • Implementing research consent management system
  • Honest Broker Service for EMR research
    • Proficiency in database management, SQL scripting, and EHR database design
    • HIPAA trained, responsible conduct of human subject research
    • Compliant with all regulatory frameworks.

Personalized Health Informatics (PHI) Lab

The PHI lab focuses on the development, evaluation, and implementation of evidence-based clinical decision support for personalized medicine. Current research projects include tailored interactive patient engagement in personalized health; pharmacogenomics-driven decision support for medication optimization; and analysis of heterogeneous health information datasets for building individualized patient care prediction models.

Research Administration-Information Technology (RA-IT)

Electronic Research Administration

Research 411 Portal

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