Message from the Director

The vision of predictive, personalized, preventive, and participatory medicine is becoming a reality. Internationally, there is an increasing emphasis on optimizing use of routine health data for research. Informatics has become critical to an effective clinical and translational enterprise. Although more data are available than ever, only a fraction is being curated, integrated, understood, and analyzed. At Mount Sinai, we increasingly use informatics to inform precision medicine, population health, and biomedical big data science.

The Mount Sinai Health System encompasses eight hospitals and a network of ambulatory practices. Mount Sinai has invested significant resources into integrating these entities into a unified Epic electronic health record with an integrated clinical data warehouse. Centralized data helps coordinate health care delivery with research and data science initiatives to develop a learning health system.

We are building a biomedical informatics ecosystem that is:

  1. More accessible to stakeholders, ensuring broad, user-friendly, integrated access to diverse data sources. Our ecosystem maintains robust, secure, bidirectional information flow between research programs and point-of-care information systems.
  2. More actionable, which enables innovative applications of translational bioinformatics research and data-driven medicine. To achieve these goals, we developed the following priority aims:

Aim 1. Establish a shared biomedical informatics ecosystem that maximizes access to core informatics competencies, coordinates data governance and stewardship, and promotes collaboration.

Aim 2. Expand and harmonize a sustainable informatics infrastructure that supports secure access to multiple interconnected data streams, promotes user-friendly tools for data analytics and research, and encourages data sharing.

Aim 3. Implement patient-centered strategies to integrate research into clinical practice and improve conduct of clinical and translational trials.

Aim 4. Provide multidisciplinary, data-driven research training to students, residents, and faculty.