The vision of predictive, personalized, preventive, participatory (P4) medicine is gradually advancing towards reality. Given an increasing emphasis on optimizing use of routine health data for research, informatics has become a central pillar in facilitating an effective clinical and translational science enterprise. Although more data are available than ever, only a fraction is being curated, integrated, understood, and analyzed. At Mount Sinai, informatics is increasingly driving research that informs precision medicine, population health, and biomedical big data science.
Since 2013, eight hospitals and a network of ambulatory practices have been integrated to form the Mount Sinai Health System (MSHS). Mount Sinai has invested significant resources into the rapid integration of these hospitals and practices into a unified Epic electronic health record (EHR) with an integrated clinical data warehouse, providing an unprecedented foundation for coordinating healthcare delivery with research and data science initiatives to develop a Learning Health System (LHS).
The informatics initiatives are focused on building a biomedical informatics ecosystem that is: 1) more accessible to stakeholders, ensuring broad, user-friendly, integrated access to diverse data sources while maintaining robust, secure, bidirectional information flow between research programs and point-of-care information systems through a flexible infrastructure; and 2) more actionable, to enable innovative applications of translational bioinformatics research and data-driven medicine. To achieve these overarching 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 collaborative team science.
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 reproducible research, and encourages data sharing.
Aim 3. Implement patient-centered informatics strategies to integrate research into clinical practice and to catalyze improved conduct of clinical and translational trials.
Aim 4. Provide data science and informatics training that engages students, residents and faculty with multidisciplinary real-life data-driven research projects, and lowers the bar to successful application of informatics for translational research.