Our central data repository contains electronic health records (EHR) for 12 million patients, across all five boroughs of New York City and the greater metropolitan area. The Network offers users access to 11 years of longitudinal, high-quality, research-ready data which adheres to the PCORnet data model. Within the INSIGHT CRN database, a limited dataset of patient health records are securely stored and reflect the diverse patient populations across five highly ranked academic medical centers in New York City: Albert Einstein School of Medicine/Montefiore Medical Center, Columbia University and Weill Cornell Medicine/New York-Presbyterian Hospital, lcahn School of Medicine/Mount Sinai Health System, Clinical Director’s Network, and New York University School of Medicine/Langone Medical Center. The Network has also successfully de-duplicated EHR records across the City’s fragmented healthcare landscape, revealing a more complete view of a patient’s dynamic pattern of care.
160 Million Encounters
The INSIGHT CRN central data repository provides researchers access to clinical encounters within our participating health systems, both for in-patients and out-patients. Additionally, our data repository contains real encounter dates, enabling more effective healthcare utilization and health systems research.
365+ Million Diagnoses
The INSIGHT CRN central data repository contains over 350 million clinical diagnoses on our patients. Clinical diagnoses are linked to visits and real dates, thus providing the foundational support for a wide variety of research, including the development of computable phenotypes for observational studies, the identification of specific diseases for public health surveillance projects, as well as patient cohort development for pragmatic clinical trials.
The INSIGHT CRN offers users access to the largest, most diverse urban clinical dataset in the country, reflecting the racial, ethnic, and socioeconomic diversity of New York City’s population. Available demographic variables include: date of birth, race, ethnicity, and gender. Additionally, the Network has emerged as a leader in linking clinical data to disparate data sources, including claims data and social determinants of health.