The Mount Sinai School of Medicine Enterprise Data Translational Architecture

Peter L. Elkin
Center for Biomedical Informatics and Department of Internal Medicine, Mount Sinai Medical Center


Abstract

Today clinical and research data are not comparable. Rarely can either clinical or research data be used beyond the study for which it was gathered. This is due in part to the lack of standardization in the naming of study fields. If there was standardization of naming and data-types for important data fields and the storage of data conformed to a consistent set of standard models then data from one experiment when appropriate could be used in future experiments. In this way our knowledge of biology and medicine would begin to grow exponentially. We propose to provide an easy method by which clinicians and researchers can codify their data and to store the output in a standard format that will easily and seamlessly allow data from one experiment or one research group to be used by another using intelligent electronic health records (iEHR).