Replacing EHR structured data with explicit representations

As part of a project to develop a roadmap for the creation of a multi-center fully identified patient data warehouse involving all State Universities of New York State (SUNY), we’ve examined patient records stored in an EHR database to 1) determine what its contents are intended to represent, and 2) develop ontologically sound models based on the principles of Ontological Realism and Referent Tracking (Ceusters, Chiun Yu Hsu, & Smith, 2014; Smith & Ceusters, 2010). The exploration of the EHR database is driven by identifying the structures that contain answers to questions that might be obtained with relative ease using the EHR system’s user interface but that are difficult to find by working directly with the database, for example: ‘what diagnoses have been made about which disorders a specific patient is suffering from; when were those diagnoses made and by whom; what entities are those diagnoses about?’ This abstract presents issues with the data model currently used in the EHR database and an approach to address them.