Building an Ontology-Based Electronic Health Record System

Electronic health record (EHR) solutions are complex, spanning multiple specialties and domains of expertise. These systems need to handle clinical concepts, temporal data, documents, and financial transactions, which leads to a large code base that is tightly coupled with data models and inherently hard to maintain. These difficulties can greatly increase the cost of developing EHR systems, result in a high failure rate of implementation, and threaten investments in this sector. Moreover, due to the wide variance in the level of detail across different settings, data exchange is becoming a serious problem, further increasing the cost of development and maintenance. To overcome these issues, we adopt ontologies to model our proposed EHR solution, not only allowing code reuse; but also enabling later extension and customization. Adopting software factory techniques, we build tools to transform ontological models into deployment-ready code. This automatically provides handling of data persistence, access, and exchange. Business logic is expressed as ontology-based process flows and rules, ensuring data quality and supporting special needs. This logic is enforced transparently and can be modified on the fly. We optimized the user experience by facilitating fast data entry and retrieval. In this paper, we present the requirements of an effective EHR solution, explain the techniques we employed, describe the main modules of our proposed system, and discuss the technical decisions we made.