Health data management with an archetype driven EHR system in low ressource environments (EHRFlex).
In: Proceedings (Med-e-Tel - Global Telemedicine and eHealth, 14-16 April 2010, Luxembourg). Zürich: ISfTeH - International Soc. for Telemedicine & eHealth, 2010. 137-140
A semantically interoperable Electronic Health Record (EHR) is one of the most challenging research fields of health informatics. EHR standards that formally describe health data structures are a prerequisite for sharing medical records. CEN EN13606 is one of the most promising approaches to solve this problem since it covers the technical needs for semantic interoperability and, at the same time, incorporates a mechanism (archetype model), which allows clinical domain experts’ to participate in the definition of the medical content of an EHR system. In this proposal we present EHRflex, a generic archetype driven system that provides a flexible EHR solution. The graphical user interface is generated on-the-fly and allows to capture data according to the archetype descriptions of the user. This empowers the clinician and allows him to manage his own EHR system in a simple and generic way, assuring, in the same time, that the user works with underlying standardized data structures, which can be shared with other people and systems smoothly. EHRflex introduces EHR standards into the clinical routine practice by delivering a technical platform that works directly on archetype based data. Archteypes that have been defined externally can be used immediately after loading them into the system. Data is linked directly with generated widgets, which allows the clinician to interact and change the medical content. Within EHRflex the data is stored in XML format according to the underlying Reference Information Model. Modules for export and import allow interaction with external patient information. EHRflex shows that the dual model approach of CEN allows the separation of software development and definition of clinical concepts. This affords to satisfy the most diverse and constantly changing data requirements and to save cost-intensive software adjustments at the same time.