Demographic management in a federated healthcare environment.
OBJECTIVE: The purpose of this paper is to provide a further step toward the decentralization of identification and demographic information about persons by solving issues related to the integration of demographic agents in a federated healthcare environment. The aim is to identify a particular person in every system of a federation and to obtain a unified view of his/her demographic information stored in different locations. METHOD: This work is based on semantic models and techniques, and pursues the reconciliation of several current standardization works including ITU-T's Open Distributed Processing, CEN's prEN 12967, OpenEHR's dual and reference models, CEN's General Purpose Information Components and CORBAmed's PID service. RESULTS: We propose a new paradigm for the management of person identification and demographic data, based on the development of an open architecture of specialized distributed components together with the incorporation of techniques for the efficient management of domain ontologies, in order to have a federated demographic service. This new service enhances previous correlation solutions sharing ideas with different standards and domains like semantic techniques and database systems. The federation philosophy enforces us to devise solutions to the semantic, functional and instance incompatibilities in our approach. CONCLUSION: Although this work is based on several models and standards, we have improved them by combining their contributions and developing a federated architecture that does not require the centralization of demographic information. The solution is thus a good approach to face integration problems and the applied methodology can be easily extended to other tasks involved in the healthcare organization.