Integration through mapping — An OpenEHR based approach for research oriented integration of health information systems

The growing need for Healthcare Information Systems that meets standards of rigor and demand, as well as the need to provide health researchers with the best quality data, has created a major challenge with regard to interoperability in information systems. Nowadays it is common patient data to be dispersed by various systems. Modern systems are tending to adopt standards for modelling and communicating information, but this is not true for legacy systems, where the precision in terms of medical concepts are not standardized. Many times these systems are developed solutions to a specific needs of a medical service, without care for the terminology of clinical concepts representation or how it is structured in terms of semantic. Research relies heavily on the available data, and in context of Big Data analysis, the possibility of aggregating data from multiple, different and distributed sources in a meaningful and straightforward way is relevant. The main objective of this work is to propose an integration architecture that enables access to clinical data from different heterogeneous sources for research purposes. This paper presents an architecture based on the openEHR standard and a proof of concept of the mapping component that provides a tool for matching the attributes of openEHR Archetypes/Templates and fields of databases. With this approach all the data distributed in various repositories, legacy or openEHR are potentially available to the researcher, through the creation of AQL queries in order to get aggregated results for additional research activities.