No abstract

Background Integration of health data systems is an open problem. Most of the active initiatives are based on the use of standards. However, achieving a widely and generalized compliment of such standards still seems a costly task that will take a long time to be completed. Even more, most of the standards are proposed for a specific use, without integrating other needs. Objectives We propose an alternative to get a unified view of health-related data, valid for several uses, that unites heterogeneous data sources. Methods Our proposal integrates developments made so far to automatically learn how to extract and convert data from different health-related systems. It enables the creation of a single multipurpose point of access. Results We present the EhRagg notion and its related concepts. EHRagg is defined as a middleware that, following the FAIR principles, integrates health data sources offering a unified view over them.

Abstract. Everyday methods providing managers with elaborated information making more comprehensible the results obtained of queries over OLAP systems are required. This problem is relatively recent due to the huge amount of information they store, but so far there are few proposals facing this issue, and they are mainly focused on presenting the information to the user in a comprehensible language (natural language). Here we go further and introduce a new mathematical formalism, the Semantic Interpretations, to supply the user not only understandable responses, but also semantically meaningful results.

In this paper, we propose a new approach for accessing the electronical health records (EHR), and we apply it to the cardiology medical specialty. Though the use of EHR improves the storage and access to the information in it regarding the previous health records in papers, it entails the risk of having the same problems of huge size and of becoming inoperative and really difficult to handle, especially if the user is looking for a specific data item. Our proposal is based on the contextualization of the access, providing the user with the most important information for the assistance act in which he/she is involved. To do this, we define the set of possible contexts and consider different aspects of the pertinence of the documents to each context. We do it by using fuzzy logic and pay special attention to the efficiency, due to the huge size of the involved databases. Our proposal does not limit the access to the EHR, but establishes a prioritization based on the access needs, which provides the system with an additional advantage, easily enabling the use of new terminals and devices like tablet PCs and PDAs, which have great limitations in the interfaces.

The main purpose of this paper is to contextualize the access to the huge amount of results and reports that a Hospital Information System (HIS) can reach to have. Our target is to integrate a semantic layer with the HIS, so that the user can employ this layer to access just the precise information needed, under his working context. Here we propose a new navigation system based on the semantic characteristics of the data acceded, their complementary characteristics, properties and relations, providing so the HIS with a new tool to solve an evident problem for the users.