Seeing the whole picture: integrated pre-surgery reports with PreOptique.

BACKGROUND: Information technology has transformed the way healthcare is conducted. There is a deluge of patient data dispersed in different systems that are commonly not interoperable. As a result, access to patient data has become a major bottleneck for healthcare professionals that struggle to find the relevant information in a timely way and without missing critical clinical information. RESULTS: We implemented PreOptique, a novel hybrid semantic and text-based system that was commissioned by a large hospital in Norway for providing integrated access to patient health records scattered over several databases and document repositories. We use ontology-based data access (OBDA) for the seamless integration of the structured databases at the hospital through the Optique platform. We employ text analysis techniques to extract vital sign measures and clinical findings from patient documents. PreOptique was developed and deployed at the hospital. This solution demonstrates how OBDA technology can provide integrated data access to disparate structured sources in healthcare, without requiring the replacement of existing databases. Unstructured clinical texts are also mined to extract patient findings, while the graphical user interface (GUI) provides a single access point that hides the underlying complexity of the system. We ran a usability study with 5 target users, obtaining a system usability score (SUS) of 86.0. Further, participants in the study stressed the simplicity of the GUI and the integration of data sources enabled by the system. CONCLUSIONS: This pilot study showcases the use of OBDA technology and text analysis to enable the integration of patient data for supporting clinical surgery operations. PreOptique is usable and can be easily employed by medical personnel to find patient data in a timely way.

PepeSearch: Semantic Data for the Masses.

With the emergence of the Web of Data, there is a need of tools for searching and exploring the growing amount of semantic data. Unfortunately, such tools are scarce and typically require knowledge of SPARQL/RDF. We propose here PepeSearch, a portable tool for searching semantic datasets devised for mainstream users. PepeSearch offers a multi-class search form automatically constructed from a SPARQL endpoint. We have tested PepeSearch with 15 participants searching a Linked Open Data version of the Norwegian Register of Business Enterprises for non-trivial challenges. Retrieval performance was encouragingly high and usability ratings were also very positive, thus suggesting that PepeSearch is effective for searching semantic datasets by mainstream users. We also assessed its portability by configuring PepeSearch to query other SPARQL endpoints.