The semantic aspect of the system combined with its generic entity-centered vision enables the processing of a large range of clinical questions. A finer annotation of the clinical texts and the addition of specific functionalities would significantly improve the results. Despite their semantic annotation, searching within clinical narratives remained the major challenge of the system. It also allows to fully exploit the semantic description of health information. It enables more genericity in the information retrieval process. Furthermore, the targeted sources of information and the search engine–related or data-related limitations that could explain the results for each criterion were also observed.Ĭonclusions: The entity-centered vision contrasts with the usual patient-centered vision adopted by existing systems. The system succeeded in fully automating 39% (29/74) of the criteria and was efficiently used as a prescreening tool for 73% (54/74) of them.
Results: We assessed the ability of the system to assist the search for 95 inclusion and exclusion criteria originating from 5 randomly chosen clinical trials from RUH. The system adopts an entity-centered vision that provides generic search capabilities able to express data requirements in terms of the whole set of interconnected conceptual entities that compose health information. Methods: The semantic health data warehouse relies on 3 distinct semantic layers: (1) a terminology and ontology portal, (2) a semantic annotator, and (3) a semantic search engine and NoSQL (not only structured query language) layer to enhance data access performances. Objective: This study aimed to present a proof of concept of this semantic health data warehouse, based on the data of 250,000 patients from RUH, and to assess its ability to assist health professionals in prescreening eligible patients in a clinical trials context. In 2017, Rouen University Hospital (RUH) initiated the design of a semantic health data warehouse enabling both semantic description and retrieval of health information. Hôpital Charles-Nicolle, 1 Rue de GermontĮmail: The huge amount of clinical, administrative, and demographic data recorded and maintained by hospitals can be consistently aggregated into health data warehouses with a uniform data model.
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