Scenario-oriented information extraction from electronic health records

Providing a comprehensive set of relevant information at the point of care is crucial for making correct clinical decisions in a timely manner. Retrieval of scenario specific information from an extensive electronic health record (EHR) is a tedious, time consuming and error prone task. In this paper, we propose a model and a technique for extracting relevant clinical information with respect to the most probable diagnostic hypotheses in a clinical scenario. In the proposed technique, we first model the relationship between diseases, symptoms, signs and other clinical information as a graph and apply concept lattice analysis to extract all possible diagnostic hypotheses related to a specific scenario. Next, we identify relevant information regarding the extracted hypotheses and search for matching evidences in the patient´s EHR. Finally, we rank the extracted information according to their relevancy to the hypotheses. We have assessed the usefulness of our approach in a clinical setting by modeling a challenging clinical problem as a case study.