Visualizing Semantic Structure of a Clinical Text Document

The increasing use of Electronic Health Records (EHRs) in healthcare delivery settings has led to increase availability of electronic clinical data. They generate a lot of patients’ clinical data each day, requiring physicians to review them to find clinically relevant information of different patients during care episodes. The availability of electronically collected healthcare data has created the need of computational tools to analyze them. One of the types of data which doctors have access to is clinical notes that resides in electronic health records. These notes are useful as they provide comprehensive information about patients’ health histories with many practical uses. For example, doctors always review these notes during care episodes to appraise themselves about the health history of a patient. These reviews are currently manual where a doctor reads a patient’s chart while looking for specific clinical information. Without the proper support, this manual process leads to information overload and increases physician cognitive workload. Current electronic health records (EHRs) do not provide support to help physicians reduce cognitive workload when completing clinical tasks. This is especially true for long clinical documents which require quick review at the point of care. The growing amount of clinical documentation available in EHRs has arose the need of tools that support synthesize of information in EHRs. The use of visual analytics to explore healthcare data is one such research direction to address this problem. However, existing visualization techniques are mainly based on structured electronic health record and rarely support therapeutic activities. Therefore, visualization of unstructured clinical records to support clinical practice is required. In this paper we propose a unique approach for graphically representing and visualizing the semantic structure of a clinical text document to aid doctors in reviewing electronic clinical notes. A user evaluation demonstrates that the proposed method for visualizing and navigating a document’s semantic structure facilitates a user’s document information exploration.