Abstract
A major challenge for radiologists is obtaining meaningful clinical follow-up information for even a small percentage of cases encountered and dictated. Traditional methods, such as keeping medical record number follow-up lists, discussing cases with rounding clinical teams, and discussing cases at tumor boards, are effective at keeping radiologists informed of clinical outcomes but are time intensive and provide follow-up for a small subset of cases. To this end, the authors developed a picture archiving and communication system-accessible electronic health record (EHR)-integrated program called Correlate, which allows the user to easily enter free-text search queries regarding desired clinical follow-up information, with minimal interruption to the workflow. The program uses natural language processing (NLP) to process the query and parse relevant future clinical data from the EHR. Results are ordered in terms of clinical relevance, and the user is e-mailed a link to results when these are available for viewing. A customizable personal database of queries and results is also maintained for convenient future access. Correlate aids radiologists in efficiently obtaining useful clinical follow-up information that can improve patient care, help keep radiologists integrated with other specialties and referring physicians, and provide valuable experiential learning. The authors briefly review the history of automated clinical follow-up tools and discuss the design and function of the Correlate program, which uses NLP to perform intelligent prospective searches of the EHR. © RSNA, 2017.
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More From: Radiographics : a review publication of the Radiological Society of North America, Inc
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