A Hybrid Reporting Platform for Extended RadLex Coding Combining Structured Reporting Templates and Natural Language Pro
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ORIGINAL PAPER
A Hybrid Reporting Platform for Extended RadLex Coding Combining Structured Reporting Templates and Natural Language Processing Florian Jungmann 1 & G. Arnhold 1 & B. Kämpgen 2 & T. Jorg 1 & C. Düber 1 & P. Mildenberger 1 & R. Kloeckner 1
# Society for Imaging Informatics in Medicine 2020
Abstract Structured reporting is a favorable and sustainable form of reporting in radiology. Among its advantages are better presentation, clearer nomenclature, and higher quality. By using MRRT-compliant templates, the content of the categorized items (e.g., select fields) can be automatically stored in a database, which allows further research and quality analytics based on established ontologies like RadLex® linked to the items. Additionally, it is relevant to provide free-text input for descriptions of findings and impressions in complex imaging studies or for the information included with the clinical referral. So far, however, this unstructured content cannot be categorized. We developed a solution to analyze and code these free-text parts of the templates in our MRRT-compliant reporting platform, using natural language processing (NLP) with RadLex® terms in addition to the already categorized items. The established hybrid reporting concept is working successfully. The NLP tool provides RadLex® codes with modifiers (affirmed, speculated, negated). Radiologists can confirm or reject codes provided by NLP before finalizing the structured report. Furthermore, users can suggest RadLex® codes from free text that is not correctly coded with NLP or can suggest to change the modifier. Analyzing free-text fields took 1.23 s on average. Hybrid reporting enables coding of free-text information in our MRRT-compliant templates and thus increases the amount of categorized data that can be stored in the database. This enhances the possibilities for further analyses, such as correlating clinical information with radiological findings or storing high-quality structured information for machine-learning approaches. Keywords Structured reporting . Natural language processing . RadLex . Medical informatics . Database
Introduction Communicating the results of a diagnostic study is a crucial part of a radiologist’s work [1]. The radiological report is the vehicle to communicate imaging findings and its interpretation in the clinical context [2]. In most cases, the written report represents the best way to transmit information to the referrer [1]. These reports are usually created by speech recognition and range from being little structured to unstructured. Radiologists often use subjective phrases in their reports without formal consensus on their meaning or impact. Lee et al. asked radiologists and clinical referrers about the meaning of * Florian Jungmann [email protected] 1
Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckst. 1, 55131 Mainz, Germany
2
Empolis Information Management GmbH, Kaiserslautern, Germany
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