AUTHOR=Souvignet Julien , Declerck Gunnar , Trombert-Paviot Béatrice , Asfari Hadyl , Jaulent Marie-Christine , Bousquet Cédric 

TITLE=Semantic Queries Expedite MedDRA Terms Selection Thanks to a Dedicated User Interface: A Pilot Study on Five Medical Conditions

JOURNAL=Frontiers in Pharmacology

VOLUME=10

YEAR=2019

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2019.00050

DOI=10.3389/fphar.2019.00050

ISSN=1663-9812

ABSTRACT=<p><bold>Background:</bold> Searching into the MedDRA terminology is usually limited to a hierarchical search, and/or a string search. Our objective was to compare user performances when using a new kind of user interface enabling semantic queries versus classical methods, and evaluating term selection improvement in MedDRA.</p><p><bold>Methods:</bold> We implemented a forms-based web interface: OntoADR Query Tools (OQT). It relies on OntoADR, a formal resource describing MedDRA terms using SNOMED CT concepts and corresponding semantic relations, enabling terminological reasoning. We then compared time spent on five examples of medical conditions using OQT or the MedDRA web-based browser (MWB), and precision and recall of the term selection.</p><p><bold>Results:</bold> OntoADR Query Tools allows the user to search in MedDRA: One may enter search criteria by selecting one semantic property from a dropdown list and one or more SNOMED CT concepts related to the range of the chosen property. The user is assisted in building his query: he can add criteria and combine them. Then, the interface displays the set of MedDRA terms matching the query. Meanwhile, on average, the time spent on OQT (about 4 min 30 s) is significantly lower (−35%; <italic>p</italic> &lt; 0.001) than time spent on MWB (about 7 min). The results of the System Usability Scale (SUS) gave a score of 62.19 for OQT (rated as good). We also demonstrated increased precision (+27%; <italic>p</italic> = 0.01) and recall (+34%; <italic>p</italic> = 0.02). Computed “performance” (correct terms found per minute) is more than three times better with OQT than with MWB.</p><p><bold>Discussion:</bold> This pilot study establishes the feasibility of our approach based on our initial assumption: performing MedDRA queries on the five selected medical conditions, using terminological reasoning, expedites term selection, and improves search capabilities for pharmacovigilance end users. Evaluation with a larger number of users and medical conditions are required in order to establish if OQT is appropriate for the needs of different user profiles, and to check if conclusions can be extended to other kinds of medical conditions. The application is currently limited by the non-exhaustive coverage of MedDRA by OntoADR, but nevertheless shows good performance which encourages continuing in the same direction.</p>