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

Abstract

Background: 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.Methods: 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.Results: 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%; p < 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%; p = 0.01) and recall (+34%; p = 0.02). Computed “performance” (correct terms found per minute) is more than three times better with OQT than with MWB.Discussion: 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.

How to interact with medical terminologies? Formative usability evaluations comparing three approaches for supporting the use of MedDRA by pharmacovigilance specialists

“…Although many studies have focused on software based on standardized terminologies, few have actually evaluated the usability of these technologies to improve it [ 3 , 4 , 50 – 53 ]. In the context of the use of MedDRA terminology, to our knowledge only one study has evaluated its usability ([ 11 ] on OQT). However, in this study the usability evaluation was only carried out subjectively using the SUS questionnaire; even if the latter enables to assess the level of satisfaction of the participants, it does not help in understanding what the users liked or disliked, and what features of the tools may have disturbed the performance of their tasks.…”

“…OntoADR Query tool (OQT) is a web-based interface to query OntoADR semantic resource [11]. It uses forms to support the creation of queries based on properties extracted from SNOMED CT semantic relationships.…”

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Fig. 2 Comparison between methods to search in the MedDRA terminology (adapted from [ 11 ] with permission). Left, usual method: string search and hierarchy search.

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Ontological and Non-Ontological Resources for Associating Medical Dictionary for Regulatory Activities Terms to SNOMED Clinical Terms With Semantic Properties

“…While McKnight (1999) recognized the need for user-directed composition of controlled health terminologies, and the required improvement of the user interface in the context of data entry, we believe that such user interface is also of great importance to enable composition for data retrieval. In a previous work, we implemented OntoADR query tools, a graphical user interface that relies on OntoADR, and compared the performances of eight users in selecting MedDRA PTs with the MedDRA web browser in a pilot study on five medical conditions (Souvignet et al, 2019). Although the number of medical conditions was low, we observed a statistically significant improvement by using OntoADR query tools compared with the MedDRA web browser for selecting MedDRA PTs (+27% precision and +34% recall).…”