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

Background: Medical terminologies are commonly used in medicine. For instance, to answer a pharmacovigilance question, pharmacovigilance specialists (PVS) search in a pharmacovigilance database for reports in relation to a given drug. To do that, they first need to identify all MedDRA terms that might have been used to code an adverse reaction in the database, but terms may be numerous and difficult to select as they may belong to different parts of the hierarchy. In previous studies, three tools have been developed to help PVS identify and group all relevant MedDRA terms using three different approaches: forms, structured query-builder, and icons. Yet, a poor usability of the tools may increase PVS' workload and reduce their performance. This study aims to evaluate, compare and improve the three tools during two rounds of formative usability evaluation. Methods: First, a cognitive walkthrough was performed. Based on the design recommendations obtained from this evaluation, designers made modifications to their tools to improve usability. Once this re-engineering phase completed, six PVS took part in a usability test: difficulties, errors and verbalizations during their interaction with the three tools were collected. Their satisfaction was measured through the System Usability Scale. The design recommendations issued from the tests were used to adapt the tools. Results: All tools had usability problems related to the lack of guidance in the graphical user interface (e.g., unintuitive labels). In two tools, the use of the SNOMED CT to find MedDRA terms hampered their use because French PVS were not used to it. For the most obvious and common terms, the icons-based interface would appear to be more useful. For the less frequently used MedDRA terms or those distributed in different parts of the hierarchy, the structured query-builder would be preferable thanks to its great power and flexibility. The form-based tool seems to be a compromise. Conclusion: These evaluations made it possible to identify the strengths of each tool but also their weaknesses to address them before further evaluation. Next step is to assess the acceptability of tools and the expressiveness of their results to help identify and group MedDRA terms

Surveillance et détection des événements inhabituels en toxicovigilance : revue des méthodes pertinentes.

International audienceBACKGROUND: Declared cases of exposures related to potential toxic agents are reported through a national database, the French Network of Poison Centers, and account on average for 200,000 cases per year, including 75,000 to 80,000 symptomatic cases. These data are currently used to investigate signals from local, national or international institutional partners (such as hospitals, local health authorities, and the Rapid Alert System for Food and Feed). Our objective is to complete this classical toxicovigilance activity through the automated detection of unexpected or unusual events in order to identify precociously signals representing potential threats for public health. To reach this objective, the inventory of surveillance and detection methods of unexpected events is necessary.METHODS: A literature review was conducted via Scopus(®) and Pubmed(®) databases, completed with grey literature and data available on worldwide vigilance systems' websites.RESULTS: The most commonly used methods are disproportional measures in the field of pharmacovigilance, some of which are subject to a routine detection at regular time intervals. Criteria of signal generation differ from one system to another, which have implemented data filtering strategies before or after analysis, in order to decrease the number of generated signals and improve their priority level. These signals are then transmitted to an experts committee for a clinical and epidemiological evaluation, and at times, for informing the patient's medical records. We also notice an interest in other approaches such as surveillance methods of temporal series or symbolic methods for associative rules extraction between one or more drugs and one or more adverse effects, with the possibility to include other types of variables, such a demographic data. The developments of probabilistic-based algorithms have also been recently developed, opening new opportunities.CONCLUSION: These surveillance and detection methods are of high interest for the automated detection of signals from the French toxicovigilance network. The initial step to developing these methods consists in studying the statistical quality of data and targeting the needs and expectations of the toxicovigilance network for what we want and what we can detect