The aim of this work is to investigate the effectiveness of novel human-machine interaction paradigms for eHealth applications. In particular, we propose to replace usual human-machine interaction mechanisms with an approach that leverages a chat-bot program, opportunely designed and trained in order to act and interact with patients as a human being. Moreover, we have validated the proposed interaction paradigm in a real clinical context, where the chat-bot has been employed within a medical decision support system having the goal of providing useful recommendations concerning several disease prevention pathways. More in details, the chat-bot has been realized to help patients in choosing the most proper disease prevention pathway by asking for different information (starting from a general level up to specific pathways questions) and to support the related prevention checkup and the final diagnosis. Preliminary experiments about the effectiveness of the proposed approach are reported.

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Introduction Prenatal exposure to valproate and related substances is associated with a risk of malformations and/or neurodevelopmental disorders. In France, prescription and dispensing conditions of oral valproate forms are subject to risk minimization measures for girls and women of childbearing potential with the aim to limit pregnancy under this treatment. These risk minimization measures were issued in 2015 and were strengthened in 2018. Objective We aimed to evaluate compliance with prescription and dispensing conditions of valproate for oral administration: an annual prescription from a specialist and a signed risk acknowledgment form. Methods Two prospective observational surveys were carried out between 2018 and 2020 on a representative sample of French community pharmacies. Data were collected from female patients aged 2-49 years presenting to one of the participating pharmacies with a valproate prescription. Results In total, 1067 and 824 valproate prescriptions were analyzed in 2018 and 2020, respectively, the majority of which were for girls and women of childbearing potential (≥ 92%). The prescription and dispensing conditions for valproate were met in 42% of cases (95% confidence interval 39-45) in 2018 and in 47% of cases (95% confidence interval 43-50) in 2020. Compliance levels were higher for prescriptions from neurologists (≥ 60%) than from other prescribers (≤ 45%). Conclusions In France, the implementation of specific risk minimization measures for girls and women of childbearing potential with respect to oral valproate forms and related substances requires a stronger involvement of stakeholders. Increased awareness and compliance among healthcare professionals regarding risk minimization measures could limit prenatal exposure to valproate.A French language translation of this article is included in the Electronic Supplementary Material.

BACKGROUND Seeking medical information can be an issue for physicians. In the specific context of medical practice, chatbots are hypothesized to present additional value for providing information quickly, particularly as far as drug risk minimization measures are concerned. OBJECTIVE This qualitative study aimed to elicit physicians’ perceptions of a pilot version of a chatbot used in the context of drug information and risk minimization measures. METHODS General practitioners and specialists were recruited across France to participate in individual semistructured interviews. Interviews were recorded, transcribed, and analyzed using a horizontal thematic analysis approach. RESULTS Eight general practitioners and 2 specialists participated. The tone and ergonomics of the pilot version were appreciated by physicians. However, all participants emphasized the importance of getting exhaustive, trustworthy answers when interacting with a chatbot. CONCLUSIONS The chatbot was perceived as a useful and innovative tool that could easily be integrated into routine medical practice and could help health professionals when seeking information on drug and risk minimization measures.