A conversational agent for querying Italian Patient Information Leaflets and improving health literacy

In the last years, the rise of digital technologies has enormously augmented the possibility for people to access health information and consult online versions of Patient Information Leaflets (PILs), enabling them to improve their knowledge about medication and adherence to therapies. However, health information may often be difficult to consult and comprehend due to an excessively lengthy and undersized text, coupled with the presence of many incomprehensible medical terms. To face these issues, this paper proposes a conversational agent as a valuable solution to simplify health information retrieval and improve health literacy in Italian by codifying PILs and making them query-able in natural language. In particular, the system has been devised to: i) comprehend natural language questions on medicines of interest; ii) proactively ask the user or automatically infer from the dialog state all the missing information necessary to generate an answer; iii) extract the answer from a structured knowledge base built from PILs of registered drugs. An experimental study has been carried out to evaluate both the performance and usability of the proposed system. Results showed an adequate ability of the system to handle most of the dialogues started by participants correctly, good users satisfaction, and, thus, proved its feasibility and usefulness.