Mind the Gap! Developing Patient Responsive Information for Epilepsy

Abstract

AbstractTechnology must adapt to changing expectations about shifting patient needs and accessing health services. Standardised websites provide information often in the “frequently asked questions” format. There is little research about how much these answer the questions of people with epilepsy (PWE).This study used social media data to analyse the questions PWE have relating to “what would you ask a neurologist/epileptologist” and “do you have any questions relating to your epilepsy”. The study resulted in 2752 questions from PWE in Europe, North America and Australia, presented in the raw data format of natural language. Questions were themed using an unsupervised topic modelling algorithm to process and categorise the data into an aggregated question set.Many of the questions are not currently answered by Epilepsy charity and medical websites, and many centre on restrictions and fears about lifestyle. This study acts as the first stage toward the supervised topic classification: providing a list of questions to be submitted for answering by healthcare professionals required for a Virtual Assistant.The ultimate aim of the project is to generate a Virtual Assistant/Chatbot for the use of PWE to provide accurate and interactive responses to their real questions.