SBIR Phase I: Create Effective COVID-19 Chatbots through High Patient Engagement Phase I

Smartbot360, Riverside CA

Investigators

Abstract

The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide on-demand customized health information. Chatbots are automated communication agents that have been successful in other sectors, but to date they have enjoyed limited success in patient engagement during the COVID-19 pandemic. Increased patient engagement leads to better health outcomes and cost savings. This project will develop a COVID-19 chatbot to address common questions and transactions, freeing healthcare staff for more complex cases and providing information to patients seeking to minimize office visits during periods of social distancing. This Small Business Innovation Research (SBIR) Phase I project will advance development of patient engagement via chatbots. This project represents a chatbot as a graph of states, wherein a transition is based on the user message. The proposed chatbot optimizer extends this model by applying reinforcement learning to dynamically compute the best response given the user profile and context. The objective of the optimizer is to reach a success state (for example, make an appointment with a counselor), accounting for the fact that a user (patient) may drop out at any time; previous work on goal-oriented chatbots has generally not included this possibility. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.