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Co-Designing an AI Chatbot to Improve Patient Experience in the Hospital; A human-centered design...
Xin Wang, Samer M Abubaker, Grace T Babalola, Stephanie Tulk Jesso

CHI 2024: The ACM CHI Conference on Human Factors in Computing Systems
Session: Case Studies: Conversational Agents and Responsible AI

Patient experience (PX) is an important reflection of healthcare quality and is highly related to patient health outcomes and hospital reputation of within the communities they serve. PX data reported by patients is also crucial for hospitals to improve the services they provide, however, current approaches to survey and analyze PX data have many limitations. Our team collaborated with United Health Services (UHS), a New York healthcare system, to co-design a prototype chatbot application for patients to use while in the hospital, yielding more accurate PX data, but also an opportunity for staff to respond in real-time. We discuss our human-centered design process, which entailed interviews, data mining, qualitative analysis, and the application of ChatGPT and other algorithms to recognize relevant PX complaints from natural language data. Through ongoing collaboration, we are developing a chatbot application to elicit PX feedback and allow PX experts to improve patient experience in real-time.

Web:: https://programs.sigchi.org/chi/2024/...

Pre-recorded video presentations for Case Studies at CHI 2024