Conversational AI for patient reported outcomes

The communication between patients and healthcare institutions is increasingly moving to digital applications. Whereas information about the patient’s wellbeing is typically collected by means of a questionnaire, this is a tedious task for many patients, especially when it has to be done periodically, and may result in incomplete or imprecise input. Much can be gained by making the process of filling in such questionnaires more interactive, by deploying a conversational agent that can not only ask the questions, but also ask follow-up questions and respond to clarification questions by the user. We propose to deploy and test such a system.

Our proposed research aligns well with the WP3 focus on human-AI communication, and will lead to re-usable conversation patterns for conducting questionnaires in healthcare. The work benefit from existing experience with patient-provider communication within Philips and build on the SUPPLE framework for dialog management and sequence expansion.

Output

A dataset on conversation(s) between a patient and a conversational AI

A dialog model derived from the dataset

Scientific publication

Project Partners:

• Philips Electronics Nederland B.V., Aart van Halteren
• Stichting VU, Koen Hindriks

Primary Contact: Aart van Halteren, Philips Research