STTR Phase I: Digital Advance Care Planning Platform

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project may significantly improve the quality of end-of-life care through Advanced Care Planning (ACP). It is not always possible to align patients' end-of-life wishes with the care they receive. The proposed project develops a digital platform for ACP.

This system will use a machine-learning guided dialogue to deliver personalized audiovisual content adapted to individual and cultural preferences. This system may improve palliative end-of-life care for many.

This Small Business Technology Transfer (STTR) Phase I project addresses the technical challenge of providing a personalized platform that performs digital motivational interviewing and adapts audiovisual content and input queries to patients’ personae. A major hurdle of applying machine learning to ACP is the variability in personal and cultural factors, as well as validation of the integrity of the responses.

The project centers on the collection and analysis of psychometric data from two patient surveys combined with other health information. The project objectives are: (a) Execute a benchmark training patient survey for the machine-learning algorithm for a study on the influence of gender, ethnicity, and health status on ACP; (b) Develop a reliable persona detection tool using machine learning algorithms guided by the data, avoiding the introduction of unconscious bias; (c) Demonstrate that the platform improves completion rates and patient satisfaction compared to ACP administered by human health workers and static online platforms without machine learning; and (d) Demonstrate the alignment of the digital process with patient wishes.

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.