AI-Enabled Patient Engagement Tools for Early Health Risk Management
Upcoming

AI-Enabled Patient Engagement Tools for Early Health Risk Management

A proposed feasibility study on accessible, AI-enabled digital tools that help people engage earlier with their health — co-designed with communities and healthcare stakeholders, in partnership with Sun Life.

Overview

Many people at increased health risk are largely asymptomatic — and so engage with care late, if at all. This proposed feasibility study asks how accessible, context-sensitive digital tools can encourage earlier, person-centred engagement in health management, building trust and lowering the barriers to care.

The work is led by Dr. Omer Ali with a multidisciplinary SETU team spanning computing, embedded systems, behavioural science and public health, in partnership with Sun Life.

Proposed approach

A mixed-methods study that begins with stakeholder consultation and community needs analysis, then co-designs and evaluates three proof-of-concept tools:

  1. a conversational support agent for personalised, empathetic health dialogue;
  2. a lifestyle recommendation system that suggests context-aware health actions; and
  3. a coordination assistant to simplify appointment scheduling and follow-up.

Prototypes are built and tested iteratively using anonymised and/or synthetic health data, with usability testing, focus groups and stakeholder feedback throughout — and privacy and data governance embedded from the start.

Status — seeking collaborators

This programme is in preparation for submission to Research Ireland’s next call. I am actively seeking collaborators and partners — across digital health, behavioural science, public health and industry — to strengthen the consortium. If that sounds like you, please get in touch. (Dates and scope shown here are anticipated and subject to funding.)