An AI reasoning tool for identifying and managing health issues of people with intellectual disability.
Video description: A two minute overview of the benefits of early detection of health changes for people living with disability, and the goals and development plans for the Know Me, Support Me tool.
Early detection of health changes
People with intellectual disability often rely on caregivers to access health care, yet early signs of deteriorating physical or mental health are frequently missed. Diagnostic overshadowing, communication barriers, and limited caregiver health literacy can lead to symptoms being misattributed to the disability itself or behaviours of concern. Comorbid conditions and underreporting further complicate timely care.
The project to develop EarlyCare AI, an accessible mobile AI reasoning tool, to support earlier detection of health changes and improve care for people with intellectual disability was funded by MRFF. As the first tool of its kind in Australia and globally, it has strong potential to improve outcomes through earlier intervention and better care planning.
The tool will analyse behavioural and health cues to assist early detection, support clearer communication of symptoms to providers, and generate personalised support plans in consultation with health professionals.
Development includes stakeholder co-design, iterative testing, and a pilot trial with 200 participants comparing AI-supported care with usual support.
This work aligns with the National Roadmap for Improving the Health of People with Intellectual Disability, which highlights the need for models of care that incorporate digital solutions to support decision-making, communication, and proactive health management.
Investigators
- University of NSW: A/Prof Margo Barr, Dr Peri O’Shea, Prof Karen Fisher, Ms Erin Forrester, Assoc Prof Natalie Taylor, Dr Cathy O’Callaghan, Dr Nishant Valecha, Dr Shona Bates, Peter Brown
- Aruma: Mrs Lisa Hutchinson
- The Kids Institute: Dr Ann Skoss
- University of Sydney: Dr Frank Iorfino, Dr Janelle Weise Prof Vivienne Riches
- Western Sydney University: Prof Nathan Wilson
- University of New England: Prof Stuart Wark
- University of Queensland: Prof Rhonda Faragher
- Gold Coast University Hospital: Dr Dinesh Palipana
- 7DX: Mr Julian Ward
- UNCAPT: Mr Ebenezer Eyeson-Annan
- Livit Disability Support: Ms Kathleen Woolford (),
- NDIS Quality and Safeguards Commission: Dr Donna Gillies
- CESPHN: Dr Brendan Goodger Life Without Barriers: Mrs Cat Lancaster
Partners
Aruma, Life Without Barriers, CESPHN, 7DX, UNCAPT, Community Living Australia, National Centre of Excellence in Intellectual Disability Health, Microboards Australia.
Stages
Stage 1: Currently working on
This first phase of the study explores how frontline disability service providers recognise changes in health and wellbeing, escalate concerns, and use systems to support care. It also examines opportunities for digital or AI-supported tools to improve care quality and efficiency. This phase includes:
- Reviewing the literature
- Administrating questionnaires with people with intellectual disability
- Conducting in-depth interviews with key stakeholders
- Conducting online surveys with family, carers or disability support workers of people with intellectual disability, Advocates (including self) for/with people with intellectual disability, and Disability service providers and health service providers of people with intellectual disability
All of the information collected will be considered at the co-design workshops to co-designing the AI tools with people with intellectual disability, carers, families, service providers and stakeholders (prior to and post prototype development).
- Administered questionnaire PISCF – people with intellectual disability (easy read)
- Key informant interview PISCF
- Online survey PISCF
- Co-design workshop PISCF
Stage 2: Year 2 – 2027
Cycles of testing of the AI with people with intellectual disability, caregivers, and health providers under different scenarios.
(more details once stage 1 completed)
Stage 3: Years 3 and 4 – 2028 and 2029
Conducting a pilot trial comparing: (a) AI-supported care with (b) usual support.
Trial arms will be compared using service provider data, health outcomes, consumer experiences, and costs through surveys, interviews, and service records.
Findings will guide potential large-scale trials, broader implementation, and adoption.
(more details once stage 1 and 2 completed)
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