The University of Wollongong in partnership with QPS Benchmarking and Warrigal Care has been awarded an ARIIA grant for their project ‘Implementing an AI Tool NutriTrack to Enhance Nutrition Care in Aged Care’.
Malnutrition has severe health consequences for older people, e.g., weakened immune system, damaged organs, and increased mortality. The methods for screening malnutrition in aged care are time-consuming and thus not timely conducted. Medical and aged care staff spend much time capturing valuable client data, including diagnosis, assessment, and malnutrition indicators, in electronic health records (EHR), often in free-text care notes.
Recent advancements in artificial intelligence and natural language processing provide great opportunities for extracting indicator data from EHR and automating clinical diagnoses and risk predictions [1, 2].
We seek funding to expand our preliminary malnutrition prediction model that has been trained on EHR data from 4,405 clients in 40 residential care facilities [3] to the national dataset captured by QPS Benchmarking. We will scale up and commercialise the decision support tool NutriTrack that we will develop. We will integrate NutriTrack into the quality improvement system to improve nutrition care governance, care model and workflow. This will bring in further benefits for dementia, social isolation, mental health and wellbeing, and palliative care.
Will conduct pre- and post-implementation in the partner aged care organisation Warrigal Care to evaluate the success of NutriTrack and promote the innovative translational research project.