Project Details
Description
2024 MRFF Early to Mid-Career Researchers
Medication safety is a global concern, particularly in residential aged care (RAC) where polypharmacy is prevalent. However, deprescribing, which is crucial for addressing medication-related issues, is not widely adopted in Australian RAC. This is primarily due to the lack of tailored deprescribing pathways and limited stakeholder communication. This research will address this issue through a highly innovative Artificial intelligence (AI)-
augmented digital deprescribing platform called AiCT-Med (Artificial intelligence-augmented Clinical decision support Targeting Medicine optimisation and deprescribing).
The project aims to: (i) develop and validate the AiCT-Med; (ii) implement and evaluate the impact of the AiCT-Med on medicine use, clinical, systems and economic outcomes and (iii) develop freely accessible online deprescribing resources to promote translation.
We have forged critical partnerships with key partners in medication management including BESTMED (used by 1000+ RAC facilities in Australia) and Choice Aged Care (serving 350+ facilities). AiCT-Med's development involves close collaboration with these partners to ensure seamless integration, enhancing user experience and workflow optimization. Our project also garnered support from professional groups such as the Australian Deprescribing Network and the Australian Association of Gerontology to contribute to and endorse project translation. Additionally, a Consumer Advisory Group provides vital input into research direction.
The project will deliver: (1) AiCT-Med, a platform seamlessly integrating with electronic systems to enhance deprescribing practices and ensure high-quality care, fostering collaboration among stakeholders. (2) A comprehensive resource will support AiCT-Med adoption, featuring an aged care industry guide for AI integration and an open-source web app for AI predictive models, promoting research translation and stakeholder engagement
in deprescribing initiatives.
Medication safety is a global concern, particularly in residential aged care (RAC) where polypharmacy is prevalent. However, deprescribing, which is crucial for addressing medication-related issues, is not widely adopted in Australian RAC. This is primarily due to the lack of tailored deprescribing pathways and limited stakeholder communication. This research will address this issue through a highly innovative Artificial intelligence (AI)-
augmented digital deprescribing platform called AiCT-Med (Artificial intelligence-augmented Clinical decision support Targeting Medicine optimisation and deprescribing).
The project aims to: (i) develop and validate the AiCT-Med; (ii) implement and evaluate the impact of the AiCT-Med on medicine use, clinical, systems and economic outcomes and (iii) develop freely accessible online deprescribing resources to promote translation.
We have forged critical partnerships with key partners in medication management including BESTMED (used by 1000+ RAC facilities in Australia) and Choice Aged Care (serving 350+ facilities). AiCT-Med's development involves close collaboration with these partners to ensure seamless integration, enhancing user experience and workflow optimization. Our project also garnered support from professional groups such as the Australian Deprescribing Network and the Australian Association of Gerontology to contribute to and endorse project translation. Additionally, a Consumer Advisory Group provides vital input into research direction.
The project will deliver: (1) AiCT-Med, a platform seamlessly integrating with electronic systems to enhance deprescribing practices and ensure high-quality care, fostering collaboration among stakeholders. (2) A comprehensive resource will support AiCT-Med adoption, featuring an aged care industry guide for AI integration and an open-source web app for AI predictive models, promoting research translation and stakeholder engagement
in deprescribing initiatives.
| Acronym | MRFF2024 |
|---|---|
| Status | Active |
| Effective start/end date | 1/09/25 → 31/08/30 |