Empowering CALD Home Care with AI: Minimising Paperwork, Maximising Workforce Capacity

Background 

This project is designed to support the aged care workforce in enhancing efficiency and effectiveness through the implementation of AI-powered digital technology. The primary focus is to deliver best practice interventions to older Australians living at home, particularly those from culturally and linguistically diverse (CALD) backgrounds. By piloting AI-driven speech recognition software EverYoung AI integrated with the CareWindow communication device or working as a standalone application, the project seeks to bridge language barriers, reduce administrative workloads, and enhance staff communication. This innovative approach will provide real-time translation, transcription, progress notes generation and an easy-to-use video calling device, ultimately streamlining case and progress notes and improving communication with clients. The overarching goal is to enable staff to dedicate more time to direct care, supporting person-centred and culturally sensitive services for aged care participants. 

The expected outcomes and impact of this project were: 

• Reduced administration time and workload, lowering staff stress and allowing more time for direct client care. 
• Improved documentation accuracy, with fewer errors and more detailed notes. 
• Enhanced communication with CALD clients, reducing miscommunication and incomplete records while supporting task automation.
• Improved digital skills across the workforce. 
• Improved funding claim accuracy, reducing reimbursement and financial risk. 

• Provides an evidence-based approach for other aged care organisations to adopt AI-driven language support for other home care organisations.

  Project Outcomes

  Trial participants were recruited from key stakeholder groups, including support workers, care partners and clients, to take part in surveys, co-design workshops, interviews and observations. 

  The partner organisation conducted research activities such as workshops (delivered online and face to face), surveys, interviews and observations. Observations took place in clients’ homes during direct support visits and in the office while care partners contacted clients to discuss their wellbeing, services and any health-related concerns. Participants provided valuable feedback on the translation application’s practical use in daily client interactions and its potential to improve communication and rapport. 

   Additionally, to the existing app and system connection, we successfully integrated the EverYoung translation application with our client management system, TurnPoint, enabling support worker progress notes and direct care updates to be captured and recorded automatically. Support workers can now record notes by voice in English or other preferred languages, with original messages, translations and summaries added directly to client records.  

  We evaluated the application’s language capabilities and improved the accuracy of the language models to increase translation accuracy and pronunciation across several languages. The standalone EverYoung AI application supports more than 90 languages and 500 dialects. For the CareWindow-integrated solution, we prioritised the five main languages used by AMCS clients: Arabic, Croatian, Greek, Italian and Polish. These improvements increased accuracy to at least 90% in the standalone app and at least 80% in the CareWindow-integrated version, although some idiomatic phrases remain challenging.  

  We identified opportunities for the use of the EverYoung real-time translation app and the CareWindow device to improve client communication, reduce manual data entry, increase documentation accuracy and lower the risk of incomplete records. The connection between the app and client progress notes enabled support workers to use their first language and provide more comprehensive feedback about services delivered and clients’ wellbeing. Care partners reported that automated note-taking helped them focus more on conversations, while video calls supported better observation of client behaviour and overall health.

  Implications for the Aged Care Sector and the Workforce

  For aged care participants, especially those from culturally and linguistically diverse (CALD) backgrounds, these advancements mean greater access to care that is both culturally sensitive and person-centred. The introduction of AI-powered translation and speech recognition tools helps to break down language barriers, making communication clearer and more inclusive. As a result, clients’ needs and preferences can be better understood and accurately documented, which leads to more tailored care plans and improved service delivery. 

  Aged care providers benefit from increased operational efficiency and higher data quality and accuracy. By automating documentation and streamlining administrative tasks, providers can reduce the risk of incomplete or inaccurate records, supporting compliance and continuity of care. This enhanced accuracy in client information contributes to maintaining high standards in service provision. 

  For the workforce, adopting AI technology can significantly reduce the time spent on manual paperwork and alleviates some of the emotional and mental load associated with documentation. Staff are empowered to communicate more effectively with clients in their preferred language, building stronger relationships and rapport. The automation of routine tasks allows care workers to spend more time on direct care, ultimately improving job satisfaction and creating a more supportive environment for both staff and clients.

  Future Plans

  The trial was implemented in a real-world home care setting rather than a controlled environment. Throughout the trial period, significant aged care reforms, including the transition to the Support at Home program and associated regulatory requirements, impacted clients, staff, and service delivery processes. These external factors influenced participant recruitment, engagement, and retention, as well as workforce capacity and operational priorities, which may have affected the trial outcomes. 

  A subsequent study conducted within a more stable and controlled service delivery environment, with fewer external system-level influences, would enable a more rigorous assessment of the effectiveness and long-term benefits of the translation app and CareWindow device. Priority populations may include clients with limited English proficiency, complex care needs, and those at risk of social isolation, where enhanced translation and video communication technologies have the potential to deliver the greatest benefit. 

  Further work will also focus on improving workflow and system integration, including better integration between AI-enabled note taking and the TurnPoint support worker app, to reduce the need for staff to move between two applications. AMCS will explore more flexible technology models, such as using clients’ own familiar devices where appropriate or shared devices transported by support workers between visits. Future co-design workshops with clients will help identify usability improvements for the CareWindow device and translation app, support greater uptake of the technology and inform broader replication across home care services.

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Contact Person 

• Magdalena Biadala-Sahingoez, Manager – ICT and Project Lead at AMCS 
• Email: Magdalena.Biadala-Sahingoez@amcservices.org.au