A leading provider of home care and residential aged care technology has developed new innovative software to reduce staff turnover amongst home care workers using Artificial Intelligence (AI) and Large Language Models (LLMs) to alleviate issues that contribute to them leaving their jobs.
An estimated 65,000 aged care workers leave their jobs each year, according a 2022 report by The Committee for Economic Development of Australia (CEDA).
Technologies using LLMs and predictive algorithms can help combat high rates of attrition, state AlayaCare.
For example, an employee retention and churn predictor uses data points to inform employers of 'at-risk' workers experiencing low work satisfaction. The software can be used proactively to pinpoint staff on the verge of leaving.
“This is an AI model that gathers information about care workers’ top three complaints: inconsistent hours, poor scheduling, and the time lag between hire date and first visit scheduled. It uses this data to predict who is at risk of quitting by reviewing their perceived satisfaction in their role," said Naomi Goldapple (above), Senior Vice President of Data & Intelligence at AlayaCare.
“We’ve created a tool that automates matching care workers with vacant visit clients, removing manual guesswork and human biases and errors in scheduling," said Naomi.
"This ensures the right care workers are matched with the right clients based on skillsets and client needs. It also optimises the physical routing of care workers to reduce drive time between visits, which they love.”
Annette Hili, General Manager Australia & New Zealand AlayaCare, and Naomi will be discussing the new tools at AlayaCare’s roadshow, Transformative technology: Navigating the landscape of AI, data and large language models.
