Does AI technology hold the answer to increasing workforce retention?

Last updated on 7 March 2024

Home care workers facing unnecessary work pressures can benefit from AI technology that alleviates admin burden and poor scheduling. [Source: Shutterstock]

Technology has a growing influence in the home care sector with workforce attrition the latest focal point. Innovative solutions that incorporate artificial intelligence (AI) and Large Language Models (LLM) are among the latest tools being used to combat scheduling woes, worker fatigue and low work satisfaction.

Key points 

  • In 2021, the Committee for Economic Development of Australia (CEDA) released a report stating that aged care would be 110,000 direct care workers short by 2030
  • One year later they released an updated report that predicted an annual shortfall of 30,000-35,000 workers, almost double their initial projections
  • Home care faces unique challenges in the wider aged care sector, with additional travel requirements, inconsistent scheduling and administrative burden among the causes of low job satisfaction

CEDA estimated 65,000 workers are exiting the aged care sector every year, just as a rising tide of older Australians are accessing aged care services. 

With this in mind, Naomi Goldapple, Senior Vice President of Data & Intelligence at AlayaCare, said it’s time for technology solution providers to take on key worker complaints such as inconsistent hours, poor scheduling, and the time lag between their hire date and first scheduled visit.

“Attraction and retention of employees is tough, especially with the silver tsunami of baby boomers coming. There just isn’t enough of us to take care of them. We need technology to help us make it through,” Ms Goldapple told hello leaders.

“We have to make being a caregiver more enticing. Having technological tools at your fingertips can help to attract younger workers and make it more delightful to do your job. It frees staff up to do more meaningful work with fewer repetitive tasks.”

AI has the potential to reduce repetitive task burden, with help from LLMs. LLMs are deep learning algorithms pre-trained on vast amounts of data to answer questions, complete sentences or summarise documents. Ms Goldapple said the use of LLMs alongside AI will be transformational for home care. 

“In home care, we have note droppings; sometimes employees leave notes and a clinical supervisor does not have the time to read all of them in a timely fashion. LLMs can automatically read these notes, synthesise them and flag the most important information so the clinical supervisor will know to look at it right away and they can act on it,” she said.

Better tech and better outcomes

According to AlayaCare’s Data & Intelligence Product Manager, Sarah Khalid, AI-influenced scheduling has resulted in 7,000 minutes saved from the manual scheduling process of roughly 4,000 care visits.

AI’s influence is expected to extend well beyond scheduling itself. Capturing essential data related to worker shift patterns presents a new opportunity to recognise when and where workers are falling out of favour or are at risk of departing. 

One tool is an employee retention and churn predictor created by AlayaCare which uses multiple data points to inform employers of ‘at-risk’ workers with low work satisfaction. This data can then be used by management or human resources (HR) to resurrect careers.

“One of the things in our research we discovered is [there is] a big point of churn in those first 30 days if you hire somebody but you don’t give them shifts right away – they get disenchanted very quickly. It’s very important to keep them in the fold through their first 30, 60 or 90 days,” Ms Goldapple said.

“Having this information at your fingertips helps because in home care, the employee doesn’t necessarily quit loudly, sometimes they just fade away. But if you can see their satisfaction metrics then you can act on it.”

For Annette Hili, General Manager Australia & New Zealand at AlayaCare, better technology is making it easier to overcome many of the challenges home care faces, including inefficient scheduling. 

“Our philosophy is that a product should help providers deliver better outcomes for their customers. There are two big things we are trying to solve. One is better tech, better outcomes; the second is helping providers gain efficiency,” Ms Hili told hello leaders.

“This is probably one of the most hard-pressed industries as far as not having enough people and too much to do. Care workers and clinicians spend a significant amount of time with their customers and effectively working with back-end solutions means they can get back to caring for them sooner.”

workforce retention
home care
artificial intelligence
administrative requirements
home care reform
annette hili
Naomi Goldapple
Sarah Khalid
Large Language Models