LeadingAge24: The AI Age Is Here. How Can Senior Care Organizations Use It for Good?

What Is AI and What Are the Opportunities for Senior Care?

AI is a broad term with many subsets. It can refer to any machine that mimics cognitive functions such as learning and problem-solving. Kurt Rahner, vice president of technology for Kendal, explained some of the subsets of AI.

Chatbots are an AI use case that relies on natural language processing to understand and generate responses.

Machine learning is a subset of AI that uses machines to analyze data and learn from patterns. Deep learning, a subset of ML, uses deep neural networks to learn from vast amounts of data. Types of neural networks include convolutional neural networks (CNNs), which are often used for images; recurrent neural networks (RNNs); and transformers. The GPT in ChatGPT stands for “generative pretrained transformers.” Rahner emphasized that transformers provide the magic.

Large language models are an example of ML that consists of algorithms designed to understand and generate humanlike text. This is the technology behind generative AI. The big-three frontier LLMs are ChatGPT, Claude and Gemini. Rahner said that it’s important for senior care professionals to know that, at a simple level, LLMs are guessing the next word in a sentence statistically, based on all of the data they have ingested using extremely complex mathematical formulas.

There is a lot of momentum around LLMs, the subset of AI that is used for generative AI solutions such as ChatGPT, and Joe Velderman, vice president of innovation at Cypress Living in Fort Myers, Fla., said it’s important for senior care organizations to pay attention to it.

DISCOVER: These tips can help senior care organizations navigate innovation and AI.

“What’s incredible to me is that the AI we’re using today is the worst AI we’ll use for the rest of our lives,” he said, while emphasizing that the AI space is evolving rapidly, meaning that everyone should be taking it seriously. “Go back to your communities and experiment with it. Find use cases and ways to apply it in your business.”

Richard Foor, vice president of IT at Givens Communities in Ashville, N.C., added that training AI is a process, and the organization may fail the first few times.

Velderman’s organization first started tinkering with automation through robotic process automation. His team analyzed the organization’s processes and determined which steps a computer could handle.

“We have 170 robotic processes running every single day in our organization,” he said. “Think about the impact of those every day. We might be eliminating 170 calls, emails, instances of note taking or walking paper down a hallway. Those are microtransactions, but when you do it at scale, they can have a big impact.”

Cypress Living then built an ML algorithm to prevent falls. The algorithm considers eight to 10 factors such as a person’s age, sex, weight, medications and whether they’ve fallen previously. It then kicks back a score of 0 to 100, rating the likeliness of that person experiencing a fall in the next 72 hours. According to Velderman, the algorithm is 93% accurate.

“Now our operations team can have an impact when trying to prevent a fall from happening,” he said. “The ML algorithm has had a transformational impact.”

Cypress Living also updated its life safety system using the Nobi smart lamp in 2022. The lamp uses computer vision AI to detect falls quickly and augments that with a typical pendent button.

Nobi CEO Roeland Pelgrims said the device lowers intervention time for falls. He emphasized that the reason some organizations have high intervention times isn’t because their staff isn’t good at delivering care, but because they can only help if they know help is needed. Another benefit is that because residents are less afraid of falling, they become more active; as a result, they fall less.

Finally, his organization has paired the generative AI feature of Microsoft Copilot with retrieval-augmented generation (RAG) to build chatbots for its clinicians and staff. HUGO is a chatbot designed to help nurses and frontline worker find information about the organization’s clinical care pathways. It can look up what to do when caring for a patient with specific chronic conditions. Dex, a chatbot for weekend staff, has been trained on the organization’s policies and procedures and can answer questions about how to handle specific situations that may arise, such as a leaky roof.

READ MORE: Harness the power of Copilot for Microsoft 365 in healthcare.

“The beauty of RAG is that you can take your internal procedures and documents that you know to be accurate and bring them into a database that is indexed with other tools. It gets tied into a generative pretrained transformer [GPT] to help create an immediate response that you know is good,” said Rahner.

Senior care leaders are also using generative AI for more straightforward use cases such as writing a plan of correction, transcribing care planning meetings or producing meeting summaries through Zoom.

“Rather than having someone sitting on the side taking notes, they can now be empowered to be part of the team,” said Foor.

At Givens Communities, Foor and his team rolled out an “AI piloteers” program that encourages employees to integrate generative AI tools, such as a chatbot in Microsoft Copilot, into their workflows. According to Foor, in the first 90 days of the program, 60% of participants used AI in their normal workflow weekly (if not daily), and 56% said AI increased their efficiency.

DIVE DEEPER: Accelerate innovation in senior living and post-acute care.

How to Best Implement AI in the Aging-Services Sector

Sarah Thomas, CEO at staffing solutions company MezTal, prefers to center the human experience when considering AI, rather than taking a technology-first approach.

“It’s not so much about what AI is doing, but about what we can do more effectively or efficiently to live better, healthier lives,” she said.

AI can make a difference in senior living and post-acute care organizations’ ability to retain employees. Thomas recommended that senior care leaders focus on how they can make employees lives better by automating rote tasks and reducing the need for overtime, while also emphasizing that they are not being replaced. AI can allow staff to be more efficient through greater insights related to organizational and clinical data.

“AI can level the playing field,” added Velderman. “If you give AI tools to someone who plays at a C level, they can become a B player. You’re elevating their skills by giving them a tool.”

However, Thomas emphasized the importance of understanding the “why” that’s driving the organization and being able to articulate that across the entire staff. Having buy-in from end users will better ensure implementation success, more so than pushing it from the top down with no explanation of how it will help staff.

It’s important to communicate transparently with residents about how organizations are using their data, said Velderman, while also sharing the “why” — for example, that it helps in maintaining an older adult’s independence for as long as possible or in providing preventive care.

“We have to break down the mainstream message about AI being bad,” he said. “We’re fighting an uphill battle.”

EXPLORE: How can AI and automation transform processes for senior care providers?

Velderman explained that technologists need to understand organizational processes at a granular level to create transformational change. They also need to know the business goals and desired ROI before they begin to automate processes with AI tools.

In addition, the organization needs solid data governance in place as “AI is only as good as the information provided to it,” he said. Cypress Living built a data lake with raw data from enterprise apps and layered that with AI to create contextual answers (rather than generic answers) based on its operations. He added that the ability to engineer effective prompts is also an important part of AI success.

“People in your organization are already using it whether you know it or not. It can be a liability to organizations. Get in front of it, and empower your employees with some guardrails, but embrace it,” said Foor. “Then your team will look to you for guidance. Having someone in the organization guiding AI use is my recommendation.”

Ultimately, Velderman said, the point of AI is to provide the right data at the right time to the right person so they can provide the right care at the right time.

“A few years from now, people will be able to have great results just by having great intentions,” said Pelgrims, who says he’s optimistic that it will make life easier without first making it hard. “That’s the magical transformation of AI.”

Keep this page bookmarked for our coverage of the 2024 LeadingAge Annual Meeting. Follow us on the social platform X at @HealthTechMag and join the conversation at #LeadingAge24.