AI Innovations in Long-Term Care: Predicting Costs and Needs, a Conversation with WaterLilly.com CEO Lily Vittayarukskul

Editor’s Note: This article was previously published in the Jewish Community Voice of Southern New Jersey as the CompuSchmooze column.

Rising costs for groceries and housing get most of the media attention about inflation, but seniors are facing dramatic increases in the cost of long-term services and supports, also known as long-term care.

In 2024, a study by AARP found that the median annual cost for most long-term care services was higher than the median assets and household income of older adults, rising by about 35% between January 2020 and September 2024.

It’s easy to understand why planning for the financial impact of long-term care is one of the biggest challenges facing older people and their families.

Now a startup company called WaterLily.com is proposing to use artificial intelligence to analyze data about health and finances to predict the age at which a person will begin to need long-term care, and how to finance the cost of that care.

Lily Vittayarukskul, Waterlily’s CEO and co-founder, was planning to be an aerospace engineer, but when her aunt was diagnosed with terminal colon cancer, she saw firsthand how gaps in healthcare coverage forced their family to take on the caregiving burden for her aunt.

In this conversation with SBN news director Steve Lubetkin, Lily discusses the innovative use of artificial intelligence in predicting long-term care needs. She shares her personal experience that led to the creation of Waterlily, the challenges families face in long-term care planning, and how the platform simplifies the process for users. The discussion also highlights the collaboration with financial professionals and insurance companies to provide unbiased predictions and effective planning tools.

You can watch a complete interview with Lily in the player below.

“It was not only incredibly financially devastating for us to pay for that out of pocket because traditional healthcare does not cover this,” she said in an interview. “But secondly, without that plan in place, we really had our familial relationships torn apart because of all the high-stakes decisions we had to make in a short amount of time.”

The experience caused her to shift from aerospace to healthcare innovation. For the past two-plus years, Vittayarukskul’s company has been building an AI model that uses social, demographic, financial, and medical information from participants to predict the age at which they are first likely to need long-term care, the level of care required, and the cost of that care.

Users complete a short questionnaire and upload copies of their insurance policies and other financial documents.

The model analyzes the information and makes predictions about the initial amounts of hours that a patient will need help with, and predicting ages at which care required might increase. The program considers existing financial and insurance resources to identify costs that families might have to cover themselves.

“So you get a snapshot of what that cost looks like, and you also get a chance to say, well, in the earlier care phase, I want to stay at home,” says Vittayarukskul. “We just make that all linear and we associate all your preferences with a cost.”

So far, the model has achieved about 80 percent accuracy with tens of thousands of patient families in the system, she says.

The primary focus of WaterLily is offering its analytical services to financial advisors and planners, and insurance professionals, to help their clients navigate the care process.

“We actually offer our software to the financial professionals who are trying to educate prospects and their clients about what long-term care is through our software because we make it so simple,” she says.

The WaterLily system can analyze the provisions of a health care insurance policy and apply its benefits to the predicted costs.

“We actually read through the 30 to 40 pages within that document that tells us how this policy actually functions,” she says. “We’ve seen that cause really positive outcomes for the space, not only in removing a lot of the complexities, but also making sure that the client has the best financial plan in place.”

Although WaterLily’s AI tool is intended for use as part of an overall financial planning process, individuals can get wait-listed on the WaterLily.com site for individual analysis.