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Using Data Science to Predict Individual LTC Needs and Identify Solutions

Helping People Identify and Plan for Their Future Long Term Care Needs:

Using Data Science to Predict Individual Long Term Care Needs and identify Solutions

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Speakers: Evan Ehrenberg and Lily Vittayarukskul, Waterlilly

 ABOUT THE TOPIC:

The complexities of long-term care (LTC) and retirement planning pose significant challenges for both individuals and professionals. As life expectancies increase and economic conditions change, understanding the risks and costs associated with aging becomes crucial. Tools used today which include national averages, zip code calculators, and Monte Carlo simulations, are woefully inadequate for charting an individual’s care path.  That’s due to the complex array of factors that play into whether and how much LTC someone might need – e.g.,   health condition, family situation and risk preferences, gender, age, other demographics, family history, lifestyle, and more. 

This talk will discuss how data science is being used to develop a planning tool designed to help individuals visualize their own future care needs and explore how various financial protection options might meet those needs.  This tool is intended to help consumers (and financial planners and others) address the educational barriers in conveying the importance of LTC planning.   The tool – called Waterlily - uses 500 million datapoints of demographic and healthcare data to predict individuals’ future LTC needs and costs and presents a range of care options and financial solutions. Details will be provided regarding the tool’s development, testing phases, and its current applications in enhancing LTC planning and awareness.

ABOUT THE SPEAKERS:

Evan Ehrenberg is Waterlily’s COO and Co-Founder, previously founded and served as CEO of Clara Health and UpperBoundAI. Before his entrepreneurial journey, Evan attended college when he was 11, graduating from UC Berkeley with his bachelor's degree in Cognitive Science and Computational Modeling when he was 16. He then went on to pursue his Ph.D. at MIT in Computational Neuroscience where he used machine learning and computer vision modeling to advance computational neuroscience and AI research. Evan dropped out of his Ph.D. just before defending his thesis when he was 21 to scale Clara Health as it took off.

Lily Vittayarukskul is Founder and CEO at Waterlilly, where she oversees the development of the interactive predictive tool that is designed to help prepare families for their future LTC needs, addressing LTC costs faced by families, state governments, and insurance carriers. Waterlilly does this using predictive AI (artificial intelligence) to create a personalized projection of an individual’s future care needs, and then guiding them and their family through building out logistics and financial plans for their care.  Prior to that, she worked at a telemedicine startup from 2019 to 2021, involved in product development, AI prototype building, successful product launches, and scaling of an IoT AI telemedicine platform. Lily also led business efforts to launch the company's first product, developed market positioning, strategy, and sales training. Prior to that, she was a Data Scientist Consultant at STELLARES. Lily also held roles as Head of Technology and Head of Growth and Development at Research to the People. Additionally, she worked as a Scientist Intern (Software Developer) at DNAnexus, and had an internship at NASA Jet Propulsion Laboratory in 2013. Lily earned a Bachelor of Arts degree in Genetics and data science from the University of California, Berkeley.



ACCESSING THE MEETING:  CLICK BELOW TO REGISTER IN ADVANCE TO RECEIVE THE ZOOM LINK FOR THE MEETING:

Registration Link

https://us02web.zoom.us/meeting/register/tZ0tfumrqT8rG9TY7r4broX-L5xRZL-_Az-B 

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March 28

Improving Home and Community-Based Services (HCBS) Access and Outcomes for Dual-Eligible Beneficiaries of Color

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August 7

Long Term Care (LTC) Actuarial Value: A new metric for evaluating LTC insurance coverage