AI to Predict & Personalize Long-Term Care Planning with Lily Vittayarukskul

Steadfast Care Planning

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🚀 Welcome back to the Steadfast Care Planning podcast, the show that helps you plan for care to live well. In this compelling episode, we’re joined by Lily Vittayarukskul, founder and CEO of Waterlily Planning and an ex-NASA data scientist. Lily shares her pioneering approach to utilizing AI and massive data insights to personalize extended care planning, inspired by her personal experience navigating her aunt's long-term care journey.
👨‍👩‍👧‍👦 In our conversation, we explore how Lily’s tool aids financial planners and individuals by predicting long-term care needs using over half a billion data points, examining costs, care trajectories, and much more. We discuss the challenges posed by financial planning for care, including insurance policies, the rate of return, and the emotional impact of preparing for aging and loss of independence.
🔍 Lily also outlines the technical and human element considerations her tool incorporates, such as disability, family caregiving involvement, and the importance of genetic and lifestyle factors. Moreover, she discusses how her models strive for accuracy, the implications of healthcare inflation, and the crucial role of family history and personal health in planning.
💡 Whether you are a financial advisor, an individual planning for the future, or a tech enthusiast curious about AI applications in healthcare, this episode offers valuable insights into the evolving landscape of long-term care planning using AI.
In this episode they covered:
🔹 How Waterlily integrates with existing financial planning resources to enhance long-term care planning
🔹 Explaining the concept of unbiased data sources as mentioned by Lily, and why is it crucial in building accurate predictive models for extended care
🔹 The fluctuating nature of caregiving commitment and how it impacted his personal well-being
🔹 Some of the technical limitations Waterlily, and how they impact its effectiveness in predicting long-term care needs
🔹 The human element involved in long-term care planning and how to address variations such as family involvement and personal health history
🔹 An accuracy rate of 70-80% in predictive insights
🔹 The importance of lifestyle and genetic factors in long-term care planning
🔹 Future enhancements or features for Waterlily to further improve the planning and management of long-term care for individuals and families
For more information about Lily Vittayarukskul and Waterlily, please visit:
https://www.joinwaterlily.com/
Or, LinkedIn:
https://www.linkedin.com/in/lily-vittayarukskul/ ______________________________________________________________________________
➡️ Watch this podcast: https://youtu.be/7EjrNWfqjtE
#LongTermCare #LilyVittayarukskul #SteadfastCarePlanning #JoinWaterlily #AIandHealthcare

For additional information about Kelly, check her out on Linkedin or www.SteadfastAgents.com.
To explore your options for long-term care insurance, click here.
Steadfast Care Planning podcast is made possible by Steadfast Insurance LLC,
Certification in Long Term Care, and AMADA Senior Care Columbus.
Come back next time for more helpful guidance!

Chương

1. Introduction (00:00:00)

2. Why Lily created Waterlily (00:00:42)

3. What is Waterlily and how it works (00:02:39)

4. Where the AI data points were collected (00:03:30)

5. How to predict long-term care for families and individuals from the data points (00:04:08)

6. What types of questions do you ask to better predict long-term care trajectories (00:04:42)

7. Finding the variables that have the highest predictive value (00:05:20)

8. Differences between the short and long intake forms (00:06:40)

9. What is the accuracy of the short version form? (00:07:30)

10. The CLTC Commercial (00:07:58)

11. Averages and the types of care that Waterlily AI is predicting for people (00:08:55)

12. The time periods that Waterlily AI predicts for people's care (00:11:11)

13. Cognitive issues and time periods of care and genetics versus lifestyle (00:11:34)

14. Who can access Waterlily, and how they can access Waterlily (00:14:05)

15. Importance of working alongside a financial advisor when using Waterlily (00:16:05)

16. How Waterlily can help the financial advisor and make sure nothing is missed in insurance contracts (00:17:35)

17. Talking to family about preferences and having tough conversations as well as discussing with financial advisors (00:18:46)

18. AMADA Senior Care Commercial (00:19:29)

19. The limitations that Waterlily has and how they should be considered (00:20:00)

20. What are the relationships like for the person that Waterlily is predicting? Knowing about human relations are a limitation to Waterlily. (00:21:10)

21. A couple with a handicapped individual will be very hard for Waterlily to use in predictive modelling because the handicapped person can't be an effective caregiver (00:22:19)

22. The 3 ways Waterlily models predictions for the cost of long-term care in the future (00:23:20)

23. Lily shares how she believes people can prepare for care to live well (00:26:40)

24. Just thinking about future long-term care and extended care is a huge step (00:26:45)

25. The sense of losing who we were, in a way, when we lose our independence, that becomes scary (00:27:55)

26. Having the tough conversations with family members is a major step forward in the long-term care planning process (00:30:00)

27. How to contact Lily and find out more about Waterlily (00:30:31)