Steadfast Care Planning

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

May 14, 2024 Kelly Augspurger Season 1 Episode 38
AI to Predict & Personalize Long-Term Care Planning with Lily Vittayarukskul
Steadfast Care Planning
Chapters
0:00
Introduction
0:42
Why Lily created Waterlily
2:39
What is Waterlily and how it works
3:30
Where the AI data points were collected
4:08
How to predict long-term care for families and individuals from the data points
4:42
What types of questions do you ask to better predict long-term care trajectories
5:20
Finding the variables that have the highest predictive value
6:40
Differences between the short and long intake forms
7:30
What is the accuracy of the short version form?
7:58
The CLTC Commercial
8:55
Averages and the types of care that Waterlily AI is predicting for people
11:11
The time periods that Waterlily AI predicts for people's care
11:34
Cognitive issues and time periods of care and genetics versus lifestyle
14:05
Who can access Waterlily, and how they can access Waterlily
16:05
Importance of working alongside a financial advisor when using Waterlily
17:35
How Waterlily can help the financial advisor and make sure nothing is missed in insurance contracts
18:46
Talking to family about preferences and having tough conversations as well as discussing with financial advisors
19:29
AMADA Senior Care Commercial
20:00
The limitations that Waterlily has and how they should be considered
21:10
What are the relationships like for the person that Waterlily is predicting? Knowing about human relations are a limitation to Waterlily.
22:19
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
23:20
The 3 ways Waterlily models predictions for the cost of long-term care in the future
26:40
Lily shares how she believes people can prepare for care to live well
26:45
Just thinking about future long-term care and extended care is a huge step
27:55
The sense of losing who we were, in a way, when we lose our independence, that becomes scary
30:00
Having the tough conversations with family members is a major step forward in the long-term care planning process
30:31
How to contact Lily and find out more about Waterlily
More Info
Steadfast Care Planning
AI to Predict & Personalize Long-Term Care Planning with Lily Vittayarukskul
May 14, 2024 Season 1 Episode 38
Kelly Augspurger

Send us a Text Message.

πŸš€ 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.

πŸ‘¨β€πŸ‘©β€πŸ‘§β€πŸ‘¦ 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.

πŸ” 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.

πŸ’‘ 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:

πŸ”Ή How Waterlily integrates with existing financial planning resources to enhance long-term care planning

πŸ”Ή Explaining the concept of unbiased data sources as mentioned by Lily, and why is it crucial in building accurate predictive models for extended care

πŸ”Ή The fluctuating nature of caregiving commitment and how it impacted his personal well-being

πŸ”Ή Some of the technical limitations Waterlily, and how they impact its effectiveness in predicting long-term care needs

πŸ”Ή The human element involved in long-term care planning and how to address variations such as family involvement and personal health history

πŸ”Ή An accuracy rate of 70-80% in predictive insights

πŸ”Ή The importance of lifestyle and genetic factors in long-term care planning

πŸ”Ή 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/ ______________________________________________________________________________

➑️ 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!

Show Notes Chapter Markers

Send us a Text Message.

πŸš€ 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.

πŸ‘¨β€πŸ‘©β€πŸ‘§β€πŸ‘¦ 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.

πŸ” 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.

πŸ’‘ 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:

πŸ”Ή How Waterlily integrates with existing financial planning resources to enhance long-term care planning

πŸ”Ή Explaining the concept of unbiased data sources as mentioned by Lily, and why is it crucial in building accurate predictive models for extended care

πŸ”Ή The fluctuating nature of caregiving commitment and how it impacted his personal well-being

πŸ”Ή Some of the technical limitations Waterlily, and how they impact its effectiveness in predicting long-term care needs

πŸ”Ή The human element involved in long-term care planning and how to address variations such as family involvement and personal health history

πŸ”Ή An accuracy rate of 70-80% in predictive insights

πŸ”Ή The importance of lifestyle and genetic factors in long-term care planning

πŸ”Ή 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/ ______________________________________________________________________________

➑️ 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!

Introduction
Why Lily created Waterlily
What is Waterlily and how it works
Where the AI data points were collected
How to predict long-term care for families and individuals from the data points
What types of questions do you ask to better predict long-term care trajectories
Finding the variables that have the highest predictive value
Differences between the short and long intake forms
What is the accuracy of the short version form?
The CLTC Commercial
Averages and the types of care that Waterlily AI is predicting for people
The time periods that Waterlily AI predicts for people's care
Cognitive issues and time periods of care and genetics versus lifestyle
Who can access Waterlily, and how they can access Waterlily
Importance of working alongside a financial advisor when using Waterlily
How Waterlily can help the financial advisor and make sure nothing is missed in insurance contracts
Talking to family about preferences and having tough conversations as well as discussing with financial advisors
AMADA Senior Care Commercial
The limitations that Waterlily has and how they should be considered
What are the relationships like for the person that Waterlily is predicting? Knowing about human relations are a limitation to Waterlily.
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
The 3 ways Waterlily models predictions for the cost of long-term care in the future
Lily shares how she believes people can prepare for care to live well
Just thinking about future long-term care and extended care is a huge step
The sense of losing who we were, in a way, when we lose our independence, that becomes scary
Having the tough conversations with family members is a major step forward in the long-term care planning process
How to contact Lily and find out more about Waterlily