Scalable Intervention Technology

for Older Adults in the Home

Holly Jimison, PhD

Department of Medical Informatics, OHSU

Funding: National Science Foundation, National Institute on Aging,

Alzheimer’s Association, and the Intel Corporation

Scalable Approach to Delivering Interventions to the Home

Remote, just-in-time, continuous care

Incorporate principles of health behavior

change

Optimal use of lower cost personnel

Integrate family & informal caregivers into the

health care team (untapped resource)

Platform for testing sustained interventions in

the home

Home Monitoring Data

Platform to Deliver a Scalable Coaching Intervention to the Home

System to facilitate a single coach in

managing a large number of clients

Semi-automated tailored messaging based on

home monitoring and self-report data

User assessment user model tailored

data sharing, action plan, coaching messages

Multiple modules – not single condition or

approach

Modular Software for Multiple Protocols

Cognitive Exercise (computer game format)

Novelty exercise

Physical Exercise

Sleep Management

Socialization

Medication Management

Mood Management

Participant Home Page

Participant home page

• Messages from coach

• Featured story

• Weekly goals

– Activities

– Surveys

• Access modules

– Physical Activity

– Sleep

– Socialization

– Novelty Mental Exercises

– Cognitive Games

• Coaching Process

• Participant Materials

6

• Messages from Coach

Coach Messaging

7

• Messages to Coach

Physical Activity Module

8

Physical Activity Module-continued

9

Sleep Module

10

Socialization Module

11

Socialization Protocols for Cognitive Health

Web cams and Skype software given to

participants and their remote family partner

Frequent spontaneous use among participants

Cognitive Computer Games - embedded monitoring algorithms

Health Coaching Platform Architecture

Health Coaching Platform Architecture

Family Interface

• Safety monitoring

• Soft alerts

•Team-based care

• Socialization

ORCATECH 16

In-Home Cognitive Health Coaching Studies

Needs Assessment

Coach Messaging Study

Ongoing Usability Testing

Feedback on Cognitive Games and Novelty Exercise

Current Coaching Study

20 participants in the ORCATECH Living Lab

20 additional participants from larger monitoring study

Average age 78.3 ± 7.8 years

70% female

Lessons Learned: Important Software Issues

User centered design – ease of use

Inference algorithms for assessing patient state and

context

Sophisticated User Models

Privacy / Security – tailored privacy models for

the sharing of home monitoring data

User models for tailoring interventions and

coaching messages

• Intelligent Interoperability

Summary: Benefits of Technology for Remote Coaching

Scalable approach to delivering interventions to the

home

Extends the reach of lower cost professionals

Community-based culturally-specific coach

Timely and continuous

Aim to keep people independent ( QoL & costs)

Integrates untapped resource of family and informal

caregivers into the care team

Tailors interventions to individuals

Integrates health and wellness interventions