Lili Liu - Technologies to Support Home Care Services and Community LIving

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5/17/2012

Quality of Life – Independent Living Panel facilitator: Eleni Stroulia • Lili Liu “Technologies to support home care services and community living” • Gary Faulkner “Rehabilitation prosthetics”

Research on smart homes Literature review of non-obtrusive technologies to enhance the quality of life and safety of older adults living at home, congregate housing, and assisted living settings.

• Bob Aloisio “Always connected, safe and secure”

Technologies to Support Home Care Services and Community Living Lili Liu, PhD Professor & Chair Department of Occupational Therapy Analytics, Big Data and the Cloud

Funded by Alberta Addiction & Mental Health Research Partnership Program

Computing Science: Eleni Stroulia, Yannis Nikolaidis, Nick Boers, Koosha Golmohamaddi Industrial Design: Robert Lederer, Greig Rasmussen Occupational Therapy: Angela Sekulic, Katie Woo, Ran Ran Zhang Pharmacy: Cheryl Sadowski, Lisa Guirguis Shepherd’s Care Fdn: Corinne Schalm, Suzanne Maisey, Beth Wilkey HSERC: Sharla King Library: Linda Seale Alberta Health Services: Angela Sekulic, Katie Woo Alberta Seniors: Carmen Grabusic

April 23-25, 2012, Edmonton, AB

Outline

1.What research has been done on technologies to support community living (smart homes)? 2.What is the Smart Condo™ project at the University of Alberta? 3.How can technologies support home-care services and community living? (HCA-T Project)

SCOPUS, CINAHL, IEEE Smart home and health; gero(n)technology; telesurveillance or telemonitoring; technology for older adults

Inclusion ≥2000; English, addressing the physical, cognitive, social, or mental health needs of older adults in home or supported living settings

4.Health Care on the Cloud

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5/17/2012

Tag clouds of top 200 words in 188 papers selected for review

Target users

Number of papers published each year

Conditions & topics

Articles published/year 2000

4

Dementia Care/Management

2001 2002

2003

2004

40

0 Other Chronic Disease Management

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39

Detecting deviations in health status or activity levels (including fall detection)

36

8

2005

10

2006

10

2007

Vital signs monitoring

20

User perceptions and acceptance of technologies

20

24 Diabetes Management

2008

8

41 Other (privacy and ethical issues, best technologies for aging, design considerations)

2009

2010 (until May)

5

54 13

Environments technologies were designed for

Country of Publication

Main players USA

Great Britain France

18

Canada

13 12

Netherlands

8

Sweden

7

China

6

Finland Germany

3

Greece

3

Japan

3

Singapore

3

Australia

2

Ireland

2

Italy

2

Korea

2

Other

58

21

10

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Type of Research Design

6

 28 Pilot and Case Studies

23

RCT Experimental Design Non-RCT Experimental Design Qualitative Mixed Methodology

  

Play & Connect Rest & Sleep Bathing & Grooming Cooking & Eating

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Summary

Smart Condo™

Technologies can support older adults with complex chronic conditions (arthritis, hypertension, heart disease, cognitive impairment) to stay at home. However challenges need to be addressed: Adaptation Accessibility Usability Privacy Accuracy Unobtrusiveness Social & ethical implications

Smart designs Smart technologies Living lab

Smart Condo™ Project at the U of A • • • • •

2008: mock design of a condo in Telus Centre 2012: Edmonton Clinic Health Academy 30 to 50 students annually (ID, OT, CS & Pharm) Universal Design, visitability Sensors, Test medical devices, e-health software, health management applications, prototype designs

Lili Liu

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How can technologies support home care services and community living?

(Our) Smart Condo technology 

Tracks patient in precise, non-intrusive way o

• Sensors to monitor activities, critical incidents (Glenrose ILS) • Medication adherence • Technologies to support health care aides in home care (HCA-T Project)

Why monitor with sensors?

Community care

◦ Clients with chronic conditions staying at home longer ◦ Transition from hospital to rehab to home

Valid assessment of function ◦ Frequent visits are misleading ◦ Cameras are intrusive

Courage Centre (GRH)

Visualizes patient’s activities o

Wireless sensor networks

Virtual world client

Flexible, inexpensive, and effective

Wireless sensors Consist of multiple components: • Sensors (e.g., acceleration, passive-infrared motion, switches, tactile pressure) • Wireless module • Microcontroller (e.g., MSP430: 8 MHz, 2 KB RAM, 48 KB flash) • Radio transceiver (e.g., TR8100: 916.50 MHz, 9.6 kbit/s) • Energy source (e.g., 9 V battery)

Wireless sensor network

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 

Screenshot (overhead)

Glenrose Independent Living Suite

Other possible views

Medical Assistance Technologies

Alerts Reports/graphs

(Katie Woo)

1. What is the current level of awareness of MATs among older adult’s care providers? 2. Are MATs designed for older adult use?

MATS (active monitoring, feedback)

Virtual world client   

Virtual representation of condo space Avatar represents patient Avatar directed by control mechanism to move between co-ordinates in virtual condo ◦ Path planning algorithm used to avoid obstacles

Other smart objects embedded in virtual space, manipulated by similar control mechanism

Major Findings Survey Study • Medication adherence issues common • over 50% encounter issues frequently • Patient or caregiver self-report most frequently used • Blister packs most recommended • MATs awareness (25%) and usage (6%) low • No significant relationships found in demographics • High interest or belief MATs could be useful (82%)

3 0

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Methods

Katie Woo

Client Trials (June – October 2011)

Technology Acceptance Model: Participant #1 and MATs

• MATs product trial with in-patients • 2 day trials, Independent Living Suite • Commercially available product • Observations, interviews, product data and evaluations Results • 2 participants • 4 team surveys completed, 2 interviews, investigator observations, 2 sets of product data

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Adapted from “The Technology Acceptance Model: its past and its future in healthcare by R.J. Holden and B.T. Karsh, 2010, Journal of Biomedical Informatics, 43,1, p. 161.

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Medical Adherence MedSignals®

Technology Acceptance Model: Participant #2 and MATs

Adapted from “The Technology Acceptance Model: its past and its future in healthcare by R.J. Holden and B.T. Karsh, 2010, Journal of Biomedical Informatics, 43,1, p. 161.

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Systems approach

Katie Woo Technology Acceptance Model: Health care providers and MATs

Adapted from “The Technology Acceptance Model: its past and its future in healthcare by R.J. Holden and B.T. Karsh, 2010, Journal of Biomedical Informatics, 43,1, p. 161.

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Health Care Aides & Technology • Alberta Health & Wellness • Five Home Care Zones • Apps for multiplatform mobile devices • Recruitment, Retention & Recognition

HCA-T Project • • • • • •

Workflow Safety (GPS) (e.g., SafeTracks) Communication Documentation Remote authorization Etc.

Summary 1. Research on technologies - home care, assistive living and continuing care; users are clients, family and caregivers; applied to chronic conditions – dementia, diabetes, activities monitoring.

Summary 2. Examples such as the U of A’s Smart Condo™ Project emphasize the importance of interdisciplinary training, research and industrial partnerships.

Summary 3. A systems approach is needed to introduce and sustain technologies targeted at clients, families and home care or community service providers.

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Health Care – the killer app on the Cloud

To support patients to live independently longer

To enable care givers to make more informed decisions about client care We need To collect data; to fuse data from different sources; to decide on actions This is what we hope cloud to do for us

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