Connected health as a tool for patient engagement - by Joseph Kvedar, MD, Director of the Center for Connected Health.

1. Connected Health as a Tool for
Patient Engagement
Joseph C. Kvedar, MD
Director
Center for Connected Health
Partners HealthCare
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2. Connected Health Goal
Integrate care into the
day-to-day lives of our patients
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3. Connected Health Innovation Process
CCH
Service
Product
develop.
Ideation &
Feasibility
r
r
Program
develop.
Trial/Test
Spin-out
License
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Internal
Hand-off

4. About the Center for Connected Health
Mission is
to facilitate
the adoption
of Connected
Health
Technology is
an enabler to
provide care
remotely
Benefits include
improved
engagement,
outcomes, and
efficiencies
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5. Connected Health Benefits
1
Just-in-time
care
2
Improved
self-care
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6. Connected Health Components
Feedback
Loop
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7. Connected Cardiac Care
Heart Failure Monitoring
50%
Drop in
Readmissions
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8. Proportion of CCCP Enrollees with
One or More Hospitalization
100
58.10
Percent
39.80
13.30
One year prior to CCCP
enrollment (point estimate
and 95% C.I.)
One year following CCCP
disenrollment (point estimate
and 95% C.I.)
Data Includes 332 CCCP enrollments among 301 unique patients discharged from the CCCP program prior
to July 1, 2009. Results are similar within more recent cohorts of enrollees discharged from the program prior
October 1, 2009 and prior to January 1, 2010.
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9. Diabetes and Blood Pressure Connect
Average drop of HbA1c: 1.5
69% achieved a drop in BP
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10. Greater engagement is associated with greater pre-post HbA1c change
Average drop HbA1c by # of uploads
1.8
1.53
Drop in HbA1c
1.6
1.34
1.4
1.2
1
0.8
0.6
0.43
0.4
0.2
0
no uploads
1 - 15 uploads
> 15 uploads
Practice engagement correlates strongly with better patient outcomes
• Patients with greater than 15 uploads had average 1.5 pre-post HbA1c change
• P< 0.03 between no uploads and uploads groups
J Diabetes Sci Technol 2012;6(6):1328-1336
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11. Proportion with 10mmHg
or greater drop in SBP
Proportion with 5mmHg
or greater drop in DBP
% of Subjects
% of Subjects
Decreases in Blood Pressure from Self Monitoring
C
I
P<0.05
C
P<0.05
Am Heart J. 2012 Oct;164(4):625-31.
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I

12. Future of Connected Health
•
More varied, miniaturized sensors
Given Imaging
Exmovere
Given Imaging
•
OMsignal
Automated, customized motivational messaging
© 2013 MD Revolution
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13. Video and Virtual Visits
• Increasing interest
among clinicians
• Consumers familiar
with software
• Payment reform
spurring interest
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14. The Future of Video Visits
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15. Feedback Loops Alone Are Not Motivating
– “I didn’t look at it online, I didn’t need to, I thought
that’s what my provider was doing”
– “If I forget to send it in, after a couple of
weeks, she [the nurse] calls me.”
– “I stopped using it for my reasons, but no one
ever called and asked why I stopped so I never
pursued it”
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16. Sentinel Effect
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17. Components of Self Care
Social
Networking
Gamification
Incentives
Coaching
Feedback
Loop
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18. Simple Reminders Can Have A Powerful Effect
Text-message
Reminder
Tues. Sunny.
High 68, Low
53. Please
apply your
sunscreen
today.
Participant reads
message and
applies sunscreen
Remote Monitoring
Data Repository
(RMDR)
Sends SMS when the
tube is opened
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19. Adherence Rate for Sunscreen Use
Weekly Adherence Rates
(mean +/- SEM)
70.0%
60.0%
% Adherence
50.0%
40.0%
Reminder group
30.0%
No Reminder Group
20.0%
10.0%
0.0%
Week 1
Week 2
Week 3
Week 4
Week 5
Study Period
Arch Dermatol. 2009;145(11):1230-1236.
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Week 6

20. The Power of Activity and Coaching
Percent Change in Average Daily Steps Per Quarter
Percent Change
C, n=30
I, n=27
15.00
10.00
5.00
0.00
-5.00
-10.00
-15.00
-20.00
Q1
Q1-Q2
Q1-Q3
Q1-Q4
Quarter (1 Quarter = 3 weeks)
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21. Habituation
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24. Improving physical activity behaviors in T2DM
(Text 2 Move)
Primary Outcomes: Change in physical activity levels
Secondary Outcomes:
Change in HbA1c in patients
Change in stage of behavior change
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25. Readiness
To Change
Connected
Health Data
Customized
Program Design
Analytic
Engine
Practice
Location
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26. Text2Move
February
January
March
10000
8000
6000
4000
2000
Contemplation
Preparation
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Action
3/29
3/22
3/15
3/8
3/1
2/27
2/25
2/23
2/21
2/19
2/17
2/15
2/13
2/11
2/9
2/7
2/5
2/3
2/1
1/31
1/29
1/27
1/25
1/23
1/21
1/19
1/17
1/15
1/13
1/11
1/9
0

27. Meet Michael Snyder
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28. Genetic Risk
Source: Cell 148, 1293–1307, March 16, 2012
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29. Personalized Prevention in Action
Glycated HgA1c (%):
6.4
6.7
(329) (369)
(Day Number)
4.9
(476)
5.4 5.3
(532) (546)
4.7
(602)
Glucose (mg/dL)
160
150
140
130
120
110
100
90
80
-150
0
200
250
300
350
400
450
500
Day Number
HRV Infection
(Day 0-21)
RSV Infection
(Day 289-311)
Source: Cell 148, 1293–1307, March 16, 2012
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Life Style Change
(Day 380-Current)
550
600

30. Motivational
State
Connected
Health Data
Customized
Program Design
Analytic
Engine
Genetic
Profile
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31. Automating Healthcare
Output
Input
Content:
Content:
Genes
Physiological
Functions
Health Info &
Social Support
Coaching
Psychological
Factors
Behavior
Games/
Contests
Incentives/
Punishments
Environmental Factors/
Socioeconomic Status
Analytics
Tactics:
Tactics:
Specimen
Collection
Sensors
Text
Voice
EMRs
Text
Analysis
Rich/
Multi-Media
Avatar/
Agent
Interactive
Software
Online & Offline
Behavior Tracking
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32. Implications of Automating Healthcare
• Social Contract
• Privacy
• Accountability
• Economics
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33. Takeaways
Feedback
Loop
• Feedback loops coupled with
personalized motivation can lead
to sustained behavior change
• Virtual care has great future
potential
• Genetic analysis provides a
powerful foundation
© 2013 Center for Connected Health – All Rights Reserved
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34. Ways to “Connect”
The cHealth Blog:
chealthblog.connectedhealth.org
www.connectedhealth.org
Annual Symposium:
October 23-24 2014; Boston
LinkedIn Group:
Connected Health Community
Twitter:
@connectedhealth
@jkvedar
Contact Me:
jkvedar@partners.org
© 2013 Center for Connected Health – All Rights Reserved
Content Confidential – DO NOT DUPLICATE.