IBM Global Healthcare & Life Sciences

1. Harnessing Population Health
Management to Promote Quality
Improvement in Healthcare
Judy Murphy, RN, FACMI, FHIMSS, FAAN
Chief Nursing Officer
IBM Global Healthcare & Life Sciences

2. Slide 2
What we will cover:
– Evolving healthcare landscape – what is changing and why
we need to change too
– Population Health Management
– Reimagining Health and Healthcare with Mobile
– Population Health Management requires Patient Engagement
– Emerging Consumerism and eCommerce
– The Need for Analytics
– The Era of Cognitive Computing (Watson)

3. Healthcare transformation is happening, driven by
fundamental shifts in expectations and critical drivers
Expectations for better
quality, value and
outcomes
Escalating incidence and
cost of chronic disease
Changing demographics
and lifestyles
Globalization of health
care
Critical resource
shortages
Increased competition
and new entrants
Advances in
technologies
and treatments
Slide 3

4. Old Healthcare New Healthcare
Fee for service Pay for performance
Volume Value
Delivery Quality Outcome
Employer-centric Consumer-centric
Prices unknown Cost transparency
One way dialogue Engaged & mobile
Transactional Brand loyal
Data poor & disconnected Integrated rich “big” data
Reactive Predictive & prescriptive
Standards Personalized & optimized
This transformation is an evolution …
to a new model for healthcare
Slide 4

5. Healthcare is moving to a system focused on value,
coordinated around the individual,
and integrated into our communities
Focus is on value,
coordinated around the
individual and integrated
into communities
Emphasis is on proactive
care to meet health needs
Payment will be based on
value and outcomes
Care is standardized
according to evidence-
based guidelines
We measure quality and
make rapid changes to
improve it
Data and Information
Understand
and
influence
their
populations
Evidence-based and
standardizedcare planning
Coordination
across
boundaries
-- share care,
accountability
and risk
Individual
engagement
and
empower-
ment
Quality
measurement
and
performance
reporting
Social Worker
Behavioural
Health
Family
Community
Pallative Care/
Hospice
Rehabilitation
Home Care
Specialists Intensivist
Physical
Therapist
Dietician
Case Manager
Caregivers
Transportation
Housing
Medications
Funding and
Payment
Primary
Care
Slide 5

6. The new model is Value Based Care –
centered around the patient
Value =
Experience
Cost
Taking steps to achieve better
results, and improve customer
(patient) satisfaction
Reducing waste, reducing
errors, managing risk, improving
efficiency and quality
Organizations
are on a journey
to improve value
Slide 6

7. Population Health Management
HEALTHY / LOW RISK CHRONICAT RISK
ACTIVE
DISEASE
No or very-low touch
Medium to
high touch
Low touch
High
touch
40-60% 5-15%20-25% 2-3%
60+
5-10% 30-40%15-20% 40-50%
RISK
STRATIFICA
TION
POPULATION
RELATIVE
COST
ENGAGE
MENT
Fully automated
Validate from data
Blended -
retail outlet,
care mgt,
automated
Mostly automated
with email, call,
text, mobile app
Active
Case
Mgmt
OUTREACH
Capability Needs
• Data (internal-external)
• Scalable platform/data
management
• Risk analytics &
management
• Insight analytics
• Similarity analytics
• Cost of care analytics
• Actuarial analytics
• Marketing analytics
• Marketing management
• Predictive modeling /
next best action
• CRM
• Campaign management
• Outreach advisor
• Remote data capture
• Mobile apps
• Network analytics
• Care coordination tool/
clinical integration~20% of population
drives ~80% of cost
ENTIRE
POPULATION
Slide 7

8. Reimagining Health &
Healthcare with Mobile
Slide 8

9. Mobile is being exploited to:
Facilitate anytime anywhere access to data and extend
services beyond traditional settings
Develop new engagement techniques and health strategies
with patients and consumers
Gain insights to provide more personalized, proactive
interventions; bring analytics to the point of care
Slide 9

10. Imagining Care Anywhere
https://www.youtube.com/watch?v=UOMtWFeyscg
Slide 10

11. The Power of Patient Engagement:
Population Health Management requires Patient Engagement
Capture and incorporate
preferences
Personalize offerings
and services
Innovate to deliver quality,
convenience and total
experience
“Know me”
“Engage me”
“Empower me”
• What’s my history?
• What are my preferences?
• How will I respond?
• What will motivate me?
• Respect my privacy
• Engage in the preferred dialog
• Be relevant (“right information”)
• Be consistent across touch points
• Show sincerity -- “you care”
• Give me the information I need
• Connect me with relevant communities
• Simplify control and access
• Enable action and convenience
Slide 11

12. Trends Supporting Greater Patient Engagement
The way we pay for and deliver care is changing.
Health IT adoption has reached a tipping point.
Technology is getting better, cheaper, faster
and more ubiquitous.
Consumers increasingly expect online
engagement, in all aspects of their lives.
Slide 12

13. Integration of health in our lives
https://www.youtube.com/watch?v=-zh9fibMaEk
Slide 13

14. So what is driving “Consumerism” in healthcare?
Source: Healthcare Payer News, May 2014
• Cost shifting – “out of
pocket” costs are
increasing for individual
healthcare consumers
• There is an increase in
the use of High
Deductible plans and
Health Savings Accounts
(HSAs), leading to more
consumer price sensitivity
Slide 14

15. New business models for delivering care are emerging,
providing people with more “choice”
Slide 15

16. Health Plan Engagement App Demo
https://www.youtube.com/watch?v=brtucoXRbTA
Consumer “Shop & Buy” activities
Slide 16

17. Successful healthcare organizations thrive by using analytics
as a core strategic foundation
Early and accurate
insights on member
health risk and
utilization to inform
Financial / Actuarial
decisions
Patient-360 insights
to inform Medical
Management in
chronic disease &
episode
management
Insights into referral
patterns and
provider quality to
support Network
Design and
Management
Inform program design &
operations for Marketing &
Sales and Customer
Service with insights on
consumer preferences &
triggers
Population
Health
Risk
Management
Consumer
Engagement
Provider
Relations
Support
Business
Functions
Impact
Continuumof
Care
Sample Analytics Applications
Facilitate insights
exchange &
messaging across care
team members. Inform
incentives design.
Enabling analytics to
empower ACOs and
providers to
succeed in value-
based payment
transformation
Next best action
analytics leveraging
real-time data to
optimize omni-
channel consumer
engagement
Provide tools to
providers to
enhance risk
stratification and
clinical decision
making
Care Path
Mining
Network
Optimization
Personality
Insights
Consumer
Segmentation
Risk
Stratification
Utilization
Prediction
Cost Patten
Detection
Channel
Optimization
Resource
Allocation
17
Slide 17

18.  What is the optimal
treatment based on the
latest literature for my
patient’s clinical profile?
 Why is this the best
protocol?
Basic
Reporting
 What happened?
 When and
where?
 How much?
Foundational
Analytics
 Who is at risk?
 What is happening?
 How can we improve?
 What is the Right
Data?
 What actions to take?
Enterprise –
Wide Data
InsightsRetrospectiv
e Reporting
Proactive
Interventions
and Improved
Outcomes
 Data Governance
 Centralize Data
 Structured and Unstructured
 Data Sharing
 Cost of Care Intelligence
 High latency reporting
 Spreadsheets
 Limited view reports
 Dept data marts
 Population Health
Analytics
 Evidence-based
medicine
 Streaming Analytics
 Similarity Analytics
Natural language
understanding
Guided consumer
experience
Watson Applications
Clinical Content Analysis
Personalized Healthcare
Dynamic
Learning for
Optimal Care
Guidance
Predictive &
Prescriptive
 What will happen?
 How can we pre-empt?
 What is the likely outcome? Who
would be best at managing this
patient?
 What is the expected response
to potential medications?
CognitiveThe Healthcare Analytics
Journey
18
Slide 18

19. Published
Knowledge
WATSON
Patient Care
and Insights
Knowledge-Driven Methods Data-Driven Methods
Observational
Data
Longitudinal health records
Claims data
Patient reported data
Scientific papers
Books
Guidelines
Patient Similarity Analytics
Identification
of evidence-
based best
practice
From population averages … To insights for individual patients
Analytics strategy must span both knowledge & data-driven methods
19 Slide 19

20. Trusted
Information
Platform
Predictive
Dashboards
Natural
Language
Cognitive
Computing
‘Big Data’
Volume,
Velocity,
Variety…
Patient
Similarity
Healthcare Analytics Progression
Slide 20

21. Watson is ushering in a new era of computing
1900 1950 2011
Slide 21

22. Cognitive Systems Era
Discover and Decide
Interact Naturally
Learn and Reason
Slide 22

23. Watson May Help Beat Cancer
Slide 23
https://www.youtube.com/watch?v=E7wpFfEqE1k

24. Slide 24
Thanks!
Judy Murphy
murphyja@us.ibm.com
@JudyMurphyHIT