Information Strategy Route Map from Optimity Advisors. Presented by Ken Barrette at WEDI-Con 15

1. Information Strategy Route Map
Outcomes-based Contracting
Presented by: Ken Barrette of Optimity Advisors
Copyright © 2015

2. Today’s Presentation
Topics:
1. Understand Concept of Outcomes-based Contracting
2. Data Discussion and Opportunity
3. Case Study
4. Delivery Framework
Key Learnings:
1. Outcomes-based Contracting
2. Importance of Data Framework / Informatics
3. Appreciation of Collaboration and Time to Implement

3. Outcomes-based Contracting
Rolls Royce pioneered concept Outcomes-based Contracting - ‘Power by
the Hour©’*
• Shifted traditional engine sales and service (paying for
unit, activity, and parts) to pay for keeping planes
‘healthy’ and operational in the air
• Aligned performance measures to outcomes expected
• Transformed reactive service and maintenance to
predictive prevention
• Provided immediate value to customers through:
Predictable costs
Reduced upfront capital investment
Prevented catastrophic events
Improved aircraft value (‘health’) over time
Happy customers – increased market share
*Source: https://en.wikipedia.org/wiki/Power_by_the_Hour

4. Outcomes-based Contracting
What is Outcomes Based Contracting?
KEY CHARACTERISTICS:
• A focus on business outcomes
rather than activities and tasks
• The use of measurable
performance standards that are
tied to the required outcomes.
• Structure, Process
Outcomes
• A pricing model that comprises
or includes rewards and risks
Traditional
Model
Outcomes-
based Model
Source: http://outcomesbasedhealthcare.com/Contracting_for_Outcomes.pdf
Source: Donabedian, A. (2005). Evaluating the quality of medical care. The Millbank Quarterly, 83, 4, 691-729.

5. What Opportunity Does Outcomes-
based Contracting Address?
Healthcare costs are growing faster than the available budgets. This is not
sustainable in the future.
Value($)
Time
Healthcare Costs
Healthcare Budget
Budgetary
Gap

6. Aligning Data Across Complex Health
Ecosystems
Developing and implementing Outcomes-based Contracting program
requires strong data and technology coordination across stakeholders.

7. Information Management Evolving
Industry standards and efforts are aligning to make Outcomes-based
Contracting ‘practical’.
Digital Maturity
Patient
Experience and
outcomes
National
Standards
Powerful
Analytical
Solutions
Quality of
Reporting
Technology
Integration
Behavioral
Insights
Cost reduction

8. Components of a Outcomes-based
Contracting Model
• Business Intelligence (data and information)
• Performance Against Outcomes Metrics
• Payment and Reimbursement Modeling
• System Readiness for Change
• Governance
Establishing an Outcomes-based reimbursement contract requires a
systematic approach to planning and realization.
Quality
-Outcomes
-Safety
-Experience
Payment
-Cost for all
health care
delivery
Value÷
Source: HFMA 2011 – Value in Healthcare: Current State and Future Directions

9. Data Discussion

10. Growth of Health Care Quality
Measures
The health quality measures inventory is growing.
U.S. Health Department of
Health and Human Services
Measures Inventory
National Quality Measures Clearing House
Source: AHRQ

11. Measuring Quality
Regulatory-driven
Measures/Reporting
Industry Standards
NCQA-
HEDIS
Meaningful Use
AMA-
PCPI
Stars
QRS
CQM
PQMP-CHIPRA
IHI-Whole System
Measures
OQR
IPR
PQRS
HIQRP
Structured and Unstructured Data
Structured Data
(Claims, Electronic Medical Record,
Financial/Actuary, Utilization,
Biometrics Lab, Pharma, etc.)
Unstructured
(Social Media, Health Monitoring,
Research, Mobile Apps, Patient Voice,
etc.)
Data Attributes
(Syntax, Format, Definition, Situation,
Relationship, Metadata Taxonomy)
Data Attributes
(Distributed Network, Hashtag,
Emoticon, Wiki-Collective, Social,
Patient Health Records)
PROM
URAC
PQA Performance
Data Capture, Aggregation, Analysis
Business Informatics
Outcomes-basedContracting
Opportunities
MACRA/MIPS

12. Basic Data Framework
Developing a Value-based Outcomes arrangement requires data aggregation and
analysis across multiple data types and measures.
Identify the treatments and
the patients that drive costs
Quantitative Data Qualitative Data
Activity-Level Data
Medical/Encounter
Prescribing Patterns
Supplies/Equipment
Financial Data
Year of Care
Cost per Occurrence
Other financial variables e.g.
- Rebates
- Excess Risk Indicators
- Risk adj. payments
Clinical Quality
Readmission
LOS
Medical Adherence
Safety
Never Events/Exclusions
Medical Adherence
Patient Experience
Simplification
Lower out of pocket
Quality of Life
Satisfaction
One-time set-up cost
Data Monitoring
Technology
Population Identification:
• Conditions
• Risk scores/stratification
• Personal data (age, gender,
ethnicity, etc.)
• Bio-physical data
• Socio-economic indicators
Construct the
Episodic/Treatment Groupers

13. Beyond Traditional Data
Standards
Healthcare has been traditionally focused on interoperable, fixed data layouts and
definitions. We have a unique opportunity to develop informatics that use
metadata, distributed networks research, and social/wiki conventions (#hashtags,
emoticons)
Data
Collection
Archiving
Sharing
Networking
Analysis
Linked Data
Patient Stories
Emoticons
Hashtags
Conversational
Context

14. Case Study

15. Case example: London-based Clinical
Commissioner
A 10 year journey to population level Outcomes-based Payment
• A membership organization of 44 Group Practices (GPs) across a
London borough commissions health services for a population of
around 310,600
• 2015-16 healthcare budget allocation of $575MM
• Key Demographic Variables
– Urban deprivation is higher than the average
– Population profile is younger than the UK average
– Population is highly ethnically diverse
– Life expectancy is below that of London and England, for both males
and females
• The combination of increasing demand for healthcare and cost
inflation in excess of income growth results in a real terms financial
challenge - in a “no change” scenario, it is estimated that this is a
“gap” of about $20MM million in 2014/15 and $15MM million in
2015/16.
• Add to this the reduction in social care budget from $130MM in
2013/14 by $10 MM in 2014/15 and a further $11MM in 2015/16

16. The journey
Moving from current reimbursement (bundled payments) to population-
based outcome contracting.
Source: Need to Nurture: Outcomes-based commissioning in the NHS, Health Foundation, 2015

17. •Identify data
sources
•Finance and
activity data for
current delivery
model
Initial target group
baseline data
analysis and
assessment
•Full baseline
data set
•Define and cost
the activity in
the new care
delivery model
Full population
baseline data
analysis
•Full baseline for
full population
•Model system
impacts
•Model upfront
investments
Model new care
delivery model
costs and volumes
•Design outcome
metrics
•Model potential
benefits for risk
and gainsharing
Alternative
payment and
reimbursement
mechanisms
Outcomes-based Model
Approach
The data and information Optimity Advisors is using to support the
roadmap development.

18. The 10 year roadmap
Using data and information to shape the journey
Identify sources
Assure comparability and data quality
Identify gaps
Determine information system
interoperability
Develop new data requirements to
support outcomes measurement
Design an integrated information
system architecture
Run new systems on contract
performance monitoring
Decision support dashboards for
contract performance monitoring
Baseline
•Population
•Finance
•Activity
•Quality and performance
Years 1-3
•Risk stratification
•Cost* versus price
•Activity shift incentivised
•Outcome contracts for 2-3
population cohorts
Years 4-10
•Population health system
analytics (commissioner)
•Decision support tools
•Performance monitoring
•Risk and gain share based on
outcomes (commissioners and
providers)
*Patient level and actual cost not
bundled payments

19. Enabling Outcomes-based
Contracting
Short term intensive baseline and setup support and long-term
performance management support
Baseline for
outcomes
contracting
Setting up the
integrated
system for real
time decisions
Performance
reporting

20. Example Technology Target
State
The target technology architecture comprises of 4 key outputs:
CACI Database
Livedash
Waiting times
Standard Reports
Performance vs Planned
1 2
WS ETL - UP
Data
Mart
FrontEnd
Business Schema
MS SQL Server
Livedash
MS SQL Server
KPI
Customer
Centric
Financial
Enterprise Data Warehouse
LaaS
Big Data Analytic Environment
Integration&DataWarehouse
File Storage
ETL
Livedash
One repository where data is collected
ETL - IN
Clinical data
dB and excel
Community
Rio
Non Clinical
dB
iCare
dB
LocalEnvironment
Data
Sources
Unstructured
data
Emails etc.
ANALYTICS
Combined analytics
Predictions
1 2
LocalLocal
Distributed Processing
Cluster
NoSQL
Data Store
MODELLING
Population modelling
1 2 big
Service Data
Performance
RTTs
Daily sit reps
Commissioners’ reports
Service Line Reports

21. Delivery Framework

22. Outcomes-based Contracting
Delivery Framework
Our approach to transformation and out performance emphasizes
collaborative business engagement, rapid and iterative implementation,
focused communication and change management to result in desired ROI
Discovery - Critical Success Factors:
 Participation and accountability cross strategy,
operations and implementation teams
 Business engagement and shared accountability for
business case, scope prioritization/sequencing and
budget
 Upfront agreement on success measurements
Implementation - Critical Success Factors:
 Deep and shared understanding of the strategic goals and business
rationale and sustained business sponsorship and engagement
 Holistic portfolio/program/product and change management approach
 Effective benefit realization measurement and reporting
Strategy
Definition
Time-Boxed Discovery
INFORM
 Project initiation
 Strategy review and intent
 Opportunities analysis and research
 Current State & Operational Pain Points
 Gap and priority analysis
 Business Case & Success Criteria
 Future State Vision, Scope & Roadmap
 Budget & Organization Plan
 Roles identification to support ongoing
innovation
Discovery
Iterative Initiative Implementation
 Business process, role and technology architecture design
 Proof of concept
 Rapid Interactive Elaboration, Design & Prototyping
 Output/Product Prioritisation & Ownership
 Data Architecture, Mining, Design, Development and
Visualization
 Change Management and Training Planning and Execution
 Program/Project, Vendor and Communication Management
throughout
Business
Process
Data &
Architecture
Design
Roll Out
&
Change
Manage
ment
Management & Oversight
Iterative Elaboration, Build and Test
Cycles
ROI /
Benefits
Realizatio
n
Measurement
and
continuous
improvement
OUTPERFORM

23. What You Need to Know
• Delivery on Results is One Component of a Successful Shared
Collaboration in Outcomes-based Contracting
• The Dawn of Using Unstructured Data is Here
• Importance of Business Informatics (vs. data warehouse)
• Define Denominator (Quality) Clearly – Identify Performance
Measures
• Start Now – Leverage Quality Measures, Episodic Groupings,
Pharma as Critical Components and Understand Iterating and Time
to Mature
• Leverage Global Health Intellectual Property/Processes/Knowledge
Sharing

24. Thanks for Participating
Questions?Ken Barrette
Partner
Washington, DC | Brussels | London | Los Angeles | New York | Zurich
1600 K Street NW, Suite 200, Washington DC 20006
d: 202.341.2651 t:202.540.9222
e: ken.barrette@optimityadvisors.com www.optimityadvisors.com
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