Edgewater Healthcare Consulting presented at the Boston Society for Information Management (SIM) with client Southcoast Health on Integrating Analytics for Value-Based Healthcare

1. Integrating Analytics for Value-Based Healthcare
Joshua McHale
Maury DePalo

2. 22
Today’s Topic …
Population Health Analytics
• Current Climate and Challenges - Program Objectives
• Driving Needs for Focused Analytics - to Improve Clinical and Financial Performance
• Mobilizing by Process Implementation & Improvement
Data Integration Challenges
• Enterprise Data Architecture
• Primary Components – Data Sourcing, Transformation, Delivery
• End-User Data Navigation Model – Integrated Data Repository
Business Intelligence and Data Exploration
• Empowering the End-User Experience – Examples
• Action-Oriented Performance Measures
Moving Forward
• Risk and Alternative Quality Contracts
• Reducing Clinical Variation
• Mobilizing for Value-Based Care
Q & A

3. 33
Population Health Analytics
Current Business Climate & Challenges
• Relentless Pressures on Quality  Outcomes  Costs
• Need for Innovation in Care Delivery, Coordination, Risk Sharing, Cost Control
• Massachusetts Health Policy Commission – Phase 2 of Community Health Acceleration,
Revitalization, and Transformation investment program (CHART-2)
• Enhance delivery of efficient, effective care at community hospitals
• Promote care coordination, integration, delivery transformation
• Advance EHR adoption  information exchange among providers
• Increase adoption of alternative payment models  accountable care organizations
• Enhance patient safety  coordination between hospitals and community-based providers
• Leveraging resources of community partners
• Focus on Pressing Healthcare Needs in Local Communities
• Targeted At-Risk Populations  Behavioral Health; Diabetes
• High Utilizers  > 4 Inpatient Admissions; > 10 Emergency Room Visits
• Improve Coordination and Access to Care
• Improve engagement of high-risk diabetes patients  incorporate into care management programs
 development of disease management registries

4. 44
Population Health Analytics
Driving Needs for Focused Analytics to Improve Clinical & Financial Performance
• Identify & Characterize Key Targeted Patient Populations
• At Risk Populations, Preventive Care, Patient Experience
• Identify Targets for Intervention & Improvement Programs
• Patient, Diagnosis
• Provider, Service Utilization, Care Coordination
• Track Quality and Financial Performance Metrics Against Baselines & Targets
• Individual and Aggregate Measures – Drill-Down on Quality & Financial Performance
• Individual Patients – Individual Providers
• Aggregate Providers – Aggregate Care Teams – Aggregate Practice Groups / Locations
• Track Attributed Populations Defined Under Risk Performance Contracts
• Track Response to Programs – Defined Quality Measures
• Track Assignment Consistency – Care Plan Compliance
• Disseminate Standards of Care Across Care Teams & Settings
• Track Variation in Outcomes, Utilization, Costs

5. 55
Population Health Analytics
Integrating Care Planning – Execution on Focused Patient Cohorts
•Examine Performance Contracts
– Patient Mix, Service Mix
•Establish Baseline Measures and
Set Patient Goals
•Begin Care Plan Activities
•Monitor Adherence according to
Care Plan & Schedule
•Track Quality and Financial
Metrics
•Measure Results of Individual
Patients & Evaluate Impact of
Program on Overall Population
•Adjust Accordingly & Schedule
Follow-ups
•Design Care Plans &
Interventions – Activities,
Observations & Measures
•Assign Patients to Tailored Care
Plans Consistent with Goals for
Overall Population
•Identify Partner Providers for
Outreach and Coordinating Care
•Identify Patients Targeted for
Intervention - Define Cohorts
•Stratify Patients Based on
Clinical or Financial Risk or
Operational Resource Demands
•Target Specific Interventions
Identify
&
Stratify
Design
&
Assign
Execute
&
Monitor
Evaluate
&
Adjust

6. 66
Achieving Value-Based Accountable Care
Pursuing a Staged Implementation – Success Factors at Each Stage
Patient Panel
Definition
Targeted
Populations &
Outcomes
Baseline
Expenditures
& Costs
Accountability
Models
Financial
Reconciliation
Population
Health
Management
 Identify Unique
Patients
 Assemble
Records of
Clinical Care
 Define Bundles
 Identify Unique
Providers
 Align Patients &
Providers
 Measure /
Manage Care
Delivery
 Measure /
Manage Care
Relationships
 Patient Panel
Analytics
 Defined Patients,
Beneficiaries or
Members
 Segmentation
 Outcomes:
Clinical,
Operational,
Financial
 Identify ACO
Parties & Roles
 Performance
Targets &
Metrics
 Targeted Care
Plans
 EBM Guidelines
for Required
Care for Patient
Needs
 Historical
Baselines
 Align Patient with
Provider Entity
 Align Provider
with ACO Entity
 Calculate
Service Fees &
Savings Targets
 Hierarchical
Segmentation &
Aggregation
 Anticipated
Services,
Charges & Costs
 Collaborative
Care Delivery
Models
 Transitions in
Care
 Communications,
Handoffs,
Follow-ups
 Contracts, Roles,
Responsibilities
 Shared Metrics,
Benefits & Risks
 Retrospective
Payments
 Shared Savings
& Costs
 Value Realization
 Allocated Gains
(Losses)
 Billing &
Payment
Distribution
 Compliance &
Adherence
Targets
 Patient
Stratification
 Comparative
Outcomes &
Quality Metrics
 Prospective &
Bundled
Payment Models
 Predictive Risk
Modeling
 Performance
Optimization
 Market Share
& Competitive
Analytics

7. 77
Population Health Analytics
Health Systems Need to Know …
How do we manage patient cohorts more systematically? How do we better
integrate and focus our care delivery across these populations & care settings?
Population Health
Management
Do we understand our charges, payments and costs? Are we reconciling these with
our care plans and our accountability models?
Financial Reconciliation
How do we implement & measure accountability across our ACO partnerships?
Where and by whom are value and costs introduced into our delivery processes?
Accountability Models
What are our baseline expenditures & care delivery costs on these targets, with this
payer? How do these align with our contract terms across payer types?
Baseline Expenditures
& Costs
What are our current targets for patients & outcomes? What quality / results are
we seeing? Are they consistent? Where do we see under- or over-performance?
Targeted Populations
& Outcomes
Who are our patients? What treatments are they receiving? What other providers
are they seeing? At what locations? With what frequency?
Patient Panel
Definition

8. 88
Data Integration Challenges
We Need Visibility Into …
- Demographics
- History
- Reported
Outcomes
- Location
- Specialty
- Relationships
- Location
- Care Team
- Structure
- Locations
- Legal Entity
- Contracts
-Care Mgmt
Teams
- Inpatient
- Outpatient
- Pharmacy
- Beneficiary
History
- Payers
- Charges,
Payments &
Adjustments
- Costs
- Margin
- Risk Contracts
- Diagnosis
- ChronicConditions
- Labs & Results
- Procedures &
Medications
- Quality
- Appts
- Scheduling
- Utilization &
Throughput
- DRG
- Location

9. 99
Enterprise Data Architecture
DataIntegration&Transformation
Patient Panel Analytics
Targeted Populations
& Outcomes
Baseline Expenditures
& Costs
Accountability Models
Financial Reconciliation
Population Health
Management
Dashboards &
Analytic Views
Contract Measures
Performance
Summary
Baseline Expenditure
Provider Profile
EMR
Billing
Provider
Master
Health
System
Payers
Claims
DataAccess–Navigation&Security
Reports
Patient
Capture Integration and Transformation Consumption
Extensible Data
Architecture
Standard Data Models
MPI
Coding
Members
Provider
Claim
Reference
Other
Master
Data
Encounter
Location

10. 1010
Data Integration Challenges
Data From Multiple Source Systems of Record and Points of Origin
• Differing Formats and Semantics
• Inconsistent Taxonomies
• Differing Data Granularities
Technical Challenges
• Timing and Granularity Differences and Conflicts
• Access to data stored in the cloud
• Positioning for Big Data Opportunities
End-User Experience
• Consistent but Responsive (Variable, Tailorable) Experience
• Power User vs. Ease of Use
• Education on Source, Meaning and Veracity of Data Elements
Data Governance
• Lack of consistent Enterprise-wide definitions
• Different groups use similar terminology for different data and meanings
Evolving Needs for Focused Analytics – Driving Clinical and Financial Performance

11. 1111
End-User Experience – Navigating Complex Data Spaces
Patient
Organization
Provider
Location
Contracts
Payer
Claims
Payments
Encounter
Charges
Costs
Diagnosis
Treatments
Chronic
Condition
Disease
Group
Procedures
Medications
Margin
Events
Data Navigation Model …

12. 1212
End-User Experience – Empowering Analytics
Navigating Multi-Dimensional Data Spaces
Intuitive & Flexible Navigation of Multi-Source Data Spaces
• Data Integrated from Numerous Sources – Network Data Model
• High-Performance Interactive UI – Free Navigation Across Subject Areas

13. 1313
End-User Experience – Empowering Analytics
Empowering the End-User with Context-Informed Search …

14. 1414
Moving Forward – Risk and Population Focused Quality Contracts
0
20
40
60
80
100
120
140
160
Year 1 Year 2 Year 3 Year 4 Year 5
PERFORMANCEAGAINSTBASELINE
CONTRACT PERFORMANCE YEAR
Performance
CPI
Efficiency
Baseline
Value Axis
Patient Count ...
{ Contract Performance } - { Aggregate Population } - { Segment by Quality Measures, Cost Components }
Segmentation
Population Segments, Quality Measures, Cost Components, ...
Savings Elements

15. 1515
Risk and Population Focused Quality Contracts
Population Composition
0
20
40
60
80
100
120
140
160
180
2008-Q2 2008-Q4 2009-Q2 2009-Q4 2010-Q2
PATIENTCOUNT
DATE OF OBSERVATION
Diabetes
PreDiabetes
Normal
Value Axis
Patient Count ...
{ Population Composition } - { Diabetes } - { Disease Severity Cohort }
Color Axis
Disease Severity ...
Disease Severity

16. 1616
0
2000
4000
6000
8000
10000
12000
14000
16000 4.8
5.0
5.2
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5.6
5.8
6.0
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6.8
7.0
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7.8
8.0
8.2
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9.0
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10.0
10.2
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10.6
10.8
11.0
PATIENTCOUNT
HB A1C - MOST RECENT OBSERVATION PER PATIENT
Poor
Good
Excellent
{ Population Composition - Distribution Analysis } – { Diabetes } – { Disease Severity Cohort }
Adherence to
Care Plan
Value Axis Color Axis
Patient Count ... Adherence to Care Plan ...
Category Axis
Hb A1c - Most Recent Observed Value
Risk and Population Focused Quality Contracts
Population Composition – Distribution Analysis

17. 1717
Risk and Population Focused Quality Contracts
Population Composition – Distribution Analysis
0
2000
4000
6000
8000
10000
12000
14000
16000
1.0
2.0
3.0
4.0
5.0
6.0
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8.0
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31.0
32.0
PATIENTCOUNT
NUMBER OF MONTHS ENROLLED ON INTERVENTION CARE PLAN
Unfavorable
No Change
Favorable
{ Population Composition – Distribution Analysis } - { Diabetes } - { Time on Care Plan Cohort }
Response to
Care Plan
Value Axis Color Axis
Category Axis
Patient Count ... Response to Care Plan ...
Number of Months Enrolled on Intervention Care Plan

18. 1818
Reducing Clinical Variation
Procedure / Treatment:
• Current Treatment
• Prior Treatments
• Response
• Adverse Events
Disease Condition:
• Diagnosis
• Complications / Comorbidities
• Demographic / Socio-Econ
Operations / Utilization:
• Service Utilization
• Resource Utilization
• Fac / Lab / Mat / Equip
• Care Planning / Mgmt,
Pathways
Financial:
• Revenue & Cost
• Profitability
• Payers & Contracts
Quality:
• Clinical Outcomes
• Patient Satisfaction
• Process Adherence
Measures:
• HbA1c, Mortality, QOL, Patient
Satisfaction, HAC, Infection
• LOS, Resource Util, Service Util
• Reimbursement, Costs of Care
• # Encounters, Care Settings, Duration
Between Encounters
• Care Plan Adherence

19. 1919
Reducing Clinical Variation
0
50
100
150
200
250
300
1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8
TotalNumberofCases
Avg LOS per Case
Rotator Cuff Repair: Distribution of Avg LOS by Surgeon
Hockensmith Hunnicutt Sexton Roderick Endicott

20. 2020
Reducing Clinical Variation
0
50
100
150
200
250
300
1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8
TotalNumberofCases
Avg LOS per Case
Rotator Cuff Repair: Distribution of Avg LOS by Surgeon
Hockensmith Hunnicutt Sexton Roderick Endicott
0
20
40
60
80
100
120
140
160
1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8
TotalNumberofCases
Avg LOS per Case
Rotator Cuff Repair: Distribution of Avg LOS by Surgeon
Hockensmith Hunnicutt Sexton Roderick Endicott

21. 2121
Reducing Clinical Variation

22. 2222
Mobilizing for Value-Based Care
Workflows Integrate Data Capture, Care Delivery, Communications & Shared Metrics
 Physician Office
 Other Care Settings
Integrated
Database & HIE
Patient Registries
& Analytics,
Financial & Quality
Measures
Workflow
Triggers, Alerts &
Escalation
 Patient Registration, Scheduling
 Call Center
 Patient Home
 Web Access Assessment & Stratification
 Individualized Care Plan
 Discharge
 Progress
Review
Labs
EMRs
Quality
Performance
Improvement
 Phone
 Outreach
Workflow Mgmt
Data Sharing
Patient Engagement
Care Plans
Practice Mgmt
Cost
of Care

23. 2323
Achieving Value-Based Accountable Care
A Business Intelligence & Change Management Platform
Patient Panel
Definition
Targeted
Populations &
Outcomes
Baseline
Expenditures
& Costs
Accountability
Models
Financial
Reconciliation
Population
Health
Management
Integrated
Data Platform
Changes to Processes
& Operations
Changing Business
Models
Population &
Practice Models

24. 2424
Integrating Analytics for Value-Based Healthcare
Accountable
Care Analytics
Clinical
Strategic
Planning
IT
Practice
Mgmt
Marketing
Finance
 Revenue Cycle
 Costs, Margin
 Payer Mix
 Stratification
 Outcomes
 Quality &
Safety
 Growth
 Market Share
 Competition
 Architecture
 Data Quality
 Tools, Applications
 Security, Governance
 Patient Satisfaction
 Panel Management
 Continuum of Care
 Outreach
 Physician Liaison
 Relationship Mgmt
 Service Improvement
Integrating Analytics for Clinical, Operational and Financial Improvement

25. 2525
Questions?
Thank You!

26. 2626
Dave Hegarty
Healthcare Business Development
Phone: 781-213-9864
Email: dhegarty@edgewater.com
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