ward slides for amga aco collaborative - 2011-07-14 final ......jul 14, 2011 · richard e. ward,...
TRANSCRIPT
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Developing the Economic Model for a Successful ACO
AMGA ACO Learning CollaborativeSwissotel, Chicago
Richard E. Ward, MD, MBAReward Health Sciences, Inc.
July 14, 2011
Health SciencesHealth SciencesREWARDREWARD
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Outline
• How can ACOs reduce cost• ACO structure dilemmas• IT investment priorities• Using analytic models
– Population Management – Provider Incentives– ACO Financial Models
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The ACO Stack
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Clinician Workstation‐ Results‐ Profiles‐ To Do List‐ Guidelines
Relative Strength of Sources of Cost Savings for ACOs (illustrative)
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Cost Impact
Reduce Use of Low Value Services of Specialists and
Facilities
PCP Referral Influence
Reduce Rate of Avoidable Clinical
Events
Patient Self‐Management Support
Care Coordination
Reduce Resources Per Clinical ServiceLean
Reduce Duplication of Services
Clinical Decision Support
Health Information Exchange
Provider Consolidation increasing Market Power
Increase Price per Clinical Service or
Episode
Delivery System Transformation
Patient‐Centered Medical Home
and
Accountable Care Organization
and
Meaningful Use of Health Information
Technology
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Fundamental Structural Dilemma #1
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HealthPlan A
HealthPlan B
HealthPlan C
Provider 1
Patients
Provider 2
Patients
Provider 3
Patients
Free Rider Problem• “If Plan A invests in core
process improvement and HIT for its providers, the other plans will receive the savings without bearing the cost. So they will gain advantage.”
Scale Problem• “If Plan A puts it’s own
care managers into clinics of its providers to serve only members of Plan A, there is not enough work to keep the care manager busy.”
Externality Problem• “If Provider 1 invests its
own resources in process improvement and IT, the savings accrue to the health plans.”
Many‐to‐Many Relationshipsbetween Plans and Providers
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• Medicare• Meaningful Use• ACO Gain Sharing• Comparative Effectiveness• Demonstrations
• Some non‐profit Blues plans with high local market share
• PCMH• P4P• Organized Systems of Care
• Health Systems• Kaiser Permanente,
Geisinger• Plan‐initiated
• HealthSpring?• Disease‐specific
• McKesson/US Oncology?• Coops formed with reform bill
funding?
2 Ways Out of Structural Dilemma #1
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Dominant Payer with Resources and a Social Mission
(Willing to invest even if some benefits accrue to other payers)
Provider with Mostly‐Exclusive Relationship with Payer
(May start as a niche but then grow by outcompeting others)
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Patients that have aCare Relationship
with PCMH
Patient CenteredMedical Home
SpecialtyGroup Practice
Hospital & Specialists
HomeHealth
Care MgmtVendor
NursingHome
DMESupplier
EmployeeHealth Clinic
Hospital
Specialist
Specialist
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Fundamental Structural Dilemma #2
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Fundamental Structural Dilemma #2
Every party’s cost savingsis another party’s revenue loss...
…and they are not going to be happy.
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Pre‐1990’s Delivery System Model
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Primary Care
Specialist HospitalHealth Plan
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Idealized 1990’s “Health System” or “Staff‐Model HMO” Model
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Primary Care
Specialist HospitalHealth Plan
Health System
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Conventional 2000’s Organizational Alignment
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Primary Care
Specialist Hospital
Hospitalist
Health Plan
Care Manager
PhysicianOrganization
HospitalSystem
Payer
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Integrated Delivery System ACO Model
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Primary Care
Specialist Hospital
Hospitalist
Health Plan
Care Manager
Accountable Care Organization
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Primary Care‐based ACO Model
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Primary Care
Specialist Hospital
Hospitalist
Health Plan
Care Manager
Primary Care‐based ACO
Co‐Managed Service Lines
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Alignment of Specialists Depends on the Focus of their Practice
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General Internists
Cardiovascular Surgeons
Nurse Care Managers
Cardiologists focused on Heart Failure
Inpatient Care andProcedures
Mid‐Levels focused on ambulatory care
Interventional Cardiologists
Radiologists
Pathologists
Anesthesiologistsin OR
Emergency
Endocrinologistsfocused on Diabetes
Physiatrists focused on surgical rehab
Pulmonologist focused on COPD
Rheumatologists focused on chronic
Osteoarthritis
Pulmonologist in Critical Care
OrthopedicSurgeonsSurgical
Oncologist
Radiation Oncologist
Medical Oncologist
Physiatrists focused on chronic back pain
Cardiologists focused on CCU
Heart & Vascular Service Line Co‐management LLP
Cancer Service LineCo‐management LLP
Psychiatrists focused on depression
Anesthesiologistsfocused on pain mgmt
Ambulatory Care and Population Management
Family Practitioners
Pediatricians
Hospitalists
Transitions of Care &Resource Stewardship
Length of Stay &Referral “Keepage”
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“Cooperative” Model
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Primary Care
Specialist Hospital
Hospitalist
Health Plan
Cooperative
Care Manager
Look familiar?
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Health Information Technology
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Accountable CarePatient CenteredPopulationProcess
Guidelines & ProtocolsMeasures
Going PaperlessClinical Data Accessibility, Efficiency, SecurityOld Vision
New Vision
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Health Information Technology
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Process
DataOld Vision
New Vision
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Benchmarks
Goals
Quality & Cost
PerformanceAnalysisLiterature
Expert Opinion
BestPractices
Data
Outcomes
Process
Feedback
IncentivesProtocols
Guide
lines Implementation
HealthCare
Care‐Delivery
Care‐Planning
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Systems to Enable Process Transformation
HealthCare
Care‐Delivery
Care‐Planning
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Leverage Workflow Automation / Business Process Mgmt Technology used in other industries
TightlyIntegrated
Care Planning ToolsPatient CenteredProblem Oriented
SmartPopulation
Care ProcessManagement Tools
Physician controlledMeasurableCoordination
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Unstructured
• Free text• Dictated and Transcribed• Dictated and voice‐
recognized• Document Images• Optical Character
Recognition
• Drawings• Clinical Images• Sounds
• Human readable
Passively Structured
• Text‐to‐code logic• Commands to include text blocks in notes
• Loosely structured messages
• Human readable with more consistent formatting
• Case finding
Actively Structured
• Registry• Questionnaire• Form‐based Template Charting
• Problem‐oriented clinical documentation templates
• Tightly structured messages
• Human readable with most consistent formatting
• Reminders and alerts• Performance measures• Comparative effectiveness
Health Information
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Clinical DataRepository
Analytical Data Repository
Admin SystemsAdmin Systems Clinical Ancillary SystemsClinical Ancillary Systems
Clinician Workstation‐ Results‐ Profiles‐ To Do List‐ Guidelines
IT Framework to Support ACOs
Analysis & Reporting
• Quality• Episode Profiling• Provider Network Analytics• Registry• Research
Clinical Workstation• Results• Profiles• In Box• Schedule• Guidelines
Clinical Process Mgmt
• Process Designer• Process Simulation• Process Monitoring• Questionnaire Designer• Order/Result Mgmt• Clinical Protocol Mgmt• Care Relationship Mgmt• Call Center Integration• E‐mail, Text & IM
Patient Apps• Results• Coaching• Telemedicine• Care Plan• Questionnaire
Care Planning• Smart Templates• Orders• Clinical Documentation
*US patents #7020618, 7707057
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Analytic Data Repository
RawVersioned
Data
Source Systems
Reports &Reporting
Applications
out
Analytic Data Repository Framework to Support ACOs
Scheduling
Admit, Discharge,Transfer (ADT)
Billing
MedicationAdministration
Operating Room
Credentialing
Etc.
in
Data Derivation Engines & Services
Disease ID Risk ScoresGaps in Care Episodes of Care
Clinical Data Repository
Cubes & Other Summary
Data Structures
Care Relationships
Specialty / Peers
ReferralRelationships Etc.
Derived data
Analyzable Data
• Normalized• Documented• With derived
entities and attributes
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MODELSREPORTS vs.
Looking back Looking ahead
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ChronicConditionsWellness
Concerns& Symptoms
Acute Conditions
ElectiveSurgical Conditions
Complex Catastrophic Conditions
Continuum of Patient Needs
Using Models for Care Management
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Is Care Management Effective?• Are drugs effective?• Is a scalpel effective?
• Which population?• What point in time?• What intervention?• What outcomes of interest?• What time horizon?• What evidence threshold?
It depends
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TARGETEDHOLISTICCompeting Intervention Design Philosophies
• Easier to design• Respects professionalism• Addresses patient complexity• Difficult to evaluate
Many “triggers”
General Assessment
Multi‐Issue Care Plan
Intervention Periodas Coach Evolves Goalsand Revised Care Plan
• Consistent intervention process enables process improvement
• Targeting protocol can be applied to comparison population for evaluation
Targeting of PatientsBased on Objective CriteriaBased on Opportunity to
Benefit from aparticular intervention
Outreach Protocol
Intervention Protocol
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Using Intervention Models to Explore Alternative Interventions
Care Transition Nurse On Site Telephonic
Identified Population/Spend $100 $100
Patients Identified in when still in hospital
$100 $48
Target Rate$100 $41
Reach and Engagement Rate
Effectiveness Rate in avoiding need for readmission
$65 $13
Total Gross Savings $20 $2
100% 48%
100% 86%
65% 32%
30% 15%
IllustrativeCopyrighted 2011, Reward Health Sciences, Inc.
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Intervention Design
Cause‐Effect Model
includes
Process Model
includes
Intervention Model
informsinformsEvaluation
Plan informs
BusinessProcessWorkflow
Diagram (BPD)
informs
Clinical ProgramOperations
orchestrates
Activity Datacreates
enablesextrapolation of
Calculated ActualOutcomes
toProjected Outcomes
For AlternativeIntervention Designs
enablescalculation of
supports assumptions of
confirms plausibility of
Effect Measurement
informs
informs
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Illustrative
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Number of IP admissions per 1000 members identified with CHF, by percentile of risk score
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
0102030405060708090100
Percentile of Symmetry risk score
IP A
dmit
Rat
e pe
r 100
0
Predicted rate per 1000
Overall IP Rate
Illustrative
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Diabetes Disease Management
(1,000,000)
-
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
0% 5% 10%
15%
20%
25%
30%
35%
40%
45%
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
100%
Finding Target Penetration that Yields Max Net Savings:Maximizing Beneficial Impact for Members for the Amount Spent
Gross Savings
Cost
Net Savings
Dollars
41%
Fixed Cost
Illustrative
Target Penetration Rate (as % of Diabetes population)
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Chronic Disease Management
(0.15)
(0.10)
(0.05)
-
0.05
0.10
0.15
0.20
0.25
- 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45
Variable Cost PMPM
Net
Sav
ings
PM
PM IHDCHFDiabetesCOPDAsthma
47% of Ischemic Heart Disease
87% of CongestiveHeart Failure
41% of Diabetes
34% ofCOPD 20% of Asthma
Max Net Savings Signature Illustrative
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Dynamic Models
• Thinking like an accountant analyzing accounts receivable
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-$5M
$0M
$5M
$10M
$15M
$20M
Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
Benefit Cost SavingsOperational CostsInvestment CostsQuarterly Economic Impact
Dynamic Models
Quarterly Economic Impact
2009 2010 2011 2012 2013 2014
Case Management
Illustrative
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Dynamic Models
Quarterly Economic Impact
2009 2010 2011 2012 2013 2014
ILLUSTRATION
Chronic Condition Management
‐$1.0M
‐$0.5M
$0.0M
$0.5M
$1.0M
$1.5M
$2.0M
$2.5M
$3.0M
$3.5M
Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
Benefit Cost Savings
Operational Costs
Investment Costs
Quarterly Economic Impact
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Analyzing UncertaintyUsing Monte Carlo Simulation
Assumptions
Calculations
90% Interval of Uncertainty
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Chronic Condition Management—Sensitivity Analysis
2014 Cumulative Net Savings Frequency Distribution 2014 Cumulative Net Savings Variable Sensitivity
Contribution to Variance
Illustrative
1%
1%
1%
1%
2%
17%
71%
7%
0% 20% 40% 60% 80%
Other
Average Length of Regular
Engagement Phone Calls (min)
MA PPO Annual Inflation (Program
Costs) Growth Rate
MA PPO Annual Medical Spend
Growth Rate Above Inflation
Double Counting Assumption
Engagement Rate (% of reached
members engaged)
Member Reach Rate (% of targeted
members reached)
Total Spend Reduction for Engaged
Members
0
200
400
600
800
1,000
1,200
‐$10M $4M $18M $32M $46M $60M
Freq
uency
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Example of “Hurricane Diagram” WCM Solution Cumulative Net Savings
90%Confidence
Note: Based on a Monte Carlo analysis with 10,000 trials, and triangular distributions on 72 input variables for entire portfolio
Range of Outcomes—Cumulative Portfolio Net Savings
ILLUSTRATION
‐$20M
$M
$20M
$40M
$60M
$80M
$100M
$120M
$140M
Jun‐10 Dec‐10 Jun‐11 Dec‐11 Jun‐12 Dec‐12 Jun‐13 Dec‐13 Jun‐14 Dec‐14
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InghamInghamInghamInghamInghamInghamInghamInghamIngham
KalamazooKalamazooKalamazooKalamazooKalamazooKalamazooKalamazooKalamazooKalamazoo
KentKentKentKentKentKentKentKentKent
OaklandOaklandOaklandOaklandOaklandOaklandOaklandOaklandOakland
WashtenawWashtenawWashtenawWashtenawWashtenawWashtenawWashtenawWashtenawWashtenaw WayneWayneWayneWayneWayneWayneWayneWayneWayne
Modeling Geographically‐Sensitive Interventions
County # Facilities # NCMs1 Annual Net
SavingsEngaged LocallyOakland County 85 10 $ xWayne County 91 8 $ xKent County 22 4 $ xWashtenaw
County 19 3 $ x
Ingham County 7 2 $ xKalamazoo
County 12 2 $ x
Engaged TelephonicallyAll Other
Counties 364 $ x
= Counties targeted locally
1 NCMs = Nurse Care Managers
ILLUSTRATIVE
In‐HospitalCare Transition Nurse
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Projected benefit cost savingsAnnual savings by initiative category
$5,006
$6,281
$7,530
$8,472
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
$8,000
$9,000
2010 2011 2012 2013
Ben
efit
cost
sav
ings
($k)
Service utilization ConditionClinical IT Core clinical processNew group Planned
Projected benefit cost savingsAnnual savings by initiative category as % of total benefit cost
0.23% 0.24% 0.24% 0.24%
0.18%
0.23% 0.25% 0.25%
0.25% 0.25% 0.25% 0.25%
0.35%
0.40%0.43% 0.44%
0.00% 0.00% 0.00% 0.00%0.0%
0.1%
0.1%
0.2%
0.2%
0.3%
0.3%
0.4%
0.4%
0.5%
0.5%
2010 2011 2012 2013
Ben
efit
cost
sav
ings
(%)
Service utilization ConditionClinical IT Core clinical processNew group Planned
Modeling Provider Incentive ProgramsSavings for Customer X for 41 Initiatives in the BCBSM Physician Group Incentive Program
ILLUSTRATIVECopyrighted 2011, Reward Health Sciences, Inc.
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MODELSREPORTS vs.
Looking back Looking ahead
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• Comparison group is not truly comparable
• Noise > Signal
• Noise = “common cause” or “random” variation in people and their response to disease and treatment
BIASVARIATION
The Two Key Challenges to Measurement
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6,533
3,450
-1,0002,0003,0004,0005,0006,0007,0008,0009,000
10,000
Pre Intervention (3 months) Post Intervention (3 month)
Aver
age
Cost
Per
Cas
e (P
MPM
)
Regression to the Mean
47.1%Reduction!
$3,083SavingsPer Case!
n=11,768
Case Management in Senior PopulationCost per Case before and after referral
Illustrative
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44*Post date ranges in relation to 5‐days after targeting.
-
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
Pre61-90
Pre31-60
Pre0-30
Post'0-30
Post31-60
Post61-90
Post91-120
Post121-150
Post151-180
Post181-210
Days in Relation to Targeting for Case Management*
Cos
t Per
Mem
ber P
er M
onth
Engaged
Illustrative
n=11,768
Case Management in Senior PopulationCost per Case before and after referral
Regression to the Mean
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45*Post date ranges in relation to 5‐days after targeting.
Engaged
Not Engaged-
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
Pre61-90
Pre31-60
Pre0-30
Post'0-30
Post31-60
Post61-90
Post91-120
Post121-150
Post151-180
Post181-210
Days in Relation to Targeting for Case Management*
Cos
t Per
Mem
ber P
er M
onth
Illustrative
n=11,768
Case Management in Senior PopulationCost per Case before and after referral
Regression to the Mean
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Pre-Intervention Actual
Pre-Intervention Trend
Expected Post-Intervention Trend
Post-Intevention Actual
Solution = Outcomes Monitoring with “Re‐qualification”
Ramp‐Up Intervention Steady State
IllustrativeRegression to the Mean
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Pre-Intervention Actual
Pre-Intervention Trend
Expected Post-Intervention Trend
Post-Intevention Actual
Solution = Outcomes Monitoring with “Re‐qualification”
Ramp‐Up Intervention Steady State
IllustrativeRegression to the Mean
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Applying Outcomes Monitoring to aVendor‐delivered Disease Mgmt Program
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Using Statistical Models
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Dynamic ACO Financial Model
• ACO gets into financial trouble if their utilization efficiency success outpaces the market conversion to performance‐based reimbursement and the ACO’s efforts to reduce its fixed cost base.
• Deals with health plans can be structured to reduce or share this transition risk.
• The key is to create a dynamic model of the economics from all parties’ perspectives, with believable assumptions and the right balance of simplicity vs. detail.
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ACO Financial ModelAccountable Care Organization
Out of Pocket (copay $, coins %)
Prem
ium sh
are
Premium
P4P
FFS
P4P
Sal
Cap
Cap
P4P
Cap
Cap
Employer
Person
ACO Legal / Contracting Entity
Bon
Sal
Bon
HospitalPCP
HospitalChain
SpecialistIncentive
PhysicianOrganization
PrimaryPractices
SpecialtyPractices
HealthPlan
HSA & Sal
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Summary
• ACO success requires attention to “ACO Stack”• Primary Care vs. Health System Model ACO structure• IT emphasis on care planning & care delivery coordination• Importance of actively structured data• Importance of models, not just reports• Models should address uncertainty and dynamics
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Thank You!
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Questions
Contact Info:Richard E. Ward, MD, [email protected]
519‐817‐8300
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