A bird's eye view of the healthcare system viewed as a continuous learning ecosystem. This suggests the need for deep collaborations and continuous sharing of insights to enable reduction of costs and improvement in outcomes

1. Towards a Continuous Learning Ecosystem:
Data Innovations and Collaborations to Improve Clinical Outcomes and
Reduce Cost of Care
Vipul Kashyap*, Ph.D.
Cigna Healthcare
vipul.kashyap@cigna.com
April 9, 2013
Medical Informatics World, 2013, Boston, MA
* Acknowledgments – Jeff Catteau, Knowledgent (jeff.catteau@knowledgent.com)
Discussions and feedback on the Economic Decision Model

2. Outline
• The Healthcare Ecosystem:
– Current State  Continuous Learning Ecosystem
• Interactions at the Point of Care
• “Coordinated Healthcare Intervention”
• Making it Happen: Incentivizing Research & Knowledge Sharing
– Economic Decision Model
• Conclusions and Next Steps

3. The Healthcare Ecosystem: Current State
Individuals Individuals
Individuals
(Populations?) (Populations?)
Hospitals
Employers Health Pharmaceutical
Advocacy Companies
Providers
Health Plans/ Clinical Research
Payors Organizations (CROs)
Employer/Payor Perspective Pharma Perspective Provider Perspective
Siloized Ecosystem – Lack of collaboration/coordination – Inefficient!

4. The Continuous Learning Ecosystem
Patient/
Individual
Lifelong Continuous Engagement
Continuous Learning
Ability to share and exchange clinical information and knowledge is a critical enabler

5. Interactions at the Point of Care
Follow Instructions:
Lab Tests, Medications, others
Medical History? Medications?
Allergies? Contraindications?
Referrals? Follow Up? Reimbursement
Continuous Learning Ecosystem: Roadblock
Does the physician have time and incentive to identify insights,
research new ideas and share them with other stakeholders?

6. Data, Analytics & Knowledge
Demographics Diagnosis Medication Procedure Allergy Contraindication Order Referral Result Reimb
Patient 1
Patient 2
Patient 3
Patient 4
Patient 5
Patient 6
Patient 7
Patient 8
Patient 9
Patient 10
Patient 11
Patient 12
Patient 13
Patient 14
Observation/Hypothesis:
Physicians implicitly leverage experience to create patterns or “Care Archetypes ”
Opportunity:
Leverage “Care Archetypes” as an organizational framework for improving cost/outcomes
Sharing and communication of “Care Archetypes” across the Ecosystem

7. Interactions at the Point of Care: Populations
Medication/Therapy compliance
Discuss Alternatives, Activation and
Engagement
Cost Effective? Affordable?
Good Outcomes? Alternate Treatments?
Risk? Engagement/Outreach?
Behavioral Archetype? Compliance?
Incentivized?
Continuous Learning Ecosystem: Roadblock partially addressed
Transition to Pay for Performance has begun!
However: Improving Performance requires research – and sharing of insights and results
Pay for Insight/Pay for Research is not yet on the agenda!

8. Interactions at the Point of Care: Research
Comparative Effectiveness Research
Clinical Trials
Clinical Studies
New Interventions (Therapeutic, Incentives, Engagement)?
Impact of new ongoing research? Patient Participation?
Contribution of Insights:
New Cost Effective approach, Drug Side Effects, New Behavioral Incentives
Granular Care Delivery contexts where Interventions are effective?
Genomic correlates of behavioral/activation characteristics?

9. Aligning Research and Practice
Do physicians have the orientation to do research in the context of clinical practice?
Opportunity
Analysis Hypothesis
Ideation
Generation
Clinical Trials/
Populations/ Studies
Segments
Outcomes
Measurement
Differential Diagnosis/
Possible Likelihood Estimation
Diagnoses
Therapeutic
Intervention
Care
Archetypes
History Lab Tests/
& Physical Longitudinal Follow Up
Physicians continue as usual – Automated Infrastructure pulls data and performs “Research Analytics”

10. Data, Analytics and Knowledge
Population Clinical Care Genome Toxicity/ Cost Risk Quality Behavioral/ Therapeutic Engagement/ Payment Patient
Dimensions* Efficacy Activation Intervention Outreach Incentives Incentives
Popltn 1
Patient 1 Interventions that need
Patient 2 to be studied/evaluated
Patient 3
Patient 4
Activation Segments
Care Archetypes
Patient Stratification
Patient 5
Populations
Popltn 2
Patient 6
Patient 7
Patient 8
Patient 9
Patient 10
Popltn 3
Patient 11
Patient 12
Patient 13
Patient 14
Alignment
Patient Care Archetypes  Cost/Quality Populations  Behavioral/Activation Segments
 Patient Stratification

11. Coordinated Healthcare Intervention
Therapeutic Intervention Informational
- Drugs, Procedures - Outreach
- Devices - Wellness Apps
Coordinated
Health Intervention
Motivational
Cost and Risk Sharing
- Engagement
- Provider Incentive
- Personal Incentive
• Optimal Health Interventions will require collaborations between stakeholders
across the ecosystem
• Optimizes a set of criteria:
outcomes, cost, toxicity, efficacy, utilization, economic benefit

12. Scenario: Emergence of the Third Party RO/A
Engagement Protocols
Medication
Incentives, Compliance
Infrastructure Investment Insights
Research/
Behavioral Validation
Data/Insights Licensing Model
Prescribing/
Administration Medication Adherence Licensing Model
Protocols Insights
• The Healthcare Ecosystem as a “Continuous Learning System” – Driven by Research
• Reduce barriers to participation: Provide common infrastructure and a set of incentives
• Need to incentivize sharing data generated from on going observations and measurement
• Need for a trusted “Third Party Research Organization/Aggregator”

13. Towards an Economic Decision Model
U = R – (Ic + Ir) U = R – (Ip + Ir)
Ir consists of one time and incremental Ir consists of investments in utilization
investments: ui = ri + d – Ii and incentives
Um/2 = (Uprovider + Upayor + Upharma)
U = utility, R = Revenue Ui = U + (ri) – (Ic + Ir)
I: Investment in Care (Ic), Ir consists of investments in compliance
Research (Clinical, Utilization, Incentives) (Ir), and incentives
Payment (Ip)
• Utilization Model for Research drives investment in research to address the information gap
• Providers will rationally consume results to drive cost/outcomes improvement in clinical care
• Payors and Pharma will drive investments in infrastructure and incentives to drive research
• Optimization curve for market based on marginal gains for various components

14. Conclusions
• The Health Ecosystem needs to evolve into a Continuous Learning Ecosystem to achieve
cost/outcome objectives
• Need for Deep Collaborations & Information Sharing to close the Information Gap
Care Archetypes  Populations Activation/Behavioral Segmentations  Toxicity/Efficacy
Stratifications
• Need to invest in infrastructure and incentivize research and knowledge sharing
– Reducing Information Gap creates value (in terms of cost/outcomes) which is consumed by
different stakeholders in the ecosystem
– Information Gap always exists (due to new knowledge and information)  new economic
incentives market evolution/continuous learning
• Trust – a key roadblock – may lead to the emergence of third party research
organizations/aggregators
• Next steps: Develop Economic Decision Model and Work on a Roadmap of Incentives to
achieve a Continuous Learning Ecosystem!

15. Blog
http://continuouslearningecosystem.blogspot.com
Look forward to comments, feedback, critique, suggestions!