Integrating Analytics for Value-Based Healthcare
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The document discusses the integration of analytics in value-based healthcare, emphasizing the importance of population health analytics to improve clinical and financial performance. It outlines challenges in data integration, the need for focused analytics, and strategies to mobilize healthcare delivery, while highlighting the role of accountable care organizations and alternative payment models. The content also addresses achieving better care coordination and patient engagement strategies for targeted populations, alongside identifying and stratifying patients for tailored care plans.
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 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2 8.4 8.6 8.8 9.0 9.2 9.4 9.6 9.8 10.0 10.2 10.4 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 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0 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
- 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
- 26. 2626 Dave Hegarty Healthcare Business Development Phone: 781-213-9864 Email: dhegarty@edgewater.com Contact Us … If you would like to see a demo of any of our analytics applications, please contact: