1. Harnessing the Power of Predictive Modeling Future Trends

2. Harnessing the Power of Predictive Modeling Future Trends Traditional Applications Recent Applications Future Trends –Motivation Index –Forecasting Disease Specific Risk –Provider Market Forecasting Preventable Events

3. Predictive Models Traditional Applications Risk Stratify the Population for care management –Manage complexly ill members (Inpatient avoidance) –Refine disease management strategies –Manage pharmacy services Underwrite more accurately Reimburse based on illness burden Evaluate physician management strategies

4. Predictive Models Changing Focus Traditional Application has been to Identify: –High Risk / High Cost members –Inpatient Risk Recent Applications –Forecasting additional Cost Components ER Visit Risk Pharmacy Cost forecasting –Identify Intervenable or Actionable members Future Trends –Member Motivation –Disease Specific Complications –Preventable Events for the Provider Market

5. Recent Application Identifying Actionable Members Method A –Query population by multiple filters: Disease Cost Risk Inpatient Risk Pharmacy Risk Mover Risk Method B –Impact Index : Model that identifies members who have the greatest potential for outcome improvement based on guideline compliance

6. Recent Application Multiple filters to identify actionable members Total Population: 216,842 members High Risk Index Top 2% High Risk + Mover 4,362 Members Forecasted Cost: $25,741 Prior Year Cost: $45,006 Savings Potential: -$84,033,930 498 Members Forecasted Cost: $20,084 Prior Year Cost: $8,832 Savings Potential: $5,603,496

7. Total Population: 925,407 Diabetes: 50,847 High-Risk Index Risk Level 4&5 High Impact Index Top 15% 14,250 Members Forecasted Cost: $14,634 Prior Year Cost: $14,527 Savings Potential: $1,524,750 13,872 Members Forecasted Cost: $8,698 Prior Year Cost: $5,089 Savings Potential: $50,064,048 Recent Application Impact Index to identify actionable members

8. Recent Application Impact Index These Drivers –Disease –Age/Sex –Comorbidities –Guideline Compliance Patterns Determine future impactability Determine potential cost savings

9. Future Trends Motivation Index Identify members –more motivated to ‘self-manage’ –comply with instructions from providers –pursue ways to improve health status To create index use data sources –Lifestyle Data –Health Risk Assessment –Demographics –Claims Data

10. Future Trends Motivation Index Drivers Lifestyle Data –Net Worth –Credit History –Magazine Subscriptions –Hobbies –Clubs Claims Data –Compliance Patterns –Preventive Care –Physician Visit Patterns Claritas US Census Bureau Media Mark

11. Future Trends Motivation Index Variables Claims Data –Compliance Patterns To Guidelines To Psych-Related Drugs To Maintenance Drugs –Preventive Care Use of preventive health services Compliance to Preventive Lab Test Compliance to standard preventive guidelines –Physician Visit Patterns Gap/Frequency between Acute Care & Physician visits Gap/Frequency between Physician visits per disease –Cost Ratios for Inpt / Rehab / Rx / Physician Demographic / Misc –Age/Sex –Obesity / Smoking –Drug/Alcohol Dependency –Mental Health

12. Future Trends Motivation Index Drivers Patients with higher motivation scores have –Better guideline compliance –Older age –Higher preventive care use –Lower acute-care use –Shorter (Time-frames from Inpt discharge to phys-visit) –Females 40 t0 65 Higher mammogram compliance –Asthmatics Lower ER visits –Hypertension Higher hypertensive drug use –Depression Higher depression related drug use

13. Future Trends Motivation Index Drivers Higher Antidepressant Use within Depressed Population correlates with higher motivation

14. Future Trends Motivation Index Drivers Mammogram Use in Female Population correlates with higher motivation

15. Future Trends Motivation Index Drivers ER Visits within Asthma Population correlates with lower motivation

16. Future Trends Forecasting Disease Specific Outcomes

17. Future Trends Provider Market Future Trend –Forecasting Preventable Events Pre-discharge Preventable readmissions Catheter-Associated UTI Pressure Ulcers Vascular Catheter-Associated Infection Mediastinitis after CABG-Surgical Site Infection Hospital-Acquired Injuries

18. Future Trends Why Identify Potentially Preventable Readmissions? Comparing provider performance to enhance quality Developing pay for performance systems Readmission rates provide quality benchmark Costs associated with readmissions are substantial –30 billion in play for Medicare Defining Preventable Readmissions –some initial discharges for which subsequent readmits excluded (e.g. LAMA, cystic fibrosis) –Readmissions are for same diagnosis –Readmissions are for related diagnosis

19. Future Trends Data for Forecasting Preventable Events Electronic Medical Record Data –HL7 Format –Near-real time data outflow Forecasting Model –Near-real time forecast of Readmission / Decubitus Probability Risk Index Drivers Data Needed –Vital Signs –Lab Results –Drug Dosage and Timing –Admission Discharge Transfer Data –Chief Complaint –Prior Discharge Diagnoses –Supplies

20. Future Trends Forecasting Decubitus Drivers to forecasting Risk of Decubitus when a patient is admitted –Vital Signs Fever Pulse / BP / Respirations –Lab Results White Blood Cell Counts Blood Culture Results –Drug Dosage and Timing Antibiotic at admission –Chief Complaint – Diarrhea –Admission Source From SNF – Prior Discharge Diagnoses Diabetes / CHF / Senility –Demographics –Supplies Depends

21. Future Trends Hospital Revenue Loss with Preventable Events Source:CMS;Advisory Board Analysis

22. Future Trends ROI from Forecasting Preventable Events

23. Predictive Modeling Applications for Care Management – Paradigm Changes Historical Current Transformed Predictive Modeling Applications for Care Management – Paradigm Changes Future Model Predictive Modeling: Used to identify early members who are trending toward high-risk events Mbr Educ UR/UM Demand Mgmt Concurrent Case Mgmt Disease Mgmt Personal Health Mgmt Population Risk Mgmt UR/ UM Proactive Case Management Disease Management Decision Support Personal Health Mgmt Population Risk Mgmt UR/ UM Proactive Case Management Disease Management Decision Support Actionability Motivation Index Disease Specific

24. About the Future “Never let yesterday use up too much of today.” - Will Rogers The best way to predict the future is to create it. “Never let yesterday use up too much of today.” - Will Rogers The best way to predict the future is to create it.