Complex Chronic Children Population Analytics Jacqueline Kueser Vice President, Analytics

1. Complex Chronic Children Population Analytics Jacqueline Kueser Vice President, Analytics Matt Hall, PhD Principal Biostatistician

2. Objectives: 2012 R&D Network Models Today - Differentiate Patient Populations • Define sick children to better understand longitudinal resource utilization patterns for potential prospective payment methodologies. Next - Define Pediatric Accountable Network Models • Identify optimal resources and payment models

3. U.S. Health Care $2.7 TrillionMedicaid Chronic Kids Relatively Small Medicaid: $79 billion; 31 million children $366 billion Medicaid: Adults & Children $900 billion Medicare & Medicaid Medicaid: $32 billion; 7 million chronic, complex & critical children

4. Pediatric Segmentation Definitions (Revised post June 2012 ED presentation)

5. U.S. Child Enrollees (extrapolated, 2 data sets) US Medicaid Enrollees based on Kaiser Family Foundation estimates of average monthly users: 31 million Medicaid and CHIP, 8 million uninsured, and calculated commercial of 36 million (75 million US children – 39 million Medicaid/CHIP/uninsured) pediatric enrollees. Medicaid extrapolated across groups from one state data set; Commercial extrapolation from one multi-state data set.

6. “Some” In Blind & Disabled Category Federal Benefit Payments by Eligibility Category (Outlays in Billions of Dollars) Children’s Hospital Association May 2012 CFO Meeting, JP Morgan Source: Congressional Budget Office; “Medicaid Spending and Enrollment Detail for CBO’s March 2012 Baseline.”

7. Medicaid Population # & Resource Utilization, one state sample, 2009

8. Commercial Population # & Resource Utilization, multi-state sample, 2009

9. Pediatric Population Hierarchy Low Resource Utilization 2010 PHIS Data High Resource Utilization

10. Pediatric Population Hierarchy Children with a Medically Complex (CMC) Low Resource Utilization 2010 PHIS Data High Resource Utilization

11. National Market Share for Children with a Medical Complexity (CMC) Children’s hospitals are increasingly being viewed as a haven for children with special healthcare needs due to pediatric specialty care providers with equipped facilities and resources. Children’s hospitals are <1% of hospitals in the US, but … ...and growing at a rate of around 1% per year Market share is substantial at children’s hospitals… 2009 H-CUP KID Data

12. Children with a Medical Complexity (CMC) in Perspective The proportion of resources consumed by the CMC population at children’s hospitals is two times that of non-children’s hospitals Children’s Hospitals are Highly Dependent on the CMC Population 2009 H-CUP KID Data

13. Growth in Resources Consumed by Children with a Medical Complexity The growth rate of the CMC population at children’s hospitals is two times greater than at non-children’s hospitals. And the fastest growing population within children’s hospitals. 2009 H-CUP KID Data & PHIS

14. Growth in Resources Consumed by Children with a Medical Complexity Additionally, growth might be due to increased retention of adult CMC patients within children’s hospitals. Growth due, in part, to the increase in transferring of patients from non-children’s hospitals.

15. Medicaid in Children with a Medical Complexity (CMC) The percent of hospital days for CMC insured by Medicaid is higher at children’s hospitals, and growing at 1% per year 2009 H-CUP KID Data

16. Growth within PHIS Hospitals

17. 2010 PHIS Data

18. Annual Hospital Utilization Predictability Baseline patients are 30 times more predictable in their annual hospital utilization than critical patients. Baseline Proportion of Patients Chronic Complex Critical Hospital Days Source: PHIS, 2010 (CRG Grouper)

19. The Story in Summary for Children with a Medical Complexity Lack of predictable in the CMC resource utilization Future?

20. Potential Models for Managing Children with a Medical Complexity Medical Homes • CMMI Grant Home Care Care Coordination – Inpatient and Outpatient

21. Average Distance Travelled to Hospital Patients Crossing State Lines for Care Medicaid Other 11.6% 21.5% 10.9% 21.0% 9.8% 16.3% 8.2% 16.3% 2010 PHIS Data

22. Interstate Travel for Children with a Medical Complexity Source: PHIS, 2010 (CRG Grouper)

23. Distance Travelled for Critical Patients Structured clinical programs aimed at coordinating the care for critical patients may be one way to extend a hospital’s referral base. Structured Programs 2010 PHIS Data

24. How does this data help? • Identifies the need to effectively group patients by clinical complexity AND resource utilization across the continuum of care • Preliminarily identifies consistency in distribution of volumes and cost/utilization patterns for the different patient types across data sets • Defines differences between commercial and Medicaid patients • Medicaid includes higher proportion of chronic, complex chronic and critical patients • Medicaid has higher PMPM enrollee costs • To be developed: a potential cautionary tale regarding variation within distributions

25. Drill Down: Bundle Payment Analysis Model and understand how bundled payments might contribute to children’s hospitals taking on more accountability and incentives. Pediatric Chronic Conditions: Diabetes (Type 1) Cystic Fibrosis End Stage Renal Disease (excludes transplants) Member Participants: Boston Cincinnati Connecticut Chicago Dallas Indianapolis Kansas City Washington, DC Hema Bisarya, Madeleine McDowell, MD, Jacqueline Kueser, Project Leads

26. UHC Partner Project Create new products around the management of complex acute and chronic illness – targeted at payers (public and private) and consumer-oriented insurance exchanges. Such products should reduce systemic costs while allowing providers to share in efficiency gains as a safe glide path to an eventually lower equilibrium. Acute: Total Knee Replacements Longitudinal: Lung Cancer (Commercial); Chronic Heart Failure (Medicare) Member Participants: Duke University Health System (NC) Penn Medicine (PA) Rush University (IL) Oregon University Hospitals Case Medical Center (OH) Froedtert Health (WI) Health Sciences University (OR) IU Health (Clarian) (IN)

27. Volume & Variation Source: 2009-2010 Milliman Health Care Guidelines (HCG) Consolidated Database and Medstat data ESRD – Medicare claims data – 5% sample Diabetes/CF- commercial claims data *costs standardized across markets

28. Opportunities to Manage for Better Quality and Cost Efficiency Clinical and executive leaders; 8 children’s hospitals Consistent reporting that non-billable support services including care management and care coordination, particularly for the SES and non-English speaking populations drive quality and cost-efficiency.

29. Recommendation: Pilot Incremental Bundle for Longitudinal Care Recommended age groupings: <1 yr >1-6yrs 7-18 yrs

30. Next Step: Granularity in resource utilization • Consumption of specialty & other resources by patient segmentation • ESRD cost analysis Medicaid analyses • State datasets Assess network adequacy & efficiency management • Medical home management experience