Using Healthcare Data Sets to Improve the Coordination of Medical and Behavioral Health -

1. Using Healthcare Data Sets to Improve the Coordination of Medical and Behavioral Health - The Potential Role For Health Homes Richard Surles, Ph.D. May 2013 YAI International Conference New York Hilton, New York, NY

2. Agenda • Understanding & Aligning Data Sets to Optimize Care and Control Costs • Potential Use of Data Sets to Identify Members and Needs • Leveraging Data Sets to Drive Workflow in Support of Effective Medical Homes

3. Complex Conditions Require New Ideas for Coordination Beyond Traditional Medical Management • ~50% of People Who Have a Severe Mental Illness (SMI) Have Medical Co-morbidities • Higher rates of utilization and costs • Problems achieving desired treatment outcomes • Lack of access to integrated services • Major Issues in SMI Overall Care are Medication Management and Suboptimal Care Delivery combined with the Need for Non-medical Support Services • Proven Interventions • Communication between mental health and physical health providers to provide integrated care • Use of information systems (tracking RX refills, clinical visits) to promote patient adherence and improved outcomes • Targeted interventions for both patient self care and provider engagement are critical • Care Management program engagement goals: decrease isolation, promote access • Relapse prevention programs contribute to medication maintenance, increased patient self-monitoring of symptoms

4. SMI and Medical Comorbidities in ABD* Population 39% of Population Has a SMI SMI Participants Account for 58% of Total Costs Top 5% of SMI Population Account for ~25% of All Costs $321 M $778 M 118,681 $1.34 B *Aged, Blind & Disabled

5. Levels of Complexity for Aged, Blind & Disabled ABD Medicaid Spend (10/10-9/11) Category Differences by Acuity • PMPM • Low: $679.94 • Mod: $3,471.14 • High: $8,262.26 • Average Number of Conditions • Low: 1.8 • Mod: 4.9 • High: 7.1 • Average Risk Score (CDPS)* • Low: 1.9 • Mod: 5.2 • High: 10.7 • Average MDs • Low: 3.3 • Mod: 6.6 • High: 10.9 36,408 $582M * Chronic Illness & Disability Payment System; Index risk score is 1.0

6. ABD Population – Prevalent BH + Chronic Medical

7. Dimensions of Care - Supporting the Whole Person How Treatment is Delivered Intensive/Procedural Medical Treatment Rehabilitative Treatment Combined Treatment Patient Education & Counseling Self-Help & Natural Supports Marital/Familial Vocational/Financial What is Treated Social/Legal Intrapsychic Biomedical Hospital Home Office Community PartialCare Where Treatment is Done

8. Medical Services Community Services Clinical Supports

9. Are Integrated SMI Health Homes a possibility? • Affordable Care Act Encourages the Use of Health Homes for Chronically Ill and People with SMI via Financial Incentives • SMI Health Homes Addresses Behavioral Health Needs While Responding to Other Healthcare Issues • Individuals with SMI, on average, die 25 years earlier than the general population • 60% of premature deaths in persons with schizophrenia are due to medical conditions such as cardiovascular, pulmonary and infectious diseases • Second generation anti-psychotic medications are highly associated with weight gain, diabetes, dyslipidemia (abnormal cholesterol) and metabolic syndrome

10. Key Features of the Health Home: All Data Driven

11. Medical Home Has Current and Complete Information Via the Integrated Technology Platform Data Driven Plan of Care Aggregate view of all services/billing/interactions Provider Tools Real time access to data via secure Provider Portal Reports highlighting alignment to best practice, gaps in care, services received outside of Medical Home Patient Specific Information Provider panel aggregate information Service Vendor Requirements Integrated technology platform Technical assistance and training Community and telephonic member engagement Engage providers for care coordination Appointment tracking and follow up A Vision of Provider Data Support Systems

12. 47 Year Old Male with CAD, Diabetes, HTN, Asthma, Hyperlipidemia, GERD, Bipolar Disorder New enrollee at program “go live” Gaps in care analysis triggered (IP, multiple ER), General Assessment identified positive PHQ-2 and housing issues Issue Ineffective medical home Unstable diabetes and behavioral health conditions Unstable housing Model Intervention Secured stable housing Secured effective medical home Transitioned from Telephonic Health Coach to Field Health Coach intervention James R: A Member Case Study of Integration

13. James R: Member Case Study Assessments Provide Additional Information

14. James R: Member Case Study

15. Changing the Dialogue: Data Driven Systems of Care “Health Care Home” HCH IDENTIFY INTERVENE EVALUATE MONITOR Engaged, educated member >Informed HCH >Alert system for HR/HC potential >Facilitate access to care & service supports >Improve self-management skills > Data Driven, Predictive Modeling >Data analysis >Assessments Measure goal progress >Feedback on results “Provider – Clinical, Service & Community - Support and Tools”

16. The Finish: Issues for a Data Driven Health System • Access and Quality of Data • Privacy and Consumer Consent • Coordination of Medical and Behavioral Care with Pharmaceuticals • Full integration of traditional Medical Managed Care with Non-traditional Community Support Services Including: • Psychosocial Rehabilitation • Habilitation • Personal Care • Other Home and Community Care Services