Jeff Schiff, M.D., M.B.A. Medicaid Medical Director, Minnesota Department of Human Services

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Jeff Schiff, M.D., M.B.A. Medicaid Medical Director, Minnesota Department of Human Services

Components of reform Delivery redesign Payment reform Data and analytics

Delivery Redesign Health Care Home to Behavioral Health Home (and Health Home) to Accountable Care Organizations to Accountable Communities Increasing levels of integration

The Patient and Family Centered Health Care Home

What Makes Minnesota s HCH Approach Unique? Statewide approach, public/private partnership Standards for certification all types of clinics can achieve Support from a statewide learning collaborative Development of a payment methodology Integration of community partnerships to the HCH Outcomes measurement with accountability Practice level quality improvement Statewide HCH Evaluation supported by legislation. Focus on patient- and family-centered care concepts

HCH Certification Updates # Certified Clinics: 290+ 38% of Primary Care Clinics in Minnesota (6 in border states) Certified Clinicians: 2900 Approximately 2.8 million patients receiving care in a certified HCH. Applicants are from all over the state. Variety of practice types such as solo, rural, urban, independent, community, FQHC and large organizations. All types of primary care providers are certified, family medicine, pediatrics, internal medicine, med/peds and geriatrics.

Workforce Capacity Nurse practitioners Advanced dental therapists Medication therapy management pharmacists Community Health Workers Community Paramedics Doulas Behavioral health aids Peer counselors (mental health)

Health Care Home As Foundation to ACO s or Total Cost of Care Payment Methods 52

Payment reform Opportunities Tiering by complexity Increased payment for greater integration Payment for outcomes Driving integration Challenges Provider burden Billing mechanisms Defining outcomes Realigning inside provider systems

Data and analytics Measurement Risk Adjustment Attribution

Measurement A Paradigm Structural measures (e.g. clinic based quality improvement) Process measures (e.g. number of children with special health care needs with care plans) Health care outcomes (e.g. rate of asthma ED visits/admits) Health/well-being outcomes (e.g. parental days work missed, healthy days rating)

Risk adjustment Medical complexity Social determinants/complexity

HCH Population Based HCH is Your Entire Clinic 50% TIERS 1-4 HCH Participants: More Complex Severe Conditions TIERS 1-4 HCH Patients Need: More intensive care coordination by a care team. TIER 0 HCH Participants No chronic conditions or less complex conditions. TIER O HCH Patients Need Routine Panel Management & Preventive Care 50% HCH CERTIFICATION AND OUTCOMES MEASUREMENT

Children as compared to adults Children 31% Neurological 15% Pulmonary 12% Skeletal 12% Psychiatric 9% Developmental Adults 27% Cardiovascular 23% Psychiatric 17% Skeletal 17% Neurological 16% Pulmonary CDPS Frequency % in disabled benficiaries Kronick, et. al. Health Care Finance Review, 2000

Developing a Social Complexity Model Project Objective Develop a method for Medicaid agencies to identify children who have significant family and environmental risk factors

Social Complexity Data Uses administrative data only: Claims and encounter data Enrollment data Cash assistance data Child protection data

Administrative Data Advantages: Cost-effective Feasible to implement Disadvantages: Likely undercount on indicators taken from medical claims (e.g. mental illness diagnoses) Instability of some data (e.g. income) Unreliability of data when self-report indicators are not defined well (e.g. homeless indicator)

Social Complexity Indicators among Children on a Public Health Care Program (N=306,723) Risk factors of children on Minnesota Public Health Programs who have at least one parent also enrolled Family s income is <125% FPL 83% (<$30,000 for family of 4) Parent is unmarried 59% Parent has high need for medical care: 32% Medically complex child in family 16% Parent has chemical dependency dx 15% Parent has Serious Mental Illness dx 13% Parent indicated they were homeless 2%

Next steps: Improve services to our participants The social complexity data will allow us to: Guide our efforts to identify regions, populations, and risk factors that require immediate attention Identify particular children and families who would benefit from various services Implement a social complexity risk-adjustment indicator to stratify our populations for ACO gain-share payments

Next Steps: Research December 2013: Complete telephone surveys with parents (done by SCRI) and with those children s providers to validate the administrative set of social complexity indicators March 2014: Report validation study results to AHRQ, along with the description of how to identify children who would benefit from care coordination May 2014: Report differences in health care utilization and cost among children with different levels of social complexity

Support for Research Funded by AHRQ through the Center of Excellence on Quality of Care Measures for Children with Complex Needs PI: Rita Mangione-Smith, Seattle Children s Research Institute Purpose of Center of Excellence work: Develop new and improve existing indicators of quality pediatric care for children with complex needs Purpose of the social complexity project is to develop a method to identify children who would benefit from care coordination