Using Healthcare Data Sets to Improve the Coordination of Medical and Behavioral Health - The Potential Role For Health Homes Richard Surles, Ph.D. May.

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 ConferenceNew York Hilton, New York, NY

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

Agenda

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~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

Complex Conditions Require New Ideas for Coordination Beyond Traditional Medical Management

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Non-SMI42%

SMI58%

0%

20%

40%

60%

80%

100%

Number of Participants Total Costs

Non SMI SMI 75% spend SMI 75-90% SMI Top 10%

SMI39%

Non-SMI61%

SMI Participants Account for 58% of Total Costs39% of Population Has a SMI

Top 5% of SMI Population Account for ~25% of All Costs

118,681 $1.34 B

$778 M

$321 M

*Aged, Blind & Disabled

SMI and Medical Comorbidities in ABD* Population

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Category Differences by AcuityPMPM

– 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

Levels of Complexity for Aged, Blind & Disabled ABD Medicaid Spend

(10/10-9/11)

36,408 $582M

* Chronic Illness & Disability Payment System; Index risk score is 1.0

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ABD Population – Prevalent BH + Chronic Medical

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Dimensions of Care - Supporting the Whole Person

Where Treatment is Done

What is Treated

How Treatment is DeliveredIntensive/Procedural

Medical Treatment

Rehabilitative Treatment

Combined Treatment

Patient Education &Counseling

Self-Help & Natural Supports

BiomedicalIntrapsychic

Social/LegalVocational/Financial

Marital/Familial

OfficePartial Care

HospitalCommunity

Home

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Inpatient HospitalOutpatient HospitalCritical Access HospitalFQHCSkilled NursingHome HealthRural Health ClinicOther MedicalAmbulanceOffice VisitsSpecialistsLab TestsComprehensive Medication ServiceMinor ProceduresAnesthesiaMajor ProceduresER VisitsOther Tests

Medical Services Community Services

Residential FacilityIntermediate CareHabilitationOther SupportsAlcohol/Drug TreatmentCommunity Wrap-Around servicesCommunity Support ServicesCase ManagementPersonal CareNon-emergency TransportationBH Day TreatmentAttendant carePsychosocial RehabilitationCrisis InterventionAssertive Community TreatmentOther DMESupported Employment

Clinical

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Supports

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

Are Integrated SMI Health Homes a possibility?

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Key Features of the Health Home: All Data DrivenFeature Purpose

Comprehensive care management

• Predictive Modeling and Disease Stratification to identify clients with chronic disease and pinpoint risk

• Technology that integrates settings of care and data sources• Secure messaging for information sharing and coordination

Monitoring • Enhances clinical care by alerting team to client events and changes in client status

• Addresses both clients and providers• Supports innovative payment systems

Reporting & Quality • Easily accessible performance reports on key measures at multiple levels – client, provider, region, and state

• Quality improvement program for structured initiatives

Outcome Measurement

• Stabilization of acuity and reduction of symptoms• Clinical performance – engagement, medication adherence,

reduction of ER, Inpatient, Readmissions• Return on Investment analysis

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A Vision of Provider Data Support Systems 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

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James R: A Member Case Study of Integration 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

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James R: Member Case StudyAssessments Provide Additional Information

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James R: Member Case Study

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Changing the Dialogue: Data Driven Systems of Care

> Data Driven, Predictive Modeling>Data analysis>Assessments

>Facilitate access to care & service supports>Improve self-management skills

Measure goal progress>Feedback on results

Engaged, educated member >Informed HCH>Alert system for HR/HC potential

“Provider – Clinical, Service & Community - Support and Tools”

INTERVENEIDENTIFY EVALUATE MONITOR

“Health Care Home”HCH

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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

The Finish: Issues for a Data Driven Health System

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