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Lessons Learned: The TCOM Partnership of Funder, Managed Care, and Provider Barbara Dunn, Dir Program Innovation and Outcomes November 2015

Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

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Page 1: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Lessons Learned: The TCOM Partnership of Funder, Managed Care, and Provider

Barbara Dunn, Dir Program Innovation and Outcomes

November 2015

Page 2: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Abstract

Magellan has partnered with funders and providers on use of the CANS in six states based on each state’s unique goals, systems and funding structures. This presentation will address the following: • The various ways in which managed care utilizes the CANS, including a behind-the-

scenes look at how managed care operates • Misconceptions about how managed care uses the CANS in medical necessity

decisions • Magellan’s successful use of Transformational Collaborative Outcomes

Management (TCOM) in clinical decision-support, practice management, locally effective practices, outcomes-based contracting, algorithm development, predictive modeling, and quality improvement

• Development of an outcomes platform and reporting capabilities • The future of the CANS in managed care and quality improvement as part of a

proactive, transformational system, including what providers can initiate in a managed care environment and how funders can build the CANS into clinical and quality program design.

Page 3: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

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500 Miles

500 KM AK & HI not to scale

AK

TX

UT

MT

CA

AZ

ID

NV

OR

IA

CO

KS

WY

NM

MO

MN

NE

OK

SD

WA

AR

ND

LA

HI

IL

OH

FL

GA AL

WI

VA

IN

MI

MS

KY

TN

PA

NC

SC

WV

NJ

ME

NY

VT

MD DC

NH

CT

DE

MA

RI

How Does Managed Care Use the CANS?

Page 4: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Magellan’s Use of the CANS: Transformational Collaborative Outcomes Management (TCOM)

Family & Youth Program System

Decision Support Care Planning:

Collaborative Goal

Setting

Eligibility, Step-

down:

Determining Fit for

Goal Attainment

Right-sizing:

Maximizing

Probability of

Success

Outcome

Monitoring

Service Transition:

Success

Generalization

Evaluation:

Locally Effective

Practice

Identification

Performance

Contracting:

LEP Uptake

Quality

Improvement

Supervision for

Compliance:

Supervision for

Competence

Accreditation:

Meaningful Use

Reactive System:

Proactive,

Transformational

System

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Page 5: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Six states and how we have used the CANS:

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Clinical decision support

Accreditation support

Practice Management

Locally effective practices

Outcomes-based contracting

Algorithm development

Predictive modeling

Quality improvement AZ

VA WY

LA

NE PA

Page 6: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Medicaid Managed Care Myths

• Medical necessity criteria

• Denials

• Profit

• Bureaucracy

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Page 7: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Medicaid Role as Funder of Managed Care

• State Plan and Federal Waivers

• Regulations

• Memorandums of Understanding across systems

• Approvals of policy and medical necessity criteria

• Contract Monitoring

• Quarterly/Annual Performance Measures with incentives

• RFPs

• State decision on Capitated (“Risk”) or Administrative (“ASO”) financial arrangement

• Reinvestment decisions

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Page 8: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Medicaid Managed Care Value Add

• Advisor to funders

• Subject Matter Experts

• Propose medical necessity criteria

• Technology and tools

• Quality Improvement

• Member Rights closely monitored

• Outcomes driven

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Page 9: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Magellan’s Support of TCOM

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Page 10: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Clinical Decision Support: Provider Portal

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Page 11: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Clinical Decision Support: Manage Outcomes Application

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Page 12: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Clinical Decision Support: CANS MH

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Page 13: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Clinical Decision Support : LA CANS Comprehensive

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Page 14: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Clinical Decision Support: The Individual CANS Report

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Page 15: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Clinical Decision Support: SUM Scores and Severity

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Compare severity within a population Use Domain SUM to target interventions

Out of a possible 72 points

Least Severe <=12

Most Severe >=27

Max Initial = 48

Source: 2012 BHRS Severity Analysis

Youth 1: Janie comes in with a initial Global score of 32. This is more severe than 75% of cases. You flag this for review with your supervisor as a higher needs case.

Youth 2: Jared has been in services for 12 months and now has a Global score of 11. This is in the lowest 25% of severity. You consider with the family if it is time to plan transition to outpatient services.

Page 16: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Practice Management: CANS Provider Web Report Part 1 Summary Page - Global Trend Line - Diagnosis Table - Domain Trend Lines Accreditation Support for providers

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Page 17: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Practice Management: CANS Provider Web Report Part 2 Detail Pages - Items by Domain - Bar for Action threshold - Percent at “Act” (gray) - Percent at “Act Now” (red) Accreditation Support for providers

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Page 18: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Quality Improvement: Customer Outcomes Report

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Page 19: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Quality Improvement: Risk prevalence, strengths, and opportunities

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N 222 319 252 311 77 400 329

Total N = 877 Paired Initial and Discharge

Nebraska Residential June 2015

80.6

66.5 74.6

65.9

80.5

66.3

80.5

Danger to Self Danger to Others

Other Self Harm Elopement Abusive Behavior Social Behavior

Crime/Delinquency

% Improved Discharge

Page 20: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Locally Effective Practices: Significance Testing the Differences SA-MH-Dual PRTFs

Initial p < 0.05 Discharge p < 0.05

Strength Fx Risk CG Strength Fx Risk CG

MH v SA 14 v 19 6 v 11 7 v 8 4 v 7 11 v 14 2 v 6 5 v 3 4 v 5

MH v Dual 14 v 19 6 v 9 7 v 9 4 v 9 11 v 15 2 v 6 5 v 8 4 v 7

SA v Dual 19 v 19 11 v 9 8 v 9 7 v 9 14 v 15 6 v 6 3 v 8 5 v 7

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Notes: Comparison is Median score. Items on health and spiritual/religious removed from domain scores.

p < 0.05

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Locally Effective Practices: Trauma Impact on Treatment

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MH SA Dual

Strengths

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MH SA Dual

Risk

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MH SA Dual

Functioning

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MH SA Dual

Caregiver Needs and Strengths

Initial CANS Outcome No Trauma Outcomes with Trauma

Page 22: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Quality Improvement: Outcomes CANS MH

Domain Ave Ave % of Members

with

Improvement

Problem

Presentation 10.07 7.37 74.7% h 3%

Risk Behaviors 7.07 4.87 70.8% h 4%

Functioning 7.86 5.05 77.0% h 5%

Caregiver Needs 7.13 5.49 58.1% h 5%

Strengths 21.16 16.22 77.0% h 3%

Global 54.93 39.98 81.2% h 4%

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2014 CANS Youth in Nebraska Residential (N = 835)

Page 23: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Quality Improvement: Outcomes Wraparound

October 15, 2015 CANS LA Analysis 23

0

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Initial Assessment Transition DC

Domain Specific Changes

Life Domain Functioning

Child Strengths

Acculturation

Caregiver Strengths & Needs

Child Behavioral/Emotional Needs

Child Risk Behaviors

School Behavior

56.0

43.1

30

40

50

60

70

Initial Assessment Transition DC

Global Score

All improvements statistically significant (see specific results in Appendix B).

12.9 point

decrease

Page 24: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Quality Improvement: Outcomes for All, Trauma, and High Severity

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72.3

58.1

60

44.6

56

43.1

Initial Transition/Discharge

Wraparound Youth CANS Global Score Change

High Severity Youth Youth with Trauma All Wraparound Youth

Page 25: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Quality Improvement: Outcomes LA CANS Child Behavioral/Emotional Needs (CBEN)

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0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2.1

2.3

Initial Assessment Transition DC

Changes in Average: Specific Problem Presentation/CBEN Items

Impulsivity/Hyperactivity

Depression

Anxiety

Oppositional

Conduct

Adjustment to Trauma

Anger Control

All improvements statistically significant

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CSoC Waivers

B3 Members C Members

Algorithms: LA CSoC Waivers

CSoC State Governance Board – July 2015

Page 27: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Predictive Modeling: Clusters to Scales

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Six Scales Cronbach's alpha

Family Functioning .89

Child Safety .84

Resiliency/Coping .81

Sexuality .73

School Behavior .72

Danger to Self .67

Page 28: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Predictive Modeling: Scales by Item

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Family Functioning Scale (0.89) *

Domain Item

Caregiver Involvement

Caregiver Organization

Caregiver Resources

Caregiver Supervision

Caregiver Knowledge

Caregiver Safety

Functioning Family Functioning

Strengths Family (Strengths)

Coping Scale (0.81) *

Resiliency

Resourcefulness

Well-being

Optimism

Interpersonal

Inclusion

Coping significantly predicts Depression. The lower your resiliency as measured by Coping, the higher your Depression. For each 1 unit change in Coping there is a one unit change in Depression.

*1 = perfect correlation/predictor of positive outcomes

Page 29: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Lessons Learned: What providers can initiate in a managed care environment • Good clinical and quality management (TCOM)

• Learning communities, especially with multiple levels of care in a continuum

• Find the opportunity

• Make a proposal, but ask for a conversation

• SAMHSA and other grants

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Page 30: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

State Lessons Learned: How Medicaid can build the CANS into clinical and quality program design in managed care

• Training on the ground; certification online

• Only accept CANS in a data collection system

• Provider contract language

• Be transparent

• Require evidence of good clinical practices

• Expect baselining for at least a year

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Page 31: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

State Lessons Learned: How Medicaid can build the CANS into clinical and quality program design in managed care

• Be careful jumping technology

• Consider a different tool for eligibility

• Plan ahead stepped incentives

• Align the SOW with the any waiver requirements

• Initiative MOUs with other children’s systems

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Page 32: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

The Future of the CANS in Managed Care

• Healthcare

• Trauma population

• Decision support for braided funding

• Wraparound

• Waiver eligibility

• Functional Outcomes

• Performance Contracting

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Page 33: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Magellan’s CANS Plans Going Forward

• Model with High Fidelity Wraparound

• Develop predictive outcomes scales for clinical use

• Increase trauma identification and demonstrate effective interventions

• Update our internal system to a unified Core and Comprehensive Version

• Expanding our contract with the Praed Foundation for Training and Certification

• Shared savings incentive pool

• Outcomes Dashboard for Child Wellness using the CANS

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Page 34: Lessons Learned: The TCOM Partnership of Funder, Managed ... · November 2015 . Abstract ... algorithm development, predictive modeling, and quality improvement • Development of

Contact us at:

Barbara Dunn, LCSW, ACSW, Director, Program Innovation and Outcomes

[email protected]

Twitter: @MagellanCares

Linkedin: www.linkedin.com/company/5438

Facebook (MyLife program): www.Facebook.com/MYLIFEyouth

www.MagellanHealth.com

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References

Anderson, J., Lyons, J., Giles, D., Price, J., & Estle, G. (2010). Reliability of the child and adolescent needs and strengths-mental health (CANS-MH) scale. Journal of Child and Family Studies, 12(3), 297-289. doi: 10.1023/A:1023935726541

Anne Freud Centre, University College London. (2012). Mental health outcome measures for children and young people. Retrieved from http://www.ucl.ac.uk/clinical-psychology/EBPU/publications/professionals.php.

Field, A. (2009). Discovering statistics using SPSS. Los Angeles: Sage.

Hunter, J., Higginson, I., & Garralda, E. (1996). Systematic literature review: outcome measures for child and adolescent mental health services. [Review]. Journal of Public Health Medicine, 18(2), 197-206. Retrieved from http://jpubhealth.oxfordjournals.org

Kobasa, S.C., Maddi, S.R., & Kahn,S. (1982). Hardiness and health: A prospective study. Journal of Personality and Social Psychology.

Lyons, J. (2008). Child & adolescent needs & strengths: An information integration tool for children and adolescents with mental health challenges. Retrieved from http://www.praedfoundation.org/About%20the%20CANS.html#Here

Lyons, J. (2009). The child and adolescent needs and strengths. In Communimetrics: A communication theory of measurement in human service settings (pp. 93-127). New York: Springer.

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References

National Information Center on Health Services Research & Health Care Technology, & Academy Health. (2012). Health Outcomes Core Library Recommendations, 2004. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/

Nunnally, J. C. (1978). Psychometric theory. New York: McGraw Hill.

Pennsylvania Department of Public Welfare, Office of Mental Health and Substance Abuse Services, Bureau of Children's Behavioral Health Services. (2001). Guidelines for best practice in child and adolescent mental health services. Retrieved from www.dpw.state.pa.us/ucmprd/groups/public/.../s_001583.pdf.

Rashid, T., & Ostermann, R. F. (2009). Strength-based assessment in clinical practice. Journal of Clinical Psychology, 65(5), 488-498. doi: 10.1002/jclp.20595

Robinson, J. P., Shaver, P.R., & Wrightsman, L. S. (1991). Measures of personality and social psychological attitudes. San Diego: Academic Press.

Williams, S. (2008). Review of mental health screening and assessment tools for children. Retrieved from The Northern California Training Academy website www.humanservices.ucdavis.edu/academy.

Polcar, L. (2013) Redesigning a children’s needs assessment screening. Unpublished paper.

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By receipt of this presentation, each recipient agrees that the information contained herein will be kept confidential and that the information will not be photocopied, reproduced, or distributed to or disclosed to others at any time without the prior written consent of Magellan Health Services, Inc. The information contained in this presentation is intended for educational purposes only and is not intended to define a standard of care or exclusive course of treatment, nor be a substitute for treatment. *If the presentation includes legal information (e.g., an explanation of parity or HIPAA), add this: The information contained in this presentation is intended for educational purposes only and should not be considered legal advice. Recipients are encouraged to obtain legal guidance from their own legal advisors.

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