Application of Population Data for Informing Programmatic and Policy - - PowerPoint PPT Presentation

Turning Information into Insight: Vermont’s Application of Population Data for Informing Programmatic and Policy Decisions

Laurel Omland, MS Laurin Kasehagen, MA, PhD Anita Wade, MPH

Part 1: The Long Trail--

How Vermont began the journey to see both footsteps and long vistas

Laurel Omland, Director of the Child, Adolescent and Family Unit, Vermont Department of Mental Health Laurin Kasehagen, CDC Assignee to Vermont’s Department of Health & Mental Health

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Where did the Long Trail begin?

• Vermont’s story begins about 5 years ago, when the

former director of CAFU and colleagues from SAMHSA and CDC who work in early childhood mental health met to discuss how they could get better data around child mental health

• The discussion expanded from not only what was

needed, but, if there were data, how could Vermont get epidemiologic support

• Over a 12-18 month period,
• CDC’s MCH Epidemiology Program Team and CDC’s NCBDDD ECHS Team worked to

develop a unique pilot of the typical MCH assignment

• SAMHSA communicated its willingness to help support an epidemiology assignment
• Vermont communicated its need and willingness to accept an assignee
• And, through a fortuitous series of events, a potential assignee was identified

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What is an assignee?

• Maternal and Child Health Epidemiology

Program

• Located within CDC’s Center for Chronic

Disease Prevention and Health Promotion in the Field Support Branch

• 14 assignees and about 6 fellows in the

field, including Vermont

• Assignment first of its kind
• VT, CDC, NCBDDD, SAMHSA, HRSA / MCHB
• Primary focus on child and family

behavioral, emotional, and mental health and wellness

• Significant investment
• VT selected for its innovation,

collaboration, and size

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http://www.cdc.gov/reproductivehealth/mchepi/assignees.htm

• Unique aspect of assignment -- working

across programs, divisions, departments, and agencies in Vermont on issues that transcend the boundaries of any one program, division, department, and agency

• Provides subject matter expertise,

technical expertise, leadership, oversight

• f fellows / EIS officers
• Provides analyses using more complex

analytic techniques

• Usually does not have responsibility for a

particular surveillance system or for analyzing and compiling reports or data for a specific surveillance system or program

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MCH SU MH

INJ

What makes an assignee from the CDC different from state analysts or epidemiologists?

INJ = Injury MCH = Maternal and Child Health MH = Mental Health SU = Substance Use

What is the population health approach and evidence-based public health?

Population Health is an approach that

• focuses on interrelated conditions and factors that influence the health of

populations over the life course,

• identifies systematic variations in their patterns of occurrence, and
• applies the resulting knowledge to develop and implement policies and

actions to improve the health and well-being of those populations. Evidence-based public health is the mechanism by which population health information is used for the … development, implementation, and evaluation of effective programs and policies ….

6 Sources: D Kindig and G Stoddart, What is population health? Am J Public Health, 2003; 93(3):380-383; Brownson, Ross C., Elizabeth A. Baker, Terry L. Leet, and Kathleen N. Gillespie,

• Editors. Evidence-Based Public Health. New York: Oxford University Press, 2003

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• Adverse experiences, behavioral, emotional

and mental health and wellness and resilience

• Suicide, suicidal ideation, and non-suicidal

self-harm

• Anxiety, depression, conduct disorders
• ADHD
• School performance
• Impact of inattention
• Use of 504 Plans and Individualized

Education Programs (IEPs)

• Use of antipsychotic / psychotropic

prescription medications

• Substance Use Disorders (opioids, tobacco)
• Neonatal abstinence syndrome
• Moderately / most effective contraceptive use

Im Imple lementation of

• f a

a Pop

• pula

lation Healt lth Approach in in Vermont

Context Need Information / Data Partnerships Data Access Analysis Interpretation Translation Products Transfer Disseminate Diffusion Utilization Implementation

Improving population health

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Assignee Project Topical Areas Potential Sources of Data Adverse Family / Childhood / Prenatal Experiences NSCH, BRFSS, PRAMS Attention Deficit / Hyperactivity Disorder (ADHD) NSCH, NS-DATA*, Medicaid claims, VHCURES, VPMS Youth / Lifespan Suicide Vital records, NVDRS Youth / Lifespan Suicidal Ideation, Self-Directed Violence, & Accidental Poisonings YRBS, VUHDDS, Medicaid claims, VHCURES, syndromic surveillance, QI initiatives Anxiety, Depression, Conduct Disorders, NSCH, YRBS, BRFSS, PRAMS, VUHDDS, Medicaid claims, VHCURES, DMH service data, NSDUH, QI initiatives Tobacco Cessation among Pregnant Women Vital records, PRAMS, Tobacco Program data, Adult Tobacco Survey, QI initiatives Substance Use among Youth (12-17 years) and Women of Reproductive Age (15-44 years) YRBS, BRFSS, PRAMS, VUHDDS, syndromic surveillance, ADAP service data, VPMS, SBIRT ED data, NSDUH SUDs / OUDs / Neonatal Abstinence Syndrome (NAS) VUHDDS, Medicaid claims, VHCURES, VRPHP QI initiatives Unintended Pregnancies / Long-Acting Reversible Contraceptives (LARCs) BRFSS, PRAMS, Vital records, Medicaid claims, VHCURES, Title X Clinic data / Planned Parenthood

*Only national level data Acronyms: BRFSS = Behavioral Risk Factor Surveillance System NS-DATA = National Survey of the Diagnosis and Treatment

• f ADHD and Tourette Syndrome

NSCH = National Survey of Children’s Health NSDUH = National Survey on Drug Use and Health NVDRS = National Violent Death Reporting System PRAMS = Pregnancy Risk Assessment Monitoring System QI = quality improvement VHCURES = Vermont Health Care Uniform Reporting and Evaluation System VPMS = Vermont Prescription Monitoring System VRPHP = Vermont Regional Perinatal Health Project VUHDDS = Vermont Uniform Hospital Discharge Data Set YRBS = Youth Risk Behavior Survey

• Outcomes of Well-Being for Vermonters (Act 186 for

the Agency of Human Services) codified the use of Results Based Accountability How Much? How Well? Is Anyone Better Off?

• For years we’ve had service-level data on How Much?
• We have identified more of the How Well? (service

delivery process). And are improving our ability to solidly say whether Anyone is Better Off (client outcomes).

• We also wanted to know: How are all children, youth

and families in Vermont doing?

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Population Health – seeing the long vista

The “Value Add” of having an epidemiologist

• An epidemiologist has helped us
• Access and use Vermont population level data for behavioral and

mental health analyses and action

• Population level data has helped us
• Understand the context of behavioral health within our Vermont

populations

• Identify problems that affect the health of the whole population
• r a subpopulation
• See more clearly the life span implications of emotional, behavior

and mental health conditions as well as the generational influences

• Communicate the connection to the social determinants of health
• Strengthen partnerships via strong communication value –

it’s all Vermonters; it’s us, our families, friends, colleagues

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The “Value Add” of having an epidemiologist - 2

• Population level data, continued
• Identify systems issues that prevent Vermont from achieving whole person

wellness

• Identify opportunities to address the stigma of mental illness and

substance use disorders

• Think about how to tailor mental health promotion and prevention

messages in a way that resonate with the whole population

• Example: perinatal mood and anxiety disorders
• VDH Maternal Child Health and DMH partnership to screen caregivers at

well-child visits and develop system of mental health treatment providers knowledgeable about PMADs

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Part 2: The “mounting” evidence for resilience

Laurel Omland, Director of the Child Adolescent Family Unit, Vermont Department of Mental Health Laurin Kasehagen, CDC Assignee to Vermont’s Department of Health & Mental Health

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• Analysis of the prevalence of:

 Adverse family experiences  Protective factors: Flourishing and Resilience  Outcomes for school aged children, like school engagement

• Statistical modelling to understand:

 how adverse family experiences impact school engagement and the ability of a child to be able to do their homework, and  how this relationship is moderated or mediated by resilience

Project 0: Explore and develop an analytic plan for VT Adverse Childhood Experiences (ACEs)

Source of Data: 2016 National Survey of Children’s Health (NSCH)

• Conducted annually, starting in 2016
• Designed and data collected in a manner that allow valid state-to-state,

regional, and national comparisons

• Yield weighted data prevalence estimates for comparable non-institutionalized

populations in each state and nationally

• Samples 1 in 106 Vermont children
• Why this survey works well for Vermont?

HUGE sample of child population (n~125,000)

• Parents / guardians respond for child

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How is adversity measured?

Live with anyone (parent / guardian) who …

• Died
• Was depressed, mentally ill, or

suicidal

• Was a problem drinker or alcoholic
• Used illegal street drugs / abused

prescription medications?

• Served time / was sentenced to

serve time in a prison, jail or other correctional facility?

• Got separated or divorced
• See / hear parents or adults in your

house slap, hit, kick, punch or beat each

• ther up? Ever the victim or violence /

witness neighborhood violence?

• Ever treated / judged unfairly because of

race or ethnic group?

• Live in a household where it was hard to

cover basics like food or housing?

• Moved more than 4 times since birth

Adverse Family Experiences among Vermont Children, <1-17 years, by Age Group

53 64 48 34 32 35 13 4 17 Overall <1-5 years 6-17 years Prevalence (Weighted Percent) 0 Adverse Experiences 1-2 Adverse Experiences 3 or More Adverse Experiences

16 Data Source: 2016 National Survey of Children’s Health

Individual Strengths & Resilience

Individual Family Community

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9 Domains of Resilience

• Parent-child

connections

• Structure
• Consequences
• Rights and

responsibilities

• Safety and support
• Strong / key

relationships

• A powerful identity
• A sense of control
• A sense of belonging

and purpose

18 Source: Resilience Research Centre, 2014 Ungar M and Liebenberg L. Assessing resilience across cultures using mixed-methods: Construction of the Child and Youth Resilience Measure-28. Journal of Mixed Methods Research 2011; 5(2):126-149. Liebenberg L, Ungar M, Van de Vijver FRR. Validation of the Child and Youth Resilience Measure-28 (CYRM-28) Among Canadian Youth with Complex Needs. Research on Social Work Practice 2012; 22(2), 219-226.

Flourishing / Resilience among Vermont Children, 6-17 years

88 63 50 12 33 42 4 8 Shows interest/curiosity Works to finish Stays calm/in control when challenged Prevalence (Weighted Percent) Definitely true Somewhat true Not true

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RESILIENCE

Data Source: 2016 National Survey of Children’s Health

School Engagement among Vermont Children, 6-17 years

87.5 78.8 63.4 70.1 12.5 21.2 36.6 29.9 Shows interest and curiosity in new things Cares about doing well in school Works to finish tasks started Does all required homework Prevalence (Weighted Percent) Definitely true Somewhat / Not true

20 Data Source: 2016 National Survey of Children’s Health

What are the odds of not doing all required homework for children 6-17 years with 3+ AFEs (compared to those with <3 AFEs)?

Resilience Not doing all required homework Adverse family experiences

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What are the odds of not doing all required homework for children 6-17 years with 3+ AFEs (compared to those with <3 AFEs)?

Not taking into account resilience

3.8 1.4 1.0

0.0 1.0 2.0 3.0 4.0 5.0 Does all required homework

3+ AFEs 1-2 AFEs 0 AFEs

Taking into account resilience

2.5 1.3 1.0

0.0 1.0 2.0 3.0 4.0 5.0 Does all required homework

3+ AFEs 1-2 AFEs 0 AFEs

22 Note: all relationships were statistically significant

What are the odds of not doing all required homework for children 6-17 years with 3+ AFEs (compared to those with <3 AFEs)?

Not taking into account resilience

3.8 1.4 1.0

0.0 1.0 2.0 3.0 4.0 5.0 Does all required homework

3+ AFEs 1-2 AFEs 0 AFEs

Taking into account resilience

2.5 1.3 1.0

0.0 1.0 2.0 3.0 4.0 5.0 Does all required homework

3+ AFEs 1-2 AFEs 0 AFEs

23 Note: all relationships were statistically significant

As few as 1 or 2 adverse family experiences can have an impact. Resilience moderated the effect of 3+ AFEs on a child’s engagement in school and their ability to complete all

• homework. Resilience can moderate or buffer the negative effects of adversity.

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Taking Data to Action: An example of a population approach to adverse experiences, school engagement and resilience

Source: Wordle from Baltimore City Health Department

What happened with this relatively easy analysis and the use of population level data?

• Vermont realized that there were data sources

for children and topics that DMH CYF had interest in

• These data had strong communication value and

were used widely with stakeholders, legislators

• Provided a positive data framework for

developing a statewide initiative

• Helped bridge mental health and public health
• Started a movement to address adversity and

build resilience

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From planning and mapping to the hard work of action

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Counseling & Education Clinical Interventions

• Long-lasting Protective

Interventions Changing the Context to make individuals’ environments healthy

• Socioeconomic Factors

Smallest Impact Largest Impact

Ameliorating poverty and inequities in education, housing, access to healthcare

Health in all Policies, Strengthening Families Approach, PBiS, Flourishing Communities, universal childcare SBIRT for substance use, home visiting, teaching parents about child development stages, 5 protective factors Therapeutic interventions for children and families to mitigate health consequences of abuse and neglect exposure, prevent problem behaviors, reduce violence Trauma treatments for children & families such as ARC Framework; treatment for adult MH/SUD

Source: Adaptation of TR Frieden. A Framework for Public Health Action: The Health Impact Pyramid. Am J Public Health 2010; 100:590-591.

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ARC Framework

Com

• mpetency

Reg

egulation

Attachment

Engagement Trauma Experience Integration Routines & Rhythms Executive Functions Self-Development & Identity Education Caregiver Affect Management Effective Response Attunement Identification Relational Connection Modulation

Vermont’s system of care has embraced the Protective Factors framework

• Parental Resilience
• Social Connections
• Concrete Supports
• Knowledge of Parenting and Child Development
• Social and Emotional Competence of Children

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VT Legislation 2017 & 2018

• 2017 Act 43: “An act relating to building resilience for

individuals experiencing adverse childhood experiences”

• Established Principles for VT’s Trauma-Informed

System of Care

• 2018 Act 204: “An act relating to ensuring a coordinated

public health approach to addressing childhood adversity and promoting resilience”

• Director of Trauma Prevention and Resilience

Development

• Childhood Adversity Response Plan
• ACO provides incentives to existing community

services for preventing and addressing the impact of childhood adversity

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Building Flourishing Communities initiative

• Two statewide multi-disciplinary conferences focused on ACEs and

Building Flourishing Communities

• Information saturation* for communities by Master Trainers on

NEAR Sciences (neuroscience, epigenetics, ACEs, and resilience)

• Build community and family resilience
• develop community capacity
• inspire innovation across diverse groups of people
• support local groups as they address the issues that are important to them
• Turns out there’s population-level data on family resilience and

community strengths, too…

*Laura Porter, Self-Healing Communities

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6.8 14.7 78.6

All/Most of the time to 0- 1 items All/Most of the time to 2- 3 items All/Most of the time to all 4 items Prevalence (Weighted Percent)

Family Resilience among Vermont Children 17 Years and Younger

Family resilience

• Does family know where to go for help

in their community?

• When your family faces problems, how
• ften are you likely to do each of the

following?  Talk together about what to do  Work together to solve our problems  Know we have strengths to draw

• n

 Stay hopeful even in difficult times

Family resilience score

Data Source: 2016 National Survey of Children’s Health 32

VT Mental Health Payment Reform

Outcomes Pregnant women and young children are thriving Families/Communities are safe, stable, nurturing, and supported Population Indicators a. Demonstrates Resilience / Flourishing b. Prevalence of Emotional, mental

• r behavioral conditions

c. Level of severity of Emotional, mental or behavioral conditions d. How often have these conditions affect child’s ability to do things, severity of impact a. Family Strengths b. Child involvement in Community Activities c. Parent’s physical health, mental/emotional health

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Discussion & Questions

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Hands-on activity to get to the “peak”

• f our work!

Using population- level data

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Translating Data to Action

• Group work:
• You’ve partnered with your

state health department to

• btain data about ED visits for

suicidal ideation, self-directed violence and accidental

• poisonings. The

epidemiologist conducted the analysis.

• Now you have the numbers,

what’s next?

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Context Need Information / Data Partnerships Data Access Analysis Interpretation Translation Products Transfer Disseminate Diffusion Utilization Implementation

Suicidal ideation, suicidal and undetermined self-directed violence, and accidental poisoning, among Vermont Youth 10-24 Years, Vermont Uniform Hospital Discharge Data, 2010-2016, n=9,128

SI SDV AP

Figure Leg Legend SI=suicidal ideation SDV=suicidal and undetermined self-directed violence AP=accidental poisoning

n=2,531 n=2,372 n=2,161 n=158 n=1,145 n=14 n=421

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50 100 150 200 250 300 350 400 2010 2011 2012 2013 2014 2015 2016

Suicidal Ideation Combined Suicidal and Undetermined SDV Accidental Poisoning

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From 2010-2016, crude rates of suicidal ideation and SDV significantly increased from 236.9 to 333.8 (p for trend <0.0001) and 208.6 to 345.1 (p for trend <0.0001) per 100,000 youth 10- 24 years, respectively. Accidental poisoning rates increased, but the increase was not statistically significant.

Crude Rates of Suicidal Ideation, Self-Directed Violence (SDV), and Accidental Poisoning among Vermont Youth

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Number of Episodes and Crude Rates of Suicidal Ideation, Self-Directed Violence (SDV), and Accidental Poisoning (per 100,000 Vermont Resident Youth) by Age Group, Vermont Uniform Hospital Discharge Data, 2010-2016 Episode Types All Youth 10-12 years 13-15 years 16-18 years 19-21 years 22-24 years Suicidal Ideation crude rate / 100,000 youth 77.6 283.7 351.7 311.9 372.5 Combined Suicidal & Undetermined SDV crude rate / 100,000 youth 61.4 364.9 380.8 271.1 243.5 Accidental Poisoning crude rate / 100,000 youth 189.6 171.5 223.3 265.8 356.7

How Could Your State Translate Data into Action?

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Context Need Information / Data Partnerships Data Access Analysis Interpretation Translation Products Transfer Disseminate Diffusion Utilization Implementation Improving population health

Small Group Activity – 10 min

• What’s missing? Is there other data you need?
• What does this tell you about your state child/youth

population’s health?

• What stands out to you?
• Consider how this might relate to the population in MH

service

• How would you use this data? Think about policy,

communication, programmatic, fiscal, partnerships…

• Who do you need to bring to the table (roles)?

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Bear with us, it is almost break time … but now’s the time to Report Out!

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BREAK

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Translating Data into Action: Vermont

Need, Partnerships, Analysis & Interpretation

Built partnerships / participate in VDH & AHS workgroups Participate in the CDC-UIC multi-year training on the use

• f claims-based data

Analyzed data from vital records and hospital discharge data systems Interpreted analysis

Translation & Dissemination

Wrote manuscript around ideation and self-directed violence Developed QI project on coding and ED processes Participated in Child Safety CoIIN

Utilization & Implementation

Learn what works / doesn’t work and apply NMC experience to other community hospitals in VT Write manuscript on QI experience Suicide STAT

Context Need Information / Data Partnerships Data Access Analysis Interpretation Translation Products Transfer Disseminate Diffusion Utilization Implementation Improving population health

Part 3: Preparing for the Journey Ahead

Anita Wade, CSTE Applied Epidemiology Fellow, Vermont Departments of Health & Mental Health

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Im Imple lementation of

• f a

a Pop

• pula

lation Heal alth Approach in in Vermont

Context Need Information / Data Partnerships Data Access Analysis Interpretation Translation Products Transfer Disseminate Diffusion Utilization Implementation

Improving population health

What should you pack?

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What should you pack?

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What should you pack?

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What is public health surveillance?

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What is public health surveillance?

“The ongoing, systematic collection, analysis, and interpretation of health data, essential to the planning, implementation and evaluation of public health practice, closely integrated with the dissemination of these data to those who need to know and linked to prevention and control.”

51 Source: Thacker SB, Qualters JR, Lee LM. Public health surveillance in the United States: evolution and challenges. MMWR 2012;61(Suppl; July 27, 2012):3-9.

Recommended CSTE Surveillance Indicators for Substance Abuse and Mental Health,

Version 2, December 2017

• Purpose
• Provide guidance on monitoring substance use and

mental health

• Standardize surveillance activities across states
• Monitor needs and trends
• Bring key stakeholders to the table

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http://c.ymcdn.com/sites/www.cste.org/resource/resmgr/pdfs/pdfs 2/2017RecommenedCSTESurvIndica.pdf

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http://c.ymcdn.com/sites/www.cste.org/resource/resmg r/pdfs/pdfs 2/2017RecommenedCSTESurvIndica.pdf

• 18 indicators identified and

defined during October 2015-2016

• 3 groups
• Alcohol (5 indicators)
• Other Drugs (5 indicators)
• Mental health (8 indicators)
• Pilot 1- January- June 2017
• 4 States
• Pilot 2- March-June 2018
• 15 States and counties

Mental Health Indicators

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Surveillance Indicators Data Source Age Range of Focus

• 1. Suicide rate

Death Certificate Data 5 years and older

• 2. Hospital discharges for mental disorders
• Overall
• Mood and Depressive Disorders
• Schizophrenic Disorders
• Mental Disorders, except drug and

alcohol-induced Mental Disorders Hospital Discharge Data 12 years and older

• 3. Emergency department visits for intentional

self-harm Emergency Department Data 5 years and older

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Indicators using Survey Data Data Source Age Range of Focus

• 4. Self-reported youth suicide attempts

Youth Risk Behavior Surveillance System (YRBSS) Students in grades 9-12

• 5. Depressive episodes in the past year

National Survey of Drug Use and Health (NSDUH) 12-17 and 18 years and older

• 6. Any adult mental illness in the past year

NSDUH 18 years and older

• 7. Any adult serious mental illness in the past year

NSDUH 18 years and older

• 8. Frequent mental distress

Behavioral Risk Factor Surveillance System (BRFSS) 18 years and older

The “Map”

How to use the Surveillance Indicators to reach our destination

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https://www.greenmountainclub.org/the-long-trail/

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Organizing the data

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CSTE Indicator Reporting Tool

Photo source: https://www.rei.com/blog/hike/how-to-pack-for-an-appalachian-trail-thru-hike

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Instructions for collecting and organizing census data

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Age-adjustment template

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Individual sheets for each indicator

Summary sheet to compile the data

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Time to start walking

Hands-on example using indicator 14: Self-reported youth suicide attempts

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• 1. Go to:

https://nccd.cdc.gov/yo uthonline/App/Default. aspx

• Select your State from

the "State Location" drop down

• Some metropolitan

areas available as well

• 2. Click "GO"

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• 3. Under "Question", click “Unintentional

Injuries and Violence”

• 4. Select “Attempted suicide”

• 4. Under "Year", select the year of interest
• 5. Click "GO"

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• 7. Select the

demographic variables of interest in the "Column or Row Variable" drop down (Ex. Sex, Grade, Race/ethnicity)

• 8. Click "GO"

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• 9. Report Crude

percent's and Confidence Intervals

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• 10. Fill in the

reporting toolkit

• 11. Explore other

ways of stratifying the data on the YRBS website

Questions & Discussion

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Breakout questions

• Do you agree with the rates for your jurisdiction?
• Does anything surprise you?
• How could this information be used?
• Has your jurisdiction used mental health

surveillance indicators to inform policy?

• What’s worked and what hasn’t?

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Summary

• Standardized indicators help

states:

• Get a handle on severity, frequency,

economic impact, and preventability

• f various conditions
• Conduct planning and evaluation
• Limitations
• Data access
• Analytic capacity
• Age ranges of survey data
• Work-in-progress

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Photo source: http://www.cumberlandtrail.org/wp-content/uploads/2016/01/Caution-Trail-Progress_LR.jpg

Acknowledgments

• CSTE Mental Health and Substance Use Subcommittee
• Megan Toe (CSTE)
• Abby Hagemeyer (CSTE/SAMSHA)
• Vermont Department of Health - Division of Health

Surveillance

• Amanda Jones
• Jeffrey Trites
• Jennifer Hicks
• Leslie Barnard
• This work was supported in part by an appointment to the

Applied Epidemiology Fellowship Program administered by the Council of State and Territorial Epidemiologists (CSTE) and funded by the Centers for Disease Control and Prevention (CDC) Cooperative Agreement Number 1U38OT000143-05.

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Thank You We hope you get out

• n the trail

soon to enjoy the footsteps and vistas!