Briefing for the SAMHSA Workgroup on Underage and Problem Drinking Michael Dennis, Ph.D. Chestnut...

Briefing for the SAMHSA Workgroup on Underage and

Problem Drinking

Michael Dennis, Ph.D.Chestnut Health Systems, Normal, IL

Presentation for the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Workgroup on Underage and Problem Drinking, Rockville, MD. This presentation reports on treatment & research funded by

the SAMHSA contract 270-07-0191, as well as several individual CSAT, NIAAA, NIDA and private foundation grants. The opinions are those of the

author and do not reflect official positions of the consortium or government. Available on line at www.chestnut.org/LI/Posters or by contacting Michael

Dennis at 448 Wylie Drive, Normal, IL 61761, phone: (309) 451-7801, Fax: (309) 451-7763, e-mail: [email protected]

1. Estimate the size and correlates of underage and problem alcohol use

2. Demonstrate how under age drinking is particularly problematic for youth in the short and long run

3. Show how even a short screener can be used to quickly identify behavioral health problems and impact program planning

4. Describe how the GAIN has been used as a key piece of infrastructure to support the move towards evidenced based practice

5. Illustrate what we have learned by pooling data from CSAT adolescent/young adult grantees and its implications for program planning

Goals of this Presentation are to

There 41.4 Million Under Age or Problem Drinkers in the U.S.

54%

31%

34%

58%

3%

4%

9%

7%

0% 20% 40% 60% 80% 100%

Age 12 to 20(38.1mil)

Age 21+(207.9mil)

No use in past yearOnly light alcohol use in the past yearHeavy alcohol use in the past monthAlcohol abuse or dependence in the past year

17.6 Million under age

drinkers (46% of 38.1 Mil)

28.4 Million (12%) Problem Drinkers

(4.6m/12% of youth, 23.8m/11% of adult)

Source: SAMHSA 2006. National Survey On Drug Use And Health, 2006 [Computer file]

Heavy and Problem Alcohol Use is More Common Among Males

52%40%

49% 47%

67%77%

54%

68%

0%

20%

40%

60%

80%

100%

Age 12 to 20 (38.1mil) Age 21+ (207.9mil)

% M

ale



Total Population

52% 48%

Underage, Heavy and Youth Problem Alcohol Use is More Common Among Caucasians

55%61%64%

74%83%

77%72% 70%

0%

20%

40%

60%

80%

100%

Age 12 to 20 (38.1mil) Age 21+ (207.9mil)

% C

auca

sian



60%70%

Total Population

Alcohol Use Severity is associated with moreCo-occurring Cannabis Abuse or Dependence

1% 0%6% 1%

11%2%

26%

8%

0%

20%

40%

60%

80%

100%

Age 12 to 20 (38.1mil) Age 21+ (207.9mil)

% C

ann

abis

Dis

ord

er



5% 1%

Total Population

Odd Ratio=34.8 Odd Ratio=17.7

Alcohol Use Severity is associated with Co-occurring Other Drug Abuse or Dependence

1% 1%2% 1%5% 2%15%

8%

0%

20%

40%

60%

80%

100%

Age 12 to 20 (38.1mil) Age 21+ (207.9mil)

% O

ther

Dru

g D

isor

der



3% 1%

Total Population


Alcohol Disorders are associated with Co-occurring Depression

14% 10%19%

9%11% 8%

30% 25%

0%

20%

40%

60%

80%

100%

Age 12 to 20 (38.1mil) Age 21+ (207.9mil)

% D

epre

ssio

n



19% 11%

Total Population

NOTE: NSDUH does not ask about other

disorders or ask about them for those under 18


Only Alcohol Abuse/Dependence

associated with higher Psychiatric Comorbidity

National Comorbidity Study Replication (NCSR) Shows Comorbidity is Actually More Common

Source: Dennis, Scott, Funk & Chan forthcoming; National Co morbidity Study Replication

Lifetime Number of Disorders

Lifetime Pattern of Disorders

None54%

1 Disorder18%

2 Disorders10%

3 to 16 Disorders

18%

Substance Only3%

None48%

Sub.+Int4%

Ext.+Int.10%

Sub. + Ext. + Int. 8%

Sub.+Ext1%

Internalizing Only21%

Externalizing Only5%

(28%/46% Any)=61% Co-occurring

(13%/16% SUD)=81% Co-occurring

NOTE: Not asked about work if under age 15 in NSDUH

Potential Screening/ Intervention Sites: Age 12 to 20 (38.1 million)


5% 8%

0%

30%

52%

90%

6% 10%

2%

36%

75%

95%

7% 9% 5%

38%

89% 96

%

7%

15%

10%

41%

81%

95%

0%

20%

40%

60%

80%

100%

Hosptial MentalHealth Tx

SubstanceAbuse Tx

EmergencyRoom

Workplace School

% A

ny C

onta

ct


Key potential of Workplace (e.g., EAP, Wellness, HRA) and School (e.g., SAP,

EI, Prevention) Programs

Potential Screening/ Intervention Sites: Age 21+ (207.9 million)


16%

12%

1%

32%

58%

10%

13%

1%

27%

80%

7% 8%

1%

26%

87%

8%

21%

8%

34%

89%

0%

20%

40%

60%

80%

100%

Hosptial Mental HealthTx

SubstanceAbuse Tx

EmergencyRoom

Workplace

% A

ny C

onta

ct


Key potential of Workplace Programs

NOTE: Not asked about School if over age 18 in NSDUH

Severity of Past Year Substance Use/Disorders (2002 U.S. Household Population age 12+= 235,143,246)

Dependence 5%

Abuse 4%

Regular AOD Use 8%

Any Infrequent Drug Use 4%

Light Alcohol Use Only 47%

No Alcohol or Drug Use

32%

Source: 2002 NSDUH, Dennis & Scott, 2007

Higher Severity is Associated with Higher Annual Cost to Society Per Person

Source: 2002 NSDUH

$0$231 $231

$725$406

$0$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

No Alcohol orDrug Use

Light Alcohol

Use Only

AnyInfrequentDrug Use

Regular AODUse

Abuse Dependence

Median (50th percentile)

$948

$1,613

$1,078$1,309

$1,528

$3,058Mean (95% CI)

This includes people who are in recovery, elderly, or do not use

because of health problems Higher Costs

Adults & Adolescents

Severity of Past Year Substance Use/Disorders by Age

Source: 2002 NSDUH and Dennis & Scott 2007

0

10

20

30

40

50

60

70

80

90

100

12-13

14-15

16-17

18-20

21-29

30-34

35-49

50-64

65+

No Alcohol or Drug Use

Light Alcohol Use Only

Any Infrequent Drug Use

Regular AOD Use

Abuse

Dependence

NSDUH Age Groups

Severity Category

Over 90% of use and

problems start between the ages of

12-20

It takes decades before most recover or die

People with drug dependence die an

average of 22.5 years sooner than those

without a diagnosis

(2002 U.S. Household Population age 12+=

235,143,246)

Photo courtesy of the NIDA Web site. From A Slide Teaching Packet: The Brain and the Actions of Cocaine, Opiates, and Marijuana.

pain

Adolescent Brain Development Occurs from the

Inside to Out and from Back to Front

Crime & Violence by Substance Severity

0%

10%

20%

30%

40%

50%

60%

Serious FightAt School

Fighting withGroup

Sold Drugs Attacked withintent to harm

Stole (>$50) CarriedHandgun

Dependence (3.9%) Abuse (4.2%)

Weekly AOD Use (6.4%) Any Drug or Heavy Alc Use (8.8%)

Light Alc Use (12.4%) No PY AOD Use (64.3%)

Source: NSDUH 2006

Adolescents 12-17Substance use severity is related to crime and violence

Family, Vocational & MH by Substance Severity

Source: NSDUH 2006

0%

10%

20%

30%

40%

50%

60%

10 or MoreArguments with

Parents

Disliked School GPA = D orlower

MajorDepression

Any MHTreatment

Dependence (3.9%) Abuse (4.2%)

Weekly AOD Use (6.4%) Any Drug or Heavy Alc Use (8.8%)

Light Alc Use (12.4%) No PY AOD Use (64.3%)

Adolescents 12-17..as well as family, school

and mental health problems

Age of First Use Predicts Symptoms of Dependence an Average of 22 years Later

Source: Dennis, Babor, Roebuck & Donaldson (2002) and 1998 NHSDA

3945

63

71

3734

51

62

3023

4148

0

10

20

30

40

50

60

70

80

90

100

Pop.=151,442,082Pop.=176,188,916Pop.=71,704,012Pop.=38,997,916

% w

ith

1+ P

ast Y

ear

Sym

ptom

s

Under Age 15

Aged 15-17

Aged 18 or older

Tobacco: OR=1.49*

Alcohol: OR=2.74*

* p<.05

Marijuana:OR=2.45*

Other Drugs:OR=2.65*

People Entering Publicly Funded Treatment Generally Use For Decades

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence302520151050

Source: Dennis et al., 2005

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

It takes 27 years before half reach 1 or more years of abstinence or die

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence

under 15

21+

15-20

Age of First Use*

302520151050


100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

60% longer

The Younger They Start, The Longer They Use

* p<.05

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence

Years to first Treatment Admission*

302520151050


100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

20 or more years

0 to 9 years

10 to 19 years

57% quicker

The Sooner They Get The Treatment, The Quicker They Get To Abstinence

•p<.05

7.8%

20.9%

7.2%

0.5%1.0%0.4%0%

5%

10%

15%

20%

25%

12 to 17 18 to 25 26 or older

Abuse or Dependence in past yearTreatment in past year

Why we need to be expand beyond specialty care into school, work place, and health care..

Source: OAS, 2009 – 2006, 2007, and 2008 NSDUH

Over 88% of adolescent and young adult treatment and

over 50% of adult treatment is publicly funded

Few Get Treatment: 1 in 19 adolescents,

1 in 21 young adults, 1 in 12 adults

Much of the private funding is limited to 30

days or less and authorized day by day

or week by week

Health care reform

(including school based health

care, prevention care, and equity) may change this

Source: French et al., 2008; Chandler et al., 2009; Capriccioso, 2004

Cost of Substance Abuse Treatment Episode

$407

$1,249$1,132$1,384$2,486$2,907$4,277

$14,818

$0

$1

0,0

00

$2

0,0

00

$3

0,0

00

$4

0,0

00

$5

0,0

00

$6

0,0

00

$7

0,0

00

Screening & Brief Inter.(1-2 days)In-prison Therap. Com. (28 weeks)

Outpatient (18 weeks)Intensive Outpatient (12 weeks)

Treatment Drug Court (46 weeks)

Residential (13 weeks)Methadone Maintenance (87 weeks)Therapeutic Community (33 weeks)

$22,000 / year to incarcerate

an adult

$30,000/ child-year in foster care

$70,000/year to keep a child in

detention

• $750 per night in Detox• $1,115 per night in hospital • $13,000 per week in intensive care for premature baby• $27,000 per robbery• $67,000 per assault

Many SBIRT, School, Workplace and other early

intervention programs focus on brief intervention

Investing in Treatment has a Positive Annual Return on Investment (ROI)

Substance abuse treatment has been shown to have a ROI of between $1.28 to $7.26 per dollar invested

Treatment drug courts have an average ROI of $2.14 to $2.71 per dollar invested

Source: Bhati et al., (2008); Ettner et al., (2006)

This also means that for every dollar treatment is cut, we lose more money than we saved.

The Movement to Increase Screening

Screening, Brief Intervention and Referral to Treatment (SBIRT) has been shown to be effective in identifying people not currently in treatment, initiating treatment/change and improving outcomes (see http://sbirt.samhsa.gov/ )

The US Preventive Services Task Force (USPSTF, 2004; 2007), National Quality Forum (NQF, 2007), and Healthy People 2010 have each recommended SBIRT for tobacco, alcohol and increasingly drugs

CSAT, CSAP, OJJDP, BJS NIAAA and NIDA are funding several projects to develop and evaluate models for doing this in primary care, trauma, emergency departments, schools, workplaces, and justice programs

Washington State mandated screening in all adolescent and adult substance abuse treatment, mental health, justice, and child welfare programs with the 5 minute Global Appraisal of Individual Needs (GAIN) short screener

http://sbirt.samhsa.gov/

77% 86

%

73%

75%

61%67

%

83%

62%

75%

60%

57%

40% 46

%

12%

12%

47%

37%

35%

12%

11%

0%10%20%30%40%50%60%70%80%90%

100%

Substance AbuseTreatment(n=8,213)

Student AssistancePrograms(n=8,777)

Juvenile Justice(n=2,024)

Mental HealthTreatment (10,937)

Children'sAdministration

(n=239)

Either High on Mental Health High on Substance High on Both

Source: Lucenko et al (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

Washington State Results with GAIN Short Screener: Adolescent

Problems could be easily identified & Comorbidity common

http://publications.rda.dshs.wa.gov/1392/

35%

12%

11%

56%

34%

15%

9%

47%

0%10%20%30%40%50%60%70%80%90%

100%

Substance AbuseTreatment (n=8,213)

Juvenile Justice(n=2,024)

Mental HealthTreatment (10,937)

Children'sAdministration

(n=239)

GAIN Short Screener Clinical Indicators


Adolescent Client Validation of Hi Co-occurring from GAIN Short Screener vs Clinical Records

by Setting in Washington State

Two page measure closely approximated all found in the clinical record after the next two years


0 5,000 10,000 15,000 20,000 25,000

Any BehavioralHealth (n=22,879)

Mental Health(21,568)

Substance AbuseNeed (10,464)

Co-occurring(9,155)

Substance Abuse Treatment Student Assistance ProgramJuvenile Justice Mental Health TreatmentChildren's Administration

Where in the System are the Adolescents with Mental Health, Substance Abuse and Co-occurring?


School Assistance Programs (SAP) largest part of BH/MH system

SAP+ SA Treatment

Over half of system


Washington State Results with GAIN Short Screener: Adults

81%

78%

65%

64% 69

%

18%

68% 73

%

43%

44%

69%

17%

69%

51%

53%

51%

17%

4%

56%

46%

31%

31%

17%

3%

0%10%20%30%40%50%60%70%80%90%

100%

SubstanceAbuse

Treatment(n=75,208)

Eastern StateHospital(n=422)

Corrections:Community(n=2,723)

Corrections:Prison

(n=7,881)

Mental HealthTreatment(55,847)

ChildrensAdministration

(n=1,238)

Either High on Mental Health High on Substance High on Both


Problems could be easily identified & Comorbidity common


Washington State Validation of Co-occurring: GAIN Short Screener vs Clinical Records

17%

3%

59%

39%

22%

56%

0%

10%20%

30%40%

50%

60%70%

80%90%

100%

Substance Abuse Treatment(n=75,208)

Mental Health Treatment(55,847)

Childrens Administration(n=1,238)

GAIN Short Screener Clinical Indicators


Higher rate in clinical record in Mental Health and Children’s Administration.

(Important of considering urine tests and other sources of information)


0 20,0

00

40,0

00

60,0

00

80,0

00

100,

000

120,

000

Any Behavioral Health (n=106,818)

Mental Health (n=94,832)

Substance Abuse (n=67,115)

Co-Occurring (n=55,128)

Substance Abuse Treatment Eastern State HospitalCorrections: Community Corrections: PrisonMental Health Treatment Childrens Administration

Where in the System are the Adults with Mental Health, Substance Abuse and Co-occurring?


Substance Abuse Treatment is over half of treatment system for substance disorders, other mental disorders, and co-occurring


0%1%2%3%4%5%6%7%8%9%

10%11%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Total Disorder Sceener (TDScr) Score

% w

ithi

n L

evel

of

Car

e

Residential (n=1,965)

OP/IOP (n=2,499)

SAP (n=10,649)

Low

Mod. High ->

32

Total Disorder Screener Severity by Level of Care: Adolescents

Source: SAPISP 2009 Data and Dennis et al 2006

Residential Median (10.5) is higher

Outpatient & Student Asst. Prog. are Similar

(Median 6.0 vs. 6.4)

Well Targeted 95% 1+85% 3+ About 30% of OP & SAP are in the high

severity range more typical of residential

0%1%2%3%4%5%6%7%8%9%

10%11%12%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Total Disorder Sceener (TDScr) Score

% w

ithi

n L

evel

of

Car

e

Residential (n=1,965)

OP/IOP (n=2,499)

Low

Mod. High ->

33

Total Disorder Screener Severity by Level of Care: Adults

Source: SAPISP 2009 Data and Dennis et al 2006

Residential Median= 8.5(59% at 10+)

Outpatient Median=4.5(29% at 10+)

10% of adult OP missed)

About 20% of OP are in the high severity range more typical of residential

GAIN SS Can Also be Used for Monitoring

109

11

910

8

32 2

0

4

8

12

16

20

Intake 3Mon

6Mon

9Mon

12Mon

15Mon

18Mon

21Mon

24Mon

Total Disorder Screener (TDScr)

12+ Mon.s ago (#1s)

2-12 Mon.s ago (#2s)

Past Month (#3s)

Lifetime (#1,2,or 3)

Track Gap Between Prior and current

Lifetime Problems to identify “under

reporting”

Track progress in reducing current

(past month) symptoms)

Monitor for Relapse

Use of a short common screener can

Provide immediate clinical feedback that is a good approximation of diagnosis and be used to guide placement and treatment planning

Can be used repeatedly to track change

Support evaluation and planning at program or state level (e.g., needs, case mix, services needed)

Provide practice based evidence to guide future clinical decision

Be incorporated into health risk/ wellness assessments and/or school surveys

In practice we need a Continuum of Measurement (Common Measures)

Screening to Identify Who Needs to be “Assessed” (5-10 min)– Focus on brevity, simplicity for administration & scoring– Needs to be adequate for triage and referral– GAIN Short Screener for SUD, MH & Crime– ASSIST, AUDIT, CAGE, CRAFT, DAST, MAST for SUD– SCL, HSCL, BSI, CANS for Mental Health– LSI, MAYSI, YLS for Crime

Quick Assessment for Targeted Referral (20-30 min)– Assessment of who needs a feedback, brief intervention or referral for

more specialized assessment or treatment– Needs to be adequate for brief intervention– GAIN Quick – ADI, ASI, SASSI, T-ASI, MINI

Comprehensive Biopsychosocial (1-2 hours) – Used to identify common problems and how they are interrelated– Needs to be adequate for diagnosis, treatment planning and placement

of common problems– GAIN Initial (Clinical Core and Full)– CASI, A-CASI, MATE

Specialized Assessment (additional time per area)– Additional assessment by a specialist (e.g., psychiatrist, MD, nurse,

spec ed) may be needed to rule out a diagnosis or develop a treatment plan or individual education plan

– CIDI, DISC, KSADS, PDI, SCAN

Screener Quick C

omprehensive S

pecial

More E

xtensive / Longer/ E

xpensive

Longer assessments identify more areas to address in treatment planning

40%

69%

94%98%

22%

13%

3% 0%

22%

8%

1% 0%

9%8%

1% 1%3% 1% 1%7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

GAIN SS GAIN Q(v2)

GAIN Q(v3 -Beta)

GAIN I

0 Reported

1 Prob.

2 Probs.

3 Probs.

4 Probs.

Source: Reclaiming Futures Portland, OR and Santa Cruz, CA sites (n=192)

Most substance users have multiple problems

37

5 min. 20 min 30 min 1-2 hr

How does this relate to the move towards Evidence Based Practice (EBP)?

EBP means introducing explicit intervention protocols – Targeted at specific problems/subgroups and outcomes– Having explicit quality assurance procedures to cause

adherence at the individual level and implementation at the program level

Reliable and valid assessment is needed that can be used to – Immediately guide clinical judgments about

diagnosis/severity, placement, treatment planning, and the response to treatment at the individual level

– Drive longer term program evaluation, needs assessment, performance monitoring and program planning

– Allow evaluation of the same person or program over time– Allow comparisons with other people or interventions

Major Predictors of Bigger Effects Found in Multiple Meta Analyses

1. A strong intervention protocol based on prior evidence

2. Quality assurance to ensure protocol adherence and project implementation

3. Proactive case supervision of individual

4. Triage to focus on the highest severity subgroup

Impact of the numbers of these Favorable features on Recidivism in 509 Juvenile Justice Studies in Lipsey Meta Analysis

Source: Adapted from Lipsey, 1997, 2005

Average Practice

The more features, the lower

the recidivism

Evidenced Based Treatment (EBT) that Typically do Better than Usual Practice in Reducing Juvenile Recidivism (29% vs. 40%)

Aggression Replacement Training Reasoning & Rehabilitation Moral Reconation Therapy Thinking for a Change Interpersonal Social Problem Solving MET/CBT combinations and Other manualized CBT Multisystemic Therapy (MST) Functional Family Therapy (FFT) Multidimensional Family Therapy (MDFT) Adolescent Community Reinforcement Approach (ACRA) Assertive Continuing Care

Source: Adapted from Lipsey et al 2001, Waldron et al, 2001, Dennis et al, 2004

NOTE: There is generally little or no differences in mean effect size between these brand names

Implementation is Essential (Reduction in Recidivism from .50 Control Group Rate)

The effect of a well implemented weak program is

as big as a strong program implemented poorly

The best is to have a strong

program implemented

well

Thus one should optimally pick the strongest intervention that one can

implement wellSource: Adapted from Lipsey, 1997, 2005

43

Percentage Change in Abstinence (6 mo-Intake) by level of Adolescent Community Reinforcement Approach (A-CRA) Quality Assurance

4%

24%36%

0%10%20%30%40%50%60%70%80%90%

100%

Training Only Training,Coaching,

Monitoring

Clinical TrialOnsite Protocol

Monitors

% P

oint

Cha

nge

in A

bsti

nenc

e

Source: CSAT 2008 SA Dataset subset to 6 Month Follow up (n=1,961)

Effects associated with intensity of quality

assurance and monitoring (OR=13.5)

Source: 2008 CSAT AAFT Summary Analytic Dataset

553/771=72%unmet need

218/224=97% to targeted

771/982=79% in need

Importance of Targeting on Performance measures

Size of the Problem

Extent to which services are currently being targeted

Extent to which services are not reaching those in most need

Treatment Received in the first 3 months

Mental Health Need at Intake

No/Low Mod/High Total

Any Treatment 6 218 224

No Treatment 205 553 758

Total 211 771 982

Mental Health Problem (at intake) vs. Any MH Treatment by 3 months

79%

97%

72%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% of Clients WithMod/High Need

(n=771/982)*

% w Need but No ServiceAfter 3 months

(n=553/771)

% of Services Going toThose in Need

(n=218/224)


Why Do We Care About Unmet Need?

If we subset to those in need, getting mental health services predicts reduced mental health problems

Both psychosocial and medication interventions are associated with reduced problems

If we subset to those NOT in need, getting mental health services does NOT predict change in mental health problems

Conversely, we also care about services being poorly targeted to those in need.

Residential Treatment need (at intake) vs. 7+ Residential days at 3 months

36%

52%

90%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% of Clients WithMod/High Need

(n=349/980)*

% w Need but NoService After 3 months

(n=315/349)

% of Services Going toThose in Need (n=34/66)

Opportunity to redirect

existing funds through better

targeting


The GAIN is ..

A family of instruments ranging from screening, to quick assessment to a full Biopsychosocial and monitoring tools

Designed to integrate clinical and research assessment

Designed to support clinical decision making at the individual client level

Designed to support evaluation and planning at program level

Designed to support secondary analyses and comparisons across individuals and programs

The GAIN is NOT an electronic health record (EHR), but a component that can interface with and support EHRs.

More in BZ, CA, CN, JP, MX

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GA

OH

OR

MD

AZ

TX

NY

NH

WI

CA

NC

CT

FL

MA

WA

WY

No of GAIN Sites

None (Yet)

1 to 14

15 to 30

31 to 165

The GAIN was developed in collaboration with and is used by a wide range of systems in the US..

State or Regional System

GAIN-Short Screener

GAIN-Quick

GAIN-Full

3/10 49

50

Backbone Funded by CSAT to Support Grant Programs: Grantees Using the GAIN from 9/2007 to 6/2010

AK

ALAR

AZ

CACO

CT

DCDE

FL

GA

HI

IA

ID

ILIN

KSKY

LA

MA

MD

ME

MI

MN

MO

MS

MT

NC

ND

NE

NH

NJ

NM

NV

NY

OH

OK

OR

PARI

SC

SD

TN

TX

UTVA

VTWA

WI

WV

WY

PR VI

AAFTARTATDCBIRTJTDCEARMARKEATFDCJDCOJJDPORPRCFSACSCANSCYTCEYORP

Individual Grantee(s) State & Individual Grantee(s)

Some numbers as of June 2010

22 states, 12 Federal, 6 Canadian provinces, 6 other countries, and 3 foundations mandate or strongly encourage its use

1,501 Licensed GAIN administrative units from 49 states (all by ND) and 7 countries

3,270 users in 396 Agencies using GAIN ABS

60,380 intake assessments (largest in field)

22,045 (88% w 1+ follow-up) from 278 CSAT grantees

3500 variables (including 103 scales and indices)

4 dozen researchers have published 179 GAIN-related research publications to date

51

52

Expected Factor Structure of Psychopathology and Psychopathy

Source: Dennis, Chan, and Funk (2006)

Screener items were selected using the Rasch (1p IRT) Measurement Model

-1.89 -.8 -.32 +.28 +.71Items around key

decision pointSource: Riley et al 2007 53

Co-occurring Mental Health Problems are Common, but the Type of Problems also Changes with Age

Source: Chan, YF; Dennis, M L.; Funk, RR. (2008). Prevalence and comorbidity of major internalizing and externalizing problems among adolescents and adults presenting to substance abuse treatment. Journal of Substance Abuse Treatment, 34(1) 14-24 .

Internalizing Disorders go up

with age

Externalizing Disorders go down

with age (but do NOT go away)

Any Illegal Activity can be better predicted by using Intake Severity on Crime/Violence and Substance Problem Scales

58%46%

36%53%

33%26%44%

27%20%

0%

20%

40%

60%

An

y I

leg

al

Ac

tiv

ity

(mo

nth

s1

-6)

High Mod Low LowMod

High

Crime/Violence Scale (Intake)

Substance Problem Scale

(Intake)

Source: CSAT 2008 V5 dataset Adolescents aged 12-17 with 3 and/or 6 month follow-up (N=9006)

Intake Crime/ Violence Severity

Predicts Recidivism

Intake Substance Problem Severity

Predicts Recidivism

Knowing both is a better predictor(high –high group is 5.5 times more

likely than low low)

While there is risk, most (42-80%) actually do not commit

additional crime

Key Challenges to Quality Care Addressed by GAIN Logic Model1. High turnover workforce with variable education

background related to diagnosis, placement, treatment planning and referral to other services

2. Heterogeneous needs and severity characterized by multiple problems, chronic relapse, and multiple episodes of care over several years

3. Lack of access to or use of data at the program level to guide immediate clinical decisions, billing and program planning

4. Missing, bad or misrepresented data that needs to be minimized and incorporated into interpretations

5. Lack of Infrastructure that is needed to support implementation and fidelity

1. High Turnover Workforce with Variable Education

Questions spelled out and simple question format

Lay wording mapped onto expert standards for given area

Built in definitions, transition statements, prompts, and checks for inconsistent and missing information.

Standardized approach to asking questions across domains

Range checks and skip logic built into electronic applications

Formal training and certification protocols on administration, clinical interpretation, data management, coordination, local, regional, and national “trainers”

Above focuses on consistency across populations, level of care, staff and time

On-going quality assurance and data monitoring for the reoccurrence or problems at the staff (site or item) level

Availability of training resources, responses to frequently asked questions, and technical assistance

Outcome: Improved Reliability and Efficiency

2. Heterogeneous Needs and Severity

Multiple domains Focus on most common

problems Participant self description of

characteristics, problems, needs, personal strengths and resources

Behavior problem recency, breadth , and frequency

Utilization lifetime, recency and frequency

Dimensional measures to measure change with interpretative cut points to facilitate decisions

Items and cut points mapped onto DSM for diagnosis, ASAM for placement, and to multiple standards and evidence- based practices for treatment planning

Computer generated scoring and reports to guide decisions

Treatment planning recommendations and links to evidence-based practice

Basic and advanced clinical interpretation training and certification

Outcome: Comprehensive Assessment

3. Lack of Access to or use of Data at the Program Level

Data immediately available to support clinical decision making for a case

Data can be transferred to other clinical information system to support billing, progress reports, treatment planning and on-going monitoring

Data can be exported and cleaned to support further analyses

Data can be pooled with other sites to facilitate comparison and evaluation

PC and web based software applications and support

Formal training and certification on using data at the individual level and data management at the program level

Data routinely pooled to support comparisons across programs and secondary analysis

Over three dozen scientists already working with data to link to evidence-based practice

Outcome: Improved Program Planning and Outcomes

4. Missing, Bad or Misrepresented Data

Assurances, time anchoring, definitions, transition, and question order to reduce confusion and increase valid responses

Cognitive impairment check Validity checks on missing,

bad, inconsistency and unlikely responses

Validity checks for atypical and overly random symptom presentations

Validity ratings by staff

Training on optimizing clinical rapport

Training on time anchoring Training answering questions,

resolving vague or inconsistent responses, following assessment protocol and accurate documentation.

Utilization and documentation of other sources of information

Post hoc checks for on-going site, staff or item problems

Outcome: Improved Validity

5. Lack of Infrastructure

Direct Services

Training and quality assurance on administration, clinical interpretation, data management, follow-up and project coordination

Webservices, software support, and data management

Evaluation and data available for secondary analysis

Technical assistance and back up to local trainer, clinicians, and evaluators

Development

Clinical Product Development

Software Development

Collaboration with IT/EHR vendors (e.g.WITS, NetSmart)

Over 48 internal & external scientists and students

Workgroups focused on specific subgroup, problem, or treatment approach

Labor supply (e.g., consultant pool, college courses)

Outcome: Implementation with Fidelity

62

2009 CSAT Adolescent Treatment Data Set Grantees

AK

ALAR

AZ

CACO

CT

DCDE

FL

GA

HI

IA

ID

ILIN

KSKY

LA

MA

MD

ME

MI

MN

MO

MS

MT

NC

ND

NE

NH

NJ

NM

NV

NY

OH

OK

OR

PARI

SC

SD

TN

TX

UTVA

VTWA

WI

WV

WY

PR VI

AAFTARTATDCBIRTJTDCEARMARKEATFDCJDCOJJDPORPRCFSACSCANSCYTCEYORP

63

2009 CSAT Data Set by Age

Source: CSAT 2009 Summary Analytic Data Set (n=22,045)

18 Years or Older (18+)

12.7%, (n=2,793)

Under 15 Years Old (<15) 16.1%,

(n=3,547)

15-17 Years Old

71.2%, (n=15,705)

64

Diagnosis Time Period Matters

57%48%

18%

30%

32%

18%

13%19%

63%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Lifetime Past Year Past Month

No Use

Use

Abuse

Dependence


65

Definition of Substance Use Severity Matters

80%

54%

24%

93%

34%

72%

57%

48%

26%

5%0% 10

%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Past Year Substance Diagnosis

3 or More Years of Use

Weekly Use

Any Past Year Dependence

Any Withdrawal Symptoms in the Past Week

Severe Withdrawal (11+ Symptoms)

Can Give 1+ Reasons to Quit*

Client Believes Need ANY Treatment

Acknowledges Having an AOD Problem

Any Prior Substance Abuse Treatment

Source: CSAT 2009 Summary Analytic Data Set (n=21,816) *(n=11,066)

66

Multiple Clinical Problems are the NORM!

20%

41%

80%

48%

33%

63%

11%

24%

14%

34%

27%0% 10

%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Alcohol

Cannabis

Other drug disorder

Depression

Anxiety

Trauma

ADHD

CD

Suicide

Victimization

Violence/ illegal activity


67

The Number of Clinical Problems is related to Level of Care (over lapping but different mix)

41% 45%53%

65%

80%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP IOP CC-OP LTR STR

None

One

Two

Three

Four

Five to Twelve


Significantly more likely to

have 5+ problems (OR=5.8)

68

46%

71%

15%0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Low (0) Moderate (1-3) High (4-15)

None

One

Two

Three

Four

Five to Twelve

The Number of Major Clinical Problemsis highly related to Victimization


Significantly more likely to have 5+

problems (OR=13.9)

But this is the issue staff least

like to ask about!

Overcoming Staff Reluctance with General Victimization Scale

40%

31%

6%10%

1%8%9%

26%

29%7%

57%32%

19%11%

35%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Ever attacked w/ gun, knife, other weapon

Ever hurt by striking/beating

Abused emotionally

Ever forced sex acts against your will/anyone

Age of 1st abuse < 18

Any with more than one person involved

Any several times or for long time

Was person family member/trusted one

Were you afraid for your life/injury

People you told not believe you/help you

Result in oral, vaginal, anal sex

Currently worried someone attack

Currently worried someone beat/hurt

Currently worried someone abuse emotionally

Currently worried someone force sex acts

Source: CSAT 2009 Summary Analytic Data Set (n=19,318) 69

70

B1. Intoxication/Withdrawal Treatment Plan Needs

39%

22%

17%

1%

1%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Any Detox or withdrawal services

Ambulatory Detox (Risk/Mild)

Non-opioid Meds

Opiate Meds

Monitoring withdrawal and AOD medscompliance


71

B2. Biomedical Treatment Plan Needs

60%

33%

29%

17%

6%

1%

1%

78%

3%

4%

11%

16%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Tobacco cessation

Accom. for medical conditions

Discuss compliance w/ prescribed meds

Compliance with meds for PH probs

Discuss ER/hospitalization history

Currently treated for med problem

Tetanus shot

Eating disorder

Treatment of infectious diseases

Accommodations current pregnancy

Reduce sexual behavior risk

Reduce needle use/risk


72

B3. Psychological Treatment Plan Needs

59%

23%

22%

31%

18%

13%

12%

41%

74%

1%

4%

4%

8%

16%

17%

68%

72%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Any Co-occuring

Consq of behavior control problems

Refer to anger management

Suicidal risk intervention

Problems reading and writing

Compliance with psych meds

Currently treated for psych problem

Self-mutilation

Monitor self-mutilation

Cognitive impairment

Discuss lifetime mh hosp. history

Coordination with justice system

Consq of interpersonal illegal acts

Consq of drug-related illegal acts

Discuss lifetime arrest history

Consq of other illegal acts

Civil court proceedings


73

B4.Readiness Treatment Plan Needs

81%

16%

9%

3%

79%

73%

63%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Any Treatment Readiness Issues

Wrap-around or casemanagement services

Any pressure to be in treatment

Required to go to treatment

Reviw expectations for length oftreatment

Review dissatisfaction w/treatment

Partner to understandtreatment process


74

B5. Relapse Potential Treatment Plan Needs

67%

2%

84%

30%

28%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

High Relapse Potential

Recovery coach or mentor

Continuing Care aftercontrolled environment

Significant time in controlledenvironment

Discuss substance abusetreatment history


75

B6. Environment Treatment Plan Needs

63%

32%

29%

26%

32%

47%

54%

56%

70%

85%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Attended school in past 90 days

Coping with psycho-socialstressors

Child maltreatment

Recent school problems

Dissatisfaction withenvironment

Family fighting in the home

Vocational or governmentassistance

Substance use in the home

Employed in past 90 days

Housing situation


76

Individual Strengths

73%

44%

33%

49%

59%

59%

67%

73%

75%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Listening, caring or communicating withothers

Doing well at sports, exercise, physicalactivity

Doing well at with your family

Problem solving and figuring things out

Doing well at school or training

Working or playing with computers

Doing well at music, dancing, acting,other performing art

Drawing, painting, design or other artactivities

Doing well at work


77

Social Support

77%

53%

57%

71%

71%

77%

79%

85%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Family members/close partners

Someone to talk to about emotions

Legal hobby or activity

Someone to help cope with problems

People at work/school: get assignments

People at work/school: Day to day things

Friends/colleagues from othercompanies/schools

Professional counselor/health provider


78

Mentors in the Recovery Environment

52%

75%

25%

18%

58%

41%

30%

16%

63%

46%

29%

16%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

None involved in shouting, arguing orfighting most weeks

None involved in illegal activity

Know any in treatment

Know any in recoveryNone involved in shouting, arguing or

fighting most weeksNone involved in illegal activity


Know any in recoveryNone involved in shouting, arguing or

fighting most weeksNone involved in illegal activity


Know any in recovery


Hom

eS

choo

l or

Wor

kS

ocia

l P

eers

Critical gap in

connection to recovery community

79

NOMS: Early Treatment Outcomes

56%

66%

76%

84%

72%

58%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Initiation within 14 days

Evidenced Based Practice

Engagement for at least 6weeks

Any Continuing Care (91-180 days)

Substance Use-Abstinent/Reduced 50% at 3 Months

12 month cost within bandsfor initial type of treatment

Source: CSAT 2009 SA Data Set subset to 1+ Follow ups (n=11,668)

80

NOMS: Post Treatment Outcome (6-12 mo)

Source: CSAT 2009 SA Data Set subset to 1+ Follow ups

41%

90%

71%

12%

89%

80%

66%

17%

44%

99%

76%

68%

47%

44%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Use

Abuse/Dependence Sx*

Physical Health

Mental Health

Nights of Psychiatric Inpatient

Illegal Activity

Arrests

Housed in Community**

Family/Home Problems

Vocational Problems

Social Support/Engagement

Recovery Environment Risk

Quarterly Cost to Society

In Work/School**

Reduced 50%or NoProblemNo Problem

*This variable measures the last 30 days. All others measure the past 90 days

**The blue bar represents an increase of 50% or no problem

81

But Need to Control for the lack of Problems at Intake

Source: CSAT 2009 SA Data Set subset to 1+ Follow ups

98%

79%

13%

33%37%

52%

78%

61%

11%37%

42%19%

5%

2%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Use

Abuse/Dependence Sx*

Physical Health

Mental Health

Nights of Psychiatric Inpatient

Illegal Activity

Arrests

Housed in Community

Family/Home Problems

Vocational Problems

Social Support/Engagement

Recovery Environment Risk

Quarterly Cost to Society

In Work/School

* Variable measures the last 30 days. All others measure the past 90 days.

82

Change in Number of Positive NOMS Outcomes (Last Follow up – Intake)

Source: CSAT 2009 SA Data Set subset to 1+ Follow ups (n=18,770)

8%6%8%

14%

12%

29%

11%

13%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Total

Five or More

Four

Three

Two

One

None

Negative one

Less than negative one

78% Improved in 1 or more areas (65% in 3 or more)

83

Acknowledgments and Contact Information

Available at www.chestnut.org/li/posters. This presentation was supported by analytic runs provided by Chestnut Health Systems for the

Substance Abuse and Mental Health Services Administration's (SAMHSA's) Center for Substance Abuse Treatment (CSAT) under Contracts 207-98-7047, 277-00-6500, 270-2003-00006 and 270-

2007-00004C using data provided by the following 152 grantees: TI11317 TI11321 TI11323 TI11324 TI11422 TI11423 TI11424 TI11432 TI11433 TI11871 TI11874 TI11888 TI11892 TI11894

TI13190TI13305 TI13308 TI13313 TI13322 TI13323 TI13344 TI13345 TI13354 TI13356 TI13601 TI14090 TI14188 TI14189 TI14196 TI14252 TI14261 TI14267 TI14271 TI14272 TI14283 TI14311 TI14315 TI14376 TI15413 TI15415 TI15421 TI15433 TI15438 TI15446 TI15447 TI15458 TI15461 TI15466 TI15467 TI15469 TI15475 TI15478 TI15479 TI15481 TI15483 TI15485 TI15486 TI15489 TI15511 TI15514 TI15524 TI15524 TI15527 TI15545 TI15562 TI15577 TI15584 TI15586 TI15670 TI15671 TI15672 TI15674 TI15677 TI15678 TI15682 TI15686 TI16386 TI16400 TI16414 TI16904 TI16928 TI16939 TI16961 TI16984 TI16992 TI17046 TI17070 TI17071 TI17334 TI17433 TI17434 TI17446 TI17475 TI17476 TI17484 TI17486 TI17490 TI17517 TI17523 TI17535 TI17547 TI17589 TI17604 TI17605 TI17638 TI17646 TI17648 TI17673 TI17702 TI17719 TI17724 TI17728 TI17742 TI17744 TI17751 TI17755 TI17761 TI17763 TI17765 TI17769 TI17775 TI17779 TI17786 TI17788 TI17812 TI17817 TI17825 TI17830 TI17831 TI17864 TI18406 TI18587 TI18671 TI18723 TI19313 TI19323 TI655374. Any opinions about this data are those of the authors and do not reflect official

positions of the government or individual grantees. Comments or questions can be addressed to Michael Dennis, Chestnut Health Systems, 448 Wylie Drive, Normal, IL 61761. Phone 1-309-451-

7801; E-mail: [email protected]. More information on the GAIN is available at www.chestnut.org/li/gain or by e-mailing [email protected] .

http://www.chestnut.org/li/posters

mailto:[email protected]

http://www.chestnut.org/li/gain

mailto:[email protected]

Briefing for the SAMHSA Workgroup on Underage and Problem Drinking Michael Dennis, Ph.D. Chestnut...

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