Global Appraisal of Individual Needs GAIN Logic Model and its Short Screener

1
Global Appraisal of Individual Needs (GAIN) Logic
Model and its Short Screener

• Michael Dennis, Ph.D.
• Chestnut Health Systems, Normal, IL
• December 3, 2009
• Presentation at the Electronic Health Record
  Content Standards for Behavioral Health
• Expert Panel and Stakeholders Meeting, Rockville,
  MD, December 3-4, 2009. The presentation
  reports on treatment research funded by the
  Center for Substance Abuse Treatment (CSAT),
  Substance Abuse and Mental Health Services
  Administration (SAMHSA, under contracts
  270-2003-00006 and 270-07-0191), the state of
  Washington, King county, PSESD, and ESD113.. 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, Chestnut Health Systems, 448
  Wylie Drive, Normal, IL 61761, phone
  309-451-7801, fax [phone], e-Mail
  mdennis_at_Chestnut.Org Questions about the GAIN
  can also be sent to gaininfo_at_chestnut.org

2
Part 1. Overview of the Global Appraisal of
Individual Needs (GAIN) collaboration and logic
model
3
The Global Appraisal of Individual Needs (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 and secondary analysis
• A key piece of infrastructure in the move towards
  evidenced based practice and a key source of
  practice based evidence

4
As of June 30, 2009, there were 1127
administrative units (agencies, grantees,
counties, states) collaborating to use the GAIN
in the U.S.,
State or County System GAIN-Short
Screener GAIN-Quick GAIN-Full
5
Canada and other countries
1-10 Sites in Other Countries Brazil China Mexic
o Japan
6
So what does it mean to move the field towards
Evidence Based Practice (EBP)?

• Introducing explicit intervention protocols that
  are
• 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
• Introducing reliable and valid assessment that
  can be used
• At the individual level to immediately guide
  clinical judgments about diagnosis/severity,
  placement, treatment planning, and the response
  to treatment
• At the program level to drive program evaluation,
  needs assessment, performance monitoring and long
  term program planning
• Having the ability to evaluate client and program
  outcomes
• For the same person or program over time,
• Relative to other people or interventions

7
Key Issues that we try to address with the GAIN
Instruments and Coordinating Center

• High turnover workforce with variable education
  background related to diagnosis, placement,
  treatment planning and referral to other services
• Heterogeneous needs and severity characterized by
  multiple problems, chronic relapse, and multiple
  episodes of care over several years
• Lack of access to or use of data at the program
  level to guide immediate clinical decisions,
  billing and program planning
• Missing, bad or misrepresented data that needs to
  be minimized and incorporated into
  interpretations
• Lack of Infrastructure that is needed to support
  implementation and fidelity

8
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
9
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
10
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
11
Progressive 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

More Extensive / Longer/ Expensive
Screener Quick
Comprehensive Special
12
Part 2. Overview of the GAIN Short Screener and
a Summary of Major Validation Studies
13
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
• regular screening, brief intervention, and
  referral to treatment (SBIRT) for tobacco and
  alcohol abuse in general medical settings for
  everyone
• SBIRT for drug use in high risk populations
  (e.g., adolescents, pregnant and post partum
  women, people with HIV, and people with
  co-occurring psychiatric conditions)
• CSAT and NIDA are both funding several
  demonstration and research projects to develop
  and evaluate models for doing this
• Washington State mandated screening in all adult
  and adolescent substance abuse treatment, mental
  health, justice, child welfare and student
  assistant programs

13
14
GAIN-Short Screener (GSS)

• Administration Time A 3- to 5-minute screener
• Purpose Used in general populations to
• identify or rule-out clients who will be
  identified as having any behavioral health
  disorders on the 60-120 min versions of the GAIN
• triage area of problem
• serve as a simple measure of change
• Easy for administration and interpretation by
  staff with minimal training or direct supervision
• Mode Designed for self- or staff-administration,
  with paper and pen, computer, or on the web
• Scales Four screeners for Internalizing
  Disorders, Externalizing Disorders, Substance
  Disorders, Crime/Violence, and a Total

15
GAIN-Short Screener (GSS) (continued)

• Response Set Recency of 20 problems rated past
  month (3), 2-12 months ago (2), more than a year
  ago (1), never (0)
• Interpretation Combined by cumulative time
  period as
• Past month count (3s) to measure of change
• Past year count (2s or 3s) to predict diagnosis
• Lifetime count (1s, 2s or 3s) as a measure of
  peak severity
• Can be classified within time period low (0),
  moderate (1-2) or high (3)
• Can also be used to classify remission as
• Early (lifetime but not past month)
• Sustained (lifetime but not past year)
• Reports Narrative, tabular, and graphical
  reports built into web based GAIN ABS and/or ASP
  application for local hosting

16
GAIN-Short Screener (GSS)
17
Expected Factor Structure of Psychopathology and
Psychopathy
Source Dennis, Chan, and Funk (2006)
18
Co-occurring Mental Health Problems are Common,
but the Type of Problems also Changes with Age
Internalizing Disorders go up with age
Externalizing Disorders go down with age (but do
NOT go away)
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 .
19
Any Illegal Activity in the Next Six Months by
Intake Severity on Crime/Violence and Substance
Problem Scales
While there is risk, most (42-80) actually do
not commit additional crime
Source CSAT 2008 V5 dataset Adolescents aged
12-17 with 3 and/or 6 month follow-up (N9006)
20
GAIN SS Psychometric Properties
Low Mod. High
100
Prevalence ( 1 disorder)
90
Sensitivity ( w disorder above)
80
Specificity ( w/o disorder below)
70
(n6194 adolescents)
60
Using a higher cut point increases prevalence
and specificity, but decreases sensitivity
50
40
At 3 or more symptoms we get 99 prevalence, 91
sensitivity, 89 specificity
30
20
10
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Total Disorder Screener (TDScr)
Total score has alpha of .85 and is correlated
.94 with full GAIN version
Source Dennis et al 2006
21
GSS Performance by Subscale and Disorders

Prevalence

Sensitivity

Specificity

Screener/Disorder


1

3

1

3

1

3

Internal Disorder Screener (0-5)

Any Internal Disorder

81

99

94

55

71

99

Major Depression

56

87

98

72

54

94

Generalized Anxiety

32

56

100

83

44

83

Suicide
Ideation

24

43

100

84

41

79

Mod/High Traumatic Stress

60

82

94

60

55

90


External Disorder Screener (0-5)
Any External Disorder

88

97

98

67

75

96

AD, HD or Both

65

82

99

78

51

85

Conduct Disorder

78

91

98

70

62

90

Substance Use Disorder Screener (0-5)

Any Substance Disorder

96

100

96

68

73

100

Dependence

65

87

100

91

30

82

Abuse

30

13

89

25

14

28

Recommend Triage as 0Not likely 1-2
Possible 3Likely
Crime Violence Screener (0-5)

Any Crime/Violence

88

99

94

49

76

99

High Physical Conflict

31

46

100

70

38

77

Mod/High General Crime

85

100

94

51

71

100

Total Disorder Screener (0-5)
Any Disorder

97

99

99

91

47

89

Any Internal Disorder

58

63

100

98

8

28

Any External Disorder

68

75

100

99

10

37

Any Substance Disorder

89

92

99

92

20

51

Any Crime/Violence
68

73

100

96

10

32












22
GAIN SS Can Also be Used for Monitoring
20
12 Mon.s ago (1s)
2-12 Mon.s ago (2s)
16
Past Month (3s)
Lifetime (1,2,or 3)
11
12
10
10
9
9
8
8
3
4
2
2
0
Intake
3
6
9
12
15
18
21
24
Mon
Mon
Mon
Mon
Mon
Mon
Mon
Mon
Total Disorder Screener (TDScr)
Monitor for Relapse
23
Status of Translations
24
Construct Validity of GSS Internalizing Disorder
Screener
Source Dennis 2009, Education Service District
113 (n979) and King County (n1002)
25
Construct Validity of GSS Externalizing Disorder
Screener
Source Dennis 2009, Education Service District
113 (n979) and King County (n1002)
26
Construct Validity of GSS Substance Disorder
Screener
Source Dennis 2009, Education Service District
113 (n979) and King County (n1002)
27
Construct Validity of GSS Crime/Violence
Screener
Source Dennis 2009, Education Service District
113 (n979) and King County (n1002)
28
Adolescent Rates of High (2) Scores on Mental
Health (MH) or Substance Abuse (SA) Screener by
Setting in Washington State
Problems could be easily identified
Comorbidity is common
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/
29
Where in the System are the Adolescents with
Mental Health, Substance Abuse and Co-occurring?
There are more kids with mental health issues
than substance use
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/
30
Where in the System are the Adolescents with
Mental Health, Substance Abuse and Co-occurring?
2/3rd of the teens with mental health issues are
seen in substance abuse treatment or student
assistance programs
lt1
lt1
lt1
student assistance programs Represent 1/3rd of
the behavioral health system
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/
31
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
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/
32
Adult Rates of High (2) Scores on Mental Health
(MH) or Substance Abuse (SA) Screener by Setting
in Washington State
Lower than expected rates of SA in Mental Health
Childrens Admin
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/
33
Where in the System are the Adults with Mental
Health, Substance Abuse and Co-occurring?
More Mental Health than Substance Abuse
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/
34
Where in the System are the Adults with Mental
Health, Substance Abuse and Co-occurring?
More Mental Health Treated in Substance Abuse
Treatment
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/
35
Adult Client Validation of Hi Co-occurring from
GAIN Short Screener vs Clinical Records by
Setting in Washington State
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/
36
Other Validations

• Confirmatory Factor Analysis
• Dennis, Chan Funk (2006) found that the 20 item
  GSS and its four subscales were highly correlated
  (.84 to .94) with the full scale, had 90
  sensitivity and over 90 area under the curve
  relative to the full GAIN Confirmatory factors
  analysis also found it to be consistent with the
  overall model of psychopathology after allowing
  for age (CFI.92 RMSEA.06).
• Substance Disorders
• McDonnell and colleagues (2009) found that the
  5-item GAIN SS Substance Disorder Screener had
  92 sensitivity and 85 correct classification
  relative to the Diagnostic Inventory Scale for
  Children (DISC) Predictive Scales (DPS Lucas et
  al 2001) and 88 sensitivity and 88 correct
  classification relative to the CRAFFT (Knight et
  al 2001)
• Internalizing Disorders
• McDonnell and colleagues (2009) found that the
  5-item GAIN SS Internalizing Disorder Screener
  had 100 sensitivity and 75 correct
  classification relative to the Youth Self Report
  (YSR Achenbach et al, 2001) and that the 5-item
  GAIN SS Externalizing Disorder Screener had 89
  sensitivity and 65 correct classification to the
  YSR.
• Riley and colleagues (2009) found that the 5-item
  GAIN SSs Internalizing Disorder Screener had 92
  sensitivity and 80 area under the curve relative
  to the Structured Clinical Interview for DSM
  (SCID) and was more efficient relative to 11 item
  Addiction Severity Index (ASI) psychiatric
  composite score (McLellan et al., 1992), 10 item
  K10 (Kessler et al., 2002) and the 87 item
  Psychiatric Diagnostic Screening Questionnaire
  (PDSQ Zimmerman and Mattia, 2001)

37
Total Disorder Screener Severity by Level of
Care Adolescents
Outpatient Median6.0 (30 at 10)
Residential Median 10.5 (59 at 10)
Few missed (1/2-3)
Source SAPISP 2009 Data and Dennis et al 2006
37
38
Total Disorder Screener Severity by Level of
Care Adults
Outpatient Median4.5 (29 at 10)
Residential Median 8.5 (59 at 10)
10 of adult OP missed)
Source SAPISP 2009 Data and Dennis et al 2006
38
39
Part 3. Detailed Results from the Student
Assistance Prevention and Intervention Services
Program (SAPISP) in Washington State
40
Student Assistance Prevention and Intervention
Services Program (SAPISP)

• Core funding is funneled from DASA via OSPI and
  combined with a variety of other local, state,
  and federal funding sources (eg, DFSCA, SSHS,
  SPF-SIG).
• 13 grantees (the 9 ESDs and 4 largest school
  districts) hire specialists to serve about 75 of
  MS and HS statewide.
• Specialists conduct some primary prevention
  activities and serve about 16,000 students
  specifically referred for assistance related to
  mental health, alcohol or drug use, tobacco use
  or other behavioral problems
• Screening using the GAIN-SS was first implemented
  in the 2007-2008 school year.
• Reporting is optional for Quick referrals that
  are seen only once or twice.
• Data Presented here are for the 2008 to 2009
  school year

41
SAPISP Results State Wide (n10,924)
GAIN SS uses triage 0Low 1-2Mod 3High
WA State dichotomizes as 0-1Low 2High
Source SAPISP 2009 Data
42
Total Disorder Screener Severity by Level of Care
Outpatient Student Asst. Prog. are Similar
(Median 6.0 vs. 6.4)
Residential Median (10.5) is higher
Well Targeted 95 1 85 3
Source SAPISP 2009 Data and Dennis et al 2006
42
43
Total Disorder Screener by Level of Care
SAP Similar to OP/IOP on Total
Source SAPISP 2009 Data and CSAT 2008 Full
subset to Adolescent Intakes
44
Internalizing Disorder Screener by Level of Care
SAP Higher on Internalizing Disorders
Source SAPISP 2009 Data and CSAT 2008 Full
subset to Adolescent Intakes
45
Externalizing Disorder Screener by Level of Care
SAP Mod-Hi on Externalizing Disorders
Source SAPISP 2009 Data and CSAT 2008 Full
subset to Adolescent Intakes
46
Substance Disorder Screener by Level of Care
SAP Lower on Substance Disorders
Source SAPISP 2009 Data and CSAT 2008 Full
subset to Adolescent Intakes
47
Crime/Violence Screener by Level of Care
SAP Lower on Crime/Violence
Source SAPISP 2009 Data and CSAT 2008 Full
subset to Adolescent Intakes
48
Count of Problems (0-4) with Mod/High Severity by
Level of Care
Source CSAT 2008 Full subset to Adolescents and
Intake
49
Count of Problems (0-4) with Mod/High Severity by
Demographics (n10,924)
Source SAPISP 2009 Data
49
50
SAPISP Results Females (n5,363)
Higher than average on Internalizing Disorders
and Lower than average on Crime/Violence
Source SAPISP 2009 Data
50
51
SAPISP Results Male (n5,548)
Higher on Crime/Violence Lower on Internalizing
Disorders
Source SAPISP 2009 Data
51
52
SAPISP Results Black, not Hispanic (n593)
Lower than average on Internalizing and Substance
Disorders
Source SAPISP 2009 Data
52
53
SAPISP Results Caucasian, not Hispanic
(n7,030)
Average
Source SAPISP 2009 Data
53
54
SAPISP Results Hispanic (n1837)
Average
Source SAPISP 2009 Data
54
55
SAPISP Results Other (n786)
Lower than average on Substance Disorders
Source SAPISP 2009 Data
55
56
SAPISP Results Grades 6-8 (n3,482)
Higher than average Externalizing and Lower than
average Substance Disorders
Source SAPISP 2009 Data
56
57
SAPISP Results Grades 9-12 (n7,392)
Higher than average Substance Disorder
Source SAPISP 2009 Data
57
58
Number of Students Screened by County (n10,924)
59
Count of Problems (0-4) with Mod/High Severity by
County (n10,924)
Source SAPISP 2009 Data
59
60
SAPISP Results Grays Harbor (n176)
Higher than average Substance Disorder Lower
than average Crime/Violence
Source SAPISP 2009 Data
60
61
SAPISP Results King- Not Seattle (n1438)
Average
Source SAPISP 2009 Data
61
62
SAPISP Results Lewis (n187)
Lower on Internalizing Externalizing Higher on
Substance Disorders
Source SAPISP 2009 Data
62
63
SAPISP Results Mason (n62)
Lower on Internalizing Externalizing
Crime/Violence
Source SAPISP 2009 Data
63
64
SAPISP Results Pacific (n29)
Lower on Internalizing Higher on Substance
Crime/Violence
Source SAPISP 2009 Data
64
65
SAPISP Results Pierce -Tacoma (n363)
Lower on Substance Disorders
Source SAPISP 2009 Data
65
66
SAPISP Results Pierce-Not Tacoma (n1247)
Slightly lower on each
Source SAPISP 2009 Data
66
67
SAPISP Results Thurston (n162)
Lower on Internalizing, Externalizing,
Crime Higher on Substance
Source SAPISP 2009 Data
67
68
SAPISP with Tobacco Goal by Total Disorder
Screener Score
Need for Tobacco Cessation Goal is related to
other behavioral health issues
Source SAPISP 2009 Data
68
69
SAPISP with Tobacco Goal by 4 sub-Screeners
Closely Related to Other Drug Use, then Crime,
then Externalizing Disorders
Internalizing Disorder (OR1.2)
Externalizing Disorder (OR2.7)
Substance Disorder (OR6.1)
Crime and Violence (OR3.1)
Source SAPISP 2009 Data
69
70
Implications

• The GAIN Short Screener can readily identify
  youth in need of behavioral health treatment and
  distinguish the type of need
• While there is some variation, this holds across
  gender, race, age, and geographic location
• While the system was originally set up largely
  targeted at substance use, mental health problems
  are more common
• SAP are doing a good job of targeting adolescents
  with behavioral health issues but most are
  actually in the treatment range (not early
  intervention)
• Other things like tobacco use are often related
  to the the severity of behavioral health problems

71
References

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