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Juvenile Treatment Drug Court GAIN Data Issues

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Juvenile Treatment Drug Court GAIN Data Issues SAMHSA / CSAT Treatment Drug Court Grantee Meeting Melissa Ives Kate Moritz June 10, 2009 Anaheim, CA – PowerPoint PPT presentation

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Title: Juvenile Treatment Drug Court GAIN Data Issues


1
Juvenile Treatment Drug Court GAIN Data Issues
  • SAMHSA / CSAT
  • Treatment Drug Court Grantee Meeting
  • Melissa Ives
  • Kate Moritz
  • June 10, 2009
  • Anaheim, CA

2
Outline
  • Overview of current data March 2009 JDTC/FDC
    data with YORP and CSAT 2008
  • Using your own GAIN data/Resources Reminder of
    available GCC resources for evaluators
  • Using the scales and variables files
  • Review of current characteristics profile
  • Accessing CSAT GAIN data Review of process for
    requesting cross-project data for publications,
    Available Datasets
  • Full GAIN data-Version 5 records only
  • Summary analytic dataset Vertical
  • Summary analytic dataset Horizontal

3
Growth in DC data set
  • CSAT 2006 dataset, GAIN-I N 79
  • and 36 follow-ups (3m).
  • CSAT 2007 dataset, GAIN-I N 534
  • and more than 700 follow-ups (3m-12m).
  • CSAT 2008 dataset, GAIN-I N 1,147
  • and more than 1600 follow-ups (3m-12m).
  • As of March 2009, GAIN-I N 1,845
  • and more than 1,600 follow-ups (3m-12m).
  • more than doubled in 7 months!
  • It is important to have HIGH follow-up rates
  • The goal is 80 or higher each wave.

9 and 12-month follow-ups are not required for
Drug Court sites
4
Follow-up Rates for 3 and 6 month
(Of those) due for 3m wave (Of those) due
for 6m wave
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
5
Demographics
JTDC like AT Gender, Age
JTDC like YORP Minority Status (Hispanic)
Includes 2 Family Drug Court sites
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
6
Years of Use
Includes 2 Family Drug Court sites
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
7
Index Admission Level of Care
JTDC like AT Treatment Placement
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
Includes 2 Family Drug Court sites
8
Pattern of Comorbidity
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
Includes 2 Family Drug Court sites
9
Past Month Abstinence
JTDC Same pattern of improved abstinence, lower
severity
Includes 2 Family Drug Court sites 9m 12m
not required
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
10
No Past Month Substance Problems
Includes 2 Family Drug Court sites 9m 12m
not required
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
11
No Major Health Problems
Includes 2 Family Drug Court sites 9m 12m
not required
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
12
No Major Mental Health Problems
Includes 2 Family Drug Court sites 9m 12m
not required
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
13
No Illegal Activity
Includes 2 Family Drug Court sites 9m 12m
not required
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
14
No Family/Home Problems
Includes 2 Family Drug Court sites 9m 12m
not required
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
15
No problem or 50 Reduction on (at last FU)
Includes 2 Family Drug Court sites
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
16
No problem or 50 Reduction on (at last FU)
Includes 2 Family Drug Court sites
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
17
ASAM Treatment Planning Clusters
Includes 2 Family Drug Court sites
Source March 2009 YORP/JTDC, CSAT AT 2008 dataset
18
GRRS Treatment Planning Needs Substance Use and
Treatment
Source GI_GM_DrugCourt_033109_Horizontal
19
GRRS Treatment Planning Needs Mental Health
Source GI_GM_DrugCourt_033109_Horizontal
20
GRRS Treatment Planning Needs Physical Health
Source GI_GM_DrugCourt_033109_Horizontal
21
GRRS Treatment Planning Needs Environment and
Legal
Environment
Legal
Source GI_GM_DrugCourt_033109_Horizontal
22
GRRS Treatment Planning Needs SES/Vocation
Source GI_GM_DrugCourt_033109_Horizontal
23
GRRS Treatment Planning Needs HIV risk and
Child issues
Source GI_GM_DrugCourt_033109_Horizontal
24
Intoxication (at intake) vs. Detox Treatment at 3
months (es.06)
How well sites are matching service based on need
with unmet need after 3 months
Number in need at intake
3 on ASAM dimension B1 criteria
Source GI_GM_DrugCourt_033109_Horizontal
25
Intoxication (at intake) vs. Detox Treatment at 3
months
Higher values indicate more triage of services to
those in need.
3 on ASAM dimension B1 criteria
Source GI_GM_DrugCourt_033109_Horizontal
26
Physical Health problem (at intake) vs. Medical
Treatment at 3 months
3 on ASAM dimension B2 criteria
Source GI_GM_DrugCourt_033109_Horizontal
27
Mental Health Problem (at intake) vs. MH
Treatment at 3 months
3 on ASAM dimension B3 criteria
Source GI_GM_DrugCourt_033109_Horizontal
28
Tx Readiness Need (at intake) vs. Low Tx
Motivation at 3 months
3 on ASAM dimension B4 criteria
Source GI_GM_DrugCourt_033109_Horizontal
29
Relapse Potential (at intake) vs.
Urine/Breathalyzer at 3 months
3 on ASAM dimension B5 criteria
Source GI_GM_DrugCourt_033109_Horizontal
30
Recovery Environment (at intake) vs. Self Help at
3 months
3 on ASAM dimension B6 criteria
Source GI_GM_DrugCourt_033109_Horizontal
31
Residential Treatment need (at intake) vs. 7
Residential days at 3 months
Source GI_GM_DrugCourt_033109_Horizontal
32
Count of Unmet needs by Program Based on
service area and placement recommendation
High Need (ASAM B1-B6,ResTx) no treatment for
those with 3m data and valid responses for need.
Source GI_GM_DrugCourt_033109_Horizontal
33
Count of Unmet needs by Gender Based on
service area and placement recommendation
Hidden slide
High Need (ASAM B1-B6,ResTx) no treatment for
those with 3m data and valid responses for need.
Source GI_GM_DrugCourt_033109_Horizontal
34
MH issues at intake vs. MH Treatment at 3 months
Hidden slide
Source GI_GM_DrugCourt_033109_Horizontal
35
MH issues at intake vs. MH Treatment at 3 months
Source GI_GM_DrugCourt_033109_Horizontal
36
MH issues (victimization) at intake vs. MH
Treatment at 3 months
Source GI_GM_DrugCourt_033109_Horizontal
37
HIV Risk at intake vs. HIV Prevention/Education
at 3 months
Hidden slide
Source GI_GM_DrugCourt_033109_Horizontal
38
HIV Risk at intake vs. HIV Prevention/Education
at 3 months
Source GI_GM_DrugCourt_033109_Horizontal
39
Resources and Tools
GAIN-I / M90 data
Electronic Encyclopedia (GI SV)
Site Profiles
Evaluator Or Analyst
LI Analytic Training Series Memos
Syntax template files
FTP Common Site
FUL/TTL Reports
Adult Adolescent Norms
40
Using Characteristics Profiles
  • Profiles are updated quarterly (in January,
    April, July , October) for all CJ programs,
    posted on APSS site and e-mailed to each PI.
  • Profiles include
  • Demographics
  • Substance use data
  • Comorbidity data
  • Risk data
  • Treatment information
  • Selected outcomes
  • Individual site graphs
  • Two site comparison graphs

41
Where can I get more help understanding
characteristics profiles?
  • Read documentation and descriptors first on
    introduction page.
  • For specific questions, email datasubmit_at_chestnut.
    org.
  • A teleconference or web conference can be
    conducted to give targeted training on using
    characteristics reports, or FUL/TTL reports or
    anything else your site is having questions on
    regarding managing or using data.

42
Using Site data
  • Each site may use its own local data for
    analysis.
  • Sites may sign a Data Sharing Agreement with one
    or more other sites and share data for cross-site
    analysis.
  • Fully prepared datasets are provided by the GCC
    Data Team to each site on a quarterly basis
  • (JTDC data returned in January, April, July and
    October)
  • The FTP Common Site has SPSS syntax and
    information to help export and prepare local
    data.
  • For more help, contact GAINSubmit_at_chestnut.org

43
Process for accessing GAIN data
  • Submit abstract to gaineval_at_chestnut.org for
    feasibility review.
  • After feasibility review and edits, abstracts are
    distributed to all PIs via listserv.
  • PIs have 2 weeks to review and respond or
    participation is assumed.
  • CSAT project officer gives final approval. Once
    this step is complete, the GCC Evaluation team
    will create dataset.
  • For analyses on general topics using data from
    programs that are no longer in the field or if
    sites are not identified and using the full CSAT
    AT dataset of 17,000 cases, PI distribution step
    is not needed but all other steps are.

44
Creating an abstract
  • A structured abstract (maximum of 3 pages)
    containing the following information
  • 1. Title
  • 2. Lead author
  • 3. Other (potential) authors
  • 4. Proposed forum(s) (journal or conference)
  • 5. Target Dates
  • 6. Data sources (what data set, data and/or time
    periods)
  • 7. Objectives or questions to be addressed
  • 8. Methods/Design/Main analyses
  • 9. Variables to be created
  • 10. Relevance to field

45
Abstract Planning and Evaluation Resources
  • CSAT CJ Publication Policy
  • FTP Common Site Evaluator Folder
    ftp//data.chestnut.org
  • Username Common
  • Password public
  • GAIN Website www.chestnut.org\li\gain
  • Accessing GAIN Data LI Training Series Memo
  • Data Sharing Agreements
  • GAIN-I Scales and Variables File
  • Determine purpose, interpretations, availability,
    syntax
  • Norms for adolescents and adults
  • APSS website www.chestnut.org/li/APSS/DC
  • Quarterly Follow-up, Treatment Transition reports
  • Site Characteristics Profiles tables and charts
  • GAINEval_at_chestnut.org

46
What happens next.
  • Feasibility Review is completed.
  • Abstract is updated if needed based on the
    results of the Feasibility Review.
  • Final Abstract is presented to those from whom
    permission is sought (current grantees, CSAT).
  • Grantees are provided time on the conference call
    to ask questions of the author(s).
  • Grantees have 2 weeks after the conference call
    to decline participation.
  • Data sharing agreement (DSA) is completed (can be
    done concurrently with above or in advance).
  • A de-identified dataset is provided to the
    evaluator or analyst.
  • Do the work and include the acknowledgement!

Please stay in contact if you have questions and
send us a copy of the final presentation or
article!
47
GAIN datasets
  • Full GAIN Version 5 dataset
  • Includes all GAIN records received.
  • Includes all GAIN variables and calculated items.
  • Doesnt include ATM or CYT data
  • Doesnt include FUL, TTL, WAI or TxSI data
  • Summary Analytic dataset
  • Subset to records with planned GAIN Follow-up
    (not GPRA only), with GAIN-I data (no loose
    M90s), with FUL data (FUPLAN1), sites with gt80
    of GAIN data corresponding to FUL and TTL
    records, clients at or past the 3-month follow-up
    window.
  • Subset variables to Identifiers, Demographics,
    Days/Times variables, Scales, Indices, and
    calculated variables used in reports and
    analyses.
  • Matched with FUL, TTL, WAI/TxSI data (on the
    intake record.)
  • Does not include individual symptoms.

48
Horizontal vs. Vertical file WHEN to use
  • When ATM and CYT data should be used If
    comparing to newer studies, be aware of version
    differences in scales and indices,
  • When WCG measures are needed (uses FUL and TTL
    data), or costs are needed.
  • When TxSI or WAI data are to be used,
  • When planned follow-up and opportunity for
    follow-up, accurate data, standard description
    are desired,
  • Stacked Vertical File
  • When NOT looking at individual change
  • Example running mixed linear models over time
    and want to have a random intercept
  • Spread Horizontal File
  • When individual change needs to be calculated and
    used

49
Types of Measures
  • Scale a set of symptoms or items that are
    inter-correlated (e.g., dependence, depression)
    where we are interested in the pattern (i.e.
    common variance)
  • Index a set of items that may not be directly
    related but add up to predict (e.g., sources of
    stress, barriers to treatment, expenses)
  • Ratio Estimators one measure divided by another
    (e.g., percent of unprotected sex acts)
  • Status measures a categorical status based on a
    single question or created across multiple (e.g.,
    vocational status, housing status)
  • Survival Time to first event (e.g., time to
    first use)

50
Interpretative Cut-Points
  • Definition of low, moderate and high clinical
    significance bands to aid interpretation and
    decision making (scale name g for group)
  • Useful for defining need at both the client and
    program level
  • Basis
  • DSM or other clinical standards where available
    (e.g., clinical is 3/7 dependence)
  • 50th 90th percentile for common issues (e.g.,
    days of alcohol use)
  • 1 and median of 1 for zero saturated (more than
    half) and right skewed variables
  • Reverse-coded if up is low clinical
    significance (e.g. Treatment Motivation)

51
Other Ways to get Help
  • Use our email support lines
  • for GAIN and QA/certification questions
    gainsupport_at_chestnut.org
  • for software questions
    abssupport_at_chestnut.org
  • for data submission/data questions
    datasubmit_at_chestnut.org,
  • for evaluation/analysis questions
    gaineval_at_chestnut.org.
  • Contact GCC DC Project Coordinator
  • Kate Moritz
  • kmoritz_at_chestnut.org
  • 309-451-7831

52
Full presentation is available on the GAIN
website www.chestnut.org\li\gain (under
Research Presentations and Posters) or on the
APSS\DrugCourt website (under Major Meeting
Materials) www.chestnut.org/li/APSS/DC
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