Profiling Substance Use Data at Community Level

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Profiling Substance Use Data at Community Level

• Sandeep Kasat and Renee Boothroyd
• Pacific Institute for Research and Evaluation

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Epidemiological Workgroups (SEOW)

• Funded by SAMHSA/CSAP in every state/jurisdiction
  (N 65)
• Structural components of Strategic Prevention
  Framework State Incentive Grant (SPF SIG) N
  42
• Since 2006, other state/jurisdictions/tribes
  received funding (Synectics contracts) to
  establish SEOW N 23
• Network of agencies, organizations, and expertise
  to advance data-guided decisions about substance
  abuse prevention (i.e., assessment, planning,
  ongoing monitoring)

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SEOW Key Tasks/Milestones
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SEOW Contract Key Deliverables

• Set of concrete tasks framed by particular
  attention to monitoring systems
• Develop/Update SEOW charter
• Develop/Update State Epidemiological Profile
• Identify and address a significant data gap in
  the state
• Develop community level epidemiological profile

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Examples of Data Gap Plans

• Data gap - County level alcohol/drug serious
  injury/illness data
• Proposed plan Access and use inpatient hospital
  discharge data
• Data gap ER visits related to substance abuse
• Proposed plan Collect new data on annual visits
  on local/regional basis (proposed piloting 2
  hospitals initially)

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Summary of Data Gap Plans (N 19)

• Data gaps proposed
• 8 of 19 identified community level data/
  indicators (community sub-state, region,
  county)
• 9 mentioned state level data/indicators
• 2 selected special population data (inmate
  population, pregnant women in treatment
  facilities)
• Addressing data gaps
• 8 proposed refining/analyzing existing
  data/indicators while 3 mentioned adding
  indicators to existing source
• 5 mentioned acquiring data from different
  agency/department source
• 3 mentioned collecting new data

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Examples of Community Profiles

• Fact sheets with key consequences and consumption
  data for all counties (depending upon
  availability)
• Detailed profile for the biggest city, most
  populous county/region
• Web based systems/URLs

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Summary of Community Profiles (N 14)

• Defining community
• 7 of 14 defined community as county, 6 as region
  and 1 as city
• Key constructs/indicators
• Almost all profiles included consequences data
  for defined community
• All profiles included youth consumption data and
  few included adult consumption data
• Profile format
• Detailed profile, Fact sheets, Web-based systems
• Some submitted both detailed/overview document
  fact sheets

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Observations/Lessons learned

• Significant number identified community level
  data as their data gap
• Consequences data available (although may have N
  issues in smaller regions/counties)
• Majority have youth consumption data (owing to
  in-state survey), but limited adult consumption
  data
• Significant number proposed working with current
  data/indicators
• Analyzing existing data (BRFSS), adding
  indicators to existing surveys
• Some have already made progress in analyzing
  community level data and have included it in
  their community profile

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Todays Call

• Given the observations/lessons learned well
  hear from
• SD, on how to use existing data source (BRFSS) to
  generate regional estimates
• CA, about the process, decisions and issues in
  developing community level profile and
• MD about community level profile products and
  their utility