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Using Data to Determine Priority Problems

2. Florida's Strategic Prevention Framework. Sustainability

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Using Data to Determine Priority Problems

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    1. Using Data to Determine Priority Problems Epidemiological and Other Considerations 1

    2. 2 Florida’s Strategic Prevention Framework

    3. 3 State Role Goal: Establish state priorities and provide support to local communities most impacted by the problems in order to reduce use and the related consequences Assess the extent of the state’s substance abuse problems Assess state capacity to address the problems Develop state logic models and action plans that are data driven, community focused and employ relevant and effective strategies Monitor local progress and re-plan as needed at the state level Provide resources (data, training, technical assistance, funding) that support Outcome Based Prevention. Example: Creating funding streams that allow for re-planning at the local level.

    4. 4 Community Role Goal: Develop outcome-based logic models that outline a strategic response for addressing state priorities as locally defined Understand problem to be addressed Assess Contributing Factors (Intervening variables) for planning purposes that best fit community context and definition of the problem Determine priority contributing factors to address with interventions Choose/implement strategies (effective and relevant) to address contributing factors

    6. 6 We’re asking coalitions to collect information on: Consequences – evidence of the problem Consumption – the behavior that is related to the problem Intervening Variables – those things that contribute to the problem (contributing factors) Capacity – resources (human, technical and financial) available to address the problem`v First step - Data

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    8. 8 Consequences Consequences: Defined as the ultimate outcome – lack of school success, sexually transmitted disease, alcohol related accidents (crashes), teen pregnancy, violence Grantees are expected to locate local data to create a picture that is deeper than just county-level data, based on populations involved in consequences Discussion point – why consequences?? Collaboration Collaboration

    9. PRIORITIZATION Phase 1 Some Considerations 9 Begin with consequence data, and explore relationships to begin to describe problems (e.g., acute versus chronic consequences) Explore consumption patterns and how they relate to consequences to further describe problems (e.g., acute problems of alcohol use) Look at data from multiple perspectives to determine implications

    10. 10 Substance-Related Consequences (Examples)

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    12. PRIORITIZATION Step 1 SOME EPIDEMIOLOGICAL DIMENSIONS 12 Size/magnitude of the problem Increase of the problem over time and other comparisons Severity Economic costs/social impact

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    15. 15 don’t have long period of trend data Very sensitive to scale of Y axis display (a 100% increase may seem like a lot but in terms of actual magnitude) Need to clarify what the magnitude of change actually means in other terms (number of people, years of life, costs, etc) Percentage change v. percentage point change—can have very different meaning but need to be clear on how you interpreting the change What are your assumptions about change in trends? Need to be clear Use 3 year averages where possible to account for random fluctuations in trends (average first three, second three, third three, etc)—assumes enough data to do so Remember maturation effects in youth data…look for trends in like cohort (e.g. 10th over time) and follow each cohort don’t have long period of trend data Very sensitive to scale of Y axis display (a 100% increase may seem like a lot but in terms of actual magnitude) Need to clarify what the magnitude of change actually means in other terms (number of people, years of life, costs, etc) Percentage change v. percentage point change—can have very different meaning but need to be clear on how you interpreting the change What are your assumptions about change in trends? Need to be clear Use 3 year averages where possible to account for random fluctuations in trends (average first three, second three, third three, etc)—assumes enough data to do so Remember maturation effects in youth data…look for trends in like cohort (e.g. 10th over time) and follow each cohort

    16. Should we focus on this…going up over two years Note scale (Y axis here) seems to be going up radicallyShould we focus on this…going up over two years Note scale (Y axis here) seems to be going up radically

    17. Maybe we shouldn’t be focusing on this…actually down from what it was two years agoMaybe we shouldn’t be focusing on this…actually down from what it was two years ago

    18. Wow! We’ve made major headway on reducing this…can celebrate a success on this…reduced and kept down for this age groupWow! We’ve made major headway on reducing this…can celebrate a success on this…reduced and kept down for this age group

    19. Now with 5 years of data could conclude that ‘02 was a spike year and now right at the average…a fluctuation…maybe something happened in ‘02 that drove it up. If want to target reduction, then target below the average (e.g. 20-16) Now with 5 years of data could conclude that ‘02 was a spike year and now right at the average…a fluctuation…maybe something happened in ‘02 that drove it up. If want to target reduction, then target below the average (e.g. 20-16)

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    25. 25 Underage Drinking Consumption: The behavior that is the precursor to consequences (i.e. binge drinking) Must be studied by age, gender, and ethnic groups, with distinct data for underage use and for binge drinking Multiple sub-populations in the community must be assessed in whatever ways are available Discussion – Why consumption? FocusFocus

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    31. 31 Underage Drinking Each Intervening Variable will have multiple contributing factors, each of which could be measured, studied, and addressed by one or more strategies A logical plan must be developed to collect data on these contributing factors, and then the community must seek to understand them, as a “system”, and how they impact substance use Only then can strategies be effectively planned ACTION!!ACTION!!

    32. 32 Contributing Factors Community Level Factors Availability of substances (price, retail, social) Promotion of substances Social Norms regarding use Enforcement of Policies and Social Norms Individual Level Factors Perceptions of risk and harm Positive attitude toward drug use

    33. 33 Contributing Factors Availability Economic Availability - Price Retail Availability - ATOD accessibility from retail sources (money is exchanged). Social Availability – ATOD accessibility from non-retail sources (money rarely exchanged -- family and friends). Promotion- Attempts to increase the attractiveness of drinking, smoking or using illicit drugs and/or the substances themselves

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    40. PRIORITIZATION Step 2 Other Data/Broader Criteria

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