1. Utilizing CESN Data with the Strategic Prevention Framework Presented by Sarah Goan and Tim Diomede Hornby Zeller Associates, Inc. August 2012

2. Goals of Presentation Review how Community Profiles fit into SPF Provide guidance for using Community Profiles Introduce new supplemental SEOW reference tools

3. Purpose of the State Epidemiological Outcomes Workgroup (SEOW) Purpose of the Community Epidemiological Surveillance Network (CESN) Dual Purposes of SEOW/CESN Promote systematic, data- driven decision-making Guide effective and efficient use of prevention resources Identify substance abuse patterns Establish and track substance abuse trends Detect emerging substances

4. Pinpoint areas of critical concern Identify information gaps Start conversations with key players Make your case to access resources Allocate scarce resources strategically Implement programs that will affect change Monitor indicators for progress and emerging concerns Role of Data in the Strategic Prevention Framework

5. Reports for eight Maine Public Health Districts (PHDs) – Consumption – Consequences – Contributing Factors – Mental Health – Treatment Characteristics of the Community Profiles

6. Summary Justification Description 2012 Community Profiles http://www.maine.gov/dhh s/osa/data/profiles.htm Community Profile

7. USING THE COMMUNITY PROFILES

8. Does the consumption of one substance appear to be more of a problem than others? Does one consequence appear to be more of a problem than others? Is there a pattern of consumption or misuse among certain grades, age groups, or over time that is of particular concern? How does your community compare with the state or other communities? Understanding Community Needs

9. Example(s) from Profiles Comparing Prevalence Rates and Prioritizing

10. Example(s) from Profiles Prioritizing Consequences

11. Example(s) from Profiles Identifying Patterns Among Groups

12. Informing Strategy/Program Selection What are the common themes across the data sources? – What substances emerge as a high priority? What do the profiles tell you about the factors that contribute to those patterns?

13. Example(s) from Profiles Contributing Factors

14. Identify Knowledge Gaps Who is involved in the problem (age, gender, income, race/ethnicity)? Where does the problem occur? When does the problem occur? Why is the problem occurring? Guide to Assessment, Planning and Evaluation 2011 http://www.maine.gov/dhhs/osa/pubs/data/2011/GuidetoAssess.Plan.Eval.pdf

15. Example: Finding a Gap Who = Youth and young adults (18 to 25 year olds). I don’t know about gender. Where = I don’t know When = I don’t know Why = Perceptions about risk of harm are low

16. Evaluating Your Work Develop a Logic Model with measurable risk factors and longer-range outcomes Monitor longer-term outcomes over time Establish baselines and targets and see if they were met (Note: Can’t attribute change to specific work, but helps make the case)

17. Profiles and Logic Models Step: Define Need (Problem Statement)Step: Create Work PlanStep: Identify and Monitor Results Need/ Problem But why? But why here? What are we doing? What steps will we take to implement the strategy? Short-Term Outputs Inter- mediate Long- Term Too Many Youth Engage in Underage Drinking (Middle and High School) Youth do not think they will be caught by Police (Enforcement) Local Police Departments do not work together Enforcement is inconsistent Form an underage drinking task force with all local PDs Implement Model Policy/ Procedures Approach/ recruit PDs Convene group Task force reviews policies and procedures Adjustments made to policies and procedures MOUs/ Agreements Signed Departments are working together Alcohol citations for minors Youth perceptions of getting caught Fewer Youth Engage in Past Month Alcohol Use

18. Example: Baselines and Targets List of the information and data available to you that “fit” your strategy/intervention Consider those measures along with words like increased, decreased, more or enhanced Determine what percent change is feasible – Percent change equation: Subtract current rate from a target rate and divide by current rate Step 1: 42 (target) - 45 (current) = 3 percentage points Step 2: -3 / 45 = -7% Step 3: Target = 7% decrease

19. Writing and Applying for Grants Draft a “Statement of Need” Focus on goals and objectives that are data- driven and measurable Demonstrate capacity to monitor/report specific data indicators Summarize sub-state data sources and/or trends using a state-produced source With the exception of MIYHS, PHD is the lowest level you can go and still have reliable estimates.

20. Break for Questions How do you interpret the data correctly? What information should I share with my Public Health District? Not all schools in my county participate in MIYHS -- how valid is the data for us? Other Questions?

21. NEW SUPPLEMENTAL TOOLS

22. Community Data Overview Presentation 4. Comparing Communities

23. Includes indicators for: Consumption ● Consequences ● Contributing Factors Targets areas of concern/high priority – Underage drinking among 12-20 year olds – Prescription drug misuse among 12-25 year olds – Marijuana use among 12-25 year olds Two year snapshot of data Quick reference guide can be found by copying and pasting the following link http://www.maine.gov/dhhs/osa/data/cesn/indicatortableBW.docx Introduction of Quick Reference Guide

24. Underage Drinking (12-20 year olds) Public Health Districts PopulationSourceTypeIndicatorYear(s) Aroos- took Central Cumber- land Down- east Mid- coast PenquisWesternYorkMaine 7th - 8th grade Past 30 day alcohol use (any) 200911% 9%8%10% 9%10% 20115%7%6%7%9%6% 9th-12th High School Students MIYHS Consump tion Past 30 day alcohol use (any) 200932%31%32% 35%31%30%32% 201127%26%29%24%30% 27%29%28% Past 30 day binge (5 or more drinks on at least one occasion) drinking 200919% 22%21%18% 19% 201116% 17%15%18%19%16%17% Risk and Protector Factors Students who thought they would you be caught by their parents for drinking? 200944%43%42%43%42% 40%42% 201147%45%43%45%41%43%44%42%43% Students who thought they would you be caught by the police for drinking? 200913%15%16%13%14%13%15%13%14% 201114%16%17%16%14% 16%14%15% Percieved harm from binge drinking once or twice a week. 200975%71%76%67%73%70%72%76%73% 201180%78%80%77% 78%80%78% Students who percieved it to be asy to access alcohol 200970%66%69%68%67%68%67%71%68% 201166% 69%65%68% 65%69%67% Students who reported feeling so sad or hopeless almost every day for two weeks or more in a row that you stopped doing some usual activities? 200923%22%20%23% 22% 23%22% 201123%22%21%23%25%22%24% 23% Conseque nce Students who reported drinking and driving 20096% 8% 7% 20116%4%5%4%5%6%5% Students who reported riding with a driver who was under the influence of drugs or alcohol 200916%22% 24%23%22%23%25%22% 201119%20%23%18%23%22%21%24%22% significant improvement (5+ point change) some improvement little to no change setback significant setback (5+ point change) cannot trend Data unavailable

25. Underage Drinking (12-20 year olds) continued Public Health Districts PopulationSourceTypeIndicatorYear(s) Aroos- took Central Cumber- land Down- east Mid- coast PenquisWesternYorkMaine 12 to 20 year olds NSDUH Consump tion Past 30 day alcohol use (any) 2007-08 28% 2008-09 27% Past 30 day binge (5 or more drinks on at least one occasion) drinking 2007-08 19% 2008-09 17% Past 30 day alcohol use (any) 2006-0828%*24%31%29%*28%32%29%30%29% Past 30 day binge (5 or more drinks on at least one occasion) drinking 2006-08 20%*15%22%20%*18%23%17%20% All AgesUCR Consequ ence Alcohol-related crime rate per 10,000 residents2009 64.894.691.483.979.695.487.1114.594.2 2010 64.687.884.685.867.882.5 103.684.4 MHDO Outpatient hospital visits due to alcohol per 10,000 residents 2008355425394688065179123 20093551232117678473163119 TDS Percent of primary treatment admission due to alcohol 201043%44% 41%42%40%49%54%45% 201141%37%36%34%39%32%40%51%39% MDOT Alcohol/Drug related crash rate per 10,000 residents 20108.86.510.813.710.97.310.012.310.4 20115.49.18.311.910.09.27.79.38.9 16-25 year olds Number of annual alcohol and/or drug related car crashes among Maine’s 16-25 year olds2011 336 significant improvement (5+ point change) some improvement little to no change setback significant setback (5+ point change) cannot trend Data unavailable *Due to small sample sizes, Aroostook and Downeast Public Health District (which consists of Washington County and Hancock County) were combined to produce this estimate.

26. Reminder The tools have snapshot comparisons across districts The profiles have the detailed definitions/ language for each indicator as well as graphics These three tools compliment each other and should be used all together Best Approach: use along with Guide to Assessment, Planning and Evaluation!

27. Resources Maine CESN Webpage (Maine OSA site > Data > Community Epi Surveillance Network) http://www.maine.gov/dhhs/osa/data/cesn/index.htm 2012 Community Profiles http://www.maine.gov/dhhs/osa/data/profiles.htm “Community Profile Data Overview” (presentation only) http://www.maine.gov/dhhs/osa/prevention/provider/powerpoints/ppt/CommunityDataOverviewwAndn otes.pdf “Community Data Overview” (recorded webinar ) http://www.maine.gov/dhhs/osa/prevention/provider/powerpoints/audio/1hrcallCommunityDataOver view2012.wmv CESN Quick Reference Tool http://www.maine.gov/dhhs/osa/data/cesn/QuickReferenceGuideColor.pdf Guide to Assessment, Planning and Evaluation 2011 http://www.maine.gov/dhhs/osa/pubs/data/2011/GuidetoAssess.Plan.Eval.pdf MIYHS 2011 Public Health District Summary Reports http://www.maine.gov/dhhs/osa/data/miyhs/2011SummaryPHD.html

28. Questions/Comments? Timothy Diomede SEOW Coordinator/Data Analyst Office of Substance Abuse/Hornby Zeller Associates Timothy.Diomede@maine.gov Sara Goan Manager/Data Analyst Hornby Zeller Associates sgoan@hornbyzeller.com