Community Health Data Scan for Connecticut

1. Community Health Data Scan for Connecticut Educational Briefing Wed., March 28, 2007

2. Why Community Health Data Matters? • Discover areas of need • Set funding priorities • Target interventions • For specific area/groups of people • Evaluate long-term effectiveness of interventions

3. Community Health Data Scan for Connecticut • Broad range of indicators • Quantitative • Focus on race/ethnic disparities in context of kind of community • Innovative use of “Health Reference Groups” of cities and towns

4. Health Reference Groups Map

5. Use the Data Scan to: • Generate hypotheses about health disparities • Estimate rates for individual communities, or groups of communities • Link to other sources of research about particular conditions • Develop public policy recommendations • Evaluate change over time • Use maps, charts and tables on www.cthealth.org (available April 2007)

6. Why Health Data Matters - Two Cases • Binge Drinking • Metabolic Syndrome Diseases

7. Binge Drinking by HRG & Race/Ethnicity

8. Binge Drinking by Age & Race/Ethnicity

9. Metabolic Syndrome Disease • Definition • Diabetes • Heart disease • Stroke • Rates • Different types of communities • Different race/ethnicity groups

10. Diabetes Varies by Race/Ethnicity & Health Reference Group

11. Diabetes Mortality Varies by Race/Ethnicity • White – 16.6 • Black, Not Hispanic – 46.4 • Asian, Not Hispanic – 11.8 • Hispanic – 26.9 Rates are per 100,000 population, age-adjusted, 2000-2004 (see Data Scan Table 113, p 180).

12. Obesity Varies by Race/Ethnicity & Health Reference Group

13. Signs of a Coming Epidemic

14. Metabolic Syndrome Starts Early • Significant Disparities in Youth • Overweight • Lack of exercise • TV watching time • Connecticut lacks good youth data on out-of-school activity to help target programs

15. Notes on Data Scan Methods • Community rate estimation • Problems in community health data • Solutions for community health data

16. Problem of Community Rate Estimation “There is no such thing as a ‘true’ value. There are only estimates, with a probable range, and with a risk of being wrong.” Paraphrase of W. Edwards Deming

17. Key Problems • Town problem • Unreliable rates due to small numbers • Data suppression for privacy/confidentiality • Inconsistency in race and ethnicity coding • Since 2000, no race-ethnicity-gender-age population estimates for towns • Median ages are very different • White, Not Hispanic – 40.2 • Black – 29.9 • Asian – 30.7 • Hispanic – 25.4 Source: U.S. Census 2000

18. Key Solutions • Town Problem • Combine several years of data • Combine cities and towns into six demographically meaningful clusters called “Health Reference Groups” • Use confidence intervals to help interpret all differences • Race and ethnicity coding • Use standard U.S. Census classification • Population estimates • Use Census 2000 • Age-adjustment of all rates to the U.S. 2000 standard population

19. Health Reference Groups (HRGs) • Urban Centers (3) • Bridgeport • Hartford • New Haven • Manufacturing Centers (10) • Diverse Suburbs (15) • Wealthy Suburbs (27) • Mill Towns (39) • Rural Towns (75)

20. Health Reference Groups Map

21. Why Use Both Health Reference Groups & Race/Ethnicity? • Avoid the “broad brush” approach • Avoid stereotyping Asians, blacks, Hispanics & whites as being the same regardless of community context • Allow a more realistic view of community differences that may have public policy and program implications

22. Avoid “Broad Brush” Error Not accounting for differences within broad race/ethnicity groups • 74.4 percent of Hispanic residents in the Urban Centers are of Puerto Rican origin • 23.4 percent of Hispanic residents in the Wealthy Suburbs are of Puerto Rican origin

23. Take Account of both Race/Ethnicity and Context.

24. CHF’s Data Scan Web Page • Maps • Charts • Data • Notes

25. How to Access Data on CHF’s Data Scan Web Page • Visit www.cthealth.org • Click on “Community Health Data Scan” link (available April 2007) • Select area of interest from banner headlines • Select maps, charts or data tables from topics list • Download notes that contain definitions and caveats • Sign up to receive email notification of data updates

26. Data Scan Web Page

27. How to Use the Data Scan & Web Page • Legislative staff perspective • Use legislative district data • Use HRG level data to understand the context of disparities • Find tables that relate to a particular area of concern • Frame additional detailed requests to relevant agencies

28. How to Use the Data Scan & Web Page • Community-based organization perspective • Use HRG level data to understand needs and disparities • Find tables that relate to a particular area of concern • Explain that “rural” covers your town, if you are developing a proposal that focuses on one or more rural towns – even if your town is not named

29. Focus Area Criteria • Disparities demonstrated by the data • Within scope of study • Healthy People 2010 • Significant problems encountered in the study process • Science-based actions possible

30. Focus Area 1 • Focus on the health reference groups, and racial/ethnic groups in greatest need.The three Urban and ten Manufacturing Centers in Connecticut need the greatest health promoting investments. Within these communities, black/African American and Puerto Rican Hispanic residents may be in greatest need.

31. Focus Area 2 • Focus on diabetes and other conditions in the metabolic syndrome.Risk factors for diabetes and related conditions are prevalent in Connecticut in all populations, especially in the black/African American population.

32. Focus Area 3 • Focus on ensuring a medical home for all Connecticut residents.Overuse of emergency department (ED) care and hospital admissions could be avoided if every Connecticut resident had, and used, a primary care “medical home.” The medical home is a place to discuss prevention (e.g., child and youth risk issues, diet and physical activity).

33. Focus Area 4 • Focus on the binge drinking and smoking culture.Smoking and binge drinking are major contributors to many health problems and premature mortality. Youth and young adult white population is especially at risk and these behaviors may spread to immigrant populations as they acculturate. Increase investment in prevention by legal and educational means.

34. Focus Area 5 • Focus on youth risks and opportunities.Major youth health risks include sexually transmitted diseases, teen pregnancy, lack of use of seat belts and bicycle helmets, and child abuse. Black and Hispanic children are most at risk.

35. Focus Area 6 • Improve the health data system.State data system should address: access; customizing data for consumers; data delays; community health observations; more detail in race/ethnicity categories and multiple race options; health care quality and disparities indices; mental health data; out-of-school data; and documentation about the data.

36. SummaryUse the Data Scan to: • Generate hypotheses about health disparities • Estimate rates for individual communities, or groups of communities • Link to other sources of research about particular conditions • Develop public policy recommendations • Evaluate change over time • Use maps, charts and tables on www.cthealth.org (available April 2007)

37. Q&A • The floor is yours!

38. Acknowledgements • Thomas Cooke - Geography • Denise Castronovo - Mapping • Karen Clements – BRFSS Analysis • Martha Laugen – Research Associate • Elisa Del Bonis – Web Page Design

39. SigmaWorks Services • Community and Regional Assessment • Community Profiles • Risk Factors • Access to Care • Health Outcomes • Health Disparities • Training and Consultation in Assessment • Training in Outcomes Measurement • Training in Continuous Quality Improvement • Areas of Expertise • Health • Education • Workforce Development

40. Contact Information Larry Finison, SigmaWorks & Boston University: lfinison@bu.edu, 781.483.3901 Monette Goodrich, Connecticut Health Foundation, monette@cthealth.org, 860.224.2208