1. An Overview of Tribal Epidemiology Centers and Collaborations with State Vital Records to Improve Data Quality and Address Emerging Issues Judith Thierry, D.O., MPH, Indian Health Service Mei Lin Castor, MD, MPH, Urban Indian Health Institute Alice Park, MPH, Urban Indian Health Institute Chris Compher, MHS, United South and Eastern Tribes

2. Tribal Epidemiology Centers Tribal Epidemiology Centers (TEC) are American Indian and Alaska Native (AI/AN) programs working with Tribal entities and urban AI/AN communities by managing public health information systems, investigating diseases of concern, managing disease prevention and control programs, responding to public health emergencies, and coordinating these activities with other public health authorities

3. History of the TEC Started in 1996 Core funding from Indian Health Service (IHS) Focus to build public health capacity in AI/AN communities –AI/AN organizations with technical assistance from IHS –Identify health status objectives and services needed to achieve them Currently 11 TEC nationwide –Ten regionally focused –One nationwide-focus (urban AI/AN)

4. Authorization of TEC Public Health Activities “[Grantee] is acting under a cooperative agreement with the Indian Health Service to operate a Tribal Epidemiology Center, which is authorized by Section 214(a) (1), Public Law 94-437, Indian Health Care Improvement Act, as amended by P.L. 573. In the conduct of this public health activity, the [grantee] may collect or receive protected health information for the purpose of preventing or controlling disease, injury or disability, including, but not limited to, the reporting of disease, injury, vital events such as birth or death, and the conduct of public health surveillance, public health investigations, and public health interventions for the tribal communities that they serve. Further, the Indian Health Service considers this to be a public health activity for which disclosure of protected health information by covered entities is authorized by 45 CFR 164.512(b) of the Privacy Rule."

5. Healthcare Model for AI/AN Populations I ndian Health Service Facilities (IHS) T ribally-run Health Services U rban Indian Health Organizations (UIHO) I/T/U

8. Why Vital Statistics Data Is Essential To TEC No formal public health surveillance system exists for AI/AN Incomplete data in Indian Health Service statistics – Tribes, Urbans 125 AI/AN MCH publications, 1984-2003 Small numbers relative to general population Population-based data source National survey methods preclude analysis of AI/AN data (PRAMS, YRBS, BRFSS)

9. Current TEC Projects Using Vital Statistics Data Infant Mortality Project (USET) Emerging Issues –Maternal Alcohol Use –Infant Mortality –SIDS Factsheets Urban AI/AN Health Status Report Community Health Profiles

10. Urban AI/AN Health Status Report First National Urban Indian Health Status Report Covered Locally and Nationally in the Press Presented to White House and other government officials

11. Alcohol use during pregnancy by service areas, ten-year average, 1991-2000 Notes: Results pertain to UIHO service areas with 10 or more to births to AI/AN mothers who consumed alcohol during pregnancy. *Significant difference between rates for AI/AN and all races combined. Source: U.S. Centers for Health Statistics.

12. Infant Mortality by UIHO Service Areas Source: U.S. Centers for Health Statistics Notes: Results pertain to UIHO service areas with 10 or infant deaths to AI/AN mothers.*Significant difference between rates for AI/AN and all races combined. “Partial” refers to the inclusion of only those counties with a 1990 population of 250,000 or more. Six-year Averages, 1995-2000

13. Chronic Liver Disease Mortality by UIHO Service Areas Source: U.S. Centers for Health Statistics. Notes: Results pertain to UIHO service areas with 10 or more AI/AN deaths due to chronic liver disease. *Significant difference between rates for AI/AN and all races combined. Ten-year Averages, 1990-1999

14. Great Lakes Epidemiology Project http://www.glitc.org/epicenter/publications.html

15. GLITC Community Health Profile

17. Highlighting Collaborations California Rural Indian Health Board (California) Northern Plains Tribal Epidemiology Center (North Dakota, South Dakota, Nebraska, Iowa) Great Lakes Inter-Tribal Council (Michigan, Minnesota, Wisconsin) Alaska Native Tribal Health Consortium (Alaska)

18. California Rural Indian Health Board Receive mortality, natality, linked infant death, patient discharge [hospital], Cancer SEER, Medicaid (raw data, county/zipcode level) Ongoing data-sharing agreement Receive IHS and state data annually for linkage Racial misclassification

19. California Rural Indian Health Board Racial disparities a top priority for CRIHB and State Ongoing communication Appropriate confidentiality procedures Stable relationships Flexible fee schedule

20. Customized reports PRAMS collaboration

21. Communication, clarity and responsibility in analytic uses Taking lead in PRAMS application Relationship with other state entities using vital data BUT: –Some tribes report difficulty in accessing data from states

22. Data sharing agreements Request data annually –Birth/death file –STD/communicable disease –WIC Cost varies by state

23. Tribes good relationship with States Communication Ongoing data sharing agreements

24. Department of Public Health and EpiCenter drafting an agreement for data access to Vital Records –Death Records –Birth Records –Linked Birth/Death Records

25. Historical Background –Previous sharing, knowledge of confidentiality protocols Communication Education –Mutual Understanding of Health Department and EpiCenter Purpose and Needs

26. The Challenge(s) Vital statistics data show significant disparities between AI/AN and all race populations Socioeconomic indicators Maternal and child health Mortality Access to data Racial misclassification errors

27. Racial Misclassification and Data Quality Documented miscoding of AI/AN race Greater in urban areas No national standards Adjustments vary IHS (12%) National Center for Health Statistics (37%) Disparities found may be even greater due to these errors

28. Recommendations 1. Advocating for inclusion/identification of AI/AN in existing surveillance systems 2. Accessing data from various systems/sources 3. Assuring data quality 4. Improving relationships with other governmental agencies/ collaborating with other agencies

29. Thank you! Chris Compher ccompher@usetinc.orgccompher@usetinc.org Alice Park alicep@uihi.orgalicep@uihi.org