An Overview of Tribal Epidemiology Centers and Collaborations with State Vital Records to Improve Data Quality and Addre

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) Started in 1996 (Indian Health Care Improvement Act) Core funding from IHS Build Tribal Capacity Tribal organizations with technical assistance from IHS Identify health status objectives and the services needed to achieve them Currently 11 EpiCenters Started in 1996 (Indian Health Care Improvement Act) Core funding from IHS Build Tribal Capacity Tribal organizations with technical assistance from IHS Identify health status objectives and the services needed to achieve them Currently 11 EpiCenters

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." TEC acting as public health authorities on behalf of IHS.TEC acting as public health authorities on behalf of IHS.

5. Healthcare Model for AI/AN Populations IHS data systems only cover IHS facilities. Data on tribes and urbans is missing.IHS data systems only cover IHS facilities. Data on tribes and urbans is missing.

7. MAP OF TEC AREAS HEREMAP OF TEC AREAS HERE

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) No public health surveillance system exists for AI/AN � often overlooked by state health departments and not all included in IHS stats. Only 125 maternal child health studies focused on AI/AN between 1984-2003 Analysis of AI/AN MCH Literature Medline Search: Years: 1984-2004; Keywords: Native American, American Indian, Alaska Native in conjunction with pregnancy and other infant related terms This included IHS and vital record report publications Small numbers to monitor the AI/AN population Population based data source National survey methods precludes analysis of AI/AN data (PRAMS, YRBS, BRFSS) - sample size too small to allow for county or even state analysis for AI/AN.No public health surveillance system exists for AI/AN � often overlooked by state health departments and not all included in IHS stats. Only 125 maternal child health studies focused on AI/AN between 1984-2003 Analysis of AI/AN MCH Literature Medline Search: Years: 1984-2004; Keywords: Native American, American Indian, Alaska Native in conjunction with pregnancy and other infant related terms This included IHS and vital record report publications Small numbers to monitor the AI/AN population Population based data source National survey methods precludes analysis of AI/AN data (PRAMS, YRBS, BRFSS) - sample size too small to allow for county or even state analysis for AI/AN.

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 Infant Mortality Project (Nashville) The purpose of this project is to identify prenatal factors that may influence infant death.� Prenatal indicator data is obtained on all AI/AN pregnancies within the IHS Nashville Service Area from OB/GYN medical records.� Vital records data is used to identify deceased infants and their causes of death.� Death Certificate data is collected on all infant deaths within the IHS Nashville Service Area and linked to the OB/GYN medical record data to elucidate factors associated with infant death.���� Emerging Issues Vital statistics data has been used to identify emerging health issues. Maternal alcohol use among AI/AN in the Bemidji area was considerably higher compared to the rest of the nation. AI/AN infant mortality rate in the Seattle/King County area is significantly higher than the general population rate, and has prompted a case review. Likewise, high AI/AN infant mortality rate was documented in the Aberdeen area, and specifically, SIDS rates also found to be extremely high in Aberdeen area. This has strengthened collaborative efforts to determine underlying causes of elevated mortality rates and efforts to reduce infant mortality rate in the Aberdeen area. Vital statistics has also been used to develop area-specific factsheets, which community members may use to identify priority health issues in their area. Urban AI/AN Health Status Report � natality, mortality and linked infant deaths Infant Mortality Project (Nashville) The purpose of this project is to identify prenatal factors that may influence infant death.� Prenatal indicator data is obtained on all AI/AN pregnancies within the IHS Nashville Service Area from OB/GYN medical records.� Vital records data is used to identify deceased infants and their causes of death.� Death Certificate data is collected on all infant deaths within the IHS Nashville Service Area and linked to the OB/GYN medical record data to elucidate factors associated with infant death.���� Emerging Issues Vital statistics data has been used to identify emerging health issues. Maternal alcohol use among AI/AN in the Bemidji area was considerably higher compared to the rest of the nation. AI/AN infant mortality rate in the Seattle/King County area is significantly higher than the general population rate, and has prompted a case review. Likewise, high AI/AN infant mortality rate was documented in the Aberdeen area, and specifically, SIDS rates also found to be extremely high in Aberdeen area. This has strengthened collaborative efforts to determine underlying causes of elevated mortality rates and efforts to reduce infant mortality rate in the Aberdeen area. Vital statistics has also been used to develop area-specific factsheets, which community members may use to identify priority health issues in their area. Urban AI/AN Health Status Report � natality, mortality and linked infant deaths

10. Urban AI/AN Health Status Report

11. Alcohol use during pregnancy by service areas, ten-year average, 1991-2000

12. Infant Mortality by UIHO Service Areas Data limited to counties with 1990 population >250,000. Only data for 12 UIHO, partial data for 3 of these.Data limited to counties with 1990 population >250,000. Only data for 12 UIHO, partial data for 3 of these.

13. Chronic Liver Disease Mortality by UIHO Service Areas

14. Community Health Profiles � required by all TEC in the next grant cycle to do CHPs Community Health Profiles � required by all TEC in the next grant cycle to do CHPs

15. GLITC Community Health Profile Used to track trends over time.Used to track trends over time.

16. GLITC Community Health Profile GLITC provides tribal-specific community profiles on a semi-annual basis (versus annually for the Three-State Version), using the counties that IHS identifies for each tribe to be within their Contract Health Service Delivery Area (CHSDA) and it is those county-groupings that we use for the tribal-specific CHPs.� We compare county AI/AN rates to county All Race rates as well as the state AI/AN and State All Race whenever possible to provide context for the tribes within the broader scope of the statewide data. GLITC provides tribal-specific community profiles on a semi-annual basis (versus annually for the Three-State Version), using the counties that IHS identifies for each tribe to be within their Contract Health Service Delivery Area (CHSDA) and it is those county-groupings that we use for the tribal-specific CHPs.� We compare county AI/AN rates to county All Race rates as well as the state AI/AN and State All Race whenever possible to provide context for the tribes within the broader scope of the statewide data.

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) Add sentence regarding vital statistics dataAdd sentence regarding vital statistics data

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 Receiving county and zipcode-level data, even geocoded births file. Have ongoing data-sharing agreement Receive data annually Working on correcting high racial misclassification rate � 30-70% misclassification, mainly as white.Receiving county and zipcode-level data, even geocoded births file. Have ongoing data-sharing agreement Receive data annually Working on correcting high racial misclassification rate � 30-70% misclassification, mainly as white.

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 Top priority for CRIHB and State- State mandate to respond to racial disparities Communication-Send back reports & publications, know data is being used, give state opportunity to edit & review, acknowledgements Appropriate confidentiality procedures-know CRIHB very conscientious about working with confidential info & will handle data responsibly, history of working on California Health Interview Survey, which deals with small numbers too. Stable relationships-Same 1 person at State and same 1 person at CRIHB since 1998 Flexible fee schedule-Realize that TEC is underfunded, will forward data but flexible about receipt of payment GET INFO ON DATASHARING AGREEMENT FROM CAROLTop priority for CRIHB and State- State mandate to respond to racial disparities Communication-Send back reports & publications, know data is being used, give state opportunity to edit & review, acknowledgements Appropriate confidentiality procedures-know CRIHB very conscientious about working with confidential info & will handle data responsibly, history of working on California Health Interview Survey, which deals with small numbers too. Stable relationships-Same 1 person at State and same 1 person at CRIHB since 1998 Flexible fee schedule-Realize that TEC is underfunded, will forward data but flexible about receipt of payment GET INFO ON DATASHARING AGREEMENT FROM CAROL

20. Customized reports PRAMS collaboration Customized reports Used to receive data from IHS, but IHS lost funding for staff Submit table shells, and receive back populated table shells or output to fill the tables from State. No data sharing agreement required. Would like to work towards receiving raw data in the future, would require data-sharing agreement PRAMS South Dakota State-wide Tribal PRAMS Point-in-Time Project. Tribal PRAMS will provide for larger AI/AN sample & higher response rate [through monthly mailing (vs. one batch) and tribal field staff support in data collection] Lead applicant is tribe, all tribes in SD supported proposal, collaboration between tribes, TEC, State DOH and other partners Shared protocol and methodology w/N Dakota and Nebraska PRAMS; potential collaboration with MN TEC took lead in preparing PRAMS application. Went directly to Secretary of Health to propose the project. Outlined exactly what is expected from the State Talked with the Division heads. Requires collaboration with the State vital records division that maintains birth, fetal demise, and infant death data for all state residents. Customized reports Used to receive data from IHS, but IHS lost funding for staff Submit table shells, and receive back populated table shells or output to fill the tables from State. No data sharing agreement required. Would like to work towards receiving raw data in the future, would require data-sharing agreement PRAMS South Dakota State-wide Tribal PRAMS Point-in-Time Project. Tribal PRAMS will provide for larger AI/AN sample & higher response rate [through monthly mailing (vs. one batch) and tribal field staff support in data collection] Lead applicant is tribe, all tribes in SD supported proposal, collaboration between tribes, TEC, State DOH and other partners Shared protocol and methodology w/N Dakota and Nebraska PRAMS; potential collaboration with MN TEC took lead in preparing PRAMS application. Went directly to Secretary of Health to propose the project. Outlined exactly what is expected from the State Talked with the Division heads. Requires collaboration with the State vital records division that maintains birth, fetal demise, and infant death data for all state residents.

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 Communication, clarity and responsibility in analytic uses Taking lead in PRAMS application Relationship with other state entities using vital data-Department of Family Health, etc. BUT: Some tribes report difficulties accessing data from states � perhaps due to mutual lack of trust on both sides, lack of clarity in data requests, staff issues in filling customized data requests, expectation that tribes should get data from IHS Not all states � some are unresponsive, some are very responsiveCommunication, clarity and responsibility in analytic uses Taking lead in PRAMS application Relationship with other state entities using vital data-Department of Family Health, etc. BUT: Some tribes report difficulties accessing data from states � perhaps due to mutual lack of trust on both sides, lack of clarity in data requests, staff issues in filling customized data requests, expectation that tribes should get data from IHS Not all states � some are unresponsive, some are very responsive

22. Data sharing agreements Request data annually Birth/death file STD/communicable disease WIC Cost varies by state Written agreements established in last 5 years for HIPAA compliance. General protocol each year to key contacts in each state to request data No cost from some states MN free MI low cost WI expensive, only purchase AI/AN records since you pay by record. Use reports and website to pull all races data. Written agreements established in last 5 years for HIPAA compliance. General protocol each year to key contacts in each state to request data No cost from some states MN free MI low cost WI expensive, only purchase AI/AN records since you pay by record. Use reports and website to pull all races data.

23. Tribes good relationship with States Communication Ongoing data sharing agreements Historically, tribes had good relationship with States Communication When TEC established, went to state vital records folks and talked with them about access to their data and benefit to tribes. Send copies of reports, TEC newsletter Ongoing data sharing agreements, renew as needed. Historically, tribes had good relationship with States Communication When TEC established, went to state vital records folks and talked with them about access to their data and benefit to tribes. Send copies of reports, TEC newsletter Ongoing data sharing agreements, renew as needed.

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 Showed significant disparities between the AI/AN population and the all race population. These disparities were in socioeconomic indicators, maternal and child health, and mortality. Despite the likely misclassification errors, the health disparities found were still substantial. Showed significant disparities between the AI/AN population and the all race population. These disparities were in socioeconomic indicators, maternal and child health, and mortality. Despite the likely misclassification errors, the health disparities found were still substantial.

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 Identified disparities are �tip of the iceberg� Racial misclassification compromises data quality. We know that it happens. There has been documented miscoding of AI/AN race on vital statistics and other records. Unfortunately, there are no national standard hence variability in how race is coded across the country. Because of the small sample sizes, this creates real challenges for studying this. There are adjustments for errors that are used but they do vary from 12 to 37%. Why is the HIS so low? Chris will check w/Joann on thisIdentified disparities are �tip of the iceberg� Racial misclassification compromises data quality. We know that it happens. There has been documented miscoding of AI/AN race on vital statistics and other records. Unfortunately, there are no national standard hence variability in how race is coded across the country. Because of the small sample sizes, this creates real challenges for studying this. There are adjustments for errors that are used but they do vary from 12 to 37%. Why is the HIS so low? Chris will check w/Joann on this

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.org Alice Park alicep@uihi.org