an overview of tribal epidemiology centers and collaborations with state vital records to improve...
TRANSCRIPT
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 ServiceMei Lin Castor, MD, MPH, Urban Indian Health Institute
Alice Park, MPH, Urban Indian Health InstituteChris Compher, MHS, United South and Eastern Tribes
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
History of the TEC
Started in 1996Core 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)
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."
Healthcare Model for AI/AN Populations
Indian Health ServiceFacilities (IHS)
Tribally-run Health Services
Urban Indian Health Organizations(UIHO)
I/T/U
American Indian and Alaska Native Population* By Statewith Tribal Epidemiology Centers
* Census 2000, One race (AI/AN) alone
MA
RI
CT
ME
NJ
DEMD
= IHS Division of Epi
= Tribal Epi Centers
WA
OR
CA
NV
ID
MT
WY
UTCO
AZ
TX
OK
ND
KS
NE
SD
AR
MO
IA
MN
GA
TN
MS AL
LA
MI
OHINIL
WI
FL
PA
VA
NY
WV
NC
KY
SC
AK
NHVT
HI
NM
ANTHCEpi Center
CRIHBEpi Center
ITCAEpi Center
NPAIHBEpi Center
SIHBEpi Center
NPEpi Center
NNDOHEpi Center
USETEpi Center
GLITCEpi Center
OKCAITHBEpi Center
AI/AN Population by State, 2000
100,00 to 333,40050,000 to 99,999
10,000 to 49,999
1,713 to 9,999
M/W TLCEpi Center
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, 1984-2003Small numbers relative to general population
Population-based data source
National survey methods preclude analysis of AI/AN data (PRAMS, YRBS, BRFSS)
Current TEC Projects Using Vital Statistics Data
Infant Mortality Project (USET)Emerging Issues– Maternal Alcohol Use– Infant Mortality– SIDS
FactsheetsUrban AI/AN Health Status ReportCommunity Health Profiles
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
Alcohol use during pregnancy by service areas, ten-year average, 1991-2000
AI/AN: UIHO Total(5.18%)AI/AN: US TOTAL
(4.62%)
0
5
10
15
20
25
New
Yo
rk N
Y
Dal
las
TX
Fla
gst
aff
AZ
Ch
icag
o I
L
Ren
o N
V
Det
roit
MI
Sal
t L
ake
Cit
y U
T
Tu
cso
n A
Z
Alb
uq
uer
qu
e N
M
Sp
oka
ne
WA
Den
ver
CO
US
TO
TA
L
Ph
oen
ix A
Z
Po
rtla
nd
OR
Bil
lin
gs
MT
UIH
O T
ota
l
Mil
wau
kee
WI
Lin
coln
NE
Sea
ttle
WA
Gre
en B
ay W
I
Min
nea
po
lis
MN
% o
f L
ive
Bir
ths
All RacesAI/AN
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.
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.
0
5
10
15
20
25L
os
An
gel
es C
A
Oak
lan
d C
A (
Par
tial
)
Tu
cso
n A
Z
Den
ver
CO
(P
arti
al)
Ph
oen
ix A
Z
Alb
uq
uer
qu
e N
M
UIH
O T
ota
l (P
arti
al)*
US
TO
TA
L*
San
Die
go
CA
Sea
ttle
WA
*
Fre
sno
CA
(P
arti
al)
Milw
auke
e W
I
Min
nea
po
lis M
N*
Ch
icag
o IL
*
Ra
te p
er
1,0
00 L
ive
Bir
ths
All RacesAI/AN
UIHO - AI/AN: 8.8
US - AI/AN: 8.9
Six-year Averages, 1995-2000
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.
0
10
20
30
40
50
60
70
80
90
New
Yo
rk N
Y*
Dal
las
TX
Fre
sno
CA
Lo
s A
ng
eles
CA
Sac
ram
ento
CA
Oak
lan
d C
A
Ch
icag
o IL
San
Die
go
CA
*
Fla
gst
aff
AZ
*
US
TO
TA
L*
Den
ver
CO
*
UIH
O T
ota
l*
Wic
hit
a K
S*
Det
roit
MI*
Sal
t L
ake
Cit
y U
T*
Milw
auke
e W
I*
Po
rtla
nd
OR
*
Bill
ing
s M
T*
Ren
o N
V*
Sea
ttle
WA
*
Alb
uq
uer
qu
e N
M*
Min
nea
po
lis M
N*
Sp
oka
ne
WA
*
Lin
coln
NE
*
Gre
en B
ay W
I*
Ph
oen
ix A
Z*
Tu
cso
n A
Z*
20
00
Ag
e-A
dju
ste
d R
ate
pe
r 1
00
,00
0 P
ers
on
s
All RacesAI/AN
UIHO - AI/AN: 27.5US - AI/AN: 25.5
Ten-year Averages, 1990-1999
Great Lakes Epidemiology Project
http://www.glitc.org/epicenter/publications.html
GLITC Community Health Profile
Graph 4.5 Smoking During Pregnancy in XX, 1991-2000
40
42
44
46
48
50
52
54
56
91-93 92-94 93-95 94-96 95-97 96-98 97-99 98-00
Years
Per
cen
t
Smoked
Non Smoked
GLITC Community Health ProfileGraph 2.1
Top Five Causes of Death by Percent of Total Deaths in XX, 1991-2000
23
20
12
7
4
2423
4 4 4
0
5
10
15
20
25
30
Heart Disease Cancer Unintentionalinjury
Diabetes Stroke
Underlying Cause of Death
Per
cen
t
County AI/AN
State All Races
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)
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
California Rural Indian Health Board
Racial disparities a top priority for CRIHB and State
Ongoing communication
Appropriate confidentiality procedures
Stable relationships
Flexible fee schedule
Customized reports
PRAMS collaboration
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
Data sharing agreements
Request data annually– Birth/death file– STD/communicable disease– WIC
Cost varies by state
Tribes good relationship with States
Communication
Ongoing data sharing agreements
Department of Public Health and EpiCenter drafting an agreement for data access to Vital Records – Death Records– Birth Records– Linked Birth/Death Records
Historical Background– Previous sharing, knowledge of confidentiality
protocols
Communication
Education– Mutual Understanding of Health Department
and EpiCenter Purpose and Needs
The Challenge(s)
Vital statistics data show significant disparities between AI/AN and all race populationsSocioeconomic indicatorsMaternal and child healthMortality
• Access to data• Racial misclassification errors
Racial Misclassification and Data Quality
Documented miscoding of AI/AN race Greater in urban areas
No national standardsAdjustments varyIHS (12%) National Center for Health
Statistics (37%)Disparities found may be even greater due to these errors
Recommendations
1. Advocating for inclusion/identification of AI/AN in existing surveillance systems
2. Accessing data from various systems/sources3. Assuring data quality4. Improving relationships with other governmental
agencies/ collaborating with other agencies
