1 A Sporle, C Kiro, N Pearce, A Lee, D Jansen IAOS 2014 The Maori preventable mortality project: an...
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1 A Sporle, C Kiro, N Pearce, A Lee, D Jansen IAOS 2014 The Maori preventable mortality project: an indigenous partnership initiative.
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Transcript of 1 A Sporle, C Kiro, N Pearce, A Lee, D Jansen IAOS 2014 The Maori preventable mortality project: an...
1
A Sporle, C Kiro, N Pearce, A Lee, D JansenIAOS 2014
The Maori preventable mortality project:
an indigenous partnership initiative.
2
The Context of Maori Health Development
Persistent Disparities
Intra Ethnic Variation
National Health Policies + Regional Funders
URGENTLY Need more ….• Information that is
• Accessible• MAORI focussed• Timely• LOCAL• Usable
• Flexible• Rates not just counts
• Future predictionsMaori Service Providers – local– prevention focussed
3
Persistent DisparitiesSRR Maori : NonMaori
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Year
Male Female
Rate Ratio
Source MoH 2010
4
Intra-Ethnic Variation in Outcomes
0
200
400
600
800
1000
1200
1400
1600
1-2 3 4 5 6
Am
enab
le M
orta
lity
Rat
e pe
r 10
5
Social Class
Non-MaoriMaori
5
Indigenous Diversity by GeographyDifferences in:• Colonisation history• Years of contact• Social conditions• Language• Land retention• Governance• Resources
6
“to transform Maori mortality rates
from being a measure of disparity to
being a driver for action to improve
Maori health at the local and national
levels. “
Why do this?
7
Needs to: • plan services• monitor outcomes
Requires information: • local• recent• high quality
8
Why Mortality?
Key Public Health Measure:- Good quality ethnic data- Accessible by researchers- Regional data not published
Preventability:50-60% of difference in mortality due to PREVENTABLE causes
Great EXEMPLAR for improving access and use
9
The Research Team
ResearchersAndrew Sporle – social epidemiologyAlan Lee – statistician
(Auckland)Neil Pearce - epidemiology
(LSHTM)Cindy Kiro – social policy
(Victoria)Tony Blakely - epidemiologist
(Otago Uni)Antony Raymont – health services
Maori Provider Organisation
District Health Board
Advisory GroupsStakeholders – StatsNZ, Govt. ministries, local Maori organisations
Maori Researchers
10
Research Questions
How does preventable mortality vary by:• Time• Gender• Age group / cohort• Level of preventability• REGION
Purpose:To identify the best places and ways to intervene
© Departments of Statistics, The University of Auckland S11
www.stat.auckland.ac.nz/~wild/iNZight/
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Data VisualiserSelect:
Population
Age Range
Comparison
Region
Gender
Standard Population
Projection
Male, total New Zealand, 2006
0
100
200
300
400
500
600
700
Amenable Non-amenable Total Amenable Non-amenable Total
Maori NonMaori
Age standardised rates per 100,000
Males FemalesAmenable Non-amenable Amenable Non-amenable
Māori 320.5296.7–345.7
249.0228.4–270.9
189.6172.2–208.3
197.9180.1–217.1
Non-Māori 113.6109.1–118.3
123.5118.8–128.3
63.159.8–66.5
88.384.4–92.2
Ratio 2.82 2.02 3.00 2.24Pacific 248.2
216.8–282.9216.9
187.7–249.3160.0
136.1–187.0139.5
117.5–164.5Non-Pacific 128.2
123.5–133.0133.1
128.3–137.972.4
69.0–76.097.2
93.3–101.2Ratio 1.94 1.63 2.21 1.44Asian 63.8
51.5–78.076.2
62.7–91.743.8
34.1–55.344.2
34.2–56.3Non-Asian 138.3
133.3–143.4140.5
135.6–145.678.5
74.8–82.2103.0
98.9–107.2Ratio 0.46 0.54 0.56 0.43
© Departments of Sociology and Statistics, The University of Auckland S13
Secure Data Archive
Improving Data Access
Data visualiser
Regional Funders
Maori Providers
Public AccessInterface
• Region• Gender• Age• Ref Population• Relative Risk• Confidence Ints.• Graphs and Tables
Epi MethodsProtocols
Datasets
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Project Impact in 12 months
Results:• Regional differences in data quality
• Data visualiser pilot• Too early for other results
Other Projects:- Mortality by migration
and age cohort- Longitudinal mortality
study
Student placements with providers:
Teaching• Community• Providers• Students
Networks• Data users• Maori researchers
15
Maori Wellbeing Research
Independent Maori Statutory BoardMaori Development Plan• Maori Values• Key Directions• Domains and Focus Areas• Maori Outcomes• Indicator wish list
© Departments of Statistics, The University of Auckland S16
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The Future ?Improving responsive of official statistics leads to- Increased use- Improved perception- Improved quality- New ideas
If there is data – then make it available and useable
