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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A Sporle, C Kiro, N Pearce, A Lee, D JansenIAOS 2014

The Maori preventable mortality project:

an indigenous partnership initiative.

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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

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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

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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

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Social Class

Non-MaoriMaori

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Indigenous Diversity by GeographyDifferences in:• Colonisation history• Years of contact• Social conditions• Language• Land retention• Governance• Resources

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“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?

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Needs to: • plan services• monitor outcomes

Requires information: • local• recent• high quality

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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

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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

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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

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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