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The health of Indigenous Australians is poor compared to that of their counterpart Australians. Further, their health is worse by international standards. The Australian Government recently made a commitment to improving the health status of Indigenous Australians through the 'closing the health gap' initiative. Achieving this requires an improvement in the priority setting process through the use of evidence. Central to this is the need for a concept of 'benefit' from services that reflects the needs and aspirations of Indigenous Australians. The purpose of this paper is to develop an Indigenous-specific health metric that captures individual and community benefits for improving the priority setting process. A workshop-based approach identified four dimensions of benefit in Indigenous health: individual health gain, community health gain, equity and cultural security. The individual health gain dimension accounted for 42 per cent of the total perceived benefit from health care interventions, while the remaining three dimensions each weighted between 19 per cent and 21 per cent. The individual health gain had two sub-dimensions: a DALY consistent attribute and a non-DALY attribute. The DALY attributes were by far the most influential, but while the DALY as a measure of health gain in economic evaluation is desirable, alone it grossly underestimates the overall benefit from interventions in Indigenous health. © 2015, Australian Institute of Aboriginal and Torres Strait Islander Studies. All rights reserved.
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30 Australian Aboriginal Studies 2015/1
What constitutes benefit from health care interventions
for Indigenous Australians?
Michael E Otim
Australian Catholic University
Augustine D Asante
University of New South Wales
Margaret Kelaher
The University of Melbourne
Chris M Doran
The University of Newcastle
Ian P Anderson
The University of Melbourne
Abstract: The health of Indigenous Australians is poor compared to that of their
counterpart Australians. Further, their health is worse by international standards.
The Australian Government recently made a commitment to improving the health
status of Indigenous Australians through the ‘closing the health gap’ initiative.
Achieving this requires an improvement in the priority setting process through the
use of evidence. Central to this is the need for a concept of ‘benefit’ from services
that reflects the needs and aspirations of Indigenous Australians. The purpose of
this paper is to develop an Indigenous-specific health metric that captures individ-
ual and community benefits for improving the priority setting process.
A workshop-based approach identified four dimensions of benefit in Indigenous
health: individual health gain, community health gain, equity and cultural secu-
rity. The individual health gain dimension accounted for 42 per cent of the total
perceived benefit from health care interventions, while the remaining three dimen-
sions each weighted between 19 per cent and 21 per cent. The individual health gain
had two sub-dimensions: a DALY consistent attribute and a non-DALY attribute.
The DALY attributes were by far the most influential, but while the DALY as a
measure of health gain in economic evaluation is desirable, alone it grossly under-
estimates the overall benefit from interventions in Indigenous health.
Australian Aboriginal Studies 2015/1 31
Otim et al. What cons titutes benefit from health care interventions?
In Australia the health of Indigenous peoples is
poor by both Australian and international stand-
ards (ABS and AIHW 2010; CSDH 2008; Gracey
and King 2009; Kunitz and Brady 1995; Marmot
2005; NHMRC 2010). About three per cent of
Australia’s population are Indigenous and more
than half of them live in rural and remote areas.
In 2006 Indigenous people comprised one per cent
of the population in major cities, three per cent in
inner regional areas, six per cent in outer regional
areas, 15 per cent in remote areas and 49 per
cent in very remote areas (Baxter et al. 2011).
Like other Australians living in rural and remote
areas, Indigenous Australians are generally disad-
vantaged in terms of access to and utilisation of
health care services due to location and sociocul-
tural factors (AIHW 2008, 2014). Coupled with
Indigenous-specific health disadvantage, such as
higher levels of illness and disease risk factors, as
well as historical and institutional factors, improv-
ing the health of Indigenous Australians becomes
an urgent issue (COAG 2009; SCRGSP 2009).
The Australian Government has made a
commitment to raising the health status of
Indigenous Australians to a comparable level with
non-Indigenous Australians through the ‘closing
the health gap’ initiative (COAG 2009). Achieving
this requires improved processes of priority setting
in Indigenous health. Such a process requires the
development of explicit guidelines that draw on
knowledge from normative economics and social
justice theory, as well as lessons from empiri-
cal studies and the literature (Otim, Jayasinha,
Kelaher et al. 2015). This would likely improve
the priority setting process in Indigenous commu-
nities in Australia and beyond. Such guidelines
may be based on the size of the health burden,
feasibility, sustainability, equity and acceptability
of health interventions (Otim et al. 2014). These
guidelines can be applied to assess a selection
of priority setting frameworks such as Program
Budgeting and Marginal Analysis (PBMA),
Multi-Criteria Decision Analysis (MCDA) or the
Quality-Adjusted Life Years (QALYs) for suitabil-
ity for use in the Indigenous health sector.
There has been growing recognition in recent
years of the PBMA framework as the most appro-
priate and acceptable framework for priority
setting (Otim, Asante et al. 2015), largely because
of its ability to uphold both economic and social
justice principles. The due process aspect of
PBMA, in particular, is consistent with Aboriginal
values (AIATSIS 2000; Novak 2000; Synott
2003). However, PBMA results are dependent on
the concept of benefit when being used as a prior-
ity setting tool. For example, the PBMA approach
would need evidence on ‘value for money’ from
interventions as demonstrated by an economic
appraisal so as to maximise returns from invest-
ments (Ham and Coulter 2000; Otim, Asante et
al. 2015).
Central to the concept of ‘value for money’ is
what constitutes benefit from an intervention. In
Indigenous health where ‘health’ is not just the
absence of disease but is broader, and benefit
is not just individual health gain (AIHW 2004;
Joint Planning Forum 2000; NAHSWP 1989;
NATSIHC 2003a, 2003b), the concept of bene-
fit is broader than what is currently used inter-
nationally and by Australian institutions for
priority setting purposes.
The World Health Organization (WHO) has
promoted Disability-Adjusted Life Years (DALYs)
as the measure of benefit from health care inter-
ventions for priority setting in developing coun-
tries (WHO 2008, 2009). Likewise, Australian
institutions, such as the Australian Institute
of Health and Welfare and Australian Bureau
of Statistics, use mortality, morbidity, quality of
life studies, prevalence and/or DALYs as the key
measures of health outcomes and hence benefit
from interventions, as shown in several studies
(AIH W 2014; Vos et al. 2009; Zhao et al. 2004).
However, no measures exist that capture non-
medical benefits from health care interventions.
The continuing lack of data on Indigenous QALYs
means that the use of DALYs, for now at least, is
the most plausible outcome measure in the eval-
uation of Indigenous health care interventions
(Robbertstad 2005; Vos et al. 2009; Zhao et al.
2004). However, concepts of health and illness
are subjective and are influenced by different
contexts and perspectives (Varey 2008). Further,
using different theoretical approaches such
as social representations, mental and cultural
models, and subjective or lay theories can lead to
different understandings of health. Thus what is
‘normal’ life and people’s experiences of a specific
32 Australian Aboriginal Studies 2015/1
What cons titutes benefit from health care interventions? Otim et al.
disease are likely to affect the definition of health
for each context (Flick 2003). Health is therefore
defined from an operational perspective in this
paper, because these definitions are meant to aid
the development of an Indigenous metric to assess
health gain.
The concept of Indigenous health
To identify the concept of Indigenous health
from an operational perspective, we reviewed
a selection of international literature focusing
on Australia, New Zealand, the United States
of America and Canada. The literature revealed
that Indigenous scholars, community represent-
atives and government agencies in those coun-
tries view Indigenous health as a holistic issue.
The dimensions of health therefore would include
both physical health and non-physical health,
such as equity, emotional health, socioeconomic
and sociocultural factors, spiritual health and
cultural security, albeit from different perspec-
tives and in different contexts (Houston 2003;
Henry 2004; Otim et al. 2014; Peacock et al.
1997; Starfield 2001; Tito and Kavanagh 2004).
Thus dimensions of health could include both
individual and community-wide benefits, often
with a ‘cultural safety’ or ‘cultural security’ over-
lay, involving language, family formation, social
support and networking, civic participation and
land. For some authors, good health is seen as
enhancing personal empowerment and promoting
more effective and meaningful pathways to self-
determination for Indigenous people.
The focus of this study is on improving the
concept of benefit so as to improve priority
setting in Australian Indigenous health. We used
the 1989 National Aboriginal Health Strategy
(NAHS) definition of health to conceptualise
health, which is similar to the WHO definition of
health as enshrined in the Alma Ata declaration
in Primary Health Care (WHO 1978). The NAHS
defines health as:
not just the physical wellbeing of an individ-
ual but…the social, emotional and cultural
well-being of the whole community in which
each individual is able to achieve their full
potential thereby bringing about the total
well-being of the whole community. It is a
whole-of-life view and includes the cyclical
concept of life-death-life. (NAHSWP 1989)
This definition suggests that to Indigenous
Australians, just like other Indigenous peoples
elsewhere, health is more than just the absence of
diseases. The concept of benefit from Indigenous
interventions involves medical and non-medical
outcomes. The challenge is how to conceptualise
and measure such benefit. In practice, DALY is
often used. However, the DALY as a measure of
benefit from interventions has increasingly come
under scrutiny. The major criticism in the litera-
ture involves its failure to capture the multifac-
eted aspects of health (Anand and Hanson 1997;
Arnesen and Kapiriri 2004).
Indeed, in a recent study on Assessing Cost-
Effectiveness in Prevention (ACE-Prevention)
funded by a five-year Health Services Research
Grant from Australia’s National Health and
Medical Research Council (Carter et al. 2008;
Vos et al. 2010), the use of DALYs as a bene-
fit measure in the evaluation of Indigenous
health interventions came under scrutiny by the
ACE-Prevention Indigenous Steering Committee
(ISC). The ISC argued that the DALY is not
adequate in capturing wider non-health benefits
important in Indigenous health for economic eval-
uation purposes in Indigenous health. In spite of
the fact that data on DALYs were the only avail-
able data in Indigenous health, the ISC members
argued that several options exist that can be used
to improve the concept of benefit in Indigenous
health for priority setting purposes. One option
involved developing an entirely new metric for
measuring benefit.
Option one involved applying the standard
ACE methods, which involve assessing bene-
fit using DALYs, so as to allow comparability of
Indigenous outcomes and non-Indigenous ones
and then subjecting those results to second-stage
filters in an ex-post manner. These filters included
‘equity’, ‘community health gain’, ‘cultural secu-
rity’, ‘feasibility of implementation’, ‘acceptability
to stakeholders’ and ‘strength of evidence’. In this
option, models developed for the general popula-
tion could be adapted by using Indigenous DALYs
through Indigenous participation and adherence
rates, appropriate costing templates (Ong et al.
Australian Aboriginal Studies 2015/1 33
Otim et al. What cons titutes benefit from health care interventions?
2009) for remote areas and adding additional
second-stage filters.
Option two involved adopting option one plus
weighting the DALY for equity to allow compara-
bility of outcomes, and then considering further
second-stage filters. However, in attaching equity
weights to benefits, one is confronted by several
challenges, including how to value health gains.
For example, should one year gained by an
Indigenous person be valued as the same or higher
than a year gained by a non-Indigenous person,
considering the generally poorer health status
of Indigenous people? This and other challenges
illustrate the practical difficulties associated with
priority setting due to different health interven-
tions across Indigenous and non- Indigenous
population groups (Mooney 1996).
Option three involved developing an entirely
new Indigenous-specific health metric. Several
methods could be used to capture the multifac-
eted dimensions of health, including options
appraisal, multi-attribute utility (MAU), conjoint
analysis, discrete choice experiments and many
others (Jia et al. 1998; Keeney and Raiffa 1993;
Peacock et al. 2007; Weber et al. 1988). In this
study we focused on option three as guided by the
ISC. The purpose therefore was to assess whether
and how to develop a new Indigenous-specific
health metric that could potentially capture indi-
vidual and community benefits to improve prior-
ity setting. The objectives involved identifying
and measuring the dimensions of Indigenous
health, and weighting and aggregating the dimen-
sions to form the health metric. Ethics approval
for the research was obtained from The University
of Melbourne Ethics Research Committee.
A workshop-based MAU approach was used in
this study because of its recent successful appli-
cation in the Indigenous health context in South
Australia and its ability to allow Indigenous
peoples to participate in the exercise (Peacock
et al. 2007). It is acknowledged that there are
many possible ways to do each of the above steps
and, if it had been done differently, it is possible
that different results could have been obtained.
MAU is a variant of options appraisal tech-
nique and is based on decision analysis drawn
from the disciplines of psychology and economics.
It uses decision analytic techniques to model and
quantify attributes in the decision maker’s objec-
tive function. The MAU involves key methodo-
logical steps, described in the subsequent sections,
which include (Peacock et al. 2007):
1. identifying and describing dimensions of
2. calibrating and weighting dimensions to a
3. aggregating them to obtain a single unit of
The rest of this paper describes what was done
and how the workshops were conducted.
The workshops
Four workshops composed of 10–15 Indigenous
health experts per workshop were conducted
between 2006 and 2008. The experts were
mainly members of the ACE-Prevention ISC and
others were from the Indigenous community.
The ISC membership comprised ACE-Prevention
chief investigators, Indigenous representatives,
leaders in research and health services manage-
ment, and Australian Government representa-
tives. They were purposively selected from the
ACE-Prevention project and the Cooperative
Research Centre for Aboriginal Health. With the
help of an Aboriginal Elder as a facilitator,
the experts identified dimensions of health in
workshop one, and then described these dimen-
sions in workshop two, followed by email confir-
mations of workshop two results and feedback.
In workshop three the ACE investigators and
researchers discussed methodological issues,
given the political climate that was surrounding
Indigenous communities (Australian Government
intervention in Indigenous communities) after the
publication of a national report into child abuse.
In workshop four the weighting of the dimensions
was undertaken.
Identifying and describing dimensions
A draft list of dimension attributes and descrip-
tors, generated from the literature, was presented
to the workshop participants to guide the discus-
sion. Dimension attributes or descriptors of the
dimensions were carefully discussed by the work-
shop participants so that all members shared a
common understanding of the meaning of each
dimension to generate a shared understanding of
34 Australian Aboriginal Studies 2015/1
What cons titutes benefit from health care interventions? Otim et al.
what constitutes benefit. However, given the need
for a common metric in order to avoid method-
ological confounding, data tractability and rele-
vance, DALY descriptors were retained. These
descriptors served as reference points to identify
other dimensions of health that are not captured
by the DALY.
Calibrating and weighting dimensions to a scale
To calibrate the dimensions and to determine the
relative importance or weights of each dimen-
sion (attribute weights), a Visual Analogue Scale
(VAS) was used. VAS is a simple graphical repre-
sentation of preferences, akin to a thermometer
that respondents can mark to indicate their pref-
erences. It can also be used to assign a numerical
value to a certain health state based on cogni-
tive reflection rather than hypothetical trade-off
scenarios. It is a practical method, with less cogni-
tive burden for eliciting preferences (Brazier et al.
1999; Green et al. 2000).
The MAU used a VAS scaling instrument simi-
lar to a thermometer (0% to 100%), with the high-
est point (best health state) described as ‘full health’
and equivalent to 100%, and the lowest point or
worst case as ‘dead’/‘persistent vegetative state’
(0%). Participants further described and discussed
three other intermediate states that corresponded
to the 25%, 50% and 75% scores on the thermom-
eter. These descriptors provided a clearer under-
standing of each dimension and guidance on the
different levels of benefit that could occur.
However, assigning attribute weights can be
affected by ‘preference uncertainty’ (Peacock
et al. 2007), which occurs when weights elicited
at one time differ from those elicited later, due to
response error associated with framing effects or
delayed judgement making (Jia et al. 1998; Weber
et al. 1988). Thus how the question is asked may
influence the answer that a respondent gives.
The disutility of a move from equity, for exam-
ple, at its best to its worst level, is often greater
than the utility of a move in the opposite direc-
tion. This could be a sign that respondents placed
greater importance on the specific dimension in
the context of reductions to services than in the
context of expansions to services. This accords
with the political reality that decision makers and
stakeholders attach different weights to service
reductions and expansions.
Different approaches exist for addressing pref-
erence uncertainty, none of which are perfect due
to myriad psychological biases that come into
play in any decision task, and these may include
conjoint analysis, corner point value assessment,
trade-off weights, consensus building and swing
weights (Jia et al. 1998; Weber et al. 1988). Given
the many dimensions of Indigenous health, we
again decided to use VAS for its simplicity, poten-
tial cost savings and high rate of completion, and
for being a reliable technique with good levels of
consistency of response with a priori preferences
(Brazier et al. 1999; Green et al. 2000; Peacock
et al. 2007).
Aggregating dimensions: bringing all the
components together
There are two broad methods for aggregat-
ing dimension scores in health: multiplicative
and additive approaches (Peacock et al. 2007).
The weighted dimension scores are combined to
obtain the total benefit score for the intervention.
The combination of the scores would be influ-
enced by the nature of the societal preference.
Additive model: It is important to note that the
additive approach assumes that interventions have
value, even if they score zero on any one dimen-
sion. Given that the underlying principle of health
care provision is to yield health improvements
for individuals, this property of the model may
be highly undesirable in non-Indigenous health
care (Green et al. 2000; Peacock et al. 2007).
In Indigenous health, where social determinants
of health are the focus for investments, it is the
preferred model.
In theory, an additive approach would be aggre-
gated using the following assumptions: individual
health gain (H) lies on a 0 –100 scale, and total
combined benefit is a sum of weighted individual
scores. Thus the simple additive model involves a
combined benefit score for a given health service,
and is the sum of the weighted scores for each
dimension of benefit. Total benefit score (B) is
given by:
B = wH H + w1D1 + …+ wn Dn
Where: B is the combined benefit score;
wH is the weight on IHG; and
w1, … , wn are the weights on the other 1, … ,
n dimensions of benefit.
Australian Aboriginal Studies 2015/1 35
Otim et al. What cons titutes benefit from health care interventions?
Multiplicative model: the multiplicative model
applies multiplicative weights to the dimensions of
benefit from health care interventions. Individual
health gain (IHG) is weighted by the importance
of, and scores for, each of the other dimensions of
benefit when a service is evaluated. The model is
given by Edwards et al. 1998 and Peacock et al.
20 07:
B = [1+ wi d1 + …. + wn dn ] BH
d1 = the score for dimension i on a 0 –1 scale
(i.e. D1 /100) (for a given service); and
BH = the score placed on individual health
gain (for a given service)
wi = w1, … , wi are the weights on the other 1,
… , i dimensions of benefit.
Adopting a multiplicative model suggests that for
an intervention to be effective, its score on IHG
must not be zero. In this study, the workshop
members were to make the choice between addi-
tive and multiplicative models.
Identifying and defining dimensions of benefit
Four key dimensions of benefit were identified
based on the definition of health used in the 1989
National Aboriginal Health Strategy (NAHSWP
1989) as a starting point. They were individual
health gain (IHG), community health gain (CHG),
equity and cultural security (CS). IHG was
defined as physical health, emotional and spirit-
ual well being, and empowerment to participate in
personal and community activities. It consisted of
two sub-dimensions: DALY consistent attributes
and non-DALY attributes. The DALY sub-dimen-
sion was defined as the level of improvement in
the physical and mental wellbeing of an individ-
ual resulting from the use of a health service.
This dimension mirrored the EuroQol 5D — the
source of disability weights for the construction
of the DALY (Edwards et al. 1998). Non-DALY
sub-dimensions included empowerment, resil-
ience, and spiritual and emotional wellbeing.
CHG was defined as benefit realised from the
provision of a health care service, which goes
beyond what would accrue to the individual
utilising it. It involves the community’s internal
relationships (e.g. control, cohesion, co-operation,
resource sharing and promotion of resilience), as
well as its external relationships with social poli-
cies and institutions (such as general practitioners,
hospitals, schools and police), and the sustainabil-
ity of such interventions.
Equity involved fairness to Indigenous people,
and it was defined in terms of how interven-
tions and options for change impact both the
health status differential and access to good
quality health care services. The health status
differential involved the differences in health
status between Indigenous and non- Indigenous
Australians, as well as between different
Indigenous Australians. The access component
was defined as those constraints or facilita-
tors that impact the availability, utilisation and
adherence to the interventions.
CS included bot h institutional and intervention/
health service attributes. Institutional attrib-
utes covered policy systems, quality assurance
processes and professional development strategies.
Intervention or service attributes were defined as:
• an ‘affirming culture’ to enhance perceived
access, utilisation and adherence through
acknowledgment of the traditional knowl-
edge of Indigenous Australians, and interven-
tions designed in recognition of the particular
strengths of Indigenous culture/communities
‘design features’ that facilitate perceived access,
utilisation and adherence through flexibility to
respond to cultural differences and values, the
development of partnerships between provid-
ers and the Indigenous community organisa-
tions, and interventions that enable/enhance
Indigenous participation in the workforce.
Calibrating the descriptors of dimensions
Results from the discussions showed reference
states located on the five thermometer points (0%,
25%, 50%, 75% and 100%) and agreed upon by
all participants based on consensus (Figure 1).
The lower bound, 0%, was a zero score and
describes the ‘worst’ possible state. The upper
bound, 100%, was the ‘best’ possible state. Three
intermediate states were defined to correspond to
the 25%, 50% and 75% scores. These descriptors
provided a clearer understanding of each dimen-
sion and guidance on the different levels of benefit
that could occur.
36 Australian Aboriginal Studies 2015/1
What cons titutes benefit from health care interventions? Otim et al.
Table 1 provides a summary of the dimen-
sion descriptors, labelled scales and calibra-
tion. For example, the ‘best possible’ state of
community health gain involves an intervention
being completely community controlled with the
community fully engaged. At that score, there
should be an extremely strong external leverage
to other sectors. In essence, Table 1 shows the
usual five-point Likert scale labels but these were
worded such that the labels corresponded with
specific scores such as 0%, 25% or 50%.
Quantifying relative importance and
aggregating the dimensions
Using VAS as a scaling technique, each participant
indicated on a 0 –100 scale where each dimension
weight could be placed in a cumulative manner,
based on relative importance (Figure 2). This
method is termed a ‘global’ approach. It is akin to
giving each participant $100 and asking them to
spend it all to purchase the different quantities of
identified dimensions, assuming one unit of any
dimension costs $1. The amount of money spent
would indicate the relative importance attached
to each dimension by participants.
To address preference uncertainty in the global
approach, participants engaged in open discussion
as to why some dimensions were weighted higher
than others. This discussion not only clarified the
questions asked, but also encouraged consensus as
a mechanism to achieve internal validity. The rela-
tive weights of the dimensions for each respond-
ent were averaged to determine relative weights
for each dimension (Table 2).
The average scores indicated that the IHG
dimension was the most important dimension,
at about 42%. These results are very similar to
the results from the Indigenous component of the
earlier South Australian Community Health study
Figure 1: Calibration of the descriptors using a
Source: Peacock et al. 1997
Descriptor 1
Descriptor 2
Descriptor 3
Descriptor 4
Descriptor 5
Table 1: Descriptors of the dimensions of Indigenous health
IHG: DALY IHG: non-DALY Community
health gain
Equity Cultural security
No problems
in living
no pain or
no mental
health problems.
Total possible
total possible
total possible
spiritual health.
extremely strong
external leverage.
and no
Demonstrates best
possible cultural
facilitates very strong
employs only
Indigenous workers.
problems living
minor pain/
minor mental
health problems.
Good level of
good level
of emotional
good level of
spiritual health.
Good community
good community
good external
and minor
Demonstrates strong
cultural effectiveness;
facilitates strong
employs high number
of Indigenous workers,
relative to opportunity.
Australian Aboriginal Studies 2015/1 37
Otim et al. What cons titutes benefit from health care interventions?
IHG: DALY IHG: non-DALY Community
health gain
Equity Cultural security
Fair state
Some problems
some pain/
some mental
health problems.
Fair level of
fair level of
fair level of
spiritual health.
moderate external
at average
Demonstrates moderate
level of cultural
facilitates moderate level
of partnerships;
employs moderate
number of Indigenous
workers, relative to
Bad state
Lots of
problems living
lots of pain/
lots of mental
health problems.
Poor state of
poor state
of emotional
poor level of
spiritual health.
Low community
low community
low external
and major
Demonstrates no
cultural effectiveness;
facilitates no
employs very few
Indigenous workers,
relative to opportunity.
Unable to live
extreme pain/
mental health
Worst possible
worst possible
worst possible
no external
from an
and major
Culturally destructive;
likely to destroy existing
excludes and/or
penalises Indigenous
Table 1: Descriptors of the dimensions of Indigenous health continued
Table 2: Simple elicitation of weights for dimension/sub- dimension from interventions in Indigenous health
Respondent 12345678910 Mean
IHG (%) 40 60 70 40 35 25 10 20 40 75 42
DALY (% of IHG) 80 90 70 60 70 50 70 60 50 70 67
Non-DALY (% of IHG) 20 10 30 40 30 50 30 40 50 30 33
CHG (%) 20 20 10 20 35 25 20 25 10 7 19
Equity (%) 10 10 15 20 15 25 30 25 30 5 19
CS (%) 30 10 5 20 15 25 40 30 20 12 21
IHG is individual health gain, CHG is community health gain and CS is cultural security.
IHG is individual health gain, CHG is community health gain and CS is cultural security.
0% IHG 19% Equity
42% CS 19%
Figure 2: Weighting dimensions of benefit from health care intervention using the global approach (VAS)
38 Australian Aboriginal Studies 2015/1
What cons titutes benefit from health care interventions? Otim et al.
(Edwards et al. 1998). The rest of the dimensions
were of equal importance. Seven of the ten panel
members considered IHG to be the most impor-
tant dimension but one considered IHG to be
the least important. Due to the small number of
participants, the results were highly variable. The
IHG range of the results lay between 10 and 75.
Further, given that IHG was defined to include
both the DALY and non-DALY sub-dimen-
sions, respondents were again asked to indicate
the proportion of the DALY sub-dimension in
IHG. The DALY sub-dimension had a weight of
67% — about two-thirds of the IHG. Thus the
DALY contributed only 28% of the overall poten-
tial benefit from interventions although the true
value is in the range of 50–90.
The purpose of this study was to examine the
concept of benefit in Indigenous health and to
develop an Indigenous-specific health metric to
improve priority setting. The metric could poten-
tially be used to provide an acceptable basis for
developing weights to represent ‘equity’ as a basis
for weighting DALYs. Further, the metric could be
used to quantify ‘cultural security’ and ‘commu-
nity health gain’ for priority setting purposes.
Thus including Indigenous social values into the
health metric, especially the DALY or any other
measure, could improve acceptability, validity
and reliability of measures of benefit when under-
taking economic evaluation for priority setting
It was recognised that the definitions of health
are context specific and heavily value laden.
The Indigenous Australian health construct is
a holistic one of which the health of an individ-
ual is more than just the absence of a disease but
includes the wellbeing of the community and the
ability of the individual to participate in commu-
nity activities (Flick 2003). Thus benefit from
Indigenous health care interventions is broad and
covers non-health attributes such as the concern
for the welfare of others. For such attributes, the
QALY and DALY are limited measures at best
and their use for priority setting consequently
becomes limited.
In developing the Indigenous health metric,
the Indigenous health construct dictated that the
ACE method took into consideration the role of
non-individual health benefits such as commu-
nity empowerment and cultural security. It was
possible that these dimensions could have been
captured using the second-stage filters. In such a
case, incorporation of ethical values or weight-
ing the DALY would probably have been suffi-
cient. However, Carter and colleagues abandoned
such an approach in favour of the MAU approach
(Carter 2000). These questions were presented
and discussed during the workshops to aid the
In defining and weighting the Indigenous
health construct, members of the workshop
faced a number of challenges. First, in identify-
ing dimensions of benefit, there was inevitably a
creative tension between the dictates and func-
tional reality of the measurement theory (such as
clarity and cognitive load) and the policy impor-
tance of including all pertinent health issues of
Indigenous Australians. This trade-off could have
an impact on the validity, reliability, relevance
and accept ability of the instrument being devel-
oped. Repeated consultation and consensus build-
ing ensured that agreement on the key dimensions
was possible. This also ensured that acceptability
of the results was likely to be well received.
While the instrument could have achieved the
balance in the trade-offs above, there was concern
around the cognitive burden for those who would
utilise the instrument. To address that, it was
ensured that there were as few sub-dimensions
and few domains in each dimension as possible.
This enabled the workshop members to appreci-
ate the methods. Indeed, the work done by Carter
and colleagues (Carter et al. 2008) and Peacock
and colleagues (Peacock et al. 2007) demon-
strate the applicability of the MAU approach in
expanding the concept of benefit to include non-
DALY outcomes. Trialling the Indigenous metric
in practical application will resolve some of the
remaining issues about the approach, including
(i) whether there are too many descriptors for
the identified dimensions and (ii) whether the
descriptors are too complex.
Second, the explicitness of the deliberative
process was challenging. Some workshop partici-
pants wanted most of their views incorporated in
the instrument. To address that, the chairperson
of the ISC ensured that participants had opportu-
nities to give frank feedback directly during and
Australian Aboriginal Studies 2015/1 39
Otim et al. What cons titutes benefit from health care interventions?
after the workshops and these comments endorsed
the workshop results. Repeated confirmation of
the dimensions across multiple workshops indi-
cated strong internal consistency. However, that
meant that the metric derived from the workshops
embodied Indigenous ethical values and reflected
the relevant context of decision making, limiting
its use in other settings.
Third, given the small number of experts in the
workshops and the nature of their selection, these
findings may not be representative. Although this
is a valid reservation, there is confidence that
due to the extensive networks and experiences of
the members of our workshop series, and due to
the consensus-based approach that was used, the
results that were elicited were relevant to the task.
Fourth, the instrument gave a fine grading of
scores ending with 5 and 0. Participants were
free to give zero, high or low scores. To achieve
consensus, they had to discuss with other panel
members why they gave such high or low scores.
This allowed the respondents to change their
scores up and down after discussion to achieve
consensus. However, although the fine grading
reduces the risk of cognitive burden, the use of
group consensus can lead to different results.
This study has demonstrated how the objec-
tives being pursued in Indigenous health can be
captured for priority setting purposes. The results
indicated that the DALY is an important meas-
ure of benefit, but accounts for a small proportion
of what constitutes ‘benefit’ from an Indigenous
perspective. It has further demonstrated that
community health gain ought to be actively
addressed in priority setting. It was possible to
develop an instrument for measuring benefit in
Indigenous health for priority setting purposes,
which reflects Indigenous health constructs. The
study has demonstrated how the Indigenous
community and its representatives can be involved
in the decision-making process.
The importance of weights developed could
be the starting point for Aboriginal Community
Controlled Health Services and funding agencies
to discuss policy options in addressing Indigenous
health. One key policy issue is the relative impor-
tance of community health gain and finding real-
istic ways to incorporate it in the decision-making
process. A possible method is to view community
health gain (and other dimensions) as weights
to be applied to a chosen health metric. This
approach could be used to extend the weighting
of QALYs for equity purposes, which has been
extensively discussed in the literature. This is a
rich area for further empirical work and analysis.
Finally, while these findings have to be
regarded with caution, they provide an impor-
tant basis for further work. Subsequent research
should be done in a way that facilitates mapping
back the Indigenous health metric to the metric
used for the general population (such as DALY or
QALY) and determining the suitability for prior-
ity setting.
The Cooperative Research Centre for Aboriginal
Health funded the participation of the ACE-
Prevention Indigenous Steering Committee
(ISC) members in this study, and this work was
done under the auspices of the ACE-Prevention
project. We would like to thank the members
of the ACE-Prevention ISC for their active
involvement in the workshops, and Professors
Rob Carter, Theo Vos and Jeff Richardson
for their guidance on the development of the
project and methodology. We would also like to
acknowledge Dr Katherine Ong, A /Prof. Cathy
Mihalopoulos and Ms Sandra Younie for their
involvement in the workshops. Dr Ong helped to
take notes during the workshops, and Professor
Stephen Jan and Dr Asante helped to draft and
edit this paper.
No conflict of interest can be declared.
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What cons titutes benefit from health care interventions? Otim et al.
Dr Michael E Otim is a Senior Lecturer and Course
Coordinator of Public Health and a holder of an NHMRC
Early Career in Indigenous Health Fellowship at the
School of Allied Health, Australian Catholic University.
His current research focuses on health economics and
policy in Indigenous and disadvantaged communities,
and the application of economic principles in deci-
sion making. He is currently engaged in collaborative
work with several universities/research institutions
in Australia and is involved in priority setting, health
economics and financing in developing countries such
Timor-Leste and Uganda. He has led research programs
in Aboriginal health economics policy at Melbourne,
Deakin and Sydney universities, and has worked for the
Victorian State Department of Human Services and the
NSW State Ministry of Health.
Dr Augustine D Asante is a Research Fellow at
University of New South Wales. He has broad research
interests in the fields of health care financing and
economics, health systems strengthening and health
services management. His earlier works focused on
improving financial resource allocation within decentral-
ising health systems. In particular, he has looked at how
mechanisms for financial resource allocation contrib-
ute to improving equity among various health jurisdic-
tions and how health managers at district levels cope
with erratic funding flows from the centre. Current
research activities concentrate on human resources for
health development in low and middle income coun-
tries. He is interested in assessing the capacity for health
and human resource management and leadership at the
district level. He is involved in countries in the Asia-Pacific
region such as Indonesia, Papua New Guinea and Fiji,
and has interests and expertise in other regions, particu-
larly sub-Saharan Africa. Broad areas of interest include
health economics, financing and policy; health services
management and research; and global health.
Professor Margaret Kelaher is Director of the Centre
for Health Policy at the School of Population and Global
Health at The University of Melbourne. She is a social
epidemiologist who has chosen a unique focus in her
work by bringing an evidence- and intervention-based
approach to understanding complex social issues. Her
work has been at the forefront of the development of
methodologies for understanding complex social inter-
ventions and their impacts. She has conducted a number
of major studies examining Aboriginal and Torres Strait
Islander health and wellbeing.
Professor Chris Doran holds a Bachelor of Economics
(Honours) and a PhD in Health Economics (conferred
August 1999). He is an international expert in the
area of priority setting and has undertaken commis-
sioned research for the United Nations, the World
Health Organization and the South Pacific Secretariat.
His research interests include capacity building, impact
assessment and translational research.
Professor Ian Anderson is Director of Murrup Barak,
the Melbourne Institute for Indigenous Development.
In 2012 he joined The University of Melbourne’s senior
leadership team as Assistant Vice Chancellor (Indigenous
Higher Education Policy) and was appointed to the
position of Foundation Chair for Indigenous Higher
Education. He previously occupied the university’s
Foundation Chair of Indigenous Health and has chaired
the National Aboriginal and Torres Strait Islander Health
Equality Council since 2008. In 2012 he was appointed
as Co-Chair of the Aboriginal and Torres Strait Islander
Higher Education Council. His background is in medi-
cine and social sciences and he worked in Aboriginal
health for more than 25 years as a health worker, educa-
tor, general practitioner, policy maker and academic.
He has written widely on Indigenous health and devel-
opment and maintains an active research portfolio. His
family are Palawa Trowerna from the Pyemairrenner
mob in Tasmania, which includes Trawlwoolway and
Plairmairrenner and related clans.
... In Australia, as in many other countries, the acknowledgment of this failure has seen the overall concept of health in Indigenous communities being also associated with social and emotional wellbeing (AIHW 2009). This has led to a more holistic understanding of health, which has gone beyond the functioning of individuals to comprise their connection to land, their cultural and familial ties, cultural security and the impact of experiences such as child removals, cultural disruption and racism on the overall community (Newton et al. 2015;Otim et al. 2015). ...
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Healing the trauma of Stolen Generations people is a primary aim of various Aboriginal and Torres Strait Islander-led organisations across Australia. In partnership with Bringing Them Home WA the authors are assisting in the restoration and regeneration of two former mission institutions at Carrolup/Marribank and Wandering in Western Australia to be used as healing centres for Aboriginal people formerly confined at these places. This paper takes a holistic view of healing and proposes a cultural healing framework that moves beyond physical human functioning. It emphasises the connection to land, memory and community identity as critical to social and emotional wellbeing and healing, and reflects on the project process and the impact of this work on Aboriginal and Torres Strait Islander people. It elaborates on the community-centric approach that positions the Survivors as drivers and decision makers for this project. Can this approach build capacity for the Survivors in the short and long term?
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Indigenous Australians have significantly poorer health outcomes than the non-Indigenous population worldwide. The Australian government has increased its investment in Indigenous health through the "Closing the Health Gap" initiative. Deciding where to invest scarce resources so as to maximize health outcomes for Indigenous peoples may require improved priority setting processes. Current government practice involves a mix of implicit and explicit processes to varying degrees at the macro and meso decision making levels. In this article, we argue that explicit priority setting should be emphasized in Indigenous health, as it can ensure that the decision making process is accountable, systematic, and transparent. Following a review of the literature, we outline four key issues that need to be considered for explicit priority setting: developing an Indigenous health "constitution," strengthening the evidence base, selecting mechanisms for priority setting, and establishing appropriate incentives and institutional structure. We then summarize our findings into a checklist that can help a decision makers ensure that explicit priority setting is undertaken in Indigenous health. By addressing these key issues, the benefits of an explicit approach, which include increased efficiency, equity, and use of evidence, can be realized, thereby maximizing Indigenous health outcomes.
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This study aimed to examine the acceptability of programme budgeting and marginal analysis (PBMA) as a tool for priority setting in the Indigenous health sector. The study uses a mix of quantitative and qualitative methods. A survey of key decision makers in Indigenous health in Victoria was conducted to assess the acceptability of PBMA as a potential tool for priority setting. Respondents comprised 24 bureaucrats from the Victorian Department of Human Services (DHS) and 26 senior executives from the aboriginal community controlled health sector (ACCHS) in Victoria. The survey instrument included both closed-ended and open-ended questions and was administered face-to-face by a trained researcher in 2007-2008. Closed-ended questions were analysed using descriptive statistics, and content analysis was used for the open-ended ones. The PBMA was well received as having the potential to improve priority setting processes in Indigenous health. Sixty-nine percent of the DHS respondents felt that PBMA was acceptable as a routine decision-making tool, and nearly 80% of ACCHS respondents thought that PBMA was intuitively appealing and would most probably be an acceptable priority setting approach in their organisations. The challenges of using PBMA were related to resource constraints and data intensity. Programme budgeting and marginal analysis is potentially acceptable within the ACCHS and was perceived as useful in terms of assisting the decision maker to maximise health outcomes, but data systems need to be re-oriented to address its significant data needs. Proper guidelines need to be developed to facilitate PBMA application within the Indigenous-controlled community health sector. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
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Asthma is the most common chronic illness among adolescents in Australia. Aboriginal and Torres Strait Islander adolescents, in particular, face substantial inequalities in asthma-related outcomes. Triple A (Adolescent Asthma Action) is a peer-led education intervention, which aims to improve asthma self-management and reduce the uptake of smoking among adolescents. The aim of this study was to determine the cost of implementing the Triple A program in Australia. Standard economic costing methods were used. It involved identifying the resources that were utilised (such as personnel and program materials), measuring them and then valuing them. We later performed sensitivity analysis so as to identify the cost drivers and a stress test to test how the intervention can perform when some inputs are lacking. Results indicate that the estimated cost of implementing the Triple A program in five schools was $41060, assuming that the opportunity cost of all the participants and venues was accounted for. This translated to $8212 per school or $50 per target student. From sensitivity analysis and a stress test, it was identified that the cost of the intervention (in practice) was $14 per student. This appears to be a modest cost, given the burden of asthma. In conclusion, the Triple A program is an affordable intervention to implement in high schools. The potential asthma cost savings due to the program are significant. If the Triple A program is implemented nation-wide, the benefits would be substantial.
Full-text available
Introduction: The health of Indigenous Australians is worse than that of other Australians. Most of the determinants of health are preventable and the poor health outcomes are inequitable. The Australian Government recently pledged to close that health gap. One possible way is to improve the priority setting process to ensure transparency and the use of evidence such as epidemiology, equity and economic evaluation.The purpose of this research was to elicit the perceptions of Indigenous and non-Indigenous decision-makers on several issues related to priority setting in Indigenous-specific health care services. Specifically, we aimed to:1. identify the criteria used to set priorities in Indigenous-specific health care services;2. determine the level of uptake of economic evaluation evidence by decision-makers and how to improve its uptake; and 3. identify how the priority setting process can be improved from the perspective of decision-makers. Methods: We used a paper survey instrument, adapted from Mitton and colleagues' work, and a face-to-face interview approach to elicit decision-makers' perceptions in Indigenous-specific health care in Victoria, Australia. We used mixed methods to analyse data from the survey. Responses were summarised using descriptive statistics and content analysis. Results were reported as numbers and percentages. Results: The size of the health burden; sustainability and acceptability of interventions; historical trends/patterns; and efficiency are key criteria for making choices in Indigenous health in Victoria. There is a need for an explicit priority setting approach, which is systematic, and is able to use available data/evidence, such as economic evaluation evidence. The involvement of Indigenous Australians in the process would potentially make the process acceptable. Conclusions: An economic approach to priority setting is a potentially acceptable and useful tool for Aboriginal Community Controlled Health Services (ACCHS). It has the ability to use evidence and ensure due process at the same time. The use of evidence can ensure that health outcomes for Indigenous peoples can be maximised - hence, increase the potential for 'closing the gap' between Indigenous and other Australians.
Full-text available
Abstract This paper uses a simulation approach to investigate how dif ferent attribute weighting techniques affect the quality of decisions based on multiattribute value models. The weighting methods considered include equal weighting of all attributes, two methods for using judgments about the rank ordering of weights, and a method for using judgments about the ratios of weights. The question addressed is: How well does each method,perform when based on judgments of attribute weights that are unbiased but subject to random error? To address this question, we employ,simulation methods. The simulation results indicate that ratio weights were either better than rank order weights (when error in the ratio weights was small or moderate) or tied with them (when error was large). Both ratio weights and rank order weights were substantially superior to the equal weights method,in all cases studied. Our findings suggest that it will usually be worth the extra time and effort required to assess ratio weights. In cases where the extra time or effort required is too great, rank order weights will usually give a good approximation to the true weights. Comparisons,of the two rank-order weighting methods,favored the rank-order-centroid method,over the rank-sum method.
Given the growing need to value health-related quality of life, a review of the literature relating to health state valuation techniques was undertaken to appraise the current theoretical and empirical evidence available to inform on the techniques, to identify consensus, identify disagreement and identify important areas for future research. A systematic search of the literature was conducted, covering standard gamble (SG), time trade-off (TTO), visual analogue scale (VAS), magnitude estimation (ME) and person trade-off (PTO) techniques. The basic concepts of practicality, reliability, theoretical validity and empirical validity formed the criteria for reviewing the performance of valuation techniques. In terms of practicality and reliability, we found little evidence relating to ME and PTO. SG, TTO and VAS have been shown to be practical on a range of populations. There is little difference between the reliability of SG, TTO and VAS, and present evidence does not offer a basis to differentiate between them. When considering the theoretical basis of techniques, we conclude that choice-based methods (i.e. SG, TTO and PTO) are best placed to reflect the strength of preference for health, with the choice between these techniques depending on the study characteristics and the perspective employed. Empirical evidence relating to the theoretical perspective of the techniques has shown that there are problems with all techniques in terms of descriptive validity.