Incorporating an economic model in the health impact assessment approach

The current policy decision making in Australia regarding non-health public investments (for example, transport/housing/social welfare programmes) does not quantify health benefits and costs systematically. To address this knowledge gap, this study proposes an economic model for quantifying health impacts of public policies in terms of dollar value. The intention is to enable policy-makers in conducting economic evaluation of health effects of non-health policies and in implementing policies those reduce health inequalities as well as enhance positive health gains of the target population. Health Impact Assessment (HIA) provides an appropriate framework for this study since HIA assesses the beneficial and adverse effects of a programme/policy on public health and on health inequalities through the distribution of those effects. However, HIA usually tries to influence the decision making process using its scientific findings, mostly epidemiological and toxicological evidence. In reality, this evidence can not establish causal links between policy and health impacts since it can not explain how an individual or a community reacts to changing circumstances. The proposed economic model addresses this health-policy linkage using a consumer choice approach that can explain changes in group and individual behaviour in a given economic set up. The economic model suggested in this paper links epidemiological findings with economic analysis to estimate the health costs and benefits of public investment policies. That is, estimating dollar impacts when health status of the exposed population group changes by public programmes – for example, transport initiatives to reduce congestion by building new roads/ highways/ tunnels etc. or by imposing congestion taxes. For policy evaluation purposes, the model is incorporated in the HIA framework by establishing association among identified factors, which drive changes in the behaviour of target population group and in turn, in the health outcomes. The economic variables identified to estimate the health inequality and health costs are levels of income, unemployment, education, age groups, disadvantaged population groups, mortality/morbidity etc. However, though the model validation using case studies and/or available database from Australian non-health policy (say, transport) arena is in the future tasks agenda, it is beyond the scope of this current paper.

Increasing socio-economic inequalities in drug-induced deaths in Australia : 1981-2002

Introduction and Aims: Since the 1990s illicit drug use death rates in Australia have increased markedly. There is a notable gap in knowledge about changing socio-economic inequalities in drug use death rates. Some limited Australian and overseas data point to higher rates of drug death in the lowest socio-economic groups, but the paucity of available studies and their sometimes conflicting findings need to be addressed. Design and Methods: This paper uses data obtained from the Australian Bureau of Statistics (ABS) to examine changes in age-standardised drug-induced mortality rates for Australian males over the period 1981 – 2002. Socio-economic status was categorised as manual or non-manual work status. Results: With the rapid increase in drug-induced mortality rates in the 1990s, there was a parallel increase in socio-economic inequalities in drug-induced deaths. The decline in drug death rates from 2000 onwards was associated with a decline in socio-economic inequalities. By 2002, manual workers had drug death rates well over twice the rate of non-manual workers. Discussion: Three factors are identified which contribute to these socio-economic inequalities in mortality. First, there has been an age shift in deaths evident only for manual workers. Secondly, there has been an increase in availability until 1999 and a relative decline in the cost of the drug, which most often leads to drug death (heroin). Thirdly, there has been a shift to amphetamine use which may lead to significant levels of morbidity, but few deaths. [Najman JM, Toloo G, Williams GM. Increasing socio-economic inequalities in drug-induced deaths in Australia: 1981–2002.

Assessing the impact of streetscape on residential property in lower to middle socio-economic areas

A number of factors have been shown to influence residential property prices in various locations. Studies have identified the importance of location in relation to services, transport and proximity to negative factors such as power lines and cell phone towers. Often the socio-economic status of a residential precinct can determine the overall quality and nature of the streetscapes in that area, with higher value suburbs or locations offering a better visual appearance compared to areas where these factors are not present. However, does the same value for a good streetscape apply in lower socio-economic areas or a buyers more motivated by less aesthetic factors such as size of the house, construction materials or land size. This paper analyses specific streets in a lower to middle socio-economic suburb of Christchurch New Zealand to determine if the location of a house in a street with good streetscape appeal has greater value, investment performance and saleability compared to adjoining streets with less aesthetic appeal.

An investigation of differences in crash characteristics between males and females involved in a fatigue-related crash or close call event

There is consensus among community and road safety agencies that driver fatigue is a major road safety issue and it is well known that excessive fatigue is linked with an increased risk of a motor vehicle crash. Previous research has implicated a wide variety of factors involved in fatigue-related crashes and the effects of these various factors in regard to crash risk can be interpreted as causal (i.e. alcohol and/or drugs may induce fatigue states) or additive (e.g. where a lack of sleep is combined with alcohol). As such, the purpose of this investigation was to examine self-report data to determine whether there are any differences in the prevalence, crash characteristics, and travel patterns of males and females involved in a fatigue-related crash or close call event. Such research is important to understand how fatigue related incidents occur within the typical driving patterns of men and women and it provides a starting point in order to explore if males and females experience and understand the risk of diving when tired in the same way. A representative sample of (N = 1,600) residents living in the Australian Capital Territory (ACT) and New South Wales (NSW), Australia, were surveyed regarding their experience of fatigue and their involvement in fatigue-related crashes and close call incidents. Results revealed that over 35% of participants reported having had a close call or crash due to driving when tired in the five years prior to the study being conducted. In addition, the results obtained revealed a number of interesting characteristics that provide preliminary evidence that gender differences do exist when examining the prevalence, crash characteristics, and travel patterns of males and females involved in a fatigue-related crash or close call event. It is argued that the results obtained can provide particularly useful information for the refinement and further development of appropriate countermeasures that better target this complex issue.

The effectiveness of using a simple ARIA based geographical classification to identify road crash patterns in rural and urban areas of Queensland

Research has noted a ‘pronounced pattern of increase with increasing remoteness' of death rates in road crashes. However, crash characteristics by remoteness are not commonly or consistently reported, with definitions of rural and urban often relying on proxy representations such as prevailing speed limit. The current paper seeks to evaluate the efficacy of the Accessibility / Remoteness Index of Australia (ARIA+) to identifying trends in road crashes. ARIA+ does not rely on road-specific measures and uses distances to populated centres to attribute a score to an area, which can in turn be grouped into 5 classifications of increasing remoteness. The current paper uses applications of these classifications at the broad level of Australian Bureau of Statistics' Statistical Local Areas, thus avoiding precise crash locating or dedicated mapping software. Analyses used Queensland road crash database details for all 31,346 crashes resulting in a fatality or hospitalisation occurring between 1st July, 2001 and 30th June 2006 inclusive. Results showed that this simplified application of ARIA+ aligned with previous definitions such as speed limit, while also providing further delineation. Differences in crash contributing factors were noted with increasing remoteness such as a greater representation of alcohol and ‘excessive speed for circumstances.' Other factors such as the predominance of younger drivers in crashes differed little by remoteness classification. The results are discussed in terms of the utility of remoteness as a graduated rather than binary (rural/urban) construct and the potential for combining ARIA crash data with census and hospital datasets.

Crash Risk Assessment with Cooperative Systems

Crash risk is the statistical probability of a crash. Its assessment can be performed through ex post statistical analysis or in real-time with on-vehicle systems. These systems can be cooperative. Cooperative Vehicle-Infrastructure Systems (CVIS) are a developing research avenue in the automotive industry worldwide. This paper provides a survey of existing CVIS systems and methods to assess crash risk with them. It describes the advantages of cooperative systems versus non-cooperative systems. A sample of cooperative crash risk assessment systems is analysed to extract vulnerabilities according to three criteria: market penetration, over-reliance on GPS and broadcasting issues. It shows that cooperative risk assessment systems are still in their infancy and requires further development to provide their full benefits to road users.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

Why creative industries matter to economic evolution

This paper proposes that the 'creative industries'(CIs) play an important yet widely unexamined function in economic evolution through their role in the innovation process. This occurs in terms of the facilitation of demand for novelty, the provision and development of social technologies for producer-consumer interactions, and the adoption and embedding of new technologies as institutions. The incorporation of CIs into the Schumpeterian model of economic evolution thus fills a notable gap in the social technologies of the origination, adoption and retention of innovation.

Application of text mining in analysing road crashes for road asset management

Traffic safety is a major concern world-wide. It is in both the sociological and economic interests of society that attempts should be made to identify the major and multiple contributory factors to those road crashes. This paper presents a text mining based method to better understand the contextual relationships inherent in road crashes. By examining and analyzing the crash report data in Queensland from year 2004 and year 2005, this paper identifies and reports the major and multiple contributory factors to those crashes. The outcome of this study will support road asset management in reducing road crashes.

A multilevel study of area socio-economic status and food purchasing behaviour

Objective: This study examined the association between area socioeconomic status (SES) and food purchasing behaviour.----- Setting: Melbourne city, Australia, 2003.----- Participants: Residents of 2,564 households located in 50 small areas.----- Design: Data were collected by mail survey (64.2% response rate). Area SES was indicated by the proportion of households in each area earning less than Aus$400 per week, and individual-level socioeconomic position was measured using education, occupation, and household income. Food purchasing was measured on the basis of compliance with dietary guideline recommendations (for grocery foods) and variety of fruit and vegetable purchase. Multilevel regression examined the association between area SES and food purchase after adjustment for individual-level demographic (age, sex, household composition) and socioeconomic factors.----- Results: Residents of low SES areas were significantly less likely than their counterparts in advantaged areas to purchase grocery foods that were high in fibre and low in fat, salt, and sugar; and they purchased a smaller variety of fruits. There was no evidence of an association between area SES and vegetable variety.----- Conclusions In Melbourne, area SES was associated with some food purchasing behaviours independent of individual-level factors, suggesting that areas in this city may be differentiated on the basis of food availability, accessibility, and affordability, making the purchase of some types of foods more difficult in disadvantaged areas.

Value-mapping for major economic infrastructure projects

The establishment of corporate objectives regarding economic, environmental, social, and ethical responsibilities, to inform business practice, has been gaining credibility in the business sector since the early 1990’s. This is witnessed through (i) the formation of international forums for sustainable and accountable development, (ii) the emergence of standards, systems, and frameworks to provide common ground for regulatory and corporate dialogue, and (iii) the significant quantum of relevant popular and academic literature in a diverse range of disciplines. How then has this move towards greater corporate responsibility become evident in the provision of major urban infrastructure projects? The gap identified, in both academic literature and industry practice, is a structured and auditable link between corporate intent and project outcomes. Limited literature has been discovered which makes a link between corporate responsibility; project performance indicators (or critical success factors) and major infrastructure provision. This search revealed that a comprehensive mapping framework, from an organisation’s corporate objectives through to intended, anticipated and actual outcomes and impacts has not yet been developed for the delivery of such projects. The research problem thus explored is ‘the need to better identify, map and account for the outcomes, impacts and risks associated with economic, environmental, social and ethical outcomes and impacts which arise from major economic infrastructure projects, both now, and into the future’. The methodology being used to undertake this research is based on Checkland’s soft system methodology, engaging in action research on three collaborative case studies. A key outcome of this research is a value-mapping framework applicable to Australian public sector agencies. This is a decision-making methodology which will enable project teams responsible for delivering major projects, to better identify and align project objectives and impacts with stated corporate objectives.

A review of the economic consequences of a policy of universal leucodepletion as compared to existing practices

Leucodepletion, the removal of leucocytes from blood products improves the safety of blood transfusion by reducing adverse events associated with the incidental non-therapeutic transfusion of leucocytes. Leucodepletion has been shown to have clinical benefit for immuno-suppressed patients who require transfusion. The selective leucodepletion of blood products by bed side filtration for these patients has been widely practiced. This study investigated the economic consequences in Queensland of moving from a policy of selective leucodepletion to one of universal leucodepletion, that is providing all transfused patients with blood products leucodepleted during the manufacturing process. Using an analytic decision model a cost-effectiveness analysis was conducted. An ICER of $16.3M per life year gained was derived. Sensitivity analysis found this result to be robust to uncertainty in the parameters used in the model. This result argues against moving to a policy of universal leucodepletion. However during the course of the study the policy decision for universal leucodepletion was made and implemented in Queensland in October 2008. This study has concluded that cost-effectiveness is not an influential factor in policy decisions regarding quality and safety initiatives in the Australian blood sector.