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In New South Wales, Australia, a cost-effectiveness evaluation was conducted of an adult drug court (ADC) program as an alternative to jail for criminal offenders addicted to illicit drugs. This article describes the program, the cost-effectiveness analysis, and the results. The results of this study reveal that, for the 23-month period of the evaluation, the ADC was as cost-effective as were conventional sanctions in delaying the time to the first offense and more cost-effective in reducing the frequency of offending for those outcome measures selected. Although the evaluation was conducted using the traditional steps of a cost-effectiveness analysis, because of the complexity of the program and data limitations it was not always possible to adhere to textbook procedures. As such, each step involved in undertaking the cost-effectiveness analysis is discussed, highlighting the key issues faced in the evaluation.

There is growing use of discrete choice experiments (DCEs) to investigate preferences for products and programs and for the attributes that make up such products and programs. However, a fundamental issue overlooked in the interpretation of many choice experiments is that attribute parameters estimated from DCE response data are confounded with the underlying subjective scale of the utilities, and strictly speaking cannot be interpreted as the relative 'weight' or 'impact' of the attributes, as is frequently done in the health economics literature. As such, relative attribute impact cannot be compared using attribute parameter size and significance. Instead, to investigate the relative impact of each attribute requires commensurable measurement units; that is, a common, comparable scale. We present and demonstrate empirically a menu of five methods that allow such comparisons: (1) partial log-likelihood analysis; (2) the marginal rate of substitution for non-linear models; (3) Hicksian welfare measures; (4) probability analysis; and (5) best worst attribute scaling. We discuss the advantages and disadvantages of each method and suggest circumstances in which each is appropriate. Keywords: Choice experiments; Attribute impact; Welfare measurement; Partial log likelihood analysis; Best worst attribute scaling

Objective: To identify the resources used and the costs incurred by people with asthma for health care and non-health care products and services to manage asthma. Methods: A prospective, longitudinal study, using self-reported and administrative data, commenced in 2001 in New South Wales (NSW). Data sources included two six-monthly surveys, hospital admission data from NSW Health, and pharmaceutical benefits and Medicare data. A cohort of 245 people with asthma, aged between 5-75 years, was recruited from the general population and from hospital emergency departments. The study measured the use and cost of health care services and products, including alternative therapies and home modifications. Costs to both the health care system and individuals were measured. Results: General practitioner visits and asthma medications were the items of health care most commonly used. Medications were also the largest component of individual costs for health care in terms of the average payment and the number of people facing an out-of-pocket cost, although home equipment and modifications were the most expensive individual items. The distribution of individual costs was highly skewed, ranging from $0 to $4,882 per person per annum (median $89). Admitted hospital care was the largest component of the cost to the health care system. Conclusion: While individual costs were not large for the majority, some people faced substantial costs, with the highest of these being for non-health care items. Implications: Asthma management policies may need to incorporate schemes to alleviate the impact of costs for the minority experiencing significant out-of-pocket expenses.

The obesity epidemic is a significant public policy issue facing the international community, resulting in substantial costs to individuals and society. Various policies have been suggested to reduce and prevent obesity, including those informed by standard economics (a key feature of which is the assumption that individuals are rational) and behavioral economics (which identifies and harness deviations from rationality). It is not known which policy interventions taxpayers find acceptable and would prefer to fund via taxation. We provide evidence from a discrete choice experiment on an Australian sample of 996 individuals to investigate social acceptability of eight policies: mass media campaign; traffic light nutritional labeling; taxing sugar sweetened beverages; prepaid cards to purchase healthy food; financial incentives to exercise; improved built environment for physical activity; bans on advertising unhealthy food and drink to children; and improved nutritional quality of food sold in public institutions. Latent class analysis revealed three classes differing in preferences and key respondent characteristics including capacity to benefit. Social acceptability of the eight policies at realistic levels of tax increases was explored using post‐estimation analysis. Overall, 78% of the sample were predicted to choose a new policy, varying from 99% in those most likely to benefit from obesity interventions to 19% of those least likely to benefit. A policy informed by standard economics, traffic light labeling was the most popular policy, followed by policies involving regulation: bans on junk food advertising to children and improvement of food quality in public institutions. The least popular policies were behaviorally informed: prepaid cards for the purchase of only healthy foods, and financial incentives to exercise. [ABSTRACT FROM AUTHOR]