Attaching unit costs to Australia`s national survey of mental health and wellbeing

Background: In mental health, policy-makers and planners are increasingly being asked to set priorities. This means that health economists, health services researchers and clinical investigators are being called upon to work together to define and measure costs. Typically, these researchers take available service utilisation data and convert them to costs, using a range of assumptions. There are inefficiencies, as individual groups of researchers frequently repeat essentially similar exercises in achieving this end. There are clearly areas where shared or common investment in the development of statistical software syntax, analytical frameworks and other resources could maximise the use of data.

Aims of the Study: This paper reports on an Australian project in which we calculated unit costs for mental health admissions and community encounters. In reporting on these calculations, our purpose is to make the data and the resources associated with them publicly available to researchers interested in conducting economic analyses, and allow them to copy, distribute and modify them, providing that all copies and modifications are available under the same terms and conditions (i.e., in accordance with the `Copyleft' principle). Within this context, the objectives of the paper are to: (i) introduce the `Copyleft' principle; (ii) provide an overview of the methodology we employed to derive the unit costs; (iii) present the unit costs themselves; and (iv) examine the total and mean costs for a range of single and comorbid conditions, as an example of the kind of question that the unit cost data can be used to address.

Method: We took relevant data from the Australian National Survey of Mental Health and Wellbeing (NSMHWB), and developed a set of unit costs for inpatient and community encounters. We then examined total and mean costs for a range of single and comorbid conditions.

Results: We present the unit costs for mental health admissions and mental health community contacts. Our example, which explored the association between comorbidity and total and mean costs, suggested that comorbidly occurring conditions cost more than conditions which occur on their own.

Discussion: Our unit costs, and the materials associated with them, have been published in a freely available form governed by a provision termed `Copyleft'. They provide a valuable resource for researchers wanting to explore economic questions in mental health.

Implications for Health Policies: Our unit costs provide an important resource to inform economic debate in mental health in Australia, particularly in the area of priority-setting. In the past, such debate has largely been based on opinion. Our unit costs provide the underpinning to strengthen the evidence-base of this debate.

Implications for Further Research: We would encourage other Australian researchers to make use of our unit costs in order to foster comparability across studies. We would also encourage Australian and international researchers to adopt the `Copyleft' principle in equivalent circumstances. Furthermore, we suggest that the provision of `Copyleft'-contingent funding to support the development of enabling resources for researchers should be considered in the planning of future large-scale collaborative survey work, both in Australia and overseas.

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