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A system dynamics model of Australian opioid pharmacotherapy maintenance treatment

A system dynamics model of Australian opioid pharmacotherapy maintenance treatment. Jenny Chalmers*, Alison Ritter*, Mark Heffernan** and Geoff McDonnell*** * National Drug and Alcohol Research Centre, UNSW; ** Evans & Peck Pty Ltd; *** Adaptive Care Systems Pty Ltd. Introduction.

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A system dynamics model of Australian opioid pharmacotherapy maintenance treatment

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  1. A system dynamics model of Australian opioid pharmacotherapy maintenance treatment Jenny Chalmers*, Alison Ritter*, Mark Heffernan** and Geoff McDonnell*** * National Drug and Alcohol Research Centre, UNSW; ** Evans & Peck Pty Ltd; *** Adaptive Care Systems Pty Ltd.

  2. Introduction • Motivation- Is there potential for pharmacotherapy programs to better meet demand in relation to availability, accessibility and affordability of treatment • Aim of research - develop a system dynamics model as a tool for policy makers to illustrate how treatment system as a whole responds to possible policy reforms • Research questions - explore 3 areas of concern • 80% of patients pay dispensing fees of $5/day. What would it cost the Government to cover them? • Can system cope with increased demand for treatment? • What would happen if supply of treatment places fell?

  3. Why use this approach? • Why a modeling approach? • Difficult to explore the impacts of policy changes in real world. • Simulation models are a safe, risk-free environment for experimenting with future policy options and gaining consensus among stakeholders. • Why system dynamics? • Rather than focus on the complex behaviour patterns of individuals, system dynamics elicits the structures, policies and “local” informal rules of the system from a range of qualitative and quantitative sources. • Pattern-oriented approach to model development and calibration with pooled data. • System dynamics 101 • A computable representation of stocks (accumulations), flows (rates) and information feedbacks that drive overall behaviour over time.

  4. Background • Australia’s pharmacotherapy system is over 20 years old • Close to 40,000 in treatment • 70% treated with methadone • Treatment system managed by state governments and funded by Commonwealth and state governments plus patient

  5. The model

  6. Model assumptions • Model is Australia-wide • Daily dispensing • Each episode of treatment identical • Each between treatment episode identical

  7. Systems of care

  8. Issue 1:Monthly methadone dispensing costs borne by Government

  9. Issue 2: Demand increase: treatment novices vs treatment experienced

  10. Issue 3: Impact on methadone patient numbers of limited entry to prescribers

  11. Conclusion • The model has the potential to serve as a spring-board for debates about policy directions • In this paper we: • Demonstrate that source of increased demand matters; • Simulate the financial implications for Government of subsidising dispensing of methadone; and • explore the implications of limiting entry of treatment seekers to prescribers.

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