A tiered model of substance use severity and life complexity: Potential for application to needs-based planning

In order to improve long-term outcomes for individuals with substance use problems, one approach is to adopt a system planning model that considers both addiction severity and life complexities. The tiered approach has been developed and tested to describe systems-level need based on levels of risk and problem severity.

An existing tiered model was modified to accommodate Australian data, incorporating substance use severity and life complexity. The hypothesis was that tiers would reflect differences in well-being amongst help seekers such that an increase in tier would be associated with a reduction in well-being, suggesting the need for more intensive (and integrated) interventions. The model was tested using 2 data sets of screening data, collected from face-to-face alcohol and other drug (AOD) service (n = 430) and online help (n = 309) seekers, drawn from a larger sample of 2,766 screens. The screen included demographic information and substance use, mental health, and quality of life measures.

There was a significant relationship between well-being and tier ranking, suggesting that the model adequately captured elements of severity and complexity that impact on well-being. There were notable differences between the help-seeking populations with a higher proportion of online respondents allocated to lower tiers and more face-to-face respondents allocated to higher tiers. However, there was an overlap in these populations, with more than half of online respondents classified as higher tiers and one fifth of face-to-face respondents classified as lower tiers. This suggests that the model can be used both to assess unmet need in out-of-treatment groups and demand in the absence of dependence in a subpopulation of the face-to-face treatment population.

The tiered model provides a method to understand levels of AOD treatment need and, as part of needs-based planning, may be used to optimize treatment responses and resourcing.