What's in an ASAM-based Assessment? Variations in Assessment and Level of Care Determination in Systems Required to Use ASAM Patient Placement Criteria

Objectives: When clients begin substance use disorder (SUD) treatment, it is critical to ensure that they receive treatment that matches their needs and preferences. A growing number of payors are requiring the use of multidimensional assessments such as assessments based on the American Society of Addiction Medicine (ASAM) criteria, which describe 6 dimensions that should be used to inform decisions about patient placement. However, ASAM guidance does not list specific questions to ask or instruments to use to elicit this information. This paper evaluates differences among the assessment tools being used by SUD service systems that are required to use ASAM-based assessments to make patient placement decisions. Methods: We analyzed 29 different ASAM-based assessments being used by California counties to make patient placement decisions using conventional and summative content analysis techniques. Results: All assessments were organized by the 6 ASAM dimensions. However, some of them only ask 1 or 2 questions per dimension, while others ask over 20, and some ask over 100 depending on patient responses. There is significant heterogeneity in the information the assessments collect and how it is used to generate patient placement decisions. Among the 29 assessments examined, there are 8 different algorithms or instructions on how to translate information from assessments into level of care recommendations. Conclusions: The differences among the ASAM-based assessments examined in this paper suggest a need to implement fidelity standards, enhance training, and create resources to help systems create and utilize assessment and patient placement tools that are consistent across the SUD treatment field.

Automated summary

The research reveals significant differences among ASAM-based assessment tools used in SUD treatment. Some assessments ask very few questions per dimension, while others are more detailed. Among the 29 assessments examined, there are 8 different algorithms for translating information into level of care recommendations.