New South Wales alcohol and other drug service providers' perceptions of the relative importance of client variables for determining treatment need.

INTRODUCTION

This study examines alcohol and other drug (AOD) service providers' perceptions of the most important variables (client complexity and demographic) for determining treatment need and intensity of intervention.

METHODS

Online cross-sectional survey of N = 188 clinicians/service managers working in AOD services across metropolitan and regional/rural New South Wales, Australia. Participants ranked the importance of demographic and family factors, substance use, physical health, mental health, functioning and activities of daily living and youth-specific variables in identifying treatment need (five-point Likert scales).

RESULTS

More than 90% of participants ranked 43 out 56 potential variables as 'very important'/'essential' in identifying treatment need. The 10 variables most ranked as 'very important'/'essential' were 'pregnant or breastfeeding' (95.2%), 'suicide/self-harm' (95.2%), 'overdose risk' (94.7%), 'abuse/neglect' (among youth/adolescent populations; 94.1%), 'mental health severity' (93.6%), 'dependent children' (93.1%), 'co-existing mental health concerns' (93.0%), 'hospitalisations due to mental health' (92.5%), 'child protection concerns' (among youth/adolescent populations; 92.2%) and 'disability' (91.5%). The 10 variables most commonly ranked as 'slightly important'/'not at all important' included 'citizenship' (63.3%), 'sex' (59.6%), 'country of birth' (54.8%), 'highest education' (50.0%), 'sexual orientation' (44.1%), 'relationship status' (33.5%), 'gender' (31.4%), 'transport' (28.2%), 'employment' (23.9%) and 'refugee status' (24.0%). Some ratings differed by geographic location (metropolitan vs. regional/rural) and job role (allied health worker, nurse, doctor or manager).

DISCUSSION AND

CONCLUSIONS

This study provides insight into service providers' perceptions of treatment need and intensity associated with a range of client factors. It is a first step towards improvements in routine data collections that are used to inform treatment planning.