An Evaluation Protocol for A Stabilisation and Referral Area (SARA): A Novel Short Stay Psychiatry Unit Serving A Remote Region of Australia.

Background: Stabilisation and Referral Areas (SARA) are a unique model of Short Stay Psychiatry inpatient care. This protocol details the comprehensive evaluation of a new SARA service within the Royal Darwin Hospital located in remote and regional Australia. Located in the Northern Territory (NT) there are just 17 specialised mental health beds per 100,000 compared to the national average of 27 per 100,000. There have been no previous evaluations of SARA services in regional and remote Australian settings, therefore their acceptability and potential effects on consumer outcomes in these unique settings is unknown. This study protocol attempts to address this knowledge gap.

Study design: A mixed method study with triangulation and including mirror methodology.

Methods: A service evaluation protocol is proposed to be conducted over an initial 12 months period with a mirror image component to enable comparison of consumer outcomes prior to the service inception. The service evaluation is guided by the "Reach, Effectiveness, Adoption, Implementation and Maintenance" (RE-AIM) framework and utilized both qualitative and quantitative measures to comprehensively describe the service.

Results: Results will include both qualitative and quantitative data using the "R", "E" and "A" component (Reach, Effectiveness and Adoption) of the RE-AIM framework.

Conclusions: Emergency departments (EDs) are not well suited to persons experiencing mental health crisis and efforts need to be made to improve the delivery of service as well as patient flow. Minimizing wait times in ED is paramount. SARA is an innovative model of care that may address some of these issues. Evaluating its performance across a range of measures is key to improving and progressing the service. The unique context of the service location which has a large First Nations population and its remote setting adds further weight to the need to understand this model within this geographical context.