Browsing by Author "Pachet, Arlin"
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- ItemAn innovative framework for psychosocial assessment in complex mental capacity evaluations(2008) Newberry-Koroluk, Andrea; Pachet, ArlinThis study describes an innovative tool developed by the Regional Capacity Assessment Team (RCAT) to assess unique psychosocial factors related to capacity evaluations. Capacity is a socio-legal construct entailing the ability to understand choices, appreciate consequences and follow through (or direct a surrogate) with chosen options. RCAT's targeted psychosocial assessment includes medico-legal factors, social history and supports, coping skills, religious/cultural factors and risk of abuse. RCAT completes the psychosocial assessment to determine whether a full capacity assessment is required (referral disposition) and to determine the impact of an adult's social functioning on their decision-making capacity (capacity determination). RCAT's psychosocial assessment protocol was developed after a comprehensive literature review of capacity assessment and incorporates recommended practices in geriatric social work and psychology. This study will synthesise the pertinent literature, discuss cultural interviewing processes significant to capacity, caregiver assessment and describe the tool itself. Suggestions for future research and appropriate implementation of this tool are provided.
- ItemAssessing capacity in the complex patient: RCAT's unique evaluation and consultation model(2007) Pachet, Arlin; Newberry-Koroluk, Andrea; Erskine, LeslieThis paper describes the development of a unique multidisciplinary patient capacity assessment team, the Regional Capacity Assessment Team (RCAT), which operates in the Calgary Health Region of Alberta. The goals of this paper are to provide a brief review of seminal models that influenced RCAT's development, discuss its ethical and theoretical underpinnings, and provide an overview of the RCAT approach to the completion of complex capacity assessments. The overview of the RCAT model will elucidate our multidisciplinary assessment algorithm, our consultation model, and describe our specialized assessment tools. This paper will be of interest to health care practitioners and administrators looking for a cost-effective, efficient, and clinically sound model for complex capacity assessments.