Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia.
Orygen, Parkville, VIC,Australia.
Epidemiol Psychiatr Sci. 2024 Sep 18;33:e39. doi: 10.1017/S2045796024000386.
The specific and multifaceted service needs of young people have driven the development of youth-specific integrated primary mental healthcare models, such as the internationally pioneering services in Australia. Although these services were designed for early intervention, they often need to cater for young people with severe conditions and complex needs, creating challenges in service planning and resource allocation. There is, however, a lack of understanding and consensus on the definition of complexity in such clinical settings.
This retrospective study involved analysis of 's clinical minimum data set from young people accessing services in Australia between 1 July 2018 and 30 June 2019. Based on consultations with experts, complexity factors were mapped from a range of demographic information, symptom severity, diagnoses, illness stage, primary presenting issues and service engagement patterns. Consensus clustering was used to identify complexity subgroups based on identified factors. Multinomial logistic regression was then used to evaluate whether these complexity subgroups were associated with other risk factors.
A total of 81,622 episodes of care from 76,021 young people across 113 services were analysed. Around 20% of young people clustered into a 'high complexity' group, presenting with a variety of complexity factors, including severe disorders, a trauma history and psychosocial impairments. Two moderate complexity groups were identified representing 'distress complexity' and 'psychosocial complexity' (about 20% each). Compared with the 'distress complexity' group, young people in the 'psychosocial complexity' group presented with a higher proportion of education, employment and housing issues in addition to psychological distress, and had lower levels of service engagement. The distribution of complexity profiles also varied across different services.
The proposed data-driven complexity model offers valuable insights for clinical planning and resource allocation. The identified groups highlight the importance of adopting a holistic and multidisciplinary approach to address the diverse factors contributing to clinical complexity. The large number of young people presenting with moderate-to-high complexity to early intervention services emphasises the need for systemic change in youth mental healthcare to ensure the availability of appropriate and timely support for all young people.
年轻人特殊且多方面的服务需求推动了青年特定的综合初级心理健康保健模式的发展,例如在澳大利亚具有开创性的国际服务。尽管这些服务是为早期干预设计的,但它们通常需要满足病情严重和需求复杂的年轻人,这在服务规划和资源分配方面带来了挑战。然而,在这种临床环境中,对于复杂性的定义缺乏理解和共识。
本回顾性研究分析了澳大利亚于 2018 年 7 月 1 日至 2019 年 6 月 30 日期间接受服务的年轻人的“临床最小数据集”。基于与专家的咨询,从一系列人口统计学信息、症状严重程度、诊断、疾病阶段、主要呈现问题和服务参与模式中映射出复杂性因素。根据确定的因素,采用一致性聚类来识别复杂性亚组。然后,采用多项逻辑回归来评估这些复杂性亚组是否与其他风险因素相关。
共分析了 113 个服务中 76021 名年轻人的 81622 个护理疗程。大约 20%的年轻人聚类为“高复杂性”组,表现出多种复杂性因素,包括严重障碍、创伤史和心理社会障碍。确定了两个中等复杂性组,分别代表“困扰复杂性”和“心理社会复杂性”(各占约 20%)。与“困扰复杂性”组相比,“心理社会复杂性”组的年轻人除了心理困扰外,还存在更多的教育、就业和住房问题,并且服务参与度较低。不同服务的复杂性分布也存在差异。
所提出的数据驱动的复杂性模型为临床规划和资源分配提供了有价值的见解。所确定的组突出了采取整体和多学科方法来解决导致临床复杂性的多种因素的重要性。大量病情中等到严重的年轻人到早期干预服务机构就诊,这强调了青年心理健康保健系统需要进行变革,以确保为所有年轻人提供适当和及时的支持。