Abstract

Objectives

Comorbid needs of people attending substance use treatment has been well documented although there is an assumption of heterogeneity in the treated population. This study utilized hierarchical cluster analysis to explore the extent and nature of client segments within the treated population. Methods: A retrospective review of comorbid health and social needs of a random sample of client case-notes (n = 300) was undertaken on all people known to treatment in an urban, inner-London community out-patient treatment service during 2018–2019. A hierarchical cluster analysis using Ward’s linkage method was implemented to explore the data to determine and describe emergent clusters. Inter cluster differences were investigated further by modeling methods. Results: High rates of physical health (63%) and mental health (50%) need were noted across the entire treatment population. The hierarchical clustering identified three discrete segments of the treatment population. The largest segment (46% of clients) was complex, socially impacted chaotic heroin and crack misusers exhibiting a wide range of multiple morbidities including social needs such as housing, unemployment and offending. This cluster also were more likely to report acute needs such as Emergency Department attendance, utilization of ambulatory services and will and episodic disengagement disengage episodically from treatment. A second segment (24% of clients) exhibited similar drug using profiles to the largest cluster, although with fewer comorbid issues. This cluster tended to be older and more likely to report respiratory conditions. A third cluster (25% of clients) was more likely to be alcohol misusers who were new to treatment. Conclusions: Treated populations are likely to be relatively heterogeneous across a range of social harms, physical and mental health needs. Identifying multidimensional needs of segments within treatment services allows for the creation of tailored treatment interventions.

中文翻译：

---

市中心英语物质滥用治疗服务中的多种发病率：分层聚类分析以推导出治疗细分

摘要

目标

尽管假设接受治疗的人群存在异质性，但参加药物滥用治疗的人的共病需求已得到充分记录。本研究利用层次聚类分析来探索受治疗人群中客户群的范围和性质。方法： 对 2018 年至 2019 年期间在伦敦市中心社区门诊治疗服务中接受治疗的所有已知患者病例记录（n = 300）的随机样本进行了对合并症健康和社会需求的回顾性审查. 实施了使用 Ward 链接方法的分层聚类分析，以探索数据以确定和描述紧急聚类。通过建模方法进一步研究了集群间差异。结果：在整个治疗人群中注意到身体健康 (63%) 和心理健康 (50%) 需求率很高。层次聚类确定了治疗人群的三个离散部分。最大的部分（46% 的客户）是复杂的、受社会影响的混乱海洛因和滥用者，表现出广泛的多种发病率，包括住房、失业和犯罪等社会需求。该集群也更有可能报告紧急需求，例如急诊科出勤、门诊服务的利用以及意愿和间歇性脱离治疗偶尔脱离治疗。第二部分（24% 的客户）展示了与最大集群相似的药物使用情况，但共存问题较少。这个集群往往年龄更大，更有可能报告呼吸系统疾病。结论：在一系列社会危害、身心健康需求方面，接受治疗的人群可能相对异质。确定治疗服务中细分市场的多维需求可以创建量身定制的治疗干预措施。