Modelling the impact on a local mental health system of previously implemented care programs: the experience of assertive outreach teams in Bizkaia (Spain).

IF 5.9 2区 医学 Q1 PSYCHIATRY
N Almeda, D Diaz-Milanes, H Killaspy, L Salvador-Carulla, J J Uriarte-Uriarte, C R García Alonso
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引用次数: 0

Abstract

Aims: The study assessed the interactions and the impact of specialist mobile community care teams (assertive outreach teams or AOTs) implemented in the mental health (MH) system of Bizkaia (Spain) using a methodology derived from an ecosystem perspective.

Methods: First, the experts assessed the system's services and codified them according to an international classification system. Second, following an iterative methodology for expert-knowledge elicitation, a clients' flow diagram showing the inter-dependencies of the system's components was developed. It included variables and their relationships represented in a causal model. Third, the system elements where the AOTs had a major impact (stress nodes) were identified. Fourth, three scenarios (variable combinations representing the 'stress points' of the system) were modelled to assess its relative technical efficiency (technical performance indicator).

Results: The classification system identified the lack of fidelity of the AOTs to the original assertive community treatment model, categorizing them as non-acute low-intensity mobile care. The causal model identified the following elements of the system as 'stress nodes' in relation to AOT: users' families; social services (outside of the healthcare system); acute hospitals; non-acute residential facilities and, to a lesser extent, acute hospital day care services. When the stress nodes inside the healthcare system were modelled separately, acute and non-acute hospital care services resulted in a large deterioration in the system performance, while acute day hospital care had only a small impact.

Conclusions: The development of the expert-knowledge-based causal model from an ecosystem perspective was helpful in combining information from different levels, from nano to macro, to identify the components in the system likely to be most affected by a potential policy intervention, such as the closure of AOTs. It was also able to illustrate the interaction between the MH system components over time and the impact of the potential changes on the technical performance of the system. Such approaches have potential future application in assisting with service planning and decision-making in other health systems and socio-economic contexts.

模拟先前实施的护理方案对当地精神卫生系统的影响:比斯卡亚(西班牙)自信的外展团队的经验。
目的:本研究使用从生态系统角度衍生的方法,评估了在西班牙比兹卡亚(Bizkaia)精神卫生(MH)系统中实施的专业流动社区护理团队(自信外展团队或aot)的相互作用和影响。方法:首先,专家评估系统的服务,并根据国际分类系统编纂。其次,遵循专家知识启发的迭代方法,开发了显示系统组件相互依赖关系的客户流程图。它包括变量及其在因果模型中表示的关系。第三,确定了aot具有主要影响的系统元素(应力节点)。第四,对三种情景(代表系统“压力点”的变量组合)进行建模,以评估其相对技术效率(技术绩效指标)。结果:分类系统确定了AOTs对原始自信的社区治疗模式缺乏保真度,将其归类为非急性低强度流动护理。因果模型将系统的以下要素确定为与辅助护理相关的“压力节点”:用户家庭;社会服务(在医疗保健系统之外);急性医院;非急症住院设施,以及在较小程度上急症住院日托服务。当医疗保健系统内部的压力节点分别建模时,急性和非急性医院护理服务导致系统性能的严重恶化,而急性日间医院护理仅产生很小的影响。结论:从生态系统角度建立的基于专家知识的因果模型有助于整合从纳米到宏观的不同层面的信息,以确定系统中可能受潜在政策干预(如关闭AOTs)影响最大的组成部分。它还能够说明MH系统组件之间随时间的相互作用以及对系统技术性能的潜在变化的影响。这些办法将来有可能应用于协助其他卫生系统和社会经济情况下的服务规划和决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.80
自引率
1.20%
发文量
121
审稿时长
>12 weeks
期刊介绍: Epidemiology and Psychiatric Sciences is a prestigious international, peer-reviewed journal that has been publishing in Open Access format since 2020. Formerly known as Epidemiologia e Psichiatria Sociale and established in 1992 by Michele Tansella, the journal prioritizes highly relevant and innovative research articles and systematic reviews in the areas of public mental health and policy, mental health services and system research, as well as epidemiological and social psychiatry. Join us in advancing knowledge and understanding in these critical fields.
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