Piroddi Roberta, Astbury Andrea, Baker Wesam, Daras Kostantinos, Rafferty Joe, Buchan Iain, Barr Benjamin
Department of Public Health Policy and Systems, University of Liverpool, Brownlow Street, Liverpool, L69 3GF, UK.
NHS Cheshire and Merseyside Integrated Care Board, 920 Centre Park Square, Warrington, WA1 1QY, UK.
BMC Health Serv Res. 2025 Jan 27;25(1):152. doi: 10.1186/s12913-024-12100-x.
Adversity in childhood is increasing in the United Kingdom. Complex health and social problems affecting children cluster in families where adults also have high need, but services are rarely aligned to support the whole family. Household level segmentation can help identify households most needing integrated support. Thus, the aim was to develop a segmentation model to identify those households with children who have high levels of complex cross-sectoral needs, to use as a case-finding tool for health and social care services, and to describe characteristics of identified households, to inform service integration.
Working with stakeholders-in an English region of 2.7m population- we agreed a definition of families having complex needs which would benefit from service integration - including households with high intensity use, who had both physical and mental health problems amongst both adults and children and wider social risks. We then used individual and household linked data across multiple health and social care services to identify these households, providing an algorithm to be used in a case finding interface. Finally, to understand the needs of this segment, and to identify unmet need, to tailor support, we used descriptive statistics and Poisson regression to profile the segment and compare them with the rest of the population.
Twenty one thousand and five hundreds twenty seven households (8% of the population of the region) were identified with complex needs, including 89,631 people (41,382 children), accounting for 34% of health and social care costs for families with children, £362 million in total, of which 42% was on children in care of local authorities. The households had contact with 3-4 different services, had high prevalence of mental health problems, most frequently co-morbid with respiratory problems, with high mental health emergency service use particularly amongst teenage girls many of whom had no prior elective treatment for conditions.
Our model provides a potentially useful tool for identifying households that could benefit from better integration of services and targeted family support that can help break intergenerational transfer of adversity.
在英国，童年逆境现象日益增多。影响儿童的复杂健康和社会问题在成年人需求也很高的家庭中集中出现，但服务很少协同一致以支持整个家庭。家庭层面的细分有助于识别最需要综合支持的家庭。因此，本研究旨在开发一种细分模型，以识别那些有复杂跨部门高需求儿童的家庭，用作健康和社会护理服务的病例发现工具，并描述已识别家庭的特征，为服务整合提供参考。
在一个拥有270万人口的英格兰地区，与利益相关者合作，我们商定了对有复杂需求家庭的定义，这些家庭将从服务整合中受益，包括高强度使用服务的家庭，这些家庭的成年人和儿童都有身心健康问题以及更广泛的社会风险。然后，我们使用多个健康和社会护理服务的个人和家庭关联数据来识别这些家庭，提供一种可在病例发现界面中使用的算法。最后，为了解该细分群体的需求，识别未满足的需求，以定制支持措施，我们使用描述性统计和泊松回归对该细分群体进行描述，并将他们与其他人群进行比较。
识别出21527户有复杂需求的家庭（占该地区人口的8%），包括89631人（41382名儿童），占儿童家庭健康和社会护理成本的34%，总计3.62亿英镑，其中42%用于地方当局照料的儿童。这些家庭与3 - 4种不同服务有接触，心理健康问题患病率高，最常与呼吸问题共病，心理健康紧急服务使用率高，尤其是在少女中，其中许多人之前没有针对相关病症的选择性治疗。
我们的模型为识别那些可能从更好的服务整合和有针对性的家庭支持中受益的家庭提供了一个潜在有用的工具，这有助于打破逆境的代际传递。
