Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08002 Barcelona, Spain.
Municipal Institute of Social Services, 08009 Barcelona, Spain.
Int J Environ Res Public Health. 2022 Feb 12;19(4):2053. doi: 10.3390/ijerph19042053.
An aging population and rising life expectancy lead to an increased demand for social services to care for dependent users, among other factors. In Barcelona, home social care (HSC) services are a key agent in meeting this demand. However, demand is not evenly distributed among neighborhoods, and we hypothesized that this can be explained by the user's social environment. In this work, we describe the user's environment at a macroscopic level by the socioeconomic features of the neighborhood. This research aimed to gain a deeper understanding of the dependent user's socioeconomic environment and service needs. We applied descriptive analytics techniques to explore possible patterns linking HSC demand and other features. These methods include principal components analysis (PCA) and hierarchical clustering. The main analysis was made from the obtained boxplots, after these techniques were applied. We found that economic and disability factors, through users' mean net rent and degree of disability features, are related to the demand for home social care services. This relation is even clearer for the home-based social care services. These findings can be useful to distribute the services among areas by considering more features than the volume of users/population. Moreover, it can become helpful in future steps to develop a management tool to optimize HSC scheduling and staff assignment to improve the cost and quality of service. For future research, we believe that additional and more precise characteristics could provide deeper insights into HSC service demand.
人口老龄化和预期寿命的延长导致对社会服务的需求增加，以照顾依赖用户等因素。在巴塞罗那，家庭社会护理 (HSC) 服务是满足这一需求的关键因素。然而，需求在各社区之间分布不均，我们假设这可以用用户的社会环境来解释。在这项工作中，我们通过社区的社会经济特征来描述用户的宏观环境。这项研究旨在更深入地了解依赖用户的社会经济环境和服务需求。我们应用描述性分析技术来探索可能的模式，将 HSC 需求与其他特征联系起来。这些方法包括主成分分析 (PCA) 和层次聚类。在应用这些技术之后，我们主要从获得的箱线图进行分析。我们发现，经济和残疾因素，通过用户的平均净租金和残疾程度特征，与家庭社会护理服务的需求有关。对于家庭为基础的社会护理服务，这种关系更加明显。这些发现可以通过考虑比用户/人口数量更多的特征来帮助在各个区域分配服务，此外，它还可以在未来的步骤中开发管理工具，以优化 HSC 调度和人员分配，从而提高服务的成本和质量。对于未来的研究，我们认为更多和更精确的特征可以提供更深入的了解 HSC 服务需求。
