Impact of Socioeconomic Environment on Home Social Care Service Demand and Dependent Users
Daniel Badell,
Jésica de Armas and
Albert Julià
Additional contact information
Daniel Badell: Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08002 Barcelona, Spain
Albert Julià: Municipal Institute of Social Services, 08009 Barcelona, Spain
IJERPH, 2022, vol. 19, issue 4, 1-21
Abstract:
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.
Keywords: social support; home care; caregivers; socioeconomic features; descriptive analytics; hierarchical clustering (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.mdpi.com/1660-4601/19/4/2053/pdf (application/pdf)
https://www.mdpi.com/1660-4601/19/4/2053/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:19:y:2022:i:4:p:2053-:d:747788
Access Statistics for this article
IJERPH is currently edited by Ms. Jenna Liu
More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().