Health is the cornerstone of life. Protecting the health of individuals receiving welfare support, including public assistance recipients, is especially important. Since 2021, welfare offices in Japan have been obliged to implement health management support programs for public assistance recipients. To provide health and life support efficiently and effectively, we have developed a new tailor-made support method using a marketing technique.
In marketing, the target audience for services is classified according to their characteristics (segmentation) to identify priority individuals and design services tailored to these characteristics. In applying this approach, we used data on public assistance recipients aged ≥65 years to extract five distinct segments via soft clustering, a machine learning technique. We examined the similarities between the extracted segments and public assistance recipients in practice by interviewing caseworkers at welfare offices. The results showed that caseworkers perceived several segments as those in practice. Moreover, we extracted segments with characteristics that caseworkers had not been aware of previously.
Accordingly, we have been developing a tailor-made health support system that presents support plans for each segment.
Article: Ueno, K., Nishioka, D., Saito, J. et al. Identifying meaningful subpopulation segments among older public assistance recipients: a mixed methods study to develop tailor-made health and welfare interventions. Int J Equity Health 22, 146 (2023).