In western countries, health care systems emerged at the end of the 19th century and in the first third of the 20th century; in the so-called “golden age” of the welfare state they then came to full development. In many low-income countries of the Global South, they remained undeveloped or underdeveloped. In recent decades, however, the emergence of complex health care policies in the Global South can be observed, as well as restructuring, privatization and re-regulation in the Global North. Long-term care (LTC) has gained in importance. In most Western countries, welfare state expansion in this area has taken place in a phase of “permanent austerity”, whereas in the Global South LTC has only recently been addressed by social policy. This will change drastically in the coming years, however, because the Global South will be most affected by demographic ageing.
Project A04 examines developments in both policy areas – health and LTC policy – in a global perspective. We assume that the development of LTC systems can only be understood by considering the specifics of the health care system within which they develop. The aim of the project is to globally trace the development of different types of health care systems and LTC systems and to explain to what extent similarities and differences between these national systems are structured by: a) horizontal relations of social, economic and political exchange between countries and b) vertical exchange relations between countries and international organisations. In a first phase, the project will explore the introduction and expansion of health and LTC systems and their spatial distribution around the globe. In a second phase the findings will be elaborated by examining the expansion of the health care and LTC services regarding scope (generosity) and the population groups covered (degree of inclusion).
Please see here for project publications: https://socialpolicydynamics.de/projects/completed-projects/project-a04-2018-21-/publications
PUBLICATIONS & OTHER OUTPUTS
|Output 1||Fischer et al. (2022) Comparing long-term care systems: A multi-dimensional, actor-centred typology |
Abstract: Like other fields of social policy, the organization of longterm care (LTC) varies temporally and geographically. The present article aims to advance the comparison of LTC systems worldwide by proposing a conceptual framework to analyse variation, putting a special focus on analysing the role of public and private actor types. In a precluding literature review of existing LTC typologies, we find that there are various promising classification approaches, but with an overwhelming concentration on European countries and often constructed in-transparently and superficially. Building on the concept of the care/welfare mix, we develop a multi-dimensional, actor-centred typology of LTC systems. In doing so, we employ the methodological procedure of theoretically constructing a typological attribute space. We argue that three dimensions, that is service provision, financing and regulation, are crucial for differentiating types. Furthermore, we chose an actor-centred approach, asking who bears the main responsibility in each dimension. Five relevant types of corporate actors are distinguished: state, societal actors, private for-profit actors, private individual actors, and global actors. Finally, we present and discuss the resulting attribute space and further illustrated the typology's use by exemplarily classifying three countries.
|Output 2||othgang et al. (2021) The classification of distinct long-term care systems worldwide: the empirical application of an actor-centered multidimensional typology |
Abstract: Long-term care (LTC) systems vary between countries in several ways. One important difference exists with regard to the question of who, that is which type of corporate actor, takes over the main responsibility in providing, financing and regulating LTC. In this article, we employ a multi-dimensional, actor-centered typology of LTC systems to classify all distinct LTC systems existing worldwide at the point in time when they were first established. In doing so, the article contributes to comparative LTC research by including novel cases and adding a historical perspective. Our 18 cases fall into eight types, which we combine tentatively into three distinct clusters: A predominantly state regulated and financed cluster, a state regulated cluster with mixed financing and provision, and a cluster with private regulation and provision plus societal financing. We find that the state plays the major role in regulation (dominant in 16 countries) and financing (dominant in 11 countries), while in provision we see a broader distribution with societal and private for-profit actors taking a major role. Interestingly, and in contrast to healthcare systems, no societal pure type emerges, not even among social insurance countries.
|Output 3||Fischer et al. (2022) Introduction of Long-Term Care Systems: The Nascent Diffusion of an Emergent Field of Social Policy |
In the present chapter, we aim to investigate what factors—international as well as domestic—have so far contributed to the introduction of LTC systems under public responsibility for the elderly worldwide. That is, our explanandum is the point in time at which states first adopted statutory entitlements concerning social protection for LTC for (at least) the old-age population. To this end, we employ data on introduction points taken from the novel Historical Long-Term Care Systems Dataset (Fischer and Sternkopf 2021). In particular, we investigate the relevance of channels of horizontal diffusion, that is, geographic proximity, cultural similarity and colonial ties, the influence of the European Union as well as domestic factors such as problem pressure, and women’s political empowerment.
KEYWORDS / CATEGORIES
|Topics||Financing LTC | Governance and LTC systems organisation | LTC Policy | LTC Reforms | LTC Systems|
|Funding type||Public (including government)|
|Methods||Comparative policy analysis | Document analysis | Literature reviews and synthesis | Mixed methods | Quantitative data analysis|