Share of residential care schemes requiring co-payment
| Quick info | |
|---|---|
| Data type | Numeric |
| Scale | Metric |
| Value labels | Not Applicable |
| Technical name | health_ltc_gen_lob_resi_copay_share |
| Category | Health and long-term care |
| Label | Share of residential care schemes requiring co-payment |
| Related indicators | NA |
This indicator provides information on the share of residential care benefit schemes requiring any kind of private copayment. Residential care refers to long-lasting provision of LTC services in an institutional live-in setting where care recipients reside jointly with other persons in need of care and receive accommodation, household services and meals besides nursing and care services. Copayments refer to the participation of benefit recipients in paying the costs for receiving said benefit.
Coding rules
The indicator is calculated by summing the occurrences of indicators confirming a co-payment requirement across the identified residential care benefits and dividing the result by the total number of residential care benefits for people in need of LTC in the country, from which data were collected. The minimum value of 0 indicates that no residential care benefit in the system requires co-payments. The maximum value of 1 indicates that all in-kind benefits provided in the system are residential care schemes and that they all require a co-payment. Benefits whose availability is known but for which no information on eligibility was available were not included in the calculation. Missing values coded in the following way: The code -888 is employed for countries which do not have a long-term care system (see Fischer, Sternkopf & Rothgang, 2023; de Carvalho & Fischer, 2020); these countries were excluded from data collection. The code -999 is employed for cases where information is missing. The code -777 is employed if a benefit type is not present in the country. Multiple data sources were employed and triangulated for constructing the indicator: national laws and regulations, academic publications and grey literature and websites such as report series from international organisations. The quality of each data point is rated by two quality ratings, plausibility and reliability assessment. Plausibility concerns are indicated if a) contradicting information was retrieved by stating “Yes, due to contradicting sources”; b) information was limited to single and/or unsound sources and values are thus uncertain stating “Yes, due to limited sources”. The reliability rating is based on two parameters: the type of sources and information triangulation between different sources. There are three levels of reliability as defined below:
- High reliability
- Information is contained in an official law or comparable legislative document in vigour during the analysed time-point. OR
- Information is consistent across at least three different sources, with two of them being either an independent, uncorrelated scientific publication (e.g., academic papers and chapters in books) and/or official government-related sources (e.g., ministry websites, government reports and bulletins).
- Medium reliability
- Information is consistent across at least three different sources, none of which is either a law, a scientific publication, or an official government-related source. OR
- Information is consistent across less than three different sources, with at least one of them being a scientific publication or an official government-related source.
- Low reliability
- Information is consistent across less than three different sources, none of which is either a law, a scientific publication, or an official government-related source.
The same ratings apply to the results of the calculation as follows. To reflect the impact that the data used, and their plausibility, have on the final result, plausibility concerns reflect the lowest quality rating among the data used in the calculation. That means that if at least one data presented some concerns due to contradicting or limited sources, this will be reflected in the plausibility assessment of the calculations. The same principle applies to reliability assessments for the result of calculations, that means that the lowest assessment among the data used for the calculation will be attributed to the results. Definitions and data collection procedures are outlined in detail in Viero & Fischer (2025).
Bibliographic info
Citation:- Viero, D., & Fischer, J. (2025). Comparative Assessment of Long-term Care System Generosity: Mapping Benefits and Inclusiveness Internationally. SOCIUM SFB 1342 WorkingPapers.
- Fischer, J., Sternkopf, M., & Rothgang, H. (2023). Covering a new social risk: The introduction of long-term care systems worldwide. In I. Mossig & H. Obinger (Eds.), SOCIUM SFB Working Papers: Vol. 25. Mapping Global Dynamics of Social Policy (pp. 32–35). Bremen: Collaborative Research Centre 1342. https://doi.org/10.26092/elib/2559
- De Carvalho, G., & Fischer, J. (2020). Health and long-term care system introduction and reform – concepts and operationalisations for global and historical comparative research. SFB 1342 Technical Paper Series, 3. https://doi.org/10.26092/ELIB/539
Misc
Project manager(s): Davide Viero and Johanna Fischer (on behalf of the A07 project)
- Version 0.001: Initial release.
Revisions: No revisions yet
Sources
- Please see Viero, D., & Fischer, J. (2025). Comparative Assessment of Long-term Care System Generosity: Mapping Benefits and Inclusiveness Internationally. SOCIUM SFB 1342 WorkingPapers.
