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Typology of LTC systems based on system characteristics Markus Kraus, Thomas Czypionka, Monika Riedel, Gerald Röhrling, Andreas Goltz 8 th European Conference on Health Economics Connecting Health and Economics 7 th – 10 th of July, Helsinki. Outline. Introduction Data collection Method - PowerPoint PPT Presentation
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Typology of LTC systems based on system characteristics
Markus Kraus, Thomas Czypionka, Monika Riedel, Gerald Röhrling, Andreas Goltz
8th European Conference on Health Economics Connecting Health and Economics
7th – 10th of July, Helsinki
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Outline
Introduction
Data collection
Method
Variables
Results
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Introduction
ANCIEN is a research project financed under the 7th Research Framework Programme of the European Commission. The project includes 20 partner institutions from EU member states such as CEPS, CPB, DIW, FPB, IHS, LSE and is organized in 7 work packages. It started in January 2009 and will last 44 months.
The objective of the project is: to review the long-term care (LTC) systems in EU member states,
to assess the actual and future numbers of elderly care-dependent people in selected countries and
to develop a methodology for comprehensive analysis of actual and future LTC needs and provision across European countries, including the potential role of technology and policies on maintaining and improving quality
The objective of WP 1 is to portray long-term care systems in light of provision of care and financing and to derive a typology of LTC systems.
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Data collection - literature review
Literature review to identify relevant typologies, indicators, variables
Topic Literature Sources
Entitlement WHO 2003, Da Roit, Le Bihan, Österle 2007
Financing: tax (Beveridge) / insurance contribution (Bismarck)
Pacolet et al. 1999, WHO 2003, Pommer et al. 2007
Target: poor / non-poor, Income testing
WHO 2003, Pommer et al. 2007, Da Roit, Le Bihan, Österle 2007
Family support as a criterion
WHO 2003
Flexibility of criteria, e.g. assessment process
WHO 2003, Da Roit, Le Bihan, Österle 2007
Level of benefits, e.g. level of cash allowance
WHO 2003, Da Roit, Le Bihan, Österle 2007
Coverage by disabilities
WHO 2003
Cash benefits
WHO 2003
Informal carer: time provided, time off-work, subsidies
Bettio, Plantenga 2004
(De-)Centralization of legislation, implementation and financing
Glendenning et al. 2004, Da Roit, Le Bihan, Österle 2007
Capacities for formal care Pacolet et al. 1999, Pommer et al. 2007
Take-up of care by care settings Pommer et al. 2007, Da Roit, Le Bihan, Österle 2007
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Data collection – questionnaire, problems
Questionnaire was designed and sent to the national experts. It was organized in several blocks of questions focussing on macrostructure, funding and financing, informal care, formal institutional care, formal home based care and policy issues.
Approach: Availability and comparability of quantitative data is rather limited (even when cooperating with national experts)
Two fold strategy to derive typology:
Approach 1: focuses on system characteristics; it relies on qualitative characteristics and uses ordinal scaled variables; including all 22 countries
Approach 2: focuses on use and financing; it is based on quantitative information and uses metric and pseudo-metric variables; including only a selection of countries
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Method (1)
2-step-procedure to derive the typology based on system characteristics
1st step:
Allocate variables to one of two groups, one describing the organizational depth and one the financial generosity of LTC systems, and recode all variables with ordinal values.
Rationale behind coding: „Which system characteristic is more preferable from the patient‘s point of view?“
Most preferable option was coded „3“, least preferable option was coded „1“.
By summing up the organization variables one gets an index in which countries with high values could be interpreted as countries with high degree of patient friendliness and vice versa.
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Method (2)
By summing up the funding variables one gets an index where countries with high values could be interpreted as countries with high degree of patient friendliness and vice versa.
2nd step:
Formal cluster analysis with SPSS K means clustering algorithm
𝑂𝑟𝑔𝑎𝑛𝑖𝑠𝑧𝑎𝑡𝑖𝑜𝑛 𝑑𝑒𝑝𝑡ℎ: 𝑋𝑖 = σ 𝑂𝑗𝑖𝑛𝑗=1 , 𝑖 = 1,…,22, 𝐹𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑔𝑒𝑛𝑒𝑟𝑜𝑠𝑖𝑡𝑦: 𝑌𝑖 = σ 𝐹𝑘𝑖𝑚𝑘=1 , 𝑖 = 1,…,22,
where 𝑖 are the 22 countries of our data set, 𝑂𝑗are the organizational variables and 𝐹𝑘are the
financial variables.
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Variables
Organizational depth: Means-tested access
Entitlement
Availability of cash benefits
Choice of provider
Quality assurance
Integration / coordination of care
Financial generosity: Cost sharing
Public expenditures as share of GDP
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Results (1)
Source: own compilation
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Results (2)
Western countries tend to have LTC-systems with a higher degree of patient friendliness.
Organizational depth: there is NO clear distinction between Western and Eastern European countries. Only Lithuania, Poland, Romania, and to a lesser degree Hungary are lacking behind in this matter.
Financial generosity: a gap between Western and Eastern European countries can be observed. Western European countries tend to be more generous to care recipients than Eastern European countries.
A Scandinavian, Continental and Mediterranean country group cannot be exactly identified but there is some degree of compatibility to this classification.
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Results (3)
The Eastern European countries do not form a cluster by themselves. Though sharing the feature of low spending on LTC, they differ widely with regard to organizational aspects.
Not even the Baltic States are altogether in one cluster. They are spread over three clusters.
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Thank you for your attention!
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Contact
Markus Kraus
Institute for Advanced Studies (IHS)Stumpergasse 56A- 1060 Vienna
Phone: +43 1/59991 141 E-Mail: [email protected]
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LTC system characteristics by country
Countries Organizational depth Xi Financing generosity Yi
Means tested access
Entitlement Cash benefits Choice Quality
assurance Integration Cost sharing
Public expenditures
Austria 3 1 3 3 1 3 14 1 3 4
Belgium 3 3 3 3 3 3 18 2 4 6
Bulgaria 3 3 1 3 3 2 15 1 1 2
Czech Republic 3 3 2 3 2 2 15 1 1 2
Denmark 3 3 1 2 3 3 15 3 4 7
England 1 2 3 3 3 2 14 2 2 4
Estonia 3 3 3 3 3 2 17 1 1 2
Finland 3 3 3 1 1 3 14 1 4 5
France 3 3 2 3 3 2 16 2 3 5
Germany 3 3 2 3 3 2 16 3 2 5
Hungary 3 3 1 3 2 1 13 2 1 3
Italy 1 3 3 2 3 2 14 2 4 6
Latvia 1 3 2 3 2 3 14 3 1 4
Lithuania 1 3 2 3 1 2 12 1 2 3
Netherlands 3 3 2 3 3 2 16 1 5 6
Poland 1 3 2 3 1 2 12 1 1 2
Portugal N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
Romania 2 1 1 3 3 1 11 2 1 3
Slovakia 3 3 2 3 3 2 16 2 1 3
Slovenia 3 3 3 3 1 2 15 2 3 5
Spain 1 3 3 2 3 2 14 2 2 4
Sweden 3 3 1 3 3 3 16 1 5 6
Source: own compilation