EUGLOREH project




11.6. Financing healthcare

11.6.4. Description of arrangements for pooling and purchasing, including benefit entitlement


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11.6.4. Description of arrangements for pooling and purchasing, including benefit entitlement


Fund pooling refers to the accumulation of prepaid healthcare revenues for a given population. There are cases where the collection and pooling of resources occurs within the same body, like when taxes are collected and also pooled at national or regional level. However, in order to spread the financial risk across the population, in cases where there are multiple collection agents as in some countries with social health insurance funds (Table 11.14), the resources generated by the funds may be pooled and then distributed to the funds. Pooling enhances efficiency because it reduces incentives for risk selection (in social health insurance systems) and may break historical patterns of politically driven resource allocation. It also increases equity and solidarity principles by sharing risks across a larger population. Generally, the extent of pooling will depend on how much of the revenues collected are pooled through a single fund or plan and whether different sources of funding are pooled or remain separated. In most countries, funds are pooled at a single, national body which has advantages of enhancing equity of access and administrative efficiency. Countries that do not pool resources at national level are those where taxes are collected locally or where individual health insurance funds are responsible for collecting their own insurance contributions (Thomson, Foubister and Mossialos 2008). In Austria and Germany (with 21 and about 290 insurance funds, respectively) 100% of funds are redistributed; the Czech Republic also aims at increasing the amount pooled from its current level of 60% to 100% by 2009 (Thomson, Foubister and Mossialos 2008).


Purchasing refers to the transfer of pooled resource to service providers on behalf of the population for which the funds were pooled. Purchasing plays a key role in ensuring equity of access to healthcare and equality and efficiency in healthcare delivery. Matching healthcare resources to healthcare need is a key means of ensuring value for money (and therefore sustainability) in health systems. Thus, the role of purchasing is paramount. In some cases, the revenue collection agents are also the purchasers (e.g. social insurance funds), whereas in countries with tax-financed health systems (except Cyprus, Ireland and Malta), the purchasing agent does not with pooling and resource collection, e.g. local health authorities or special purchasing organizations such as primary care trusts in England (Thomson, Foubister and Mossialos 2008). In order to allocate resources to the purchasers, there are various mechanisms ranging from full retrospective reimbursement to prospective reimbursement with budgets. Passive and retrospective reimbursement of all provider costs has been identified as the weakest element in most health systems. Recent years have seen a slow, piecemeal improvement in the development of more strategic purchasing relying on an active (e.g. with explicit performance contracts) rather than passive approach (e.g. full retrospective reimbursement) (Robinson et al, 2005). See section 11.3.4. Technical efficiency for information on provider payment methods.



Redistribution (or distribution) from pooling to purchasers is made more and more according to a resource allocation mechanism that is adjusted depending on the risk profile of the population covered by the pool. As people’s healthcare needs vary depending on personal and social characteristics, risk adjustment is needed to enable the cost of each plan or insurance fund member to reflect their relative healthcare expenditure needs. Increasingly, in Europe the method used to determine the budgets of the purchasers is capitation (i.e. the amount is determined based on the number of individuals in the region/fund) with some type of risk adjustment. However, many health systems continue to allocate resources on the basis of political negotiation or historical precedents.


Resource allocation based on risk adjusted capitation aims at re-allocating resources according to population needs, as well as consumer preferences and priorities. The broad goals of risk adjustment relate to equity (equal distribution of resources of funds, ensuring equal access for equal need) and efficiency (to minimize the possibility of sickness funds engaging in risk selection and to shift the financial risk onto the providers). While there is some overlap between these two aims, the former is associated more with tax-funded health systems to minimize regional inequity, and the latter with social health insurance systems, in particular where there is competition between funds (as in Belgium, the Czech Republic, Slovakia, Germany and the Netherlands). For example, redistribution of resources from relatively resource-rich regions to resource-poor regions in England is based on the risk adjustment formula that aims at: a) ensuring all health plans have a fair resource base with which to purchase health services for their population; and b) adjusting the resource base of the health plans according to variations in the need profile of the population.


One of the challenges with risk adjustment is that regional governments and health insurance funds are often reluctant to surrender revenues they have collected for redistribution to other regions. Moreover, risk adjustment mechanisms implemented to prevent risk selection amongst competing sickness funds in social insurance systems, such as Germany and the Netherlands, and in systems with regional health plans that may have different revenue bases and population risk profiles to ‘level the playing field’, require significant information at individual level to measure: a) the relative sickness of their insured population; and b) the size of their revenue base (incomes of the insured). Risk adjustment therefore incurs high transaction costs.


The potential for health insurance funds to identify and preferentially select the ‘good risks’ (healthier individuals) increases when budget allocations are established based on crude weightings of age and sex. More sophisticated formulae generate significant costs and require technical capacity for their implementation. For example, public health expertise to assess population health needs and outcomes, along with evaluation abilities to assess evidence of the cost-effectiveness of health interventions, can be critical. In many countries this information and expertise is limited or non-existent, in particular in countries of central and Eastern Europe (Thomson et al 2004). Even in the countries with the greatest experience in developing risk adjustment formulae, such as the social insurance systems listed above and England (where risk adjusted capitation has been used since the 1970s), there are doubts as to whether these are operating as intended (Rice and Smith 2002). An analysis of the risk adjustment schemes in place in five countries (Belgium, Germany, Israel, the Netherlands and Switzerland) in 2000 showed that relatively poor predictors of future healthcare consumption were used to adjust for risk. Thus, funds still have strong financial incentives towards risk select, while there is some evidence of risk selection activities (van de Ven et al, 2003). Even if the risk-adjustment mechanisms improved in the above five countries during the 2000-2005 period,  there was also increased evidence of risk selection therefore undermining some of the potential advantages of competition among insurance funds (van de Ven et al 2007).


Table 11.14. Collection and allocation of funds, and description of the resource allocation schemes





Collection agent

Allocation agent


Capitationfactors included


22 social security institutions

Each fund allocates

22 funds

No risk pooling across funds. No capitation.


National Social Security Department (RSZ/ONSS). The National Institute for Sickness and Disability Insurance (RIZIV/INAMI) for contributions of self-employed.

The National Institute for Sickness and Disability Insurance (RIZIV/INAMI)

100 competitive sickness funds

Age, sex, unemployment, disability, mortality, urbanization, income


National Revenue Agency

National Revenue Agency (central taxes)

National Health Insurance Fund (insurance premiums)

Ministry of Health (tax revenue), Municipalities (tax revenue)

28 Regional Health Insurance Funds (insurance revenue).


Insurance revenue: Age, historical allocations,

and estimates of future health-related needs



State treasury

State treasury




Ministry of Finance

Ministry of Health



Czech Republic

General fund + 7 sector/enterprise funds*

Each fund allocates




14 counties and the State

Each county allocates. State allocates to counties.

14 regional councils

Age, children of single parents (and local tax base)


HM Revenue and Customs (HMRC)

Department of Health

152 Primary care trusts (regional health plans)

Age, mortality, morbidity, unemployment, elderly living alone, ethnic origin, socioeconomic status (and cost variation)


Taxation Agency

Estonian Health Insurance Fund with 7 regional departments

Regional branches of EHIF

Capitated allocation only for primary care: Age


State, municipalities, and National Health Insurance

Each municipality allocates. State allocates to municipalities. Social Insurance institution allocates

452 municipalities

Age, disability, archipelago, remoteness (and local tax base)


Union de Recouvrement des Cotisations de Sécurité et dAllocations Familiales at local level

Agence Centrale des Organismes de Sécurité Sociale

25 regions



355 sickness funds

Federal Insurance Office

355 competitive sickness funds

Age, sex (and fund’s income base)


30 social health insurance funds. Ministry of Finance. Ministry of Health.

Each fund allocates. Ministry of Finance allocates to NHS and insurance funds to cover deficits.

30 sickness funds (employment based)

No capitation. Allocation based on historical precedent and political choice


National fund + network of 19 county offices

Each county office allocates









Department of Finance

Department of Health

8 health boards

No capitation. Services funded based on DRGs


Ministry of Finance and Regions

Ministry of Health and Regions

21 regional governments

Age, sex, mortality  (one third based on historical spend)



SCHIA allocates funds to 8 regional funds


Size and age structure


State Social Insurance Council

State Sickness Fund




Union of Sickness Funds

Union of Sickness Funds

9 sickness funds (employment based)

No capitation. Full risk pooling


Ministry of Finance

Ministry of Health




Ministry of Finance. Sickness Fund Scheme

Ministry of Health. Sickness Fund Scheme

26 competitive sickness funds

Age, sex, welfare or disability status, urbanization (and fund’s income base)

Northern Ireland

HM Revenue and Customs (HMRC)

Department of Health

4 health boards (geographically based)

Mortality, elderly living alone, welfare status, low birthweight (and rural cost adjustment)


Norwegian Tax Administration in Ministry of Finance (comprises the Directorate of Taxes, 19 county tax offices, 18 tax collectorsoffices, 431 municipality tax offices.

Ministry of Finance General Purpose Grant Scheme

19 county governments  (geographically based)

Mortality, elderly living alone, marital status (and local tax base) (50% of funding based on DRGs)


16 regional funds + 1 trade fund

Each fund allocates


Equalization fundage, average income


Ministry of Finance

Ministry of Health

5 regional health authorities

Age, relative burden of illness: diabetes, hypertension, TB, AIDS (84.5% based on historical spend)


42 District health insurance funds and 2 national funds administered by Ministries of Transportation and national security; and Ministry of Health (taxes)

National Insurance Fund and Ministry of Health

42 insurance funds and 2 national funds

mix of population risks


HM Revenue and Customs (HMRC)

Department of Health

15 regional health boards

Age, sex, mortality (and rural costs)


5 health insurance companies

Each fund allocates


Age, sex


National Health Insurance Institute

Each fund allocates




Central Ministry of Health

Central Ministry of Health

7 autonomous communities

Cross-boundary flows, declining population adjustment


National government; Swedish Social Insurance Agency; 21 county councils; 290 municipalities

National government; county councils and municipalities.

9 health care authorities (geographically based)

Age, living alone, employment status, housing tenure, previous inpatient diagnosis


93 sickness funds

Joint Organization of Insurers (known as Foundation 18)

Competitive sickness funds

Age, sex, region (and fund’s income base)


Ministry of Finance; Social insurance funds (SSK; GERF; Bag-Kur)

Ministry of Health; Social insurance funds

Ministry of Health; Social insurance funds



HM Revenue and Customs (HMRC)

Department of Health

5 health authorities (geographically based)

Age, sex, mortality (cost adjustment for sparse population)

Sources: Rice and Smith 2002; HiTs; Thomson et al 2004

* As communicated by the Czech partner, since 2007 8 funds are present in Czech Republic; these funds are also purchasers of health care services.


Defining benefits and beneficiaries


In recent decades there has been a trend towards extending coverage to health services to the whole population. Indeed, all OECD countries cover 100% or almost 100% of the population to statutory health insurance. In some countries with systems funded by social health insurance, the attainment of universal coverage is fairly recent and represents a shift from coverage being defined on the basis of payment of contributions to coverage based on residence: Belgium in 1998, France in 2000 and the Netherlands in 2006 (Thomson, Foubister, and Mossialos 2008). At the same time, there has been an increase in user charges in some countries, which has eroded coverage to some extent. Note that data on universal coverage may be misleading, in particular in the case of Germany. The situation is complex because of the public-private mix, such that privately insured individuals are not counted as insured by statutory insurance although the numbers of uninsured is very low. In CEE countries, while universal coverage of the population has been maintained in theory, inadequate financing and informal payments have led to the exclusion of some groups. Moreover, evidence suggests that public spending on health and social assistance programmes may not be meeting those in need, and tends to benefit the non-poor disproportionately (Thomson et al, 2004). There are also significant differences in the level of resources allocated between capital cities and other cities, and between urban and rural areas; these geographical inequalities may have even increased over the 1990s (Thomson et al, 2004).


Historically, the scope of benefits has been relatively comprehensive in European countries, although pressures from having to fund many and expensive health services are increasing. Defining a package of benefits (limiting what is covered) has been seen as one option to cope with the discrepancy between available (public) resources and existing (perceived) demands. Coverage of a population for health services has been characterized in three dimensions: breadth – the extent of the covered population; depth – the number of character of the covered services; and height – the level of cost-sharing (Schreyögg et al, 2005). With regards to height, it is important to notice the clear link between the benefits package and the level of cost sharing in the system; where services are not fully reimbursed the patient must pay the remainder out of his/her own pocket (see Sections on out-of-pocket payments and informal payments). Benefits packages or catalogues can be established in many ways, including legislation passed by central or regional governments, decrees by central or regional governments, directives by self-governing bodies or national/local authorities, and ‘quasi-laws’ or guidelines (Schreyögg et al, 2005).


In many countries, there is a legal basis for entitlement to healthcare services. Benefits packages are an essential part of social health insurance systems. Not only they clarify the entitlements to healthcare for citizens, they also facilitate reimbursement for providers and control the diffusion of new technologies. Less explicit definition of benefits is seen in the tax-funded NHS-style systems. The vaguest definition of benefits can be seen in England, where all services should be required as considered reasonable by the Secretary of State for Health (Schreyögg et a.. 2005).


In recent years, factors such as the rising demand by patients coupled with supplier-induced demand, the ‘medicalization’ of society and rising healthcare costs have put pressure on decision-makers to place limits on the broad frame of social health insurance systems (Gibis et al, 2004). While there is growing discussion about the possibility of restricting the benefits packages in social health insurance countries to only the core basic and medically necessary services, so far no country has been able to do so. Countries have responded by making use of two types of regulations that may be implicit, such as negative lists, or explicit, such as positive lists to define benefits packages.


Most countries rely on a combination of positive lists (e.g. benefits catalogues) and negative lists for the different sectors. For instance, in ambulatory care, many countries make use of explicit regulation i.e. a benefits catalogue or positive list (in the case of Austria, the list is not closed, rather additional benefits are possible on an individual basis) with the exception of the Netherlands (which uses a negative list for specialist care) and Switzerland (no regulation). For inpatient care, Austria, Belgium and Luxembourg rely on explicit regulation of the benefits package; in the Netherlands they also use negative list, while there is no regulation in France, Germany and Switzerland (Gibis et al, 2004). All countries explicitly regulate medical devices, and all but Germany (implicit) do so for pharmaceuticals. Decisions regarding benefit catalogues can only be formally challenged in some countries, such as for pharmaceuticals in Austria and Switzerland, and for other services in ‘social courts’ in Austria and Germany, or civil courts in Belgium and the Netherlands (Gibis et al, 2004). Unlike social health insurance and private health insurance systems, coverage through many national health service-type systems is not based on a defined list of benefits. For instance, in the UK, under the National Health Service Act, the Secretary of State for Health has a duty to provide a health service ‘to such an extent as he considers necessary to meet all reasonable requirements’. Nevertheless, the use of HTA (NICE) is highly developed and used to define services negatively or positively.


In CEE countries, the shift from a general tax funded system towards social health insurance was believed to be a possible means of generating revenue and containing costs through reductions in the benefits package. There were attempts to define a more concise or ‘basicbenefits package to be financed from the social health insurance contributions in the hope that health insurance funds could collect additional revenue by offering the excluded benefits as ‘supplements’. However, in most cases, benefit changes occurred incrementally or not at all, and attempts to develop a systematic basic package often failed. Moreover, attempts to implement a basic benefits package were met with technical and political obstacles. On the one hand, information regarding the cost-effectiveness of interventions is either not available or extremely costly to obtain, whilst entitlements generally focus on individualized curative interventions rather than on wider population interventions and public health initiatives. On the other hand, citizens and politicians in this region see comprehensive and free healthcare as a right, and are not ready to accept cuts in benefits. Opposition also comes from providers, who would see a reduction in income, being defined by benefit levels (Thomson et al, 2004).


Health technology assessment (HTA) has assumed an increasing role in national priority-setting. The general objective of HTA is to evaluate the effects of technology on health, use of resources and other aspects of the health system (e.g., health care budgets, national economy). Moreover, HTA is also concerned with the societal, organization, legal and ethical consequences of implementing health technologies or interventions into the health system. HTA provides a range of stakeholders with accessible and evidence-based information, typically in the form of assessment reports, to support various decisions surrounding a given health technology or intervention. In many countries, programmes for HTA have been established either through the provision of new agencies or institutes, in academic units or governmental and non-governmental entities. While many countries have established bodies that are dedicated to HTA (e.g. National Institute for Sickness and Invalidity Insurance in Belgium, the Pharmaceuticals Pricing Boards in Finland, Norway, and Sweden, and the Pricing and Reimbursement Committee of the Medicines Agency in Italy), often the roles and responsibilities are unclear with duplication of resource use. For example, the groups involved in reimbursement and pricing decisions often differ from those engaged in the independent assessments.


Most review bodies can be categorized as serving either an advisory or regulatory role in the decision-making process, depending on the intent and type of assessment required (Zentner et al, 2005). For example, some countries, such as the Netherlands and Denmark, require the use of economic evaluations in reimbursement decision-making, while others (e.g. France) employ the assessments primarily to inform budgetary planning or guide clinical practice (Hutton et al, 2006). The heterogeneity of HTA bodies reflects the differentiated environments of European healthcare and political systems, with variations in mandates, funding mechanisms and roles in policy formulation.


While HTA programmes have generally enhanced transparency in decision-making processes through mechanisms such as independent systematic reviews, stakeholder involvement and the production of guidance (Sorenson et al, 2007), an explicitly-defined and cost-effective benefits package has not yet been achieved in any country. Barriers to a more effective use of HTA to ensure value for money include a lack of resources and technical expertise, lack of transparency in the criteria for inclusion or exclusion of interventions and – last but not least - a lack of political will to enforce the decisions based on HTA. The trend however appears to be towards a greater reliance on HTA to review existing and new services which will lead to an enhanced sustainability of the system in the future.




In recent years, health systems have moved towards changing the way in which they manage public health, focusing on performance and efficiency. In fact, much emphasis has been placed on evaluating the process and the accessibility to health services and on management costs, rather than assessing outcomes. However, Decision no. 1350/2007 of 23/10/2007, which regards the programPublic health: programme of Community action in the field of health, 2007-2013states that “Best practice is important because health promotion and prevention should be measured on the basis of efficiency and effectiveness, and not purely in economic terms. Best practice and latest treatment methods for diseases and injuries should be promoted in order to prevent further deterioration of health, and European reference networks for specific conditions should be developed”. Of interest is that outcome research is the “research on measures of changes in patient outcomes, that is, patient health status and satisfaction, resulting from specific medical and health interventions. Attributing changes in outcomes to medical care requires distinguishing the effects of care from the effects of many other factors that influence patientshealth and satisfaction” (Kane, 1997).

Indeed, the outcome of a specific procedure is not purely the result of medical care, but is also influenced by other factors such as the severity of cases and differences in clinical practice among populations, geographic areas or healthcare providers, and specific characteristics of the population being considered (e.g., socio-economic level, income) in, for example, a given geographic area or environment as opposed to another area or environment..

Through outcome research it is possible to measure the quality of the healthcare provided. According to many studies, hospital discharge records are a good source of data that are useful for implementing probabilistic models for assessing performance in terms of both epidemiological and economic aspects. Moreover, in order to compare the performances of different providers or specific populations, it is important to identify which factors affect the measures of the outcome (that is, “a factor that modifies the effect of the exposure on the outcome of interest. In case of a dichotomous effect modifier, the relationship between the exposure and the outcome will be different in the absence, or presence, of this factor” (Rothman and Greenland, 1998) ). Furthermore, to compare hospitals or populations, it is necessary to define indicators, i.e. measures that can be used to describe a situation that exists and to measure changes or trends over a period of time. Most health indicators are quantitative in nature but some are more qualitative) (Vaughan and Morrow, 1989). In some cases, outcome indicators could be expressed as measurements of survival or waiting time (e.g. in case of hip fracture, the time elapsed between the fracture and the surgical procedure). Finally, it is possible to assess the influence of the confounding factors (e.g. the specific characteristics of the examined population and/or the healthcare providers) and to define the benchmark (i.e. the pool of hospitals or reference populations who showed significantly better performance) by using specific statistical analyses known as risk adjustment methods.

The European Public Health Outcome Research and Indicators Collection (EUPHORIC) is a multidisciplinary project funded by the EC and aimed at defining a common set of outcome indicators in a few clinically relevant areas and validating them among the participating European countries. It represents a pilot exercise for the establishment of a system for benchmarking health outcomes. The first phase of the project was aimed at identifying the tools and the operational conditions that will be used in the implementation of the second phase of the project. By analysing international literature, websites and materials regarding validated indicators, nine disease areas (orthopaedics, transplantation, emergency, neonatal/maternal, miscellanea) and a list of 54 outcome indicators adopted in European and Extra-European countries was defined. From the 10 participating institutions, established in 10 countries, information was collected on healthcare systems and sources of health data available to compute the selected outcome indicators, the type of data source and period covered, linkage with other archives (e.g. hospital discharges, mortality records), the basic unit of analysis and the variables available for stratified analysis. This information was organised in a database accessible to the public ( The analysis of collected data showed that there is a high variability among the participating countries in terms of the availability of data and the type of data sources. Hospital discharge records are available for most of the selected diseases, whereas clinical records and registers are available only for some diseases. Automatic linkage between different databases on a national basis is available only in Scandinavian countries. The implementation of risk adjustment models is possible only for very few diseases and in few countries, given that most of the collected data are not sufficiently detailed.

To implement the pilot phase, orthopaedics and cardiovascular disease and surgery were taken into consideration because of their high clinical and public health importance and because all of the participants were able to provide information.

The cardiovascular pilot defined a simple set of factors that determine quality of healthcare outcome in myocardial infarction patients who underwent CABG, coronary angiography or percutaneous revascularization. The orthopaedic pilot findings describe how to develop outcome indicators for arthroplasty, based on existing national projects, in accordance with the requirements of ongoing European Commission projects.

The results of the analysis will be published on the EUPHORIC website as soon as they will be available.