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Viewpoint (April 2003)

Author: Dov Chernichovsky, Scholar in Residence 2002-03, The World Bank; Professor of Health Economics and Policy, Ben Gurion University of the Negev, Israel. 

The aims of finance, organization and management of a health system, within an appropriate regulatory framework, are multiple: health; equity; containment of rising medical care costs; efficient provision or production of care; and client satisfaction. While improved health outcomes are the ultimate goal of any health care system, other aims, equity in particular, have emerged as important in their own right, serving both health as well as other social and economic goals.

While health system aims are universal, their relative significance varies across nations, communities, and with time. For example, while improving their health systems, developing communities may set improved health outcomes as the highest priority and client satisfaction from service lowest. Developed communities, mainly those with relatively long life expectancies, may choose cost containment and client satisfaction as top priorities. That is, policymakers may have different preferences and priorities, and different priority settings require specific solutions involving the finance, organization and management of the health system. 

Regardless of level of financing, health system finance can be envisioned as comprising the following basic elements:

  1. sources
  2. management and allocation
  3. payment to community providers
  4. payment to hospitals
  5. public-private mix

For each element we can identify several policy options that need not be mutually exclusive. The options for sources of finance, for example, include private finance (e.g., main source in the U.S.A.); vouchers (e.g., Singapore); mandatory earmarked contributions by groups to sickness funds which pool risk at a group level (e.g., Germany); mandatory earmarked contributions to regional and national funds which pool risk at different state levels (e.g., Russia); general taxation (e.g., the United Kingdom); or any combination thereof. Similarly, alternatives exist for the other elements of health finance.

In a publicly financed health care system, levels and sources of finance reflect social and macro-economic choices in which health system outcomes may not be a key concern. That is, level and sources are not subject to the policy-making taking place within the health system, whereas the other elements are. The allocation of finance needs to reflect health system aims and priorities, including specific health objectives and medical interventions or programs. Payments to providers need to guide providers through appropriate incentives towards meeting the different priorities. And, the 'public-private mix' that affects a health system's ability to meet its aims, must be set so as to minimize interference, and possibly even support, all other elements. That is, to effectively advance the aims and particular priorities of a health care system, the financing options selected for each element of finance must be coherent, consistent, and mutually reinforcing.

The implied delicate balancing act is easily upset by a number of interrelated factors. The first is lack of a common language. For example, "social health insurance" takes on different meanings in different contexts. The second factor is lack of a database to guide policy makers as to what financing options can work best in different settings. The third is the complexity of the balancing act. As outlined above, we have five health system aims that can be prioritized in different ways. Each aim is to be served by applying a particular policy option or a combination of options from several available for each of the five financing elements. The appropriate option or combinations of options, for each element, depends on particular health system priority aims. The right choice or balance presents a formidable programming challenge. The fourth factor, reinforced by the previous factors, comprises the political and institutional gaps between policy makers who need to make decisions on level and sources and often on public-private mix (e.g., Ministries of Finance), and those who need to decide on allocation, payment, and mix (e.g., ministries of health and health system managers).

Consequently, when policymakers and managers debate health care financing and related organizational and managerial issues, each person involved has, more than likely, a different definition and understanding of the issues and thus approaches them in his or her own way. More specifically, policymakers and system managers tend to be guided by ideology, particular points of reference, experience, and intuition rather than by a systematic approach.

The absence of such an approach, combined with politics (ascribing the health system's woes summarily to the lack of funding), prompts policymakers and managers to focus on the level of finance while ignoring the other elements mentioned above. This is particularly true in low- and middle-income countries where financial constraints act as serious impediments to achieving system objectives, and where significant public expenditure has serious fiscal consequences. In other words, there is a relative preoccupation with the quantity of finance - an issue about which health system managers have the least influence -- and a relative lack of concern about its quality or the way in which it is established throughout the system - an issue about which those managers have much influence.

To help design and implement effective health system finance, which naturally reflects system organization and management, we came up with a structured approach that goes a long way towards overcoming the limiting factors highlighted above. Indeed, the approach involves language, an expert system, and Fuzzy Logic.

Language means agreeing on definitions of terminology and application of concepts. For example, "social health insurance" is defined to deal with different types of such insurance depending on level of pooling risk. In lieu of a missing database, the expert system involves organizing "common knowledge" or what we might consider the "consensus" on the relative impact of alternative options for each element of finance on health system aims. For example, there is most likely a broad consensus that health care financing by public revenues is more equitable than by private financing. Consequently, the expert system comprises statements such as "general taxation is more equitable than private finance." We then apply Fuzzy Logic to systematically manage such statements in a way that provides a structured answer to "which options, for each financing element, serve best the specific health system aims and priorities?"

To simplify matters, we assume in our basic design that all system aims have equal welfare weights, e.g., each aim has the same priority, and that financing policy options for each of the five element are mutually exclusive, e.g., general revenues can be the only source of finance in the system. This particular model yields 24 health financing policy options. Employing Fuzzy Logic helps make the right choice amongst those by identifying the best option for each financing element. The choices are as follows. 'Mandatory contributions' paid directly to sickness funds are the best source of revenues; a 'retrospective capitation' is the best allocation mechanism; 'capped physician fees' are the best method of paying community doctors; Diagnostic Related Groupings (DRGs) is the best method to reimburse hospitals; and complete segregation between 'public' and 'private' is the best public-private mix. Assignment of priorities or welfare weights to system aims and allowing mixes of policy options would yield a different set of preferred options.

The development of the approach summarized here is at an early stage. This notwithstanding, the underlying philosophy is noteworthy in the relevant context. Unlike the approach taken by World Health Organization (WHO 2000), the Fuzzy Logic approach does not involve an explicit ex post facto comparison amongst health systems by scoring different 'outcome' elements and ultimately ranking systems by an aggregate score. WHO scores can be a useful but are not an essential input in our approach. The Fuzzy Logic approach allows us to organize and program common thinking or accepted wisdom based on theory, common sense, as well as on comparative evidence, about the association between specific financing policy 'inputs' and system 'outcomes'. Thereby this approach provides the financial levers that the policy maker can use for considering and steering the health system in the direction he or she desires.

Dov Chernichovsky

Further Reading 

  • Chernichovsky, D. 1995. "What can Developing Economies Learn from Developed Economies?" Health Policy 32:79-91. 
  • Chernichovsky, D., Bolotin, A. and D. de-Leeuw. 2003. "A Fuzzy Logic Approach toward Solving the Analytic Enigma of Health System Financing" The European Journal of Health Economics. Forthcoming.
  • McNeil, D., and P. Freiberger. 1993. Fuzzy Logic: The Discovery of a Revolutionary Computer Technology That is Changing Our World. Touchstone, New York. 
  • World Health Organization. 2000. The World Health Report 2000. The World Health Organization. Geneva. 

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