Equalization in the Polish Health Insurance System

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1 Equalization in the Polish Health Insurance System Task 1of the Worldbank project Private Sector Initiatives in Health Insurance and Health Facilities of Poland: An Analysis of Key Issues (IBRD Loan No POL, Ref.No. TOR /A/1/JW) Final version Prof. Juergen Wasem, Ph.D. Chair of Health Systems Management Department of Law and Economics University of Greifswald, Germany in co-operation with Michal Marek, Ph.D. Unuz, Warsaw, Poland April 16th, 2001 Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 1

2 0 Preliminary Remarks This paper is the final version of a series of papers, regarding the issue of Equalization. The issue of equalization is one major part of Task 1 of the ToR of the project Private Sector Initiatives in Health Insurance and Health Facilities of Poalnd: An Analysis of Key Issues (IBRD Loan No POL). During the performance of Task 1, local experts and the foreign consultant agreed on focusing primarily on equalization, because the conceptual deficits of the existing formual of equalization between the Polisk sickness funds became quite visible during the perfomance of the project. The issues were discussed with representatives of UNUZ, and the final version of this paper is heavily build on these discussions. 1 Introduction The Polish General Health Insurance Act provides for a competitive health insurance system: The insured persons are insured mandatory but can choose, with which sickness fund they want to insure. Because of the fact that the revenues as well as the risk structure of the insured of the sickness funds differ, there has been introduced a system of financial equalization, which is regulated in Art. 135 of the health insurance law and on which the Council of Ministers is regulating further details. In this paper we will analyze the existing system of equalization, and we will make proposals for a refinement of that system. We will start with some general remarks on the purpose of equalization (section 2). In section 3 we will analyse the existing system of equlaization, its strengths and weaknesses. In section 4 we will give an overview over potential methods to improve the formula in the Polish eauliazation system. In section 5 we will finally make a concrete proposal, how the future formula should look like and what should be done to implement this proposal. The paper is based on existing international experience as well as on knowledge of health insurance economists. The first author has been the official evaluator of the German risk adjustment in the years 2000 and 2001; the experience of this evaluation has also shaped this paper. The paper has profited as well from discussions with Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 2

3 representatives of UNUZ and from discussions with representatives of the National Center for Health Information Systems. 2 On the purpose of equalization in competitive health insurance systems In the 1990 th, a large number of countries have introduced competition into their social health insurance systems for instance, the Netherlands, Switzerland, the Czech Republic, Germany, and Israel. In all these countries, the insured persons are entitled on a regular basis to choose between various sickness funds. All of these countries have introduced equalization systems which are called risk adjustment systems in most of these countries at the same time. There are mainly two reasons, why equalization mechanisms are increasingly used in resource allocation within health care systems: Achieving equity: Allocation of resources for health care decides, how much health care can be bought by the individual sickness funds for their insured and how it is distributed. If sickness funds had to rely exclusively on the revenues collected from their insured, differences in income levels of the insured and differences in the risk structure of the insured would lead to the fact that some sickness funds would have plenty of resources available in relation to the health needs of their insured, whereas for other sickness funds there would be a large need of resourced. The access of the insured to health services would, therefore, be rather unequal. With equalization, the relation between resources available and health needs between the insured of the various sickness funds can be narrowed, if the sickness funds who insure the insured with high incomes (and therefore have more contribution revenue available) pay money to those sickness funds, which insure the insured with low income (and therefore have less contribution revenues available). At the same time, the equalization system will achieve more equity if resources are transferred from the sickness funds who insure the young and health people (and which do not need that much revenues to guaranty the benefit package to their insured) to those funds which insure the elderly and sick people (and which need more resources to finance the benefit package of their insured). Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 3

4 Avoiding cream skimming: Competing sickness funds who are not allowed to calculate risk adjusted contributions for their members, can gain comparative advantages in competition, if they insure only "good risks" especially the young and healthy (who need less health care) and the people with high income (who pay higher contributions). Insurers who insure above average such good risks are financially better off than those who insure above average bad risks. Sickness funds therefore have a strong interest to engage in "cream skimming", which means to focus actively or passively on selecting good risks. Cream skimming, however, does neither lead to more equity nor to more efficiency in health care provision. From the viewpoint of health policy, engaging in cream skimming is a waste of resources therefore. Equalization is a mechanism to "neutralize" interests of competing health insurers for cream skimming: If money from insurers with above average good risks is transferred to insurers with above average bad risks, it becomes less attractive to insure good risks and more attractive to insure bad risks. In addition, it become more difficult for health insurers to define, which risks are good and which risks are bad. Both reasons for an equalization mechanism, equity considerations as well as avoiding cream skimming, are relevant in the Polish situation today. Even if sickness funds have not started to engage in risk selection on a large scale, international experience clearly shows that this will develop rather soon. It is therefore rather adequate that the Polish General Health Insurance Act provides for the establishment of an equalization formula. Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 4

5 3 Analysis of the present system of equalization in the Polish general health insurance system The present system of equalization is regulated in Art. 135 of the Health Insurance Act and in further decrees of the Council of Ministers Description of the present system of risk adjustment According to that regulation, the equalization mechanism is as follows: For a sickness fund (n) two figures are compared: o the planned revenue of that sickness fund in the following year (P n ), o a weighted share of that fund from all planned revenues of all sickness funds (we call this weighted share for convenience P n weight). In case that P n weight > P n, the fund receives 40 % of the difference from the equalization mechanism: pw n = 0,4 x (P n weight P n ); in case that P n weight < P n, the fund pays 40 % of the difference into the equalization mechanism. P n weight is calculated by multiplying the total planned revenue of all sickness funds (ΣP n ) with the share of weighted insured of the sickness fund (S n ) as part of all weighted insured of all sickness funds (ΣP n ): P n weight = ΣP n x (S n / ΣS n ). The weights to calculated the weighted insured S n take into account two elements: o the age of the insured: whereas each insured below the age of 61 (u n,<61 ) is weighted with 1, each insured above the age of 60 (u n,>60 ) is weighted with k = 2,5679. k is the same for all sickness funds. It is based mainly on calculations for the year The preliminary number of weighted insured is S n prelim = u n,<61 + k x u n,>60. 1 Rozporzadzenie Rady Ministrow z dnia 27 pazdziernika 1998r. w sprawie algorytmu wyrownia finansowego dokonywanego miedzy Kasami Chorych oraz wysokosci procentowej przzewidywanych przychodow, ktore nie sa uwzglednione w wyrownaniu Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 5

6 o The preliminary number of weighted insured is divided through the revenue factor d n to get the final number of weighted insured: S n = S n prelim / d n. The revenue factor d n is giving the ratio of per capita planned revenues of sickness fund n in comparison to all sickness funds: d n = (P n / [u n,<61 + u n,>60 ]) / (ΣP n / Σ[ u n,<61 + u n,>60 ]) 3.2. Effects of the present system of equalization: The system of equalization just described has the following main effects: Because of different economic situations there are rather large differences in average per capita income of the insured between sickness funds, which also lead to large differences in average per capita revenues of sickness funds. Due to the equalization mechanism, this differences are reduced significantly, although not completely. Sickness funds with higher planned revenues per capita before equalization, other things being equal, still have higher planned revenues per capita available after equalization. Due to different age structures of the membership of the sickness funds, the funds are confronted with different average per capita health care costs. The equalization mechanism shifts more revenues to those funds which insure a above average share of elderly (above 69). However, other things being equal, sickness funds with a larger share of the elderly have less revenues per weighted insured (taking variable k as a weight) than sickness funds with a share of the elderly below average. The equalization mechanism is not complete, therefore, with regard to the equalization of the costs effects of the two age groups. In some regions, health care costs are on average higher than in other regions. Sickness funds whose membership is concentrated in these regions face above average health care expenditures. At the same time, in many of these regions per capita revenues are above average. Because of the fact that differences in revenues per capita are not equalized completely, those sickness funds can use parts of their above average revenues to finance above average health care expenditures. Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 6

7 With regard to the first two effects described, it is quite clear that they go into the right direction: The redistribution from the sickness funds who insure the young to those who insure the elderly is desirable. Also the redistribution from the sickness funds who insure high income people to those who insure low income people is desirable. At least in short term perspective it is also clear that there must be some redistribution from those sickness funds who insure in regions with low health care costs to those sickness funds who insure in regions with high health care costs. Also, it is without any doubt a wise decision to have an equalization formula (instead of having MoH or some other agency distributing the money as they want to), because a formula assures transparency and strengthens responsibility. At the same time, however, the mechanism has some strong weaknesses too. We will distinguish between weaknesses regarding the equalization of the revenues side (subsection a) and weaknesses regarding the modeling of differences in morbidities in the formula (subsection b): a) Weaknesses in the mechanism of equalization of planned revenues: As we have seen in the description of the formula, differences in planned revenues are equalized simultaneously in two ways: First, sickness funds, whose weighted share of planned revenues is larger than their actual planned revenues (P n weight > P n ), get 40 % of the difference, which in itself equalizes differences in planned revenues by 40 %. Second, in weighting the insured, sickness funds with below average planned revenues per capita get more resources per insured than those with larger planned revenues per capita (because of S n = S n prelim / d n ); this also equalizes differences in planned revenues, the size of which is not uniform, however, because it depends on the age structure of the insured (the more the sickness funds with above average planned revenues insure the young, the stronger the equalizing effect of that part of the formula). The combination of both elements equalizing 40 % of the differences between the weighted share of all revenues and the planned revenues at the one hand and weighting Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 7

8 the insured according to the revenues at the other hand makes the equalization on the revenue side rather intransparent. It would be more desirable to have one clear element of equalizing differences in planned revenues. At the same time, it is not desirable, that taking both elements of equalization of planned revenues together, there remain still significant differences in planned revenues per capita. These differences in planned revenues per capita provide incentives for risk selection with regard to income: Sickness funds, who manage to attract people with higher income, are in a more comfortable situation than those funds, who insure primarily the people with lower income. Even if they might not engage in risk selection with regard to income at present, it seems likely that the sickness funds will develop activities with regard to that in the future. As far as we understand, the main reason for not completely equalizing differences in planned revenues is related to differences in per capita health care expenditures between region: It can be observed in Poland that in regions with higher per capita income there are also traditionally higher health care expenditures per capita. In the present situation sickness funds whose activities focus mainly in these regions, have more money available, because they can keep parts of the revenues generated from the difference between the regional per capita income and the national per capita income of the insured. Therefore, they are enabled to finance above average per capita expenditures by means of above average planned revenues. Although this is a valid argument, the logic of it is merely empirical: At present, sickness funds who insure members with above average income, also insure in regions with above average revenues. Because of the fact, that the insured have a right to choose their sickness fund, it may happen soon that the empirical basis for this argument may become invalid. For instance it can happen that a sickness fund manages to attract high income insured from low health care cost regions, whereas another sickness fund may be left with low income people in high income regions in this case the first sickness fund will have above average planned revenues after equalization although it does not really need them, whereas the second sickness fund will suffer from insufficient planned revenues after equalization. Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 8

9 It would be more adequate therefore to include a regional variable in the equalization formula), so that sickness funds get more revenues if they insure people in more expensive regions. This is done for instance in the Medicare Risk Adjustment Mechanism in the US or in the risk adjustment mechanisms of the sickness funds systems in the Netherlands and in Belgium. We have learned that the Mazovian fund has proposed to include an epidemiological characteristic of a region as well as the number of health care providers (and their reference level) into the formula; this proposal would also be able to take into account different health care costs between regions. Having an explicit regional variable in the formula also would make a rational discussion possible, how much interregional differences in health care expenditures are desirable in the country. It also would have to be discussed, to what extent sickness funds are able to influence these differences through their contracts with health care providers. A final consideration with regard to the revenues side deals with the fact that planned revenues are taken as a basis for equalization. Insofar as actual revenues and planned revenues differ between the regions (for instance because of different economic development), this element may lead to different financial situations of the different sickness funds. It also leads to a strong strategic interest of the funds to underestimate planned revenues and it is an open question whether UNUZ is able to counterbalance this strategic interest. b) Weaknesses in the modeling of morbidity In the present equalization formula morbidity is represented through the k variable, the level of which is fixed in the decree of the Council of Ministers. With regard to this approach to measure morbidity, there are certain shortcomings, which will be analyzed in this subsection: Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 9

10 The weights for the two groups of the elderly and the young (the variable k in the formula) are not updated regularly. If the situation has changed since the period, from which these weights were generated, sickness funds will be put in different financial situations. The following Figure 1 gives an example: It shows how the ratio between per capita expenditures of the elderly (here: above 65) and the young (here: 65 and below) has changed in German private health insurance funds during the last 20 years. Whereas in the beginning of the 1980 th, per capita expenditures for the elderly were about 4.3 of those of the young, in the middle of the 1990 th this factor was about 6.5. If something like this has happened also in the general health insurance system in Poland, than it is quite clear, that holding the weight in the risk adjustment formula constant will lead do a financial disadvantage of those funds who insure the elderly. 7,0 TARIF: SM6 G: 1 6,5 b 6,0 5,5 5,0 4,5 4, JAHR Figure 1: Ratio of expenditures per capita: insured above and below 65, private health insurance funds, Germany Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 10

11 It is true that because of the fact that all Polish sickness funds are relatively large, the age distribution of the sickness funds members does not differ dramatically. But still, differences are large enough so that a wrong k-variable will have a significant effect on financial situation of the sickness funds. For some sickness funds, the proportion of insured aged 61 and more is about 15 %, for others it is more than 25 %. The latter profit from a incorrect low figure of the k-variable. Health care expenditures do not only differ between those below and above age 60. Instead, average expenditures considerably differ by age below as well as above the age of 60. Figure 2 illustrates the distribution of health care expenditures based on estimations from the Czech Republic. Figure 2: Distribution of health care expenditures by age and sex in the Czech Republic 4,000 (females, age = 1,000) 3,500 3,000 2,500 2,000 1,500 1,000 0,500 0,000 male female age Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 11

12 If there are similar differences in health care expenditures in Poland as shown in Figure 2 for the Czech Republic, it is quite clear that equity with regard to the capacity of health care financing is not sufficiently achieved through the present redistribution mechanism. Average expenditures for those between age 70 and 80 are clearly higher than for those between age 60 and 70. Also in the group of insured below the age of 60, there are clear difference for instance expenditures for those between 45 and 60 are much higher than for those below 45. This lack of differentiation does not only create problems of equity. It may also create unwanted incentives to cream skimming: for instance, it is more profitable to insure those between age 60 and 70, but not those between 70 and 80. Or another example: a sickness fund can improve its financial situation by attracting insured up to age 45. Also here it is true that the sickness funds are rather large so that distribution by age within the two age groups of the young (below 60) and the old (above 60) does not differ dramatically; but still differences are quite remarkable: The share of those (more expensive young insured) between 50 and 59 among all insured below the age of 60 is about 10 % in some funds, but more than 15 % in other funds. Those funds, who insure the young among the young profit from the present equalization mechanism, whereas those who insure the elderly among the young are disadvantaged. As Figure 2 shows, there are also strong differences in expenditures between men and women for instance in the age group between 15 and 45, expenditures per capita for women are considerably higher than for men, whereas the opposite is true in the age group beyond 65. Those sickness funds who insure more young women are disadvantaged by the present system whereas those who insure more elderly women are in a better situation. The international health economics research strongly has emphasized during the 1990 th that age and gender are not sufficient to describe the costs related to morbidity of groups of insured persons: Whereas one insurer might insure more healthy elderly, others might insure the sick among the elderly. Therefore even Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 12

13 with a better differentiation with regard to age and with a differentiation with regard to gender, the performance of the equalization mechanism remains poor according to international standards. It may be argued that sickness funds in Poland are so large that differences in morbidity may not play a crucial role. International experience however shows that even when comparing large sickness funds, there often are differences in morbidity which are too large to neglect. In Poland, one indicator for these difference might be differences in standardized mortality rates (which is a good proxy for morbidity) by the regions of the sickness funds: They differ by more than 10 %. So it can be assumed that also morbidity will differ considerably. 4 Overview over potential methods to improve the formula in the Polish eauliazation system In this section we will give an overview on methods, how the present formula for equalization in the Polish health insurance system could be improved. In the next chapter (sectin 5) we will then make a specific proposal for change. In both section the general idea is that changes are necessary if the concept of a competitive system of health insurance based on the principles of solidarity between the health and the sick, the young and the elderly, those with higher income and those with lower income shall not be threatened. In this section, we will first (in subsection a) give an overview on those changes which deal with the revenue side, then we will deal with a regional variable (in subsection b), finally (in subsection c) we will deal with the morbidity side: a) Potential proposals regarding the revenue side Following the analysis of the present mechanism, we see two potential improvements with regard to the revenue side of the equalization formula: Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 13

14 (1) It could be considered to replace the two-step but incomplete mechanism of equalization of revenues through a one-step but complete mechanism. This means: the d -variable would be deleted completely, and the w -variable would be set to 1: w = 1 (2) It could be considered to have at the end of a year a second step of the equalization mechanism, in which the difference between planned revenues and actual revenues is equalized. This could be done as well in the present system of equalization as in a system with a revised formula for the equalisation of revenues (as described above). b) Potential proposal of the introduction of a regional variable: It could be considered to include an explicit regional variable into the equalization formula. This could be done by given each insured a region specific weight (like the k -variable in the present system). The weight could be either derived from statistical data (which would have to be drawn from regular samples making use of available data, for instance those data hospitals deliver already today), or if these interregional differences are seen as too large they would be set politically). The elements proposed by the Mazovian sickness fund (epidemiological characteristic of a region, number of health care providers) could also be used in deriving the weights for the regional variable. c) Potential proposals regarding the morbidity side With regard to the morbidity, which is (as has been shown) measured at present through the k-variable, there are a variety of proposals how to improve the equalization mechanism. They all will lead to more justice and less incentives for cream skimming or risk selection. At the same time it must be emphasized that most of these proposals are more demanding in terms of the requirement for data than the Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 14

15 present design of the mechanism. A crucial question is, therefore, whether these requirements for data can be fulfilled. (1) Regular update of the k variable: As we have pointed out, the existing k-variable is based on information on health care costs of 1994 and it is rather likely that this is no more relevant. A first proposal could be, therefore, to adjust the k variable regularly. Empirical evidence, which has been given to the authors of this paper, shows that changing the value of k has a limited influence in terms of the absolute volume of transfers. If it would be set at k = 3,0, for instance, transfer volumes would have changed in the year 2000 in the range from less than Zloty (in the case of the fund of Świętokrzyska) up to not more than 4.4 million Zloty (in the case of the fund of Mazowiecka). In terms of the relative level of transfers, the changes would be relatively minor for most funds (e.g. for 11 funds transfer payments would change less than 2 per cent), but for some funds the relative change would be quite considerable (e.g. more than 10 per cent for the fund of Lubuska and even more than 50 per cent for the fund of Dolnośląska). In order to adjust the k-variable, it would be necessary to have some information, at least for a sample of insured, available for average per capita costs of the two age groups (below 61and above the age of 60). Parts of the information could be mad available from more recent versions of the modular studies on health care expenditures. For other parts of the information the further development of the use of the chip card (smart cards) would be of central importance. (2) Definition of more than two age groups: As we have seen in Section 3, there are remarkable differences in per capita health care costs within the two age groups below 61 and more than 60. If it is possible to generate data on per capita health care costs, which are more differentiated with regard to age, a more demanding approach than to adjust the k- Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 15

16 variable regularly would be to use this information for a better formula of equalization. We have learned, that the Mazovian sickness fund is proposing to differentiate the formula as follows: age groups of 0-1, 1-3, 3-7, 7-10, 1-15, and then each 5-year period, and the last group 90+. This proposal looks very reasonable, taking the age specific per capital health care costs into account, which Figure 2 has demonstrated. For such an improvement of the equalization formula, two types of information would be necessary: On the one hand information on the distribution of all insured among the different age groups in all sickness funds in necessary. UNUZ would have to be able to control this information, otherwise the sickness funds might have interest in manipulating the figures. Secondly, information on the average per capital health care costs for these age groups in the system of general health insurance would be needed. It is not necessary that this information is available for all insured. Instead, a representative national sample of insured would be necessary. We have learned that in the future development of the smart cards this information might be available. It would be necessary that health care providers deliver the relevant information with the PERCEL-No. to the sickness funds or directly to UNUZ. We have learned that for hospitals that kind of information could be made available already now, with regard to length of stay in hospital, which could function as a proxy for costs. (3) Definition of age groups separately for men and women: In case that either proposal a) or proposal b) are realized, it should be possible easily to differentiate the per capita health care costs for men and women. A potential method of improving the risk adjustment system would be therefore, to have a separation in the process of weighting the insured between men and women. As mentioned above, the per capita costs would be needed only for a representative Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 16

17 national sample of insured, whereas the information of the number of insured men and women in the age groups would be needed for all insured of all sickness funds. (4) Going beyond age and gender in measuring morbidity A far more demanding type of proposals would be to go one further step towards better targeting of morbidity should be done. During the last decade there have been several very promising developments and models are running in many places. In the last year, official evaluations have been done to assess the equalization systems in Germany, the Netherlands and Switzerland in all three countries the evaluation teams proposed to go beyond age and gender in measuring morbidity. In such models indicators for above average morbidity are used to calculate the equalization sums. We briefly want to mention three of these models, which might be useful for Poland as well: Sickness funds could be granted additional money in the equalization scheme for extreme expensive cases. For instance, they could get refunded out of the equalization mechanism for insured that cost more than 50,000 Zloty per year. Or, expenditures for certain very expensive disease (e.g. HIV) could be refunded partially by the equalization mechanism. Arrangements like these are practiced in many places in the US; it is proposed within the social health insurance systems of Switzerland, Germany and the Netherlands. It is also practiced in Israel. There could be a separate calculation for expensive chronic diseases. For instance in the Netherlands, there will be implemented a model in 2002 according to which for insured who use specific expensive drugs regularly, there will be calculated standardized costs in the equalization mechanism. Finally, standardized costs could be calculated according to information for diagnosis. Models like this have been implemented for instance in Medicare and many public health plans in the US. They are discussed at present for the sickness fund system in Germany. Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 17

18 All of these approaches would make the equalization system much more adequate towards its goals with regard to equity, efficiency and avoiding of cream skimming. At the same time, however, these models are much more demanding with regard to the data needed, and it must be discussed whether this information could be made available within the Polish health insurance system. 5 The authors proposals to change the equalization system In the preceeding section we have given an overview on potential changes of the equalization system. In this section we want to give specific recommendations. We will give a short term proposal (subsection a) and a long term proposal (subsection b). The authors know that at present it is not clear whether certain informations can be made available. They therefore make the short term proposal in order to have at least those changes been done of which the authors think that they are unavoidable. The long term proposal is made, because we think that this would push equlization more ahead; it can be realized however only if certain data requirements are fulfilled. a) Short term proposal The short term proposal is as follows : a1) Changes in the prospective formula The d -variable in the equlalization formual will be cancelled The w -variable will be set to 1: w=1 (which means that it will be cancelled). A regional variable will be introduced for each of the 16 regions. For each sickness fund the number of insured in each of the regions will be relevant. The number of insured of sickness fund n in region r with age below 61 is denoted as u n,r, <61 and for insured with age above 60 it will be denoted as u n,r,>60. The weight which will be attached to each region will be r. The regional variable shall reflect differences in number and reference level of providers. We propose that r shall be set in a range between 0.8 < r < 1.2, and that UNUZ shall develop an index to set the values of r for the relevant regions. The value for r should be adjusted every three years. Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 18

19 The k-variable will be updated regularly (we propose: every three years) by using selected information from modular studies and other sources of information with regard to the ratio of expenditures for those above and below 60. With these changes the new equalisation formula will be: p n n ( + 1) = S n S n ( 1) ( + 1), ( 1) ( pw) P n in this formula, the weighted insured S n will be calculated as follows: S ( 1) 16 r= 1 u n, r, < 61 ( 1) n = r + k r. 16 r= 1 u n, r, > 60 ( 1) a2) Introduction of a second, retrospective equalization stage We have analyzed above, that sickness funds might be affected by different developments between planned and actual revenues. We therefore propose that a second stage of equalization should be introduced, in which the differences between the equalization payment (pw) n calculated from planned revenues and a new calculation from real revenues, after the year has been passed, would be equalized. Let (pw n corr ) be the correction payment after the year has been passed, and let (p n * ) be the real revenues of that year (and p n (+1) will still be the planned revenues for that year). The correction payment will be: n ( + 1) * ( ) S n ( ) pw corr p n p n = ( 1) P n ( 1) P n * S n. + ( 1) b) Long term proposal The long term proposal we make is, to include information on costs related to diagnosis of the insured into the calculation of the equalization mechanism. Each insured will be assigned each year to one specific diagnostic class out of x classes. For instance in the equalization system of Medicare in the US, each insured is assigned Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 19

20 to one of 13 classes where class 1 is for the most expensive diagnostics and class 13 is for insured without any of the relevant diagnosis in the last year. For this proposal it would be necessary to calculate average per capita costs per diagnostic class for all insured of the Polish sickness fund system. In the US, usually the modells used, calculate the per capita costs in a specific diagnostic class for the coming year (+1) for those insured who had this diagnosis in the last year (-1). Let D x (+1) be the average per capita costs in the Polish health insurance system of diagnostic class x in the coming year for insured who had this diagnosis in the last year. The usage of diagnostic information will most likely not replace completely the usage of the K -variable, because there are still some differences between young and elderly in one diagnostic class. The value of the k-variable will have to be calculated during the process of calculation of costs of the diagnostic classes. We recommend as well to keep the regional variable (which we proposed in the short term proposal) in the system. The value of it has to be reflected, however, because parts of the differences in costs between regions are now captured by the diagnostic variable. For the insured in the beginning who are insured with a specific sickness fund at the beginning of a year, the calculation of S n will be as follows: S ( 1) 16 X D r= 1 x= 1 x ( + 1) u n, r, d, < 61 ( 1) D n = r + k r. 16 X r= 1 x= 1 x ( + 1) u n, r, d, > 60 ( 1) We recommend to discuss in the Polish context, which steps can be done that information on costs related to diagnosis for individual insured can be made available. This long term proposal can only be implemented if these data requirements can be fulfilled. Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 20

21 6 Summary and conclusions In this paper we have analysed the existing system of equalization between sickness funds in Poland. This system has some strengths but also some strong weaknesses. The major weaknesses are as follows: differences in planned revenues between sickness funds are only equalized partly, so that sickness funds with above average revenues per capita have, ceteris paribus, more resources available for the health care of their insured. differences between planned and realized expenditures are not equalized at all, which effects sickness funds who work in specific regions where the economic development during a specific year is below average. morbidity is measured only through a variable ( k ), which distinguishes between insured below and above 60. In addition, the costs measured with this variable are not adjusted regularly. There are huge differences in costs between regions, which should be captured explicitly in the equalization formula and not (as today) implicitly. Out of this analyses we made two proposals short term proposal and a long term proposal: The short term proposal is: to update the k-variable regularly, to include a regional variable to simplify and complete the equalization of planned revenues to introduce a second step of equlalization of differences between plannes and realized revenues. The long term proposal is: to introduce information on diagnostic costs into the equalization system. Prof. Wasem - Final Paper on Equalization - Worldbank-Project - April 2001 page 21

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