Public Health and Average Health Status: Do Health Inequalities Matter? (Panayotov Matrix) more

FOR SUSTAINABLE AND PROSPEROUS SOCIETY HEALTH ECONOMICS Public Health and Average Health Status: Do Health Inequalities Matter? (Panayotov Matrix) Jordan Panayotov Jordan Panayotov Jordan Panayotov is Founder and Director of the Independent Centre for Analysis and Research of Economies in Melbourne, Australia. He was born in December 1961 in Sofia, Bulgaria. In April 1984 he got a degree in Economics, Labour Economics, from The University of National & World Economy Sofia. In his thesis Panayotov pays special attention to efficiency of labour in so called non-material sphere: education, health, arts, science. During 1984 – 1991 he had different positions at Medical Academy, Sofia. From May 1991 till January 2002 Panayotov was Managing Director of a company, exclusive distributor for Bulgaria of several world-leading producers of medical equipment and consumables. He gained extensive inside experience for both: the demand and the supply side in health care sector. In 1992 Panayotov initiated patients’ participation in decision-making process, which resulted in maximizing health outcomes from the available resources in renal treatment in Bulgaria. In 2004 Panayotov received degree of Master of Public Health, Health Economics, from The University of Melbourne and founded the Independent Centre for Analysis and Research of Economies. Panayotov works for improving efficiency in relation to health. His interests are in decision-making process and priority setting, with particular attention to power asymmetry influencing the outcomes of this process. Panayotov has developed model for evaluation of public health policies, programs and interventions. The model analyses the correlation between average health status and health inequalities in its dynamic, being constantly affected by the implementation of different policies. The model provides proper theoretical framework for health impact assessment of policies, programs and interventions in other spheres of the economy, as well as for addressing social determinants of health. It has been presented successfully on several international forums. Public Health and Average Health Status: Do Health Inequalities Matter? (Panayotov Matrix) Jordan Panayotov Health Economics Department Independent Centre for Analysis and Research of Economies Melbourne, Australia Melbourne, 08.08.08 This work is protected by copyright law. Except as specifically permitted in writing, no portion of this work may be distributed or reproduced by any means, or in any form, without prior written permission. Copyright © 2004 – 2008 Jordan Panayotov. All rights reserved. Suggested Citation: Panayotov J., Public Health and Average Health Status: Do Health Inequalities Matter?, ICARE 2008 For further information, or to obtain appropriate permission, please visit www.icare.biz or contact permissions@icare.biz To our children’s children and beyond “Even if enjoying good life, a man shall die and another one shall be born. Let the later born, when seeing this, remember its creator.” Tarnovo inscription Omurtag, the Builder Great Khan of Bulgaria 814 – 831 Content Foreword Foreword to the open access release of the paper, 08.08.2008……..……………..i to the release of the paper for Academia.edu, 22.01.2010……………….ii Abstract …………………………………………………………………..……iii Introduction ……………………………………………………………………1 Opposing Interests When Allocating Resources ……………………….3 Graph 1. Opposing Interests When Allocating Resources ……………………....3 ………….5 Table 1. Health Expenditure by Source of Financ ing, OECD Countries Implications for decision-makers ………………………………………….6 Average Health Status - Health Inequalities Matrix ………………...…..7 Table 2. Panayotov Matrix ………………………………………………..…8 Graph 2. Average Health Status – Health Inequalities Matrix (Panayotov Matrix in Tim e) ……………...………………………………...9 Minor Combinations between AHS and HI ……………………….………9 Main Combinations between AHS and HI ………………………………11 Implications for decision-makers ………………………………………..14 Conclusion …………………………………………………………………...15 Notes …………………………………………………………………………..17 References ……………………………………………………………………18 Foreword to the open access release of the paper, 08.08.2008 Health is the most precious asset for any individual, family, business, community, or state. Therefore health is an important issue bo th: fo r every individual and for peo ple altogether. Thus health is everybody’s business. During the whole history of mankind, regardless differences in the conditio ns of living – geography, culture, religion, education, level of economic and social development, or position in social hiera rchy – good health is always recognized as a premise fo r achieving anything else in people’s lives. Today armies of providers and insurers, researchers and po licy-makers are engaged in improving peo ple’s health and wellbeing, thereby making health the largest sector of the economy in many co untries. The result is that people today have longer and healthier lives than in the past. However, this improvement appears to be disproportionate amo ng different groups of the population. There is no evidence so far that hea lth inequa lities – being differences in hea lth status among individuals, which are considered to be avoidable and unfair – exist anywhere e lse in the nature apart from human societies. This, by itself, is evidence that hea lth inequa lities are man-made and man-maintained. While fo r some societies, fo r example, those in favour of slavery, the differences in health and wellbeing between master a nd slave were co nsidered to be the “natural” state of affairs, it is not the case for societies which are based on the premise that all individuals – irrespective of their personal characteristics and position in the society – are of equal value. Although that the later have declared repeatedly their intention to reduce hea lth inequalities, these tend to persist and in many cases even grow. During the last decade of 20th century as well as the first decade of 21st century there are many attempts to explain empirical findings and more importantly to determine “what works” in relation to reducing health inequalities. So far these attempts were unable to produce a framework which provides universal explanations and predictio ns, something what a pro per theory should do. This paper offers a model with universal e xplanations and predictions. It is now only up to the people to decide whether to use it, o r not, because as Kurt Lewin no ted “There is nothing so practical as a good theory” The model has been presented on several international forums:  3rd International Conference on Urban Health, Octo ber 2004 in Bo ston, USA;  International Conference on Engaging Communities, August 2005, Brisbane, Australia, a n initia tive of the United Natio ns and the Queensland Government;  36th Annual Co nference of PHAA, September 2005, Perth, Australia;  11th World Congress on Public Health, Aug ust 2006, Rio de Janeiro , Brazil;  4th Biennial Conference of International Society on Equity in Health, September 2006, Adelaide, Australia;  37th Annual Co nference of PHAA, September 2006, Sydney, Australia;  Setting an Ethical Agenda for Health Promotion, September 2007, Ghent, Belgium;  CPHA 2008 Annual Conference, June 2008, Halifax, Canada;  136th APHA Annual Meeting, October 2008, San Diego, USA (forthcoming) No funds from any governmenta l, NGO, public or private institution or entity, or perso n were ever received, as well as no any o ther form of suppo rt has ever been received neither during the process of creating the model, no r fo r presenting it on any o ccasion. Melbourne, 8th of August 2008 Jo rdan Panayoto v i Foreword to the release of the paper for Academia.edu, 22.01.2010 While there are well developed methodologies and techniques to find out “what works”, “to whom it works” and “how it works” for interventions implemented on individuals, there is a gap regarding interventions implemented on populations. In an editorial paper “The role of theory in evidence-based health promotion practice” Green (2000) notes that the accumulation of empirical evidence is of limited value unless accompanied by general principles which might inform wider application. Later, Heller at al. (2004) emphasize that “unless public health programs are based on sound theoretical bases, they will fail”. In another two editorial papers “Critical realism and health promotion: effective practice needs an effective theory” and “More public health theory please – but make it adequate” Connelly (2001, 2005) points out the importance of theoretical framework based on critical realism (if A then always B), which therefore can be used for universal explanations and predictions. Since October 2004 I am explaining at different forums that for any intervention implemented on populations the distribution of the benefit is the most important factor influencing the outcomes, no matter whether improving the health of the population is primary objective ( in public health ) or not ( in health impact assessment ). I’ve established that the evidence for interventions implemented on populations is relative and depends on the distribution of the benefit in any specific case. Therefore, the appraisal of any intervention implemented on populations should start with analyzing the distribution of the benefit at local level. I have identified eight combinations of this distribution, leading to very different results. Once this is sorted out, an appraisal of the alternatives for certain distribution can identify the best valuefor-money in specific case in order to maximize the outcome for whole populations. More than one year ago on 9th of October 2008 I have presented Panayotov Matrix at 9th International Health Impact Assessment Conference in Liverpool, UK, specifically explaining its relevance to HIA. Being based on critical realism (if A then always B), Panayotov Matrix provides universal explanations and predictions. While since there are some publications with claims for making predictions regarding distributions of outcomes for interventions implemented on populations, still, as far as I am aware, there is no other theoretical framework based on critical realism. No funds from any governmental, NGO, public or private institution or entity, or person were ever received, as well as no any other form of support has ever been received neither during the process of creating the model, nor for presenting it on any occasion. Melbourne, 22nd of January 2010. Jordan Panayotov References: Green J., The role of theory in evidence-based health promotion practice, Editorial, Health Education Research, Vol. 15, No. 2, 125-129, Oxford University Press 2000 Connelly J., Critical realism and health promotion: effective practice needs an effective theory, Editorial, Health Edu Research, Vol.16, No2, 115-120, Oxford University Press 2001 Connelly J., More public health theory please – but make it adequate, Editorial, Journal of Public Health, Vol.27, No.4, p. 315, 2005 Heller R. et al., UK health inequalities: the class system is alive and well, MJA 2004; 181 (3): 128 ii Public Health and Average Health Status: Do Health Inequalities Matter? Abstract Any policy, program or intervention is decision for resource allocation. Whatever intervention is implemented there are winners - people who benefit of it, and losers - people who benefit less of it. Choices or prioritizing competing demands are inevitable, since resources are limited and less than the needs. Always when allocating resources there are opposing interests – who will benefit from it. Having losers de facto means that some claims of the recipients are declined. The question is: “W hich claims will be declined?” and more importantly: “On what basis some claims will be declined?” Around the world decision-makers are puzzled – What is best for improving health of populations: increasing average health status, or decreasing health inequalities? Is there interdependence between health gain and health equity? This article is about theoretical investigation of the correlation between average health status and health inequalities. How they relate one to another, why they relate the way it is observed empirically, how would different interventions impact them? Focusing on improvement in average health status can mask widening of health inequalities. This situation, where health gain and health equity are not interdependent, has supporters, as it complies with Kaldor-Hicks criterion for efficiency. However, does it comply with declared by the society ethics that people, irrespective of their personal characteristics, are of equal value? The right of an individual to the highest attainable health should not be achieved by denying this right to others. Therefore different approach is needed when allocating resources in public health. This article provides a useful tool for researchers, decision-makers and local practitioners to: explain and analyse empirical findings; make predictions about future developments of average health status and health inequalities; make proper choices for policies, programs and interventions in line with the goal of WHO and public health. Key words: Health Equity, Health Inequalities, Social Determinants of Health, Evidence-Based Policy, Health Impact Assessment, Average Health Status, Health Disparities, Decision-Making, Priority Setting iii Public Health and Average Health Status: Do Health Inequalities Matter? (Panayotov Matrix) Introduction In its Constitution the World Health Organization (WHO) has stated that every human being without any discrimination has the right to the highest attainable health. Article 1 sets as objective the attainment by all peoples of the highest possible level of health. Don Nutbeam (1998) defines the new public health as “a social and political concept aiming at improving health, prolonging life and improving the quality of life among whole populations“. Fundamentally all public health interventions are decisions for resource allocation. Whatever policy, program or intervention is implemented, as a result there always will be winners - people who benefit of it, and losers - people who benefit less of it. When people benefit less from a certain policy, but they are not worse-off compared to their situation before the change, they are relative losers. People are absolute losers, if as a result from the change, they are worse-off compared to their previous situation. Since resources are limited and less than the needs, choices or prioritizing competing demands are inevitable. What should be the response from decision-makers when making choices for interventions in order to maximize the outcome in line with the goal of WHO and the new public health? Health status of different people varies because of different factors. Probably it will never be possible to eliminate completely all differences in health status between individuals. Therefore Margaret Whitehead (1990) suggests that decision-makers should be concerned “to reduce or eliminate those (health differences), which result from factors which are considered to be both avoidable and unfair”. Based on this, health inequalities are measurable differences in health status between people which are avoidable and unfair. Health inequalities can also be regarded as unequal distribution of adverse health effects among populations. 1 There are three important points here. First, if differences in health status are not measurable and/or the distribution of the benefit from an intervention among population is not determined, i.e. if it is not clear who-gets-what, then the decisions for allocating resources are made in blind, or are based on intuition at best. Second, avoidable means that there is no real reason not to eliminate these differences in health status other than the will itself of the people to do so. This means that all necessary conditions: technologies, resources, knowledge, institutions, etc. to deal with the adverse health effects of interest are available. It is only the willingness of the people to utilize these conditions appropriately. Third, unfair means that people realize that the outcomes – consequences of what has been done and/or what hasn’t been done to address adverse health effects among population – could have been better for the whole population if other interventions with different distribution of the benefit were implemented. It is important to point out that maximizing the outcome from individual’s perspective differs from maximizing outcome from public – tax payers’ – perspective. Therefore for achieving efficiency in cases of public funding, the later perspective should be considered as well. Financial, organizational and political sustainability requires allocative efficiency. Inefficiency de facto means waste of limited resources which leads to increased tension between the components of the health system. This in turn increases the pressure both: within the system and towards other sectors. As result people’s dissatisfaction with the system might grow which can lead to political instability and possible frequent change of decision-makers. 2 Opposing Interests When Allocating Resources Curve AB on Graph 1. represents all possible efficient allocations of given resources between two persons/groups. According to Pareto Optimality concept allocation of resources is efficient, if it is not possible to increase someone’s benefit (OAi for person/group A, or respectively OBi for person/group B) without at the same time decreasing another one’s benefit. Consequently, when allocating resources there are opposing interests – who will benefit from it? From individual’s perspective allocating all resources to one person/group is justified in order to achieve highest attainable health for the recipient. However, maximizing the health of specific individual/group, although justified from individual’s perspective, is in direct conflict with the goal of WHO and public health – maximizing health and quality of life of whole populations. If resources are allocated according to individual’s preferences (in point A or in point B), goals of WHO and public health will never be achieved, since the other person/group will get no resources and respectively there will be no benefit/improvement for them. Probably for this reason Richard Smith (1999) argues that: “Individual preferences (of recipients), reflecting utility, are not necessarily the desired outcome of health care interventions”, and Per Rosen (2002) argues that: “From a society’s perspective, health maximization might be more important objective than letting the physician give every single patient the best possible treatment and care”. elucidate the claims they make. However, both fail to Graph 1. Opposing Interests When Allocating Resources B S1 B1 B2 S2 O A1 A2 A AB – Possible efficient allocations of given resources OAi – Benefit for person A (max = OA, when allocation is in point A) OBi – Benefit for person B (max = OB, when allocation is in point B) Si – Allocation of resources providing benefit OAi + OBi S1 – Allocation of resources providing benefit OA1 + OB1 S2 – Allocation of resources providing benefit OA2 + OB2 3 Allocation of public resources based only on individual preferences of recipients de facto means acknowledging greater right to health for the recipients. Focusing on individual’s health maximization effectively deprives resources from another individual. Does this mean that the right to highest attainable health of the former is greater than the same right of the later? Do people value one person/group more than another? If people value all individuals equally irrespective of their personal characteristics, as they say they do (1), then the right of an individual to the highest attainable health should not be achieved by denying this right to others. Since it isn’t possible to allocate limited resources in point A and in point B at the same time, what preferences of the recipients are, a different approach is needed when allocating resources in public health. Given inevitability of having losers from any intervention people should realize that there always will be claims which will be declined. The question is: “Which claims will be declined?” and more importantly: “On what basis some claims will be declined?” Red curve on Graph 1. represents the opposing interests of person A and person B for allocating limited resources in order to achieve highest attainable health/benefit, which is OA for person A, and respectively OB for person B. Allocation in point A means that all claims of person B are declined, and allocation in point B means that all claims of person A are declined. In different points of time and in different societies claims are declined on different basis: person’s ability to pay; availability and extent of health insurance; first-come-first-serve basis; need; severity; etc. Interestingly, allocation in any other point on AB curve, different from point A or point B, i.e. declining some claims of both recipients (2), although not maximizing individual’s health/benefit, achieves greater sum of both persons’ health/benefit OAi + OBi. Allocation in point S1 means that some claims of both recipients are declined. Consequently, person B misses part of the benefit (B1B) from the potential maximum OB, which he/she would get if the allocation was in point B. Similarly, person A misses part of the benefit (A1A) from the potential maximum OA, which he/she would get if the allocation was in point A. However, from public perspective allocation in point S1 gets sum of the benefit OB1 + OA1 , which is greater than the potential maximum of the individual’s benefit OB alone or OA alone. Similarly, in point S2 person A misses part of the benefit (A2A) from his/her potential maximum OA, and person B misses part of the benefit (B2B) from his/her potential maximum OB. However, from public 4 perspective allocation in point S2 gets sum of the benefit OB2 + OA2, which again exceeds benefit OB alone or OA alone. This new approach for allocating public resources (and for priority setting), which takes into account who-gets-what from chosen interventions and, based on that, decisions are made in order to maximize the outcome/benefit for whole populations, will be more successful in achieving the goal of WHO and public health. Using the same resources this approach provides greater outcome/benefit in relation to the goal for maximizing health and quality of life of whole populations. This approach is more efficient as well, since efficiency by any definition is comparing the outcome/benefit with resources spent for achieving it. This approach successfully accommodates claims for equity in health by justifying such resource allocations, which benefit not one recipient only, but achieve the highest attainable health for whole populations. This approach is in line with declared by the society ethics – that all people are of equal value. This approach properly takes into account preferences of the tax payers who finance health collectively. In all OECD countries (3) public spending on health dominates (Table 1). People, valuing all individuals equally, want to maximize their health, thus fund this collectively. Therefore tax payers’ preferences should be taken into account from decision-makers when choices for interventions are made. Table 1. Health Expenditure by Source of Financing, OECD Countries, 2004 5 Implications for decision-makers When making choices for allocating public money, decision-makers should be aware of the fact that, although that a population is sum of individuals, achieving highest attainable health for an individual and for whole population is not the same thing. Since any allocation of limited resources leads to declining some claims of the recipients (i.e. either all claims of one of the recipients, or some claims of both recipients), concrete decisions regarding which claims of which recipient will be declined in a specific case in order to maximize the outcome/benefit for whole population depend on the local context. If certain intervention was successful some when and somewhere, because it did “work” on a specific population, it doesn’t mean that if replicated somewhere else it will automatically “work” again for the new population. All this means that the concept for Evidence in relation to public health changes. The Evidence that an intervention “works” is not something absolute, like it is in evidence-based medicine, but becomes something relative, depending on the distribution of the benefit or who-gets-what from the intervention at local level. When declining some claims in order to maximize the outcome/benefit for whole population, decision-makers should always take into account who-gets-what, i.e. who are better-off (winners) and who are worse-off (losers), both: currently and from the new intervention to be implemented. Based on this, the concrete decisions should be made in order to maximize the outcome/benefit for whole population at local level, i.e. to maximize the sum OAi + OBi. If this is not the case, meaning that previous and new winners and losers are not considered and the decisions are made in order to achieve better results on average, no matter that losers from the new intervention might be those who are worse-off before the change (i.e. some individuals/groups continue to lose out), the long-term consequence can be only one: growing differences between individuals in relation to whatever has been decided to be improved. In other words, if the benefit from the new interventions for those, who already are worse-off before the change, is lesser than the benefit for those, who already are better-off, then the differences in health and quality of life between these persons/groups will only grow. And when those measurable differences are avoidable and unfair, they represent health inequalities. 6 Improving average health status without taking into account who-gets-what from implemented interventions can actually create and widen health inequalities when the distribution of the benefit among population is ignored or neglected. These health inequalities will grow over time, if distribution of the benefit from the new interventions does not aim greater benefit for those groups who already are worse-off. Achieving better results on average and trumpeting that nobody is worse-off compared to their previous situation may not be a step towards the ultimate goal of WHO and the new public health. If the goal is improving health and quality of life of whole populations, then the distribution of the benefit or who-gets-what from an intervention, regarded in dynamics – over time – is the most important factor influencing the outcomes. However, maximizing the outcome/benefit from individual’s perspective is not the same as maximizing the outcome/benefit from public – tax payers – perspective. Improving average outcome is not the same as maximizing the outcome. So, if people strive for improving health and quality of life among whole populations, do health inequalities matter? Average Health Status – Health Inequalities Matrix (Panayotov Matrix) Table 2. shows how the outcome from an intervention implemented on population impacts average health status (AHS) and health inequalities (HI). From any intervention people can be either better-off or worse-off, or without a change. Different combinations of distribution of the benefit before and from a new intervention mould the correlation between AHS and HI. Yes indicates a change, and if it is in a box under Better-off, there can be only No in the corresponding box under Worse-off. And Yes in box under Worse-off means that there can be only No in the corresponding box under Better-off. Any row can have either zero times Yes (meaning no change for all groups), or one Yes, or maximum two times Yes. Two times Yes under Better-off mean that AHS always will increase, and two times Yes under Worse-off mean that AHS always will decrease, while the situation for HI (increase, decrease, or remains the same) will depend on the balance of gain/loss between recipients. Specific combination of distribution of the benefit from an intervention can achieve nothing else, but the predicted for this combination impact on AHS and HI. 7 Table 2. Panayotov Matrix OUTCOME FROM NEW POLICY, PROGRAM or INTERVENTION Better-off Previo us Winne rs YES NO NO NO YES NO YES NO NO Previous Losers NO YES NO NO NO YES YES NO NO Worse-off Previous Previous Winners NO NO NO YES NO YES NO YES NO Losers NO NO YES NO YES NO NO YES NO X* X* AHS HI Case (Graph2) X X X X X* X* X* X* X X X X X X X^ X^ X^ X^ X^ 1 2 3 4 1, 3, 5 2, 4, 6 1, 2, 7 3, 4, 8 X X X X^ X 9 * Whether AHS increases, decreases or remains the same depends on the ^ balance of the gain/loss between recipients (can be positive, negative, or neutral). Whether HI increase, decrease or remain the same depends on the ba lance of the gain/loss between recipients (can be positive, negative, or neutra l). Graph 2. represents the correlation between AHS and HI in time as result from different combinations of distribution of the benefit among population. The concrete curve for specific population is not something fixed or static. It is something dynamic, which is constantly impacted by the distribution of the benefit from implemented policies, programs and interventions among this population. In other words, the concrete situation constantly changes depending on who-gets-what from implemented policies, programs and interventions in their interaction. The last part means that there might be simultaneous implementation of different interventions, which affect the population with different force (magnitude) and in different directions, i.e. winners from one intervention might be at the same time losers from another intervention. For simplicity general trends of the interaction between AHS and HI will be analysed here. 8 Small variations over relatively short periods of time, or the interaction between simultaneous interventions will not be considered here, since these will result in equivalent resultant trends, or in other words – in an aggregated cumulative impact. Nevertheless the general rules described below, which shape the correlation between AHS and HI, apply in all cases of interaction whether it is at micro level over short periods of time, or at macro level over long periods of time. Theoretically there are eight possible combinations between AHS and HI, plus one when there is no change in both variables. Of these nine, four combinations (“major”) have change in both variables – AHS and HI, and four (“minor”) have change in one variable while the other remains the same. Major combinations are represented in the following cases (Graph 2.): 1) AHS increases and HI increase (red line) 2) AHS increases and HI decrease (green line) 3) AHS decreases and HI increase (black line, left & up) 4) AHS decreases and HI decrease (dashed black line, left & down) Graph 2. Average Health Status – Health Inequalities Matrix Panayotov Matrix in Time HI DPP AHS AHS – Average Health Status HI – Health Inequalities DPP – Dead Perform ance Point Minor combinations (not shown on Graph 2.) are represented in the following cases: 9 5) AHS is the same and HI increase This would be a vertical black line going upwards (continuous DPP, explained below). Case 5) means that although that there is improvement in health for some persons, growing health inequalities have caused AHS to stall, because some individuals are now absolute losers and any improvement among the winners is offset completely by deterioration among the losers – the gain of the winners equals the loss of the losers. When deterioration among the losers exceeds the improvement achieved by the winners, the system moves on Case 3). This happens if the new interventions still do not address accumulated HI by benefiting more the previous losers. Usually this situation is result from interventions continuously creating double losers – people are losers for long periods of time. Consequently, HI grow to a point when some people become absolute losers and the deterioration among them is not offset by the gain among others. 6) AHS is the same and HI decrease This would be a vertical black line going downwards. Although that HI decrease, the changes are not to be considered positive. There is something fishy with it. If no one is absolute loser, i.e. worse-off compared to his/her previous situation, any decrease of HI should lead to an increase of AHS. Case 6) means that those who were better-off (previous winners) have become absolute losers from the new intervention and the improvement among those who were worse-off (previous losers) is offset by this deterioration, therefore AHS stalls. This is an intervention where the improvement achieved is offset by deterioration among those who were better-off. 7) HI are the same and AHS increase This would be a flat red line which can be not bad, if the level of HI is low, but this is not good either. Even if the level of HI is relatively low, decision-makers should aim to achieve Case 2), or “bringing health differentials down to the lowest levels possible”, as Whitehead (1990) suggests. Case 7) means that although that there is improvement in health status for the whole population, the implemented interventions actually maintain the same level of differences in health status between the individuals. Such situation where HI remain the same is not a comfort, especially if the level of HI is high. Maintaining high levels of HI pulls the system towards Case 1), where HI continue to grow. 10 8) HI are the same and AHS decrease This is very bad situation, a flat red line going backwards – from right to left. This case represents equal deterioration in health for the whole population. Such “fairness” hardly can be a comfort. This case is an example of wrong choices of interventions, which represent highly inefficient use of limited resources. It means that the allocation of resources is not on Pareto Optimality curve AB from Graph1., but in a point which is somewhere inner and therefore everyone gets less benefit. 9) No change both in AHS and HI This may not be bad, if HI are low, but still it is not good enough. Even if HI are low, decision-makers should always aim to achieve Case 2). Why would people bother with implementing new intervention, if as result there is no improvement? This situation means inefficiency – waste of time and resources to implement something, which makes no difference. If this is the case, then from societal perspective keeping the existing situation would be better-off. The resources spent for developing and implementing new intervention, which brings no result, could have achieved some other extra benefit, if these resources have been allocated for another intervention. Main Combinations between AHS and HI Case 3), AHS decreases and HI increase (black line, going left and up) is example for a system, which drifts away from the goal of WHO and public health. This case does not mean that everyone is worse-off. This case is result of interventions creating absolute losers among the previous losers. This means that some people (previous winners) may continue to improve their health and quality of life, while the health of other individuals deteriorates. Since the deterioration among the losers exceeds the improvement among the winners, the result is that AHS starts to decrease while HI continue to grow. This situation happens when some parts of the population are most of the time winners from implemented interventions, while other parts of the population are most of the time losers. When the benefit which the relative losers get (if any) from implemented interventions is not enough to maintain their health, the only thing that can happen with their health is to deteriorate. This, although being already a step away from improving health and quality of life of whole populations, may not lead immediately to a decrease of AHS, provided that the gain of the winners can exceed the loss of the losers. However, when the gain of the winners can not any more 11 compensate the loss of the losers, AHS starts to decrease and it becomes obvious that the results from implemented interventions actually deviate from the goals set. Case 4), AHS decrease and HI decrease (dashed black line, left & down) represents very bad situation. The decline in HI is not due to some positive effects of implemented interventions. This is due to rapid deterioration affecting large groups of the population. This can happen during a war, or natural disaster on a massive scale when hospitals are destroyed, there are no medicines, no clean water, no food, no shelter, etc. The greater the destruction in area and magnitude, the more people will be affected, thus the greater the decline in AHS will be. Within affected territory, initially the level of HI might be retained. When individuals experience equal adverse conditions, those who have better initial health might have better chances. However with time passing, i.e. with longer exposure to such conditions, HI will start to diminish. Red line represents Case 1), increasing AHS with an increase of HI. This happens when the health of those who are better-off improves faster than rest of the population and as result HI increase. In other words, those individuals who were better-off (winners) before, once again benefit more from the new intervention, therefore their health and quality of life gets further ahead from rest of the population. When this situation repeats over time the differences in health and quality of life among population grow. When these differences are considered avoidable and unfair, they represent HI. The line gets steeper, because with accumulation of HI it becomes more difficult for AHS to increase at the same pace. This is so, because some of the improvement achieved is needed to compensate accumulated HI first. In order to improve faster AHS of whole population it might be tempting for decision-makers to develop and implement interventions which benefit those who already are better-off, because they have greater capacity to improve. However, continuing with such practice inevitably makes the whole picture not so nice in long-term. Focusing on improvements in AHS by using only average data for presenting the outcomes can mask widening of HI. If it is not clear who-gets-what from a certain intervention, then the real picture can be blurred substantially. Paradoxically AHS can increase even when the health of some individuals deteriorates, provided that the improvement among those who are better-off from an intervention can exceed the deterioration among the others. This situation, where health gain and health equity are 12 not interdependent has its supporters, as it complies with Kaldor-Hicks criterion for efficiency, which states that, if the gain of the winners is greater than the loss of the losers, we have net social gain. However, resource allocation (interventions) being continuously based on Kaldor-Hicks criterion, can not achieve the ultimate goal of WHO and public health. As explained above, when the losers from new intervention are those who already were losers before the change (even if they are relative losers, and not absolute losers), the result can be only one: growing differences between individuals’ health. Apart from being unfair, this is inefficient as well, since the result – health and quality of life among whole populations - is not the maximum that could have been achieved from the same resources if these were allocated for intervention with different distribution of the benefit. With accumulation of HI much more resources are needed in order to enable AHS to continue to grow, although much slower. Even maintaining existing levels of AHS and HI requires more resources and the governments are faced difficult choices. In report “Rising health costs put pressure on public finances” OECD (2006) notes that, if current trends continue governments will need to rise taxes, cut spending from other areas, or make people spend more out-of-their-pocket in order to maintain the existing systems. Now, in 2009, the situation is even more difficult with the global financial crisis. When health gain among those who get it can not anymore exceed the deterioration in others, the system comes to Dead Performance Point (DPP), i.e. growth of AHS stalls in spite of growing resources spent. In DPP there is no increase in AHS, although that there can be substantial improvement in health and quality of life for some individuals – the winners. Accumulated, but not addressed HI among the losers are now causing health deteriorations, which offset completely any health gain in those individuals who benefit from implemented interventions – the winners. DPP is unsustainable point, because the occurred health deteriorations require more resources to be spent for achieving enough health improvements to compensate the deteriorations in order to prevent AHS from slipping back, i.e. to decrease. However, extra resources invested will not improve AHS, if allocated improperly, i.e. if the existing losers continue to lose again. Such interventions will mark the start of Case 3), where HI continue to grow while AHS starts to decline. If there is no change in the distribution of the benefit (still not targeting previous losers), or if the invested extra resources (provided that these are available) can not achieve improvement 13 among the winners which is big enough to compensate the deterioration among the losers (provided that tax payers who finance health collectively (Table 1.) are happy with such distribution of the benefit), then the system moves on the black line – Case 3) explained above. Green line represents Case 2), increasing AHS with decrease of HI. This happens when the health of those, who are worse-off, improves faster than rest of the population and as result HI decrease. In other words, those individuals who were losers before are now winners from the new intervention, therefore their health and quality of life is catching up with rest of the population. With such interventions AHS increase while the differences in health and quality of life among population decrease. How steep is the green line depends on the initial level of HI and the commitment of the society to diminish these inequalities by resource allocations with appropriate distribution of the benefit among population. This means developing and implementing interventions which target HI, without at the same time creating absolute losers among those who already are better-off. Implementation of Case 2) can start from any point of any other case mentioned above, provided that there is a will from the society to do so. Implications for decision-makers Creating double losers – when those who were losers before are once again losers from the new intervention – is the fundamental cause for increasing differences in people’s health and wellbeing. Creating double losers is a step away from the high goal of WHO and public health, as it does not maximize the outcome/benefit for whole population. Creating double losers is inefficient as well, since different allocation of the same resources (i.e. other intervention) could have achieved greater outcome/benefit for whole population. Creating double losers leads to growing health inequalities, as those who benefited less from the previous policy/intervention continue to miss out from the new policy/intervention. Creating double losers is not in line with declared by the society ethics that all individuals are of equal value and have the same rights, since by such resource allocation (policies, programs or interventions) some individuals/groups are favorized while other are neglected. Creating double losers does not take into account preferences of the public – tax payers – who fund health collectively (Table 1.), when choices for policies/interventions are made. 14 AHS–HI Matrix is a model which analyses the distribution of the benefit from an intervention within the population. Being based on critical realism, i.e. “if A then always B”, the model provides universal explanations and predictions. The model explains the generative mechanisms which impact the correlation between AHS and HI. In other words, the model explains the generative mechanisms which create, widen or diminish HI. It is the distribution of the benefit, it is the combinations of winners and losers from an intervention at local level, which mould this correlation. The model offers a solution for the problems with evidence in public health. The evidence, whether an intervention implemented on population “works” or doesn’t, is something relative and depends on the distribution of the benefit, in other words, on considering previous and new winners and losers in a specific case. Identical interventions achieve very different outcomes when applied to different populations, because of the differences in the distribution of the benefit in a specific case. Different combinations of previous and new winners and losers among these populations lead to different outcomes from implemented identical interventions. Since people’s health and quality of life are influenced – although indirectly – by other activities outside the health system, this model is valid also for interventions in other spheres of the economy to the extend that these impact people’s health and wellbeing. Therefore this model provides the theoretical framework for Health Impact Assessment (HIA), which tries to determine and assess the distributional health impact of a policy, program or intervention on different groups within the affected population. The model is useful for justification on efficiency ground of policies, programs and interventions addressing Social Determinants of Health (SDH). The greater the impact of an intervention on people’s health and wellbeing, the greater the power, validity and applicability of this model is. Conclusion There are always winners and losers when allocating resources. People choose which path from Graph 2. to follow by deciding what will be the distribution of the benefit or who-gets-what from an intervention. Having losers from an intervention is inevitable and de facto means that some claims of the recipients for getting more resources are declined. The art for decision-makers is to make proper choice for allocating limited resources, which will maximize the outcome/benefit for whole population. 15 In real life even when appropriate interventions are in place HI may tend to zero, but might never reach nil. This should not prevent decision-makers always to aim diminishing of HI by developing and implementing interventions with distribution of the benefit according to Case 2). Avoiding double losers is not only an act of fairness, it also improves efficiency in use of public resources in relation to health. Such distribution of the benefit achieves greater outcome for whole populations with limited resources – precisely what the public wants and what the goal of WHO and public health is. It is important to emphasize that the goal for improving AHS should go hand in hand with the goal for reducing HI, as a premise for financial, organizational and political sustainability. AHS–HI Matrix – Panayotov Matrix – is a useful tool which helps researchers, decision-makers at any level, as well as local practitioners to: a) explain and analyse observed empirical findings; b) make predictions about future direction of AHS and HI; c) make proper choices of policies, programs and interventions in line with declared by the society ethics and with goal of WHO and the new public health. ____________________________________ 16 Notes: (1) On 16 April 1997 Swedish Parliament adopted in bill No. 1996/97:60 The Ethical Platform, where explicitly is stated that “all people are of equal value and have the same rights, irrespective of their personal qualities or functions in the society”. (2) In relation to health, as in other sectors, there is diminishing return from allocated resources. This means that an extra dollar allocated to someone who gets much less achieves greater benefit than an extra dollar allocated to someone who gets much more. On the other hand, the consumption of additional units of a particular good brings to the consumer less utility than the previous units, which is called diminishing marginal utility. These two - a) diminishing return, from point of view of those who provide resources, and b) diminishing marginal utility, from point of view of those who consume resources – together provide the justification for declining some claims of the recipients, if the goal is maximizing health and quality of life of whole populations. Apart of this, in relation to health the agency relationship in combination with information asymmetry and power asymmetry are the premise for a phenomenon called supplier induced demand (SID). Sherman Folland et al. (2001) noted that “SID occurs when physicians abuse the agency relationship with their patients in order to generate demand for personal gain”. Thomas Rice (1999) has noted “the waste (of resources) is thought to be generated through provision of unnecessary services far more than through excess demand by patients.” Declining some claims of both recipients does not mean that essential, lifesaving goods and services are denied. It is rather about declining claims for goods and services from which the recipient can not benefit. For example: unnecessary, excessive and duplicated diagnostics and/or other procedures with no benefit for the recipient. In Sweden, SOU (1995), the Parliamentary Commission on Priority Setting stated in its final report that “you have only need for something that you have use of, or … you have no need for something that you have no use of.” (3) Woolhandler and Himmelstein (2002) show that in USA tax-funded share of health spending is higher than the figure in OECD report and actually is almost 60 %. 17 References: Folland, Sherman et al. 2001. “The Economics of Health and Health Care”, 3rd edition, Upper Saddle River, NJ: Prentice Hall Nutbeam, Don. 1998. “Health promotion glossary”, Health Promotion International, 13(4), 349-364 OECD (Organisation for Economic Co-operation and Development) 2006. Press release: “Rising health costs put pressure on public finances”, 26/06/2006 http://www.oecd.org/document/37/0,3343,en_2649_201185_36986213_1_1_1_1,00.html (Last Accessed: August, 2008) Rice, Thomas. 1999. “The Economics of Health Reconsidered”, Health Administration Press Rosen, Per. 2002. “Attitudes to prioritization in health services”, Nordic school of public health, Goteborg, Sweden Smith, Richard. et al., Resource Allocation Decisions and the Use of Willingness-topay as a Valuation Technique Within Economic Evaluation, Working Paper 87, CHPE, Melbourne, 1999 SOU, 1995:5, p.112, Vardens svara val. Slutbetankande fran Prioriteringsutredningen. Stockholm: Socialdepartementet. Whitehead, Margaret. 1990. “The concepts and principles of equity and health”, World Health Organisation, Regional Office for Europe, Copenhagen Woolhandler, Steffie and Himmelstein David, (2002). “Paying For National Health Insurance – And Not Getting It”, Health Affairs, Volume 21, No.4: 88-98 18