ESTIMATES OF NATIONAL HEALTH ACCOUNTS(NHA) FOR 1997

Jean-Pierre PoullierPatricia Hernández

GPE Discussion Paper Series: No. 27

EIP/GPE/FARWorld Health Organization

The authors are indebted to Chandika Indikadahena who has maintainedthe data files on which the NHA-2000 have been constructed. Thisconstruction would not have been possible without an input from severaldozen persons who have responded to data request and commentedpreliminary versions of the data files; this input will be acknowledged ina forthcoming releases on NHA.

Contents

I. National Health Accounts: Why and How?......................................... 3

II. What is the NHA tool ......................................................................... 5

The 15 / 75 - 85 / 25 divide ................................................................. 6

NHA boundaries and NHA attributes ................................................ 10

Selected identities of the NHA-2000 ................................................. 15

III. Methodological considerations ....................................................... 17

Public Expenditure on Health ............................................................ 18

Private Expenditure on Health. .......................................................... 24

The NHA-2000 template .................................................................... 25

Non-financial variables ...................................................................... 29

The underlying data for the WHR 2000............................................. 29

IV. A tentative state-of-the world 1997 overview ................................ 31

South East Asia................................................................................... 33

The East Mediterranean...................................................................... 33

The Pacific.......................................................................................... 34

Sub-Saharan Africa............................................................................. 35

A Latin American Perspective: Social Financing............................... 36

Europe & Central Asia After the Shemasko era ................................ 37

Wealth and Health .............................................................................. 38

V. Bibliography..................................................................................... 46

VI. Annex. ............................................................................................. 47

I. National Health Accounts: Why and how?

A sunray is the most powerful of disinfectantsJustice O.W. Holmes

Differentials in the health status of populations are considerable(see World Health Report 2000, annex 5). There is a strong correlationbetween health status and real income, more precisely the acquisitivepower that accompanies wealth. In the present state of measurement,under a tenth of that acquisitive power is oriented towards goods andservices that directly enhance health. Non-medical as well as medical-para-medical determinants are frequently referred to in policy analyses,though only marginally captured by rigorous tools. As they attractresources, a challenge of the next five years is the integration of neglecteddeterminants of health into the accounting framework and theestablishment of weights to attach to medical and to non-medicaldeterminants of health.

The basket of goods and services that directly enhance the healthstatus of the population experiences huge differentials in productivity andin costs. Variations in the quantities consumed of these goods are largewithin small areas, as well as across nations, or continents. The financingpaths adopted result in a wide array of incentives and disincentives, andin greater (or lesser) patterns of citizens' equality irrespective of age, sex,income and social status, disease and disability. A keener knowledge ofspending levels and trends, of the efforts deployed in each nation toprovide health enhancing services, of the costs and the use patterns ofdeterminants of health status improvements, of the incidence of healthcare costs on the income status of the sick and disabled, appears thus tobe essential to a more effective deployment of resources. The majorunresolved policy puzzles of inappropriate allocation of resources tax theability of the statisticians called to monitor policy and their outcomes.The search for a more effective use of the whole array of allocativeinstruments towards social goals attainment, requires greatertransparency. Given the intertwined paths to deliver and to finance healthservices, an extensive knowledge of privately funded health enhancementtransactions is further required.

National Health Accounts (NHA) aims to achieve a comprehensiveand consistent synthesis of health-related activities by enlightening themain policy parameters of society. It can facilitate simulations that canbetter reflect an increasing complex system of delivering and financing

care in light of a rapid evolution of medical technology and otherorganizational determinants.

Only a tenth of the World Health Organization countries haveundertaken a financial synthesis respecting fully NHA standards,including institutionalisation that supplies figures on a recurrent basis. Inorder to accelerate the emergence of NHA in the rest of the world'scountries not yet equipped with a synthetic tool to monitor healthspending and finance, the WHO is providing a basic set of NHAindicators for all of its 191 Member countries, hereafter referred to asNHA-2000. The latter are not a compilation of existing country-specificNHA; they respond to a methodology developed to ensure a comparablesynthesis across nearly 200 countries. Breaking down the 191 countrysegments, the figures for two thirds of the countries are based on periodicspecialised international publications and one third is estimated based onvarying degrees of information available, completed using standardestimation techniques.

NHA-2000 uses, as much as possible, a common framework thatplaces a greater emphasis on the financing side of the NHA triangle thanon its consumption or production sides. In the ideal National Accounts,the three sides –– are in equilibrium as an equilateral triangle or, due tostatistical conventions, at least as an isosceles triangle. No NationalAccounting system, nor any National Health Accounts, has to datemanaged during its first iteration to capture the complex reality of themacroeconomic relationships it seeks to describe. Successive iterationsshould altogether transform NHA into a daily life managerial policy tool.

This note recalls in Part II some conceptual underpinnings of NHAand the rationale of the WHO exercise for the World Health Report 2000.Part III dwells on the methodological options adopted to estimate healthexpenditure, and Part IV discusses the set of measured levels of healthexpenditure (or sets, as different regions of the world and different areaswithin each region exhibit altogether commonalties in spending patternsand considerable heterogeneity in their delivery, financing and statisticalmodalities). The quantitative observations in this discussion paper and inthe World Health Report 2000 refers to the 1997 calendar year (oradjacent fiscal year). Like for any first undertaking, the essential lies,however, not so much in the precision of the orders of magnitudepublished as in the drive towards transparency.

II. What is the NHA tool

NHA may be defined as an integrated set of cross-classificationspurporting to measure health related activities and economic flows:inputs, output and resource use, contributing to the enhancement of healthstatus.

NHA is a reductionist model of society, and caters to thepopulation at large. It lessens the myopia of a policy machinery temptedto deal with problems in sequence and in isolation. It creates an informedconstituency of stakeholders around identified objectives and diverseorganisational arrangements. It distributes the gains of policyinterventions and of individual commitments across the entire spectrumof the system.

Chart 1 illustrates the strategic convergence at which NHA islocated in a global information system monitoring interventions on thesystem and health gain. The flowchart idealises real world conditions inwhich NHA are often rudimentary and are not integrated in a cogent anddecision-prone information sub-system. A picture of the more idealsetting provides a horizon of the potential of the tool, if not an ambitionand a target.

As developing country governments face the many challenges ofstrengthening stewardship and managing health system reforms, theimplementation of NHA provides an opportunity to considerably expandthe monitoring of these systems. The strengthening of a health system’smonitoring capacity constitutes an important step towards themodernisation of its governance. Active stewardship requires interactionbetween financial/non-financial information which would permitdecision-making in the face of diverse challenges caused by economy-wide constraining factors such as austerity programmes and their impacton health needs and systems.

Irrespective of the financial formulas that prevail, povertyreduction efforts require additional resources, a strengthening of capacitybuilding, and a more efficient deployment of resources. More effectivestewardship requires a greater focus on norms and a standard setting.These are not easily translated into an accounting framework, but NHAcan provide a tool that permits a sharper and transparent focus onstructural change and on distribution issues ..

Chart 1. An Accounting Approach to the Production Flows in theHealth System.

The 15 / 75 - 85 / 25 divide

A wide gap in health research has previously been documented:about nine tenth of the world’s R & D on medicine and related healthsciences is allocated to the alleviation of around one tenth of the world’sdisease burden and, conversely, nine tenths of the world disease burdenattract around one tenth of the world R & D effort. The gap is barelysmaller in the total allocation of resources towards care and cure. Themeasured input into the health systems of the world shown in Table 1 –which summarises by mortality stratum the information captured in theWorld Health Report 2000 – suggests that the high income countries(AMR-A, EUR-A, WPR-A, together 15 % of the estimated worldpopulation) capture three quarters of health spending while 85 % of the

world’s population has a quarter of the total resources devoted to thealleviation of disease and disability. Expressed in a standard of livingequivalent currency, the three quarters – one quarter divide is marginallyless dramatic than the inequality indices depicted in Charts 2 and 3whereby some 120 countries spend less than $ 20 per capita per month onhealth compared to over $ 200 in AMR-A (made up of the United States,$ 4,187 per head per year, Canada $ 1,783, and Cuba $ 131). Theillustration shows one among many dispersions masked by regional orsub-regional averages. These intra-regional disparities matter: inequalitieswithin low-income countries are often larger than those found in betterendowed countries and, at times, exhibit utilisation patterns thatconstitute a social waste.

Table 1. Measured spending on health in the world, 1997Mortality

sub-region

Numberof

countries

Totalexpenditure onhealth at X-rate

($ million)

Share of worldexpenditure on

health%

Share ofworld

population%

Per capitaspending at X

rate(US $)

AFR-D 26 6,461 0.3% 4.7% 24AFR-E 20 14,097 0.6% 5.4% 45AMR-A 3 1,143,480 44.9% 5.4% 3,652AMR-B 27 75,895 3.0% 7.3% 180AMR-D 5 5,312 0.2% 1.0% 94EMR-B 13 25,247 1.0% 2.3% 193EMR-D 9 12,965 0.5% 5.7% 39EUR-A 26 766,765 30.1% 7.0% 1,876EUR-B 19 26,232 1.0% 3.9% 115EUR-C 6 28,897 1.1% 4.0% 125SEA-B 3 12,637 0.5% 4.8% 45SEA-D 7 29,208 1.1% 20.3% 25WPR-A 5 339,450 13.3% 2.6% 2,235WPR-B 22 59,407 2.3% 25.5% 40Total 191 2,546,054 100.0% 100.0% 438

Notes:1. The area sub-totals refer to total mortality levels, ranked from low (A) to high (E) level, ascale developed at WHO on the basis of an analysis of the data file that collates mortalityfigures by age-sex and ICD cause for all countries; clusters have been designed on the basisof an analysis of the disease burden in the world (see World Health Report 2000, pp 204-5). Astands for very low child and very low adult mortality, B low child and low adult mortality, Clow child high adult mortality, D high child and high adult mortality, E very high child and veryhigh adult mortality. AFR stands for the African region, AMR for the Americas, EMR for theEast Mediterranean region, EUR for Europe and part of Central Asia, SEA for South EastAsia and WPR for the West Pacific region.2. Total Expenditure on Health is the measured level of public and private outlays convertedat the exchange rate obtainable on average from commercial banks during 1997.Sources: WHO NHA-2000 data files for expenditure on health, IMF for exchange rates, UN forpopulation.

A keener knowledge of the paths towards greater effectiveness isacquired through a domestic planning and evaluation process.Comparative analyses help to focus on strengths and weaknesses offoreign experiences, thereby shortening the learning curve and generatingeconomies of scale. Modern policy analyses of health systems relyincreasingly on quantitative demonstrations. The expenditure, provision,and financing paths traced by countries facing much the same challenges,pursuing much the same goals, facilitate policy simulations in countriesseeking similar successes or desirous to avoid the same pitfalls. Policysimulations, however, are not automatic as no two countries have thesame mix of instruments, incentives and regulations.

Chart 2. Inequality of opportunity revisited: Distribution ofmeasured per capita expenditure on health, 1997

Source: WHO, NHA-2000 data files.

NHA are intrinsically flexible so as to apply to an ample spread ofalternative policy set-ups on the financing as well as on the delivery side.Different models of NHA express, however, central features of the healthsystem to which they apply. The “Harvard model” (which has inspired amajority of the NHA developments to date in Latin America, the EastMediterranean Basin, South East Africa), stems from the multi-payerHCFA (US Health Care Financing Administration) approach. The Dutch,French, German and a number of other European models place moreemphasis on spending functions where a more limited number of payersdevote a larger part of its attention to the price-volume interface. Asmaller number of countries, such as Norway, have opted instead forinput-output models with emphasis on production; satellite Health

0%10%20%30%40%50%60%70%80%90%

100%

< 700 700-1,300 1,300-40,000

GDP per capita strata

Share of w orldexpenditure onhealth

Share of w orldPHE

Share of w orldPvtHE

Share of w orldpopulation %

Accounts (satellite to the National Accounts) require this close level ofcorrespondence with value added. The ambitious OECD model, designedto apply in a complex, multi-dimensional process environment, addressesthe three main sets of questions :

• where does the money come from? (sources of funding)• where does the money go? (provider of health care services and goods)• what kind of services is performed and what types of goods are purchased?

The latter is a step towards outcome measurement, a perspective greatlyenhanced by achievements in the field of summary measures such asDisability Adjusted Life Expectancy (DALE), Potential Years of LifeLost (PYLL), and Disability Adjusted Life Years (DALY).

Chart 3. Distribution of countries by per capita expenditure onhealth, 1997.

Source: WHO, NHA-2000 data files.

Health policy analysts regularly stress the uniqueness of eachhealth system as it is instituted to respond to culturally determineddemands. To the uniqueness of the supply-demand interaction correspondunique indicators. In business, however, the discipline to establish world-wide reporting norms make it possible for companies to compile one setof books for investors everywhere. The International AccountingStandard (IAS) blueprint is gaining increasing recognition. A similarjustification imposes homogeneous concepts, definitions andmethodological guidelines to model and trace the economy at large. TheSystem of National Accounts (SNA) is complemented in a number ofareas by specific statistical systems under the aegis of the United Nationsand its specialised agencies, the IMF, the World Bank, the OECD, the

130

18

25

13

5

0 50 100 150

< 250

251 -500

501 -1 ,500

1 ,501 -2 ,500

2 ,501 -4 ,200

THE

per c

apita

Number o f c oun tr ies

Statistical Office of the European Union and numerous regional statisticalbodies.

As the economies moved more global, the reach of SNA extendedin depth and in width with satellite accounts in areas such as agriculture,education, R&D, tourism and transport. A handful of countries have alsoinitiated a satellite account for health but most of these have been partialachievements due to inaccessibility to needed data to build a full-fledgedsatellite account.

The NHA-2000 has not adopted the path leading to a satelliteaccount, as this would have required full consistency with the frameworkof the SNA and a more detailed cross-classification of transactions, ofproviders and of income flows than what is available. The prospectivebenefits are not commensurate with the costs entailed, not countingconsiderably greater lead times before availability of usable results. Withdisparities such as those shown in Chart 3, for comparative purposes thegreater accuracy of satellite accounts is perhaps not warranted.

NHA boundaries and NHA attributes

Conventionally confined to medical care and a few relatedactivities, the policy relevance criterion (listed below as a major attributeof NHA) dictates that its boundaries should be extended to include arange of non-medical interventions whose primary intent is theenhancement of health status, and for which the implementation resultsfrom interventions over which the health system is accountable for. Asfor other areas of economics and social accounting, when a pro rataallocation of joint products is not practical, the entirety of the jointproduct is classified in the branch with the heaviest weight. As ineconomic and social accounting, boundaries are set in respect of definedclassifications and with a degree of flexibility to accommodate “culturalexceptions”.

Practical difficulties have impeded the implementation of theseprinciples in the NHA-2000. A lack of disaggregated data has often beena roadblock, though they relate to areas in which an extension of theconventional boundaries might have encountered only limited opposition.

The boundaries are often difficult to distinguish between the basicsurvival function (which includes food, access to drinking water, andshelter) with the health function (which includes community values, the

ability to perform in society without impairments, handicaps anddisability). In many sub-Sahelian and tropical countries, ministries ofhealth have the provision of safe drinking water within theirresponsibility, and consider it a health related expenditure. In theAmericas and in Europe the sanitation function is distinct from the healthfunction. The primary intent moved from health enhancement to that ofsecuring a minimum level of environmental amenities and access to afloor level of facilities.

Should there be different boundaries in different NHA around theworld? Should key amenities be included as an addendum item below thehealth total? Should the “ancillary” services be only reported assanitation? The latter is the solution adopted by the classification of thefunctions of government, COFOG, one of the pillars of the system ofnational accounts. Should the production of seat-belts and airbags beconsidered as serving more a primary health intent than a transportationcomfort? Does the removal and disposal of solid waste not contribute tohygienic as well as to aesthetic values? The reduction in exposure topesticide contamination, chemical and industrial pollution, air pollution,sewage, lead pollution, radioactive wastes, head a list of environmentalprogrammes designed to reverse neurological, respiratory, endocrine andmental impairments of the affected populations.

There needs to be a periodic review of what it is that societies needto monitor and where they classify the provision processes and theconsumption functions. Fluoridated toothpaste has strongly contributed toreceding tooth decay in the richer societies; in statistical records, thesepurchases are not readily separated from cosmetics and toiletries whosecontribution is more of an olfactory nature. The need for flexibility inclassifications is highlighted further by epidemiological and technologicaltrends. Catastrophic illnesses, such as AIDS, consume increasing sharesof the total health bill. Countervailing strategies require conventional aswell as non-conventional strategies; it is important that the latter be fullymonitored. With computarisation, the level of disaggregation and thegeographical extension of alternative classification extends already tomiddle income countries a statistical sophistication open yesterday tohigher-income countries.

Although country details have not been forthcoming to ensure anitemised implementation in the NHA-2000, the latter has been notablyconstructed using an implicit draft classification of public healthfunctions. The prevention and health promotion components of thisclassification reach out to interventions, or the production of goods whose

primary intent is the enhancement of the health status of target groups inthe population. Education and the training of health personnel, researchand development, food hygiene and drinking water control, andenvironmental health are some of the domains retained. Whereas curativemedicine and the relevant classification mainly deal with interventions onthe pathos (disease as a real event), public health mainly deals with nosos(disease as a threat, a risk) that requires more evidently a widermultidisciplinary approach and interventions. A System of HealthAccounts (hereafter referred to as the OECD Manual) shares much thesame approach.

The NHA matrices condense a complex reality made of a zilliontransactions around simplified classifications, depicting particularattributes of these transactions. A comprehensive, systematic andstandardised quantification path of all financial resource variables, theiruse and distribution is summarized in chart 4. Whilst NHA-2000concentrated on providing aggregate information for 191 countries, futureeditions will seek to supply more disaggregated information.

Chart 4. The main financial flows in a health system.

As a statistical system, the NHA process entails respect of ten majorattributes. Their simultaneous pursuit is difficult because several areseemingly contradictory. The essential attributes of NHA are:

• Policy sensitivity: NHA seek to identify and quantify parameters, aswell as to focus on providing information describing components ofthe health system susceptible of changes through interventionsdesigned to improve selected facets of the system's effectiveness;

• Comprehensiveness: NHA strive to monitor all the health fieldexpenditure, provision, inputs and outputs, intermediate and finaloutputs, financing flows of the institutions / and of the functions thatmake up a health system;

• Consistency: internal coherence and avoidance of contradictions areachieved through standardised classifications, explicit identities andexacting accounting rules;

• Bookkeeping + imputations: an accounting system does not stop atintegrating dispersed data from a variety of institutional sources.When an economic function performed by the system is not

Other public sources(taxes, wealth)

Households and FirmsExternal resourcesGrants & loans

Compulsory contributions(through public agencies):

Payroll taxes, social security premiums

Voluntary contributions(through public & private agencies):

Purchases, donations, copayments

Public health budget Social security budget Private medical insurance &other pooled payments

Direct payments

Sources ofSources ofFinancingFinancing

Provider AgentsProvider Agents

For non-insured population For insured population Not-for-profit providers For profit providers

*

* Includes mandated employer** Includes collective consumption and investment, such as administration, R&D and public health.

FunctionsFunctions

Health goods and services provision **

Hospital services Ambulatory services Pharmaceutical &therapeutic appliances

Other health careservices

quantified in the available sources of information, the relevant orderof magnitude must be simulated and entered alongside;

• Standardisation: the application of identical rules is a requisite foranalyses over time and across countries. At individual country level,this process yields economies of scale in supplying ready-madeconcepts, definitions, nomenclatures and other methodologicaldevices;

• Multidimensionality: the expenditure analysis is not relevant per sebut in terms relative to the population needs to be satisfied and to theinstitutions to which they refer. This entails that expenditureinformation needs to be complemented with non-financialinformation of a demographic, epidemiological, service utilisationnature, as well as by stocks of human, tangible and intangiblecapital;

• Accuracy: the levels and time series reflect arbitrages betweencompleteness and accuracy, since large data sets built for diversepurposes, according to different methodologies and for differentdates/or periods have to be combined;

• Timeliness: while survey data are structural information whosebehavioural relationships evolve only slowly, trends of selectedcomponents of NHA may exhibit rapid and deep changes.Opportunity to interact with policy decision is greater when apreliminary NHA synthesis is completed within six to ten monthsafter the close of the fiscal year to which it relates (strenghtened,whenever possible, by a projection of trends based on a no-policychange scenario). The planning and budgetary process requirespreliminary data susceptible to be adjusted before formal publicationin a second round estimation. In the countries that release their firstestimates before the budget has to be voted on, a provisional releaseof the macro-health aggregates offers a more reasoned base on whichthe government and the parliament can act. The balance betweentimeliness and accuracy may be struck by an arbitrage in which theadded value of new information is weighted against theconsequences of delayed action by policy-making bodies;

• Recurrence: behavioural monitoring is assured only through acontinuous estimation. Continuity of estimates is the only way tojudge if results of estimates are exceptional or expected. Continuityentails the benefits of a learning curve to improve the quality of the

estimates and diminish the costs of producing them: single year’ssyntheses are a financial survey or analysis, not a NHA..

• Distributions: the amount of resources consumed or funds spent isthe initial synthesis established. An essential policy dimension is tocater to strata of consumers of health goods and services, of healthfunctions, of care providers, as well as to balance inputs for theproduction of health goods and services and to balance healthfunding.

Selected identities of the NHA-2000

The NHA are a sequence of identities centred around:

≡ ≡

The expenditure and production identities are expressed in value terms:

Value = Quantity (volume) * Price or V = P * Q

In national accounting, quality is a quantity, that of a good or service withhigher or lower attributes. To calculate expenditure trends, price levelsand volume indicators are required. Average prices are used foropportunity costs analyses, medical-specific prices for productivityanalyses. Volume indicators are often used to proxy quantity indices.

Total expenditure on health (THE) is defined as the sum of public (PHE)and private (PvtHE) outlays on health. Each entity is composed ofdifferent elements.

THE = PHE + PvtHE

Public outlays on health (PHE) is defined as the sum of health enhancingexpenditure of the central-federal (CGHE), regional-state-provincial(RGHE) and local-municipal governments (LGHE), of social securityinstitutions (SSHE) and of extra-budgetary outlays (EBHE). Public

Expenditure =consumption +

investmentprovision of goods

and services

Sources of financing=

Taxes+Payrolltaxes+Privatedisbursements

expenditure includes the direct provision of services as well as indirectpayments, such as the subsidisation of providers or transfers tohouseholds for the payment of their health bills, enterprise programmesenhancing the health status of their employees (and, sometimes, theirrelatives), non-profit institutions serving households health needs, directand indirect (notably through insurance) payments by households,investment in private and public facilities. This can be formalised in thefollowing way

PHE = CGHE + RGHE + LGHE + SSHE + EBHE

A crude attempt has been made, based on the available sources, toestimate in Annex table 8 of the World Health Report 2000 expenditureon health paid for by general revenue or tax-funded health expenditure(TFHE). TFHE is calculated as general government expenditure on health(GGEH) minus SSHE. SSHE has been deemed for this exercise to beessentially funded through contributions and not through income orexpenditure taxes. This is not the case in the real world. Social Security isalso partly funded in some countries through intra-government transfers.TFHE includes other governmental resources, such as external borrowingor grants, and wealth income (endowments, profits from publiccorporations other than taxes accruing to the State budget). Externalresources could only be singled out for a small number of countries sothat it is not shown as a distinct source in NHA-2000 but it is a strategicvalue to highlight in future editions. External resources transiting viaPHE and/or PvtHE (mainly non governmental organisations, NGO) it hasbeen inferred in NHA-2000 that they are expenditures of government orof NGO.

TFHE = GGEH - SSHE

Private outlays (PvtHE) integrate health insurance (PvtHI) andprepayment schemes, mandated enterprise health expenditure (MEHE),expenditures on health through non-profit health services (NGOHE) andco-payments to public health services, as well as direct payments or out-of-pocket expenditures in health goods (OOPS), which are mainlypharmaceuticals, co-payments for ambulatory care, and expenditures byfor-profit agents, such as private investment expenditure on health(PvtInvH).

PvtHE = PvtHI + MEHE + NGOHE + OOPS + other (includingPvtInvH).

Expenditure on health integrates the main components of the economicclassification:

PHE, PvtHE = consumption + investment

The financing of health expenditure comprises wages salaries, thepurchase of goods and services for the delivery of care and cure, subsidiesto producers, transfers to households, gross capital formation and capitaltransfers contributing to private investment. In order to undertakeopportunity cost analysis, private investment must be recorded. Currentexpenditure and health utilisation data do not reflect the level of privateinvestment that is responding to the rapid growth in demand for privatehealth care. A separate capital account is more necessary in the low- andmedium-income countries than it is in the higher income countries, asinvestment (private and public) accounts there for two to five times therelative levels observed in the OECD countries. Capital utilisation andcapital maintenance costs appear important variables to monitor.

Identities and conversion factors in NHA, as in most macro-economic accounts, rest on fundamental assumptions such as someone'sexpenditure is someone else's receipt or gross income. The first of these isValue = Price * Quantity. Services being by nature difficult to stock,expenditure identities applied to health typically omit (or exhibit onlyminimal) changes in inventories. The paucity of detailed information ontherapeutic appliances leads typically to equate consumption data withtotal expenditure, though conceptually this is not fully correct. Thatassumption should, however, not be equated as the absence of delayedprovision. Like most distribution issues, presently ill-monitored by NHA,delayed provision requires a special analysis and through distributionflow charts can be integrated into an NHA framework.

III. Methodological considerations

NHA require that all agents transacting in health-relatedcommodities and all transactions be monitored, cross-classified, andvalued, i.e. purchases by ultimate user or beneficiary (households forindividual consumption, the population for collective consumption),commodities by producing agents (hospitals, health centres, office-basedphysicians and other professionals, specialised retailers of healthcommodities such as children vaccination clinics, insurers and public

administrations regulating and monitoring health activity), by financialstatus (public services, insurers, charities, foreign financial institutions,households). This requires a careful mapping of all agents and alltransactions in health-related activities.

The NHA-2000 exercise has pursued two distinct aims. First, thecreation of a transitory expenditure financing statement for each WHOMember country in order to provide a reasonable order of magnitude ofresources consumed to enhance the health status of its population.Second, the stimulation of a large number of national administrations toestablish genuine NHA for their respective countries.

Each national segment has over two hundred health specific and ahundred macro-economic and demographic variables. The informationgathered permits a basic analysis of the policy-relevant public and privateexpenditure flows. The two sectors are further split into insurance andalternative prepayment schemes and outlays funded from own sources(taxation for government, mandated enterprise schemes and directpayments or out-of-pocket for private flows).

Social security programmes compulsory for a sizeable segment ofthe population are an integral part of public expenditure on health. For theprivate segment, the intent has been to distinguish expenditure on healthfrom households as prepayment and private health insurance, from that ofdirect out-of-pocket payments to purchase health goods and services(including payments for pharmaceuticals), NGO and for-profit privatehealth services. Whilst conventional National Accounts treat occupationalhealth care provided by firms as intermediate outlays, the NHA-2000classifies it as final expenditure.

Public Expenditure on Health

Public Expenditure on Health (PHE) in the context of the NHA-2000 relates to outlays for which a government entity pays. The publicentities are those subject to governmental financial and/or political and/orsocial control, whatever their legal status and whatever territory theyexert their power over. The sectoring adopted emphasises financialtransactions, not that of the legal status of the delivery agent.

General government includes central-federal authorities, regional-state-provincial authorities, local-municipal authorities and social securityinstitutions whose affiliation is compulsory for a sizeable segment of thepopulation. In respect of the latter, discrepancies are found betweencertain national classificatory rules and the international ones applied forNHA-2000. On the grounds of legal status and of discretionary decisionpowers vested in boards that act without government control, a number ofnational statisticians have opted to treat Social Security distinctly fromterritorial authorities.

Other extra-budgetary funds operate in the array of institutionsmapped in the WHO area. Their resources originating from a territorialgovernment, or on the basis of payroll or other taxes authorised by aterritorial government, are classified in NHA-2000 under GeneralGovernment.

Conceptually there is a fourth territorial level that can play a role inhealth financing: supranational authorities. For instance, the EuropeanUnion has contributed to investments in the Irish or in the Greek healthsystem. The supranational route appears to have played a minor role inthe other regions of the world. In NHA-2000 they have not been treatedas a distinct sub-sector. External resources supply huge amounts of fundsto a few low-income countries, such as Bhutan and Nepal (which transitmainly via general government budgets), or Lesotho (where NGOs –notably religious missions – play an active role). These transactions arerecorded under government financing, non-tax revenue or under non-governmental organisations income and outlays.

The economic transactions retained in NHA-2000 are thoseclassically found in the economic accounts of nations, differing in twomajor ways from the bookkeeping conventions initially adopted by someinfluential statisticians: the explicit incorporation of subsidies and transferpayments, the imputation of real flows without overt financialcounterpart. An illustration may take the place of a formal justification. Ina country determined to set-up NHA, the institutions mapped as addingup to the health share in the income and outlays of the nation summed upto around 2.8% of GDP; when the subsidised enrolment of poorer citizenswas included, when a subsidy making up the shortfall of hospital revenuebased on an official nomenclature of fee-for-service compared to actualcosts was added (virtually doubling the revenue formally billed), andwhen the deficit of the social protection schemes made up by a Statepayment entered the pictured, that nation's health bill rose by twopercentage points.

In line with an SNA 93 recommendation in respect of subsidies tonon-market producers (e.g. government-owned hospitals) lowering theprices charged or the costs reported, the OECD Manual rules that finalconsumption values should be recalculated by adding subsidies to therecorded costs. The implementation of this principle in NHA-2000 hasonly been haphazard. Few national authorities publish subsidies classifiedby function. As for imputations of real flows into a health system withoutgenuine financial counterpart, time constraints have prevented asystematic consideration of the value of tax concessions (e.g. reducedimport tariffs for pharmaceuticals compared with tariffs on othermanufactured products) or in-kind donations (e.g. religious missions). InNHA, subsidies should be entered as expenditure-equivalent values. Thisprinciple matters particularly when the subsidies are non-cashtransactions for a government agency such as tax exemptions. Anintractable case consists in estimating the subsidy equivalent of a loanguarantee that, usually, involves no cash payment, nonethelesssubstantially lowers the borrowing costs associated to, say, theconstruction of an hospital. The level of detail in the countries’ recordsthat have been accessed did not allow adjustments of this kind in NHA-2000. Subsequent re-evaluations should at times thread on such aterritory.

The economic transactions in NHA are rigorously classified. Thebulk of the OECD Manual deals with an interrelated system ofclassifications. Although each reporting system is based on classificationsof one kind or another, it has not been possible in the time allotted, toimplement in NHA-2000 a single classification, nor even to examine eachcountry’s detailed data. Even the OECD countries are only graduallyaligning their classifications. In Japan, for instance, eyeglasses andselected appliances until recently were not classified as “medical goods”because they are not part of the reimbursable benefits under the statutoryhealth insurance, etc. Classificatory exercises have taken place in severalcountries. In Hong Kong, Lebanon, Sri Lanka, the classificationsproposed by OECD have served as benchmark and have been assessed asproviding a fairly good basis, largely adaptable to the reporting systemsof these countries. Other middle-income countries have seemingly usedthe same classificatory principles, though many could implement themonly at a semi-aggregate level. While this is positive news for a NHAProducers’ Guide being drafted under WHO, World Bank and PHR’sauspices, the efforts required to reach harmonisation across a widespectrum of countries should not be underestimated. The current revisionof the International Standard Industrial Classification (ISIC), for instance,

is somewhat old for an activity in which medical manuals are out of dateevery five years or so. On the other hand, the OECD classifications aremore exacting than what many countries (including some OECDcountries) are able to record in a systematic way in mid-2000, requiringthus a simpler classification.

An operational challenge will be to reconcile the functionalclassifications with the prevailing institutional and legal structures. Theconventional National Accounting rules, applied in most NHAframeworks constructed to date, have been respected. For example,territorial government levels (central-federal authorities, State-regions-provinces-constitutional equivalent in other legal systems, localauthorities-municipal governments) and extra-budgetary arrangement(among which social protection schemes not consolidated under centralgovernment), which are often legally empowered to raise compulsorypremium akin to, but different from, universal taxation have beenexplicitly categorised as public.

Public corporations which derive a substantial part of theirresources from the sale of commodities or services, such as mining,utilities, transport, and communications, are a source of considerableconfusion in the build-up of NHA. Publicly owned facilities arefrequently classified as government outlays in budget statements. UnderSNA 93 rules, they are allocated to the income and outlays account of theenterprises sector, aggregated with similar utlays of private businessenterprises. For a number of oil producing countries, the private-publicmix of expenditure on health exhibited in national sources (and in WorldBank reports) differs from the NHA-2000 subtotals mainly onclassification grounds of mandated business health programmes and/oroccupational health care, and not because of genuine differences in thesize of the estimates.

An underlying NHA-2000 principle is one of a distinct preferencefor an economic rationale as opposed to a legal convenience. Unsettledamong professional health accountants is the issue of imputedtransactions. The direct costs to a health system of nursing servicessupplied by members of a religious order are minimal but the servicesrendered important. Should these services not be assessed at replacementcost with an imputed transfer payment? When the under-priced servicevanishes the substitute arrangements are usually much dearer. Theconventional view is to leave most imputations to analysis, thedescription of observable parameters to bookkeeping-accounting.National Accounts contain, however, dozens of imputed values. NHA-

2000 adopted the stance that the tool is an appropriate locus to estimateopportunity costs. Cases for potential imputations abound, such asimplicit-subsidies to pharmaceutical imports at below “normal” customstariffs.

How should foreign assistance be valued? At local wage rate plus ascarcity premium incorporating part of the higher compensation offoreign experts with only token overhead costs? Charging the full wagesupplements the foreign salary scale, plus travel costs, housing and localtransportation amenities, the financing agency’s administrative costs,etc)? The limited accessibility to details has not facilitated ahomogeneous treatment in NHA-2000, which has leaned towards ameasure of the recurrent economic value to the health system of theservice with a separate entry for the transitory “import premium”.

A considerable practical hurdle – that may have led to under- orover estimation – has been the determination of the level of expendituredata. A number of regional or local authorities exert a discretionaryspending power but the underlying financing originated in intra-governmental transfers, not in an autonomous taxation capacity. In theNHA-2000, the principal agent has been deemed to be the centralgovernment whenever local authorities enjoyed no autonomous taxationcapacity in the health field. By exception to that rule, the national healthbudget originating in external financial sources has been assumed to beequivalent to a tax resource for the largest part (a share transits in somecountries via non government organisations and non-profit institutionsserving mainly households). When these data can be isolated, financingflows originating from multilateral international agencies and bilateralprogrammes are monitored in a complementary table of NHA-2000. Thequantity of information collected and the quality of the disaggregationattained (grants, loans, direct costs) was not sufficient to report (theexternal flows) in Annex Table 8 of the World Health Report 2000. Theshare of grants that can be allocated to NGO has been included in privateexpenditure and has likewise not been reported.

For convenience, the International Monetary Fund's GovernmentFinance Statistics (GFS), which supplies central government expenditureby function for 73 WHO countries, has been used as a main source ofinformation (see Chart 4). Though the IMF guidelines are unambiguous, amajority of countries report only part of their central government outlaysfor health, usually those related to Ministries of Health. A few countriesadd the outlays of Social Welfare Departments. Metadata on the actualcontents of the series are attached to the country segments. Only in the

case of Bulgaria and Yemen is the indication regarding the healthfunction crystal clear: for Bulgaria, according to GFS the outlays of allministries’ for the advancement of health are reported. For Yemen, thepost-reunification period (1990 onwards refers to one ministry only). Forsome countries the data refer to consolidated central governmentexpenditures including social security, regional and local agencies (e.g.Bolivia). Other countries only report general government expendituresand social insurance funds (e.g. Luxembourg). Others report in additionextra-budgetary expenditures (e.g Austria, Bahrain, Latvia, Macedoniaand Poland). Some countries changed the content of reporting categoriesover time (e.g. Italy has not included autonomous agencies since 1993).Occasionally, others exclude international grants in reporting extra-budgetary funds (e.g. Estonia). Others only report non-consolidatedcentral government expenditure (Paraguay and Singapore). Theseexamples are illustrative of the wide spectrum of institutional andregulatory set-up.

IMF guidelines require the consolidation of Social Security withcentral government. While this is frequently abided by, a number offinance ministries or central banks skip a full consolidation,. For examplethey report only social protection schemes whose main function is thedelivery or the funding of medical care at the exclusion of other schemes(such as those of old age insurance, civil service insurance, railroadworkers insurance, workmen compensation act systems, which may havea sizeable though not dominant medical care function). Underreporting ofthis kind may have occurred in China, Iran, and other countries of Asia.As more information is obtained, a more sophisticated institutionalmapping is expected for subsequent NHA syntheses. WHO Healthprofiles are available for a third of WHO member countries. A countrywishing to set-up an NHA should consider mapping its health systemprofile as a priority.

An effort has been made to collect health expenditure data inDefence (Armed Forces Health Services), Mining-Oil-Utilities (Mexico,Saudi Arabia or Zambia run schemes for their employees and relatives),Transport (notably railroad worker schemes, and seamen’s insurance),Education (notably teaching hospitals) and Civil Service insuranceschemes. The modest amount of data collated suggests that a fair numberof central government outlays cover a wide “health” territory but theprogrammes included in the provisional NHA are only mildlycomprehensive. Further enquiries have been launched that may modify insubsequent rounds of NHA some of the arbitrages made.

Private Expenditure on Health

The intent of the collection process to be comprehensive. In theNHA-2000, the private sector data (PvtHE) comprise four groups ofstakeholders: enterprises purchasing medical care as part of theremuneration package offered to their employees or because of a legalmandate to do so, non-profit institutions serving mainly households(NPISH), non government organisations (NGO), and the householdsthemselves. The diversity of the legal, institutional and behaviouralarrangements applicable to these four groups in each country and acrossthe spectrum of countries is large. Illustrations include legal orcontractual obligation by size of enterprise, nature of productive activityor regulatory criteria. NPISH and NGO may be religious institutions andcharities, advocacy groups concerned with specific diseases or causes offunctional disability, and self-help associations. Direct purchase ofinsurance by better-off segments of society and the use of payment-in-kind or under-the-table payments, direct purchases of medicines etc., arenot easily traceable unless good household surveys are available.

The most sizeable component of private expenditure in middle- andlow-income countries is direct out-of-pocket spending (OOPS). It is oftenobtained as a residual of private consumption on medical goods andservices net of private insurance. The United Nations National AccountsStatistics 1995 provides for 45 countries an estimate of privateconsumption on medical care for the period up to 1995. The healthexpenditure to total expenditure ratio of the household survey has beenused to provide the appropriate multiplier to apply to total privateconsumption for 31 countries. The estimates have been projected forwardto 1997 assuming a stable consumption pattern between 1995 and 1997.Total private expenditure provides a control variable in four cases out offive. To prevent double counting, government (social security or other)transfers to households for medical care benefits (THH) and premiumspaid for private insurance or for prepaid health protection programmeshave to be deducted from private consumption on health (PCH). Theoutlays of non-profit institutions or NGO when these benefits are notseparated from the household should also be deducted.

In a number of institutional settings households pay for medicalgoods and services for which they are subsequently reimbursed. Thesetransfers, can be obtained up to 1995 from the UN National Accounts andfrom consistent national sources. The 1997 level was projected assuming

a stable pattern since the mid-1990s. The mandated provision of medicalbenefits by employers needs to be added to occupational health services(treated under SNA rules as intermediate, not as final consumption). Inthe NHA-2000 financing matrix, external resources are included as publicor as private spending; a supplementary set of detailed financing flowsrecords external resources as a specific rest-of-the-world transfer.

The NHA-2000 template

A selection of variables for which the NHA-2000 country segmentsattempts to collate time series is presented in Tables 2 & 3. It illustratesthe complexity of operating with several data sources whose concepts anddefinitions are not necessarily homogeneous. Rows 64 and 68 aresupplied by the IMF, rows 74 to 81 and 87 by the OECD and by the UNNational Accounts, and rows 86, 88, 89, 90 by OECD Health data.

Differences between consolidated general government outlays andtotal government outlays are small except in 1997, an estimate subject toa revision to be released later this year. Row 73 has been made equal torow 86, the gap being outlays by communes, which in the countryconcerned is funded by a combination of block grant intra-governmenttransfer between central and local governments, and local taxation. Row73 has been made equal to row 86. In most of the 191 countries, row 81 isequal to row 73. The reclassification of statistical data from SNA 68 toSNA 93 introduces minor changes by lowering the levels shown (about 1percent for those countries not yet reporting according to SNA93 rules).

Table 2. Measured expenditure on health in the country segments(millions of NCU)

1993 1994 1995 1996 199764 Consolidated Central Government Expend. 6211 5935 6242 7017 742665 State, regional, provincial expenditure66 Local government expenditure67 Territorial Government Expenditure68 Social insurance expenditure 5680 5489 5709 6489 691369 Extra-budget/autonomous funds73 Consolidated General Government Outlays 31262 30605 32136 34038 3519574 Government consumption 24511 24177 25543 26865 2716375 Compensation of employees 19619 19549 20550 21594 23900

77 Subsidies to medical producers78 Transfers to households 5457 5029 5479 5903 652979 Investment 1180 1069 1170 1228 147180 Capital transfers

81 Total Government Outlays 31262 30605 32136 34038 3519586 Public Expenditure on Health (=73) 31262 30605 32136 34038 3519587 Private consumption of medical care 13998 14376 15420 16598 1740088 Private insurance & other prepaid schemes 1045 1013 1039 1065 114489 Out-of-pocket expenditure on health 8170 8269 8717 9039 921190 Non-profit institution consumption (NGO) 1211 1232 1328 1357 142091 Mandated entreprise health services93 Other privately funded health care97 Private investment98 Private Expenditure on Health 10426 10514 11084 11461 1177599 Total Expenditure on Health (=86+98) 41688 41119 43220 45499 46970Notes:1) The upper tier of rows corresponds to an institutional classification in a publicfinance approach.The second tier of rows corresponds to the economic classification in a NationalAccounts approach.The lower tier corresponds to an ad hoc economic classification of the spendingcategories most frequently encountered in the world during the NHA-2000 build-up.2) The level of row 73 exceeds the sum of rows 67 to 69 because the referencesources used do not publish the outlays by the communes, the largest public spendingagent. Small discrepancies subsist between rows 73 and 81.Sources:WHO, NHA-2000 data files.

Table 3. Measured financing in the country segments(in millions of NCU)

1993 1994 1995 1996 1997101 General Taxation, General Government 25582 25116 26427 27549 28282102 General Taxation, Central Government 6211 5935 6242 7017103 General Taxation, States/Regions/Province104 General Taxation, Local105 Extra-budgetary funds106 Social security 5680 5489 5709 6489 6913107 Employer contributions 612 626 607108 Employee contributions109 Government transfers to Social Security110 Trust funds111 Intra-government transfers from Cent.Govt.112 Intra-government transfers from State Govt.113 Intra-government transfers from Local Govt.114 General .govt. transfers to NGO/NPISH115 General Govt. transfers to households 5457 5029 5461116 Of which Social Security transfers to Households117 External resources118 International agencies119 Bilateral assistance to Government120 Bilateral flows to NGO121 Bilateral, direct operations122 Private to General Government123 Private to NGO124 Private, direct interventions

125 Enterprises126 Mandated delivery127 Direct delivery128 Public corporations129 NGO's & non-profit institutions 1211 1232 1328 1357130 Private insurance & other prepaid schemes 861 832 853 866 940131 For-profit132 Non-profit133 Net out-of-pocket expenditure 2223 3486 3645 3932 4140135 Private funds n.e.c. 619 639 647 701 766141 Tax Expenditure for Health CareNotes: An ad-hoc classification derived from a tally of frequently encountered financingagents in the WHO area.Source: WHO, NHA-2000 data files.

An allowance has been made in several country segments forprivate investment in health facilities (PIH) about which virtually nodirect information is gathered. Private investment is known to havegrown considerably during the 1990’s in many Latin American and insome Asian countries. By and large, many statisticians do not reportprivate investment in health facilities because of inherent recordingproblems and to avoid a risk of double counting (an allowance for capitalusage and depreciation is meant to be included in the fees perceived byprivate producers for imaging, laboratory tests, hospitalisations, …).Double counting is less of an issue when current and capital expendituremay be separated and depreciation is deducted from gross receipts. Thesignificant amount of investment in health facilities observed in middle-and low-income countries equipped with NHA confirms the importanceof adequate monitoring of assets and asset build-up. The notional valueattached to it for 1997 varies between 2% and 10% of direct householdspayments.

When private consumption of medical goods and services (PCH) isnot accessible, OOPS has typically been calculated on the basis ofhousehold budget surveys or level of living surveys. Out of pocketspending comprises discretionary purchases of medical and paramedicalgoods and services by patients and their families, as well as co-paymentsin public schemes providing benefits-in-kind with some form of cost-sharing or user charge. The 'medical' care ratio obtained (including, whererelevant, “traditional” healing services) has been applied to the NationalAccounts private consumption aggregate (PC). As household surveys areonly conducted intermittently, time series for OOPS have been derivedthrough statistical techniques and, when no household survey areavailable, estimates have been necessary. Though inspired by the same

general approach across the spectrum of countries, household surveysdiffer in the questions asked; they nevertheless provide acceptableapproximations or cross-checks of each PCH.

The private-public mix exhibited in the second and third columnsof annex table 8 in the World Health Report 2000 is also affected byshifting statistical conventions, such as those resulting from the gradualadaptation of SNA93 replacing SNA68 rules. In the original NationalAccounts’ functional breakdown, expenditure was classified according toits object (such as medical care) irrespective of the underlying financialarrangements, at least within the main two sectors of the economy:government and private. SNA-93 abolished the principle with respect togoods and services co-financed by social security or another publicsource and by households and private insurance (A System of NationalAccounts, pp 194-6). While the NHA-2000 applies a similar divide ex-post, the heterogeneity of the data sources led to an effective allocation ofthe social subsidy to the public share whenever the underlyinginformation was based on the new National Accounts, a more haphazardone when the underlying information was based on the former NationalAccounts (still the majority of countries in the first half of 2000).

A sizeable number of financing flows had to be estimated fromcrude expenditure data. Conceptually, this procedure entails a risk ofdouble counting, as well as, paradoxically, a risk of not beingcomprehensive. Examples cited above relate to central governmentoutlays by function. It is often the case that only the disbursements ofMinistries of Health are included at the exclusion of intervention by otherministries whose primary intent is also the enhancement of the healthstatus of the population. Conversely, in many countries, the recordsaggregate the co-payments received (a flow originating directly from thehouseholds) with the share of general government revenue attributed tothe Ministry of Health, usually transferred from the Ministry of Finance.A risk of double counting exists when the household surveys on whichthe out-of-pocket outlays rest also include the value of co-payments. Inthe initial development stages of an accounting system, involuntarydouble counts are unavoidable. Most of household surveys do not registerthe institution receiving the co-payments and often they do not includereimbursements. In one country, the standards used by two state agenciesproviding macro-economic data lead to a difference up to a factor of 6when measuring private health consumption, that is 3% of GDP; forNHA-2000 purposes, the arbitrage was made on a plausibility criterion.

Non-financial variables

In a full-fledged information system (see Chart 1 above), thefinancial monitoring has to be complemented with several types ofquantitative monitoring instruments. They include:

• a needs assessment (mortality, morbidity and dysfunction ofpopulation segments);

• resource and production information (amount of services and type offunctions covered, health services utilisation);

• a social and economic context (prices, production, income andamenity distribution);

• a geographic and demographic distribution;• a technology assessment (geared to better appreciate the

appropriateness and cost-effectiveness of medical procedures andmedical equipment);

• quality assurance programmes (focused on value for money at bedsideor regarding specific classes of interventions in the delivery andfinancing of health care).

The underlying data for the WHR 2000

For several countries, the public expenditure measures underlyingthe World Health Report-2000 - Annex table 8 may include an over-countor undercount. For example no systematic evidence was available onwhether state/provincial/regional and local authorities spend money theyraise through taxes or whether they access their resources throughtransfers from the central-federal authorities. Metadata accompanying thecountry segments indicate the assumptions made. Many statisticalyearbooks, ministry of health and other official reports accessed fail toprovide information on the contents of the series they publish.

For total private consumption, aggregate national accounts shouldbe preferred because of their comprehensiveness. At functional level,only some 45 countries report medical care goods and services (PCH),complemented by national information. Household budget surveyssupplied the basis for 31 countries (see Chart 5). Living Standards andhousehold budget surveys are frequently less comprehensive. For

example some of them exclude, imputed rent, which is a sizeablecomponent of private consumption. In many middle income countries upto three quarters (even more) of dwellings are owner-occupied,generating an undercount when using household and level of livingsurveys as the base source. Chart 4 summarises the main sources tappedto construct the NHA-2000.

Chart 5. Sources of information for the NHA-2000

(# of countries, State of the play end-March 2000)

Source: WHO, NHA data files.

The NHA-2000 template provides a series of summary ratios. Thedenominators of these ratios are macro-economic aggregates andpopulation. Both are at the root of much of the discrepancies found in theinternational comparisons from different sources. The entries underlyingthe ratios in annex table 8 of the World Health Report 2000 are found intable A-1 at the end of this discussion paper. The United Nations, theWorld Bank and the International Monetary Fund still release differentestimates of Gross Domestic Product (GDP). The IMF GDP, readily

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available for all years, has been retained in the NHA2000 as thedenominator for the summary ratios. When International FinancialStatistics does not release national accounting aggregates (for countriesnot member of IMF or countries that, for reason of war, civil strife,breakdown of governance discontinued the supply of information toIMF), other sources have been tapped. As part of the WHO countriesbegin to report on the basis of SNA93 and other countries do not, atransitory element of non-comparability has emerged.

Public Expenditure on Health (PHE) is shown as a share of totalGeneral Government Expenditure (GGE). International FinancialStatistics releases estimates of central government disbursements (CGD).The CGD series often equal the GGE series as intra-governmentaltransfer payments or block grants cover or nearly so the outlays of theregional/state/provincial and local/municipal authorities. The UNNational Accounts supplies an estimate of total current disbursements andnet savings for 73 countries through 1995. These have been extrapolatedthrough 1997 (for the OECD countries, the estimates are accessible inOECD Health Data 99, reproducing series from OECD NationalAccounts. When institutional data suggest that GGE is greater than CGDand no direct information is readily available, ad hoc statistical techniquesare used to inflate the accessible CGD estimates to a plausible GGE level.

The population estimates are those produced by the UnitedNations. The data in the annex table are reported in millions of nationalcurrency units, except the series on spot exchange rates expressed innational currency units, and population data, reported in thousandpersons.

An attempt has been made to use as much as possible the samemethodology and homogeneous sources for all WHO countries. Only theprimary or principal sources of data are listed in the meta-data files. Asthey fill over a hundred pages equivalent, only a gross summary of themain sources is supplied in chart 5.

IV. A tentative State-of-the-world message, 1997

A rigorous analysis of private and public expenditure on healthrequires orders of magnitude. The contents of the exercise initiated byWHO differs from previous studies first on comprehensiveness grounds:a measure is achieved for all 191 Member countries. Second, there hasbeen a wider canvassing of the sources of funds (including the latent

ambition to survey the share of external resources). Third, there is aunique temporal dimension (trends in the main aggregates are traced for aperiod of one to three decades).

The first results of the exercise exhibit a level of expenditure thatis, on average, higher than the levels or ratios previously quantified. Thecorrelation between wealth and health frequently documented for high-income countries is strong also for medium and low-income countries.The sizeable dispersion within the WHO regions invites an explanationabout the nature of these gaps. An expansion of NHA in the direction ofnew distribution matrices on the expenditure side as well as on theincome side appears to be a necessary extension of the conventionalapproaches to NHA. A distributional analysis has been developed in thecontext of the World Health Report-2000 which could not be integratedin the NHA-2000 but the interface between the two is strong (see Xu K etal, Analysis of the Fairness of Financial Contribution in 21 countries.Geneva, World Health Organization 2000, GPE Discussion Paper No.25).

The ratios in chart 6 exhibit regional averages for standardindicators. The lowest total expenditure on health; calculated as shares inGDP (THE/GDP), the lowest per capita expenditure are found in Africa,next in South Asia, the highest in Western Europe and in the Americas.Differences in per capita amounts are fivefold between regions, reflectingdifferences not only in income and wealth levels but also in socio-political organisation. These are more directly observable in theTHE/GDP and PHE/GDP ratios. Europe and the Pacific region exhibithigher shares of public financing.

Chart 6. Measured levels of total expenditure on health, 1997

Total expenditure on health per capita, % of GDP

0 5 10

AFR

AMR

EMR

EUR

SEAR

WPR

WORLD

Total expenditure on health per capita, US dollars at X-rate

0 500 1000

A FR

A MR

EMR

EUR

SEA R

WPR

WORLD

Notes:1) The regional expenditure ratios are unweighted.2) The per capita figures are weighted averages expressed in US $ at exchange rate.Source: WHO, NHA-2000 data files.

South East Asia

The region comprises countries with a headstart in the constructionof NHA and countries where that prospect has seemingly not yet beenevoked. Access to institutional and to public finance variables has beenhaphazard at times. Nepal with an estimated US$ 8 per capita at exchangerate and Thailand with an estimated $ 13 per head contribute to a regionalaverage of $48 per capita. The average public and private expenditureshares (external resources included) are 41 and 59% respectively. Therole of private insurance and mandated employer schemes appear to bemodest in the region, suggesting that out-of-pocket spending plays arelatively important role. The level of total expenditure on health inIndonesia is lower than expected because no household survey providinga plausible level of out of pocket health expenditure has been unearthed(Table 5).

Table 5. Expenditure on health in the SEAR area, 1997.

THEas %

ofGDP

OOPSAs % of

THE

THEas % of

GDP

OOPSAs % of

THE

THEas % of

GDP

OOPSas %ofTHE

Bangladesh 4.9 54.0Bhutan 7.0 53.8 Indonesia 1.7 47.4 Nepal 3.7 74.0DR Korea 3.0 16.4 Maldives 8.2 36.1 Sri Lanka 3.0 51.8India 5.2 84.6 Myanmar 2.6 87.4 Thailand 5.7 65.4Source: WHO NHA-2000 data files.

The East Mediterranean

For the East Mediterranean, the levels shown below reflect thedocumentation readily accessible at the time of the World Health Report2000 was drafted. It may underreport somewhat on average expenditurelevels according to new estimates obtained by intergovernmental agencies

operating in the EMR area. Sizeable expenditure programmes are notablyoperated by the armed forces, or companies, public and non profitinstitutions catering to refugees and displaced populations, whose recordsare not readily accessible. Also, in some countries, the expenditureprogrammes reported related to the resident population, the demographicdata including on the contrary the non resident population. Pending acomparison of notes with those of an on-going NHA estimation exercisein eight countries, the estimates collected suggest that the averageresident of that area spent US$ 269 at average exchange rate for the year,ranging from around $ 2 in Afghanistan to an estimated $ 1,042 in Qatar.The cross-country variations are very sizeable as noted in Table 6.

Table 6. Expenditure on health in the EMR area, 1997.

THEas % of

GDP

OOPSas % of

THE

THEAs % of

GDP

OOPSas % of

THEAfghanistan 3.2 59.4 Morocco 5.3 59.3Bahrain 4.4 37.7 Oman 3.9 35.9Cyprus 5.9 63.1 Pakistan 4.0 77.1Djibouti 2.8 27.1 Qatar 6.5 42.5Egypt 3.7 73.1 Saudi Arabia 3.5 6.3Iran 4.4 57.2 Somalia 1.5 28.6Iraq 4.2 41.1 Sudan 3.5 79.1Jordan 5.2 32.8 Syria 2.5 66.4Kuwait 3.3 12.6 Tunisia 5.4 53.0Lebanon 10.1 53.8 U A Emirates 4.2 3.8Libyan Arab J. 3.4 45.8 Yemen 3.4 62.1Source: WHO NHA-2000 data files.

The Pacific

For the Pacific, the estimation process in a region that comprisesthe world’s most populated nation and a number of island-nations that donot report much about themselves, has constituted a true challenge. LowChinese expenditure reported translates in part the inaccessibility to animportant source of financing at the time the World Health Report 2000went to print, the total and the public share of total expenditure are thusexpected to be revised upwards in future releases of NHA-2000.

Total outlays per capita average US$ 415 in 1997, varying between$ 13 in Laos and $ 2,373 in Japan. On average, two thirds of these outlaysare classified as public (table 7) and one third as private.

Table 7. Expenditure on health in the WPR area, 1997.

THEas % of

GDP

PHEas %

of THE

THEas % of

GDP

PHEas %

of THE

THEAs % of

GDP

PHEas %

of THEAustralia 7.8 72.0 Malaysia 2.4 57.6 Philippines 3.4 48.5Brunei Darus 5.4 40.6 Marshall I. 9.0 74.3 Rep of Korea 6.7 37.8Cambodia 7.2 9.4 Micronesia 7.4 92.3 Samoa 3.8 88.9China 2.7 24.9 Mongolia 4.3 82.0 Singapore 3.1 35.8Cook Islands 7.4 76.7 Nauru 5.0 99.0 Solomon Isl. 3.2 99.3Fiji 4.2 69.2 N Zealand 8.2 71.7 Tonga 7.8 46.0Japan 7.1 80.2 Niue 5.7 87.6 Tuvalu 5.9 91.5Kiribati 9.9 99.3 Palau 6.0 90.0 Vanuatu 3.3 64.3Laos P.D.R. 3.6 62.7 Papua N G 3.1 77.6 Vietnam 4.8 20.0Source: WHO NHA-2000 data files.

Sub-Saharan Africa

Annual public expenditure by function could not be obtained for allcountries of Sub-Saharan Africa. Readily accessible information suggeststhat only a handful of countries operate social security schemes. In somecountries the Ministry of Health has only a planning and evaluationfunction, a Health Board is charged with the bulk of the implementationfunction. It has been difficult to obtain information on mandatedcorporate and private insurance schemes, such as those operating inZimbabwe. External resources (grants and loans to governments, but alsoto NGO) play a sizeable role in a majority of the region countries butinformation on them is scarce at best. Even the intergovernmental andinternational aid agencies do not report this information in a consistentmanner. A careful meshing of information collated by teams reporting onpreliminary NHA should yield a genuine improvement of the estimatesprepared.

Expenditure on health is correlated to real incomes. Imperfection ofthe data notwithstanding, the greater poverty of Africa is reflected in aspending estimate of US$ 45 per person with important inter-countryvariations: an estimated $ 4 per capita in Ethiopia and an estimated $ 424per capita in the Seychelles. The PHE share reported in table 8 is likely tooverestimate in most countries the real state (except in the DemocraticRepublic of Congo, an implausible figure even for a country beset bypublic strife) because of the dearth of household expenditure surveys.

Table 8. Expenditure on health in the AFR area, 1997.

THEas % of

GDP

PHEas % of

THE

THEAs % of

GDP

PHEas % of

THEAlgeria 3.1 50.8 Lesotho 5.6 72.6Angola 3.6 59.6 Liberia 3.0 66.7Benin 3.0 47.2 Madagascar 2.1 53.8Botswana 4.2 61.0 Malawi 5.8 59.2Burkina Faso 4.2 30.9 Mali 4.2 45.8Burundi 4.0 35.6 Mauritania 5.6 30.3Cameroon 5.0 20.1 Mauritius 3.5 52.9Cape Verde 2.8 63.8 Mozambique 5.8 71.3Central African Rep 2.9 68.9 Namibia 7.5 51.7Chad 4.3 79.3 Niger 3.5 46.6Comoros 4.5 68.2 Nigeria 3.1 28.2Congo 5.0 36.6 Rwanda 4.3 50.1Côte d'Ivoire 3.2 38.4 Sao Tome & Principe 4.0 75.0Dem Rep of Congo 3.7 0.9 Senegal 4.5 55.7Equatorial Guinea 3.5 57.2 Seychelles 5.9 76.2Eritrea 3.4 55.7 Sierra Leone 4.9 9.7Ethiopia 3.8 36.2 South Africa 7.1 46.5Gabon 3.0 66.5 Swaziland 3.4 72.3Gambia 4.5 45.9 Togo 2.8 42.8Ghana 3.1 47.0 Uganda 4.1 35.1Guinea 3.5 57.2 United R. Tanzania 4.8 60.7Guinea-Bissau 5.7 75.6 Zambia 5.9 38.2Kenya 4.6 64.1 Zimbabwe 6.2 43.4Source: WHO, NHA-2000 data files.

A Latin American Perspective: Social Financing

The ratios presented seldom originate from a single source, notablythe distinction between social security and other public funds.Considerable enhancements of the ratios should also be brought by amore recurrent reporting of mandated employer schemes and privateinsurance schemes. AMRO and the World Bank have released ratios ofTotal and of Public Expenditure on Health to GDP, in the absence oflevels expressed in millions of national currency units, these could not becompared with the levels and trends obtained through the NHA-2000process. A reconciliation of differences between the two sets of ratioscould not be worked out before the World Health Report 2000 went toprint. The Americas are reckoned to have spent US$ 407 per capita withnaturally large disparities between the USA: an estimated $ 4,187 perperson, and Haiti: an estimated $ 18 per person. The rapid increase of theprivate provision of health services accentuates a downward pressure to

spend publicly. On average, the Social Security share in the measuredpublic funding of health care reaches almost the half mark (Table 9).Where tax funded health expenditure is given as 100, the indication is thatthere is no nation-wide social insurance but not that all resources are tax-based; external resources contribute in several countries to the funding ofthe health system, non-tax revenue (profits of state-owned firms) also.

Table 9. Expenditure on health in the AMR area, 1997.

THEas % of

GDP

TXFHEas % of

PHE

SSHEas % of

PHE

THEas % of

GDP

TXFHEas % of

PHE

SSHEas % of

PHEAntigua & B 6.4 100 … Guyana 5.1 100 …Argentina 8.2 39.6 60.4 Haiti 4.6 100 …Bahamas 5.9 100 … Honduras 7.5 74.6 25.5Barbados 7.3 100 … Jamaica 6.0 100 …Belize 4.7 100 … Mexico 5.6 26.4 73.6Bolivia 5.8 42.7 57.3 Nicaragua 8.0 80.1 20.0Brazil 6.5 100 … Panama 7.5 44.5 55.5Canada 8.6 98.9 1.1 Paraguay 5.6 49.8 50.2Chile 6.1 24.0 76.0 Peru 5.6 44.2 55.8Colombia 9.3 62.5 37.5 S Kitts & Nevis 6.0 100 …Costa Rica 8.7 16.2 83.8 Saint Lucia 4.0 100 …Cuba 6.3 100 … StVincent & G. 5.9 100 …Dominica 6.0 100 … Suriname 7.6 100 …Dominican R 4.9 73.0 27.0 Trinidad & Tob 4.3 100 …Ecuador 4.6 59.4 40.6 United States 13.7 57.9 42.1El Salvador 7.0 48.5 51.5 Uruguay 10.0 89.0 11.0Grenada 6.3 100 … Venezuela 3.9 66.6 33.4Guatemala 2.4 53.7 46.3Source: WHO, NHA-2000 data files.

Europe & Central Asia after the Shemashko era

Long time series have proved to be elusive in countries that madethe transition from centrally planned system to a market economy andlittle quantitative evidence could be used in the comparative frameworkretained. The structural reforms under way have not generated yet in thearea a comprehensive and consistent information system, even incountries with a longer tradition in reporting. Gaps in reporting ofselected schemes have been a cause of under-reporting. The averageoutlay per capita, including the richer OECD-Europe and the AsianRepublics of the former Soviet Union, stands at US$ 920 per capita. InTajikistan, it is estimated to have been $ 11 and in Switzerland $ 3,564.The temporary demise of public responsibility in a few countries over-represents the permanent role of households in the health financing sharesshown in Table 10.

Table 10. Expenditure on health in the EUR area, 1997.

THEas % of

GDP

PHEas % of

THE

THEas % of

GDP

PHEas % of

THEAlbania 3.5 77.7 Lithuania 6.4 75.7Andorra 7.5 86.7 Luxembourg 6.6 91.4Armenia 7.9 41.5 Malta 6.3 58.9Austria 9.0 67.3 Monaco 8.0 62.5Azerbaijan 2.9 79.3 Netherlands 8.8 70.7Belarus 5.9 82.6 Norway 6.5 82.0Belgium 8.0 83.2 Poland 6.2 71.6Bosnia &Herzegovina 7.6 92.6 Portugal 8.2 57.5Bulgaria 4.8 81.9 Rep of Macedonia 6.1 84.8Croatia 8.1 79.7 Rep of Moldova 8.3 75.1Czech Republic 7.6 92.3 Romania 3.8 60.3Denmark 8.0 84.3 Russian Federation 5.4 76.8Estonia 6.4 78.9 San Marino 7.5 73.5Finland 7.6 73.7 Slovakia 8.6 81.8France 9.8 76.9 Slovenia 9.4 80.8Georgia 4.4 8.6 Spain 8.0 70.6Germany 10.5 77.5 Sweden 9.2 78.0Greece 8.0 65.8 Switzerland 10.1 69.3Hungary 5.3 84.9 Tajikistan 7.6 87.8Iceland 7.9 83.8 Turkey 3.9 74.0Ireland 6.2 77.3 Turkmenistan 4.3 86.0Israel 8.2 75.0 Ukraine 5.6 75.5Italy 9.3 57.1 United Kingdom 5.8 96.9Kazakhstan 3.9 63.6 Uzbekistan 4.2 80.9Kyrgyzstan 4.0 69.6 Yugoslavia 4.5 64.8Latvia 6.1 61.0 OECD – Europe 7.8 76.0Note: OECD-Europe is an arithmetic average of 22 countries.Source: WHO, NHA-2000 data files.

Wealth and health

The strong correlation between disposable income and expenditureon health, frequently demonstrated in the high-income countries, appearsto be a structural feature in the world as a whole. The association betweenhealth expenditure and wealth in the 191 WHO countries is strong,virtually linear when plotting total expenditure on health goods andservices (Chart 7 logarithmic scale, R2= 0.978). Values are shown innational currency units (NCU) both for GDP per capita and total healthexpenditure per capita. Because NCU are not “comparable” with standardof living equivalent indices are, Chart 7 expresses only a relationship

between the two variables for each country, not the relative position thateach country would have in a measured based on universal currency.Chart 7 does not have a normative or comparative value. Each dotcorresponds to measured per capita income and per capita health careconsumption, in that country’s own currency. Typically, a weak currencyis represented by large figures; some rich countries have, however, a largefigure for both per capita income and health expenditure.

The THE/GDP ratios range between 1.5% to 13.5% in the world.The relationship between the two variables is a straight slope. Theaverage per capita GDP mask, however, wide variations in the incomedistribution of countries. Given large disparities between and insideWHO regions, the implications of that correlation have to be consideredin greater depth.

Chart 7. Per capita expenditure on health and income flows, 1997.(in National Currency Units)

Source: WHO, NHA data files.

Public commitment towards health goods and services, expressedin Chart 8 for the same 191 countries, appears to be nearly as stronglytied to income per capita as total expenditure is (logarithmic scaleR2=0.984). As for chart 7, this relationship does not qualify the positionof each plot. Because the logarithmic scale tends to compact thedispersions around the plot, small variations in the association hide ratherwider real dispersions. Inequalities in risk pooling are not limited tocross-national inequalities in wealth. The role and extent of thiscommitment has been changing in many countries in the recent past and

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1 10 100 1,000 10,000 100,000 1,000,000 10,000,000 100,000,000 1,000,000,000

GDP per capita, NCU

THE

per c

apita

, NC

U

is not as easy to capture as a string of numbers suggests. Specifically,measured public expenditure on health hovers around half of measuredtotal expenditure on health. By region, the variation extends from 41% inSouth East Asia to 74% in Europe and Central Asia. The world globalaverage, in its end-March 2000 calculation status, is 59.2% of total healthexpenditure. Based on the countries for which data have been collated,social security accounts for nearly a quarter of THE, and around half ofPHE. Because only part of the processes is transparent, the levels andratios provide a questionable picture for a few countries.

Chart 8. Public commitment towards health, 1997.(in National Currency Units)

Source: WHO, NHA data files.

Private spending ratios are not immune from myopia. Theregistration of private payments is one explanation. When compulsorysocial insurance are channelling resources towards private practice, theflows should remain nonetheless classified as publicly financed. In the

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

100,000,000

1 10 100 1,000 10,000 100,000 1,000,000 10,000,000 100,000,000 1,000,000,000

GDP per capita, NCU

PHE

per c

apita

, NC

U

NHA-2000, the direct payments by the users of the system, labelled out-of-pocket (OOPS) for convenience, have been estimated deducting fromthe total private spending insurance and mandated enterprise expenditure,as well as NGO external resources. When considering OOPS per capita,the association with per capita GDP is also present (logarithmic scale,R2= 0.92). The remarks made on the previous charts apply here too. Thischart includes two values with a very low estimate for OOPS. Themeasured level of private spending encompasses more restrictions as notall countries develop household surveys nor private providers expenditurefor health (Chart 9).

Chart 9. Household ability to pay for health: a close link to nationalincome, 1997

(in National Currency Units)

Source: WHO, NHA data file.

Not all countries supply routinely enough information to allow acomprehensive measure of direct household payment, often estimatedthrough a series of deductions from a private expenditure aggregate. Incountries with sizeable expenditure and NHA breakdowns, such as theUnited States, OOPS are a relatively low share of THE because thedeductions could be made. Elsewhere, this was only crudely attainable.

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

1 10 100 1,000 10,000 100,000 1,000,000 10,000,000 100,000,000 1,000,000,000

GDP per capita, NCU

OO

PS p

er c

apita

, NC

U

The emerging picture is thus not fully transparent. A high privateexpenditure share may not be a predictor of a sizeable out-of-pocket sharebecause of an extensive network of private insurers and managed careschemes. Conversely a country with a medium-sized private sector mayturn out in a map or in a table to exhibit an oversized out-of-pocketexpenditure due to non-accountability of private insurance, mandatedemployer schemes, and NGOs.

A map illustrates some strengths and weaknesses of the NHA-2000exercise. The orders of magnitudes it exhibits relate to more variables andto more countries than any previous attempt at measurement that precedeit. While important revisions are a certainty, a consolidation of the ordersof magnitude for a large number of countries is also likely.

OOPS as % Pvt Cons Exp0 - 1.591.60 - 2.892.90- 4.104.11 - 6.426.43 - 10.00

An Unequal Health Care Burden of Households Around the World, 1997Out-of-Pocket Outlays on Health as a Share of Measured Total Private Consumption

The boundaries and names shown and the designations used on this map do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the lega l status of any country, te rritory, city or area or of its authorities, or concerning the delimitation of its frontier s or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement.

WHO 2000. All r ights reserved

At the beginning of the 1980s less than a handful countries haddeveloped the backbone of a domestic NHA. The number has timidlygrown over time but, until the mid-1990s, the NHA developers havemainly been confined to the high income strata of countries, contributing-- without intent to do so -- to widening disparities across nations: whenapplied to decision-making the countries with the highest access toresources have the potential to allocate these resources more rationally onaccount of greater transparency. The intelligence gap can, however, beclosed rapidly.

That gap is actually being reduced. Initiatives taken notably by theUnited States Agency for International Development (USAID), the WorldBank, two of WHO's regional offices, the Interamerican DevelopmentBank (IADB), several International Development agencies of the Nordiccountries of Europe have recently contributed two dozen National HealthExpenditure and financing surveys in middle- and low-income countries(see Chart 10). More are in the mill in Latin America, the Arabic Gulf,Eastern Europe, Central Asia and Africa. In the Pacific area, too, animportant consolidation effort has been launched. These NHA are,however, not comparable with one another. The non-comparabilityshortcoming diminishes the usefulness of NHA for policy analysis, as theimpact of alternative structures and of reforms undertaken by othercountries cannot readily be assessed. When national or regionalexperiments are comparable, they act as a kind of real scale laboratorieson behavioural parameters.

Chart 10. Coverage of national health accounts by region

Source: WHO, NHA-2000 data files.

The manufacturing of NHA at the centre (by WHO) has a meaningonly if the segments are repatriated in the appropriate national capitals.Only at that level is there a guaranteed enrichment as their authoritiesencounter policy challenges for which they have to produce monitoringinstruments. International organisations at best get involved in fragmentsof the policy spectrum faced by a country.

0%5%

10%15%20%25%30%35%

AFRICA AMERICAS EMRO EUROPE SEARO WPRO

PERCENTAGE OF COUNTRIES IN EACH REGION IN WORLD TOTAL (N=191)PERCENTAGE OF COUNTRIES EQUIPPED WITH AN ESTABLISHED OR AN INCIPIENT NHA (N=64)

By the nature of the tool, explicit or implicit NHA accompanyeverywhere the reform process. An NHA thrives only when it is policyrelevant, thus only when its developmental process is tied to decision-making.

The country templates have deliberately been made simple so as tobe applicable to nearly 200 different environments, to be achievable by avery small team within a year. Enlargement will be required and mademore rigorous as the burden of reconstruction and of maintenance passesto ministries of health, ministries of planning and central statisticalinstitutes. Reconstruction at national level is compatible with amaintenance and updating function of the variables contained in NHA-2000 in order to ensure continuity.

The NHA-2000 exercise has made evident the dearth of statisticalinformation of all kinds in most WHO countries. The NHA-2000framework may serve as a focal point to reorganise the observation andquantitative analysis apparatus of those Member countries which willwant to immediately get a better grasp on the performance of their healthsystems. The active preparation of producer’s guidelines (inspired fromthe OECD manual) will facilitate the implementation of that target whereit is adopted.

Several of the conclusions derived from the first world NHAexercise are not new: the fortune of interventions on health is closely tiedto the wealth of nations, and the wealth of nations depends on a betterhealth status of the workforce, of mothers and children, of the elderly.The quantification of the resources required constitutes nonetheless aprospective tool for the planners. Every country faces a distinct challenge.Since its neighbours face some of the same hurdles policy makers maylearn from the mistakes of countries that have preceded their own countryon the path of reform. They can also learn from the success story of someof their neighbours.

The implementation of reforms in more countries as well as thedevelopment of a monitoring tool may, paradoxically, lead both tostatistical shortcuts as well as to greater analytical complexity.

The measurement of health expenditure remains an undevelopedtask. More detailed and comprehensive data need to be mined. Morerelationships between the delivery and financing of health and itseconomic environment have to be explored. Every country needs more

and better financial data to improve the health planing and assessmentprocesses. The WHO effort contributes to this aim, though the indicatorsprovided in the World Health Report-2000 are only rudimentary.Imperfect information facilitates, comparative analyses and the promotionof greater transparency of health financing across the world more than thedearth of information. The supply of updated NHA is a public good. TheWHO contribution is, however, merely a means to incite local NHAefforts, or an instrument that precede them.

V. Bibliography

Berman P (1997). National Health Accounts in Developing Countries:Appropriate Methods and Recent Applications, Health Economics, Vol6:11-30.

Hernández P, Poullier J-P, Brugiatti MA (2000). Cuentas Nacionalesde Salud. Manual del usuario. Opciones e instrumentos para la mejora delsistema de salud en Panamá. MINSA - BID - CSS - Universidad Latinade Panamá, Panamá.

ILO (1995). Household income and expenditure statistics. Geneva, ILO.

IMF(1998). Manual on government finance statistics. Washington D.C.,IMF.

IMF. Government finance statistics yearbook 1999. Washington DC.,IMF. 1999.

IMF (2000). International financial statistics. March 2000. WashingtonD.C., IMF.

OECD. Economic and development review monographs. Severalcountries. Paris, OECD.

OECD. A System of Health Accounts for International Data. Paris,OECD, 2000. (Also www.oecd.org.els.health).

OECD. Health data 1998. Paris, OECD. 1998.

OECD. Health data 1999. Paris, OECD. 1999.

OECD. National accounts. Vol 1. Paris. OECD. 2000.

OECD. National accounts. Vol 2. Paris. OECD. 1998.

Poullier J-P. La santé malade de ses comptes [Health sick ot itsaccounts]. In: Edith Archambault and Oleg Archipoff (eds). Lacomptabilité nationale face au défi international. Paris,. Economica. 1990.

Poullier J-P. Administrative costs in selected industrialised countries,Health Care Financing Review, Summer 1992, pp. 167-172.

Poullier J-P. Public health in a national accounting framework.http://www.unescap.org/aphen/nha_2.htm

UN, IMF, CEE, WB, OECD. System of national accounts, 1993.Washington DC, UN. 1994.

UN. Classifications of expenditure according to purpose.ST/ESA/STAT/SER.M/84. UN. New York, 2000. UN. National accounts statistics: main aggregates and detailed tables,

1995. New York 1999. Waldo D. Creating National Health Accounts in Developed and

Developing Countries. US. Health Care Financing Administration.Mimeo 1997.

WHO. World health report 2000. WHO. Geneva.

VI. Annex.

Table A1. The data underlying the NHA entries

in the World Health Report 2000(Million of National Currency Units, except Exchange-rate: NCU per US$;

population: thousand persons).

TotalExpenditure

on Health

GDP Publicexpenditure

on health

Privateexpenditure

on health

Generalgovernmentexpenditure

Exchangerate

Population

Afghanistan 1500 46872 609 891 3000 20893Albania 11937 341716 9273 2664 97472 148.93 3132Algeria 74960 2457700 38100 36860 783600 57.71 29394Andorra 13380 178000 11600 1780 30160 146.41 66.8Angola 38140 1054000 22740 15400 125000 22904 11715Antigua &Barbuda

101 1576 58.0 43.2 363 1.96 66.5

Argentina 24090 292859 13852 10238 64200 1 35671Armenia 62900 798555 26100 36800 199639 490.85 3551Australia 42624 549290 30700 11924 198700 1.34 18333Austria 219961 2514400 151563 68398 1273200 12.2 8099Azerbaijan 451523 15352200 357875 93648 2689600 2896.2 7642Bahamas 228 3850 114 114 829 1 291Bahrain 105 2387 61.2 43.5 640 0.38 583Bangladesh 68740 1403050 31640 37100 348800 43.89 122650Barbados 318 4371 199 119 1458 2 267

Belarus 21086208 356080000

17425000 3661208 175021601 25964 10351

Belgium 694846 8712000 578000 116846 4387000 35.77 10127Belize 57 1222 29.6 27.8 362 1.45 224Benin 37860 1249800 17860 20000 312450 583.67 5629Bhutan 1015 14477 469 546 4631 36.31 1945Bolivia 2411 41860 1423 987 13750 5.25 7774Bosnia &Herzeg

1342 17585 1242 100 2000 4.95 3520

Botswana 741 1748 452 289 7660 3.65 1541Brazil 5612 864111 27521 28991 292000 1.85 163700Brunei Darus 438 8051 178 260 4000 1.48 308Bulgaria 825188 17103433 675580 149608 6742200 1676.5 8393Burkina Faso 54310 1390200 16800 37510 319100 583.67 11001Burundi 13910 431037 4950 8960 74900 352.35 6362Cambodia 647561 9025268 60745 586816 870000 2946.3 10478Cameroon 248300 5017400 50020 198280 6993600 583.67 13924Canada 74692 873950 53765 20927 352200 1.39 30261Cape Verde 1245 45101 794 451 19037 93.18 399Central AfricanRep.

16454 566000 11344 5110 177000 583.67 3420

Chad 27246 886900 21612 5633 163389 583.67 7086Chile 1930687 31567300 946900 983787 7013200 419.3 14625China 202170 7489500 50370 151800 923356 8.29 1244202Colombia 11279560 12170750

06141453 5138107 35701313 1141 40043

Comoros 3812 85074 2600 1212 29776 437.75 640Congo 67025 1334600 24517 42508 530000 583.67 2709Cook Islands 11 150 8.6 2.6 100 1.51 19Costa Rica 196983 2260479 151774 45210 754000 232.6 3748Côte d'Ivoire 189913 6176200 72913 117000 2240000 583.67 14064Croatia 9622 119053 7668 1954 34395 6.1 4484Cuba 1445 22952 1265 180 12663 1 11068Cyprus 254 4337 89.0 165 1604 0.51 763CzechRepublic

127699 1668800 117818 9881 739600 31.7 10301

Dem. Rep.Congo

11097000 304342000

97000 11000000 78953000 106000 47987

Dem. Rep.Korea

1835 61400 1535 300 20000 2.2 22610

Denmark 89362 1117800 75362 14000 584100 6.6 5256Djibouti 2470 88900 1800 670 31649 177.72 617Dominica 39 655 25.5 13.8 249 1.96 70.9DominicanRep

10466 215065 4028 6438 38500 14.27 8097

Ecuador 3599273 79040013 1900000 1699273 21280000 3998.3 11937Egypt 9583 256250 2583 7000 78503 3.39 64731El Salvador 6845 97428 2545 4300 12028 6.36 5911Equator.Guinea

10170 316290 5812 4358 73430 598.81 420

Eritrea 160 4713 88.9 70.8 2589 7.2 3433Estonia 4099 64324 3232 867 30709 13.88 1447Ethiopia 1573 41465 570 1003 10017 6.71 58218Fiji 130 3102 90.0 40.0 1082 1.44 786Finland 46970 632880 35195 11775 329600 5.19 5141France 808560 8224900 621739 186821 4512800 5.84 58472Gabon 91770 3117400 61000 30770 988000 583.67 1137

Gambia 144 3189 65.9 77.6 900 10.2 1189Georgia 298 6798 25.6 272 750 1.3 5121Germany 369000 3667200 299000 70000 2028285 1.73 82057Ghana 430000 14113400 202000 228000 2908900 2050.2 18656Greece 2612700 33021800 1720000 892700 13620000 273.06 10569Grenada 54.0 850 25.1 28.8 247 1.96 90Guatemala 2709 107873 1640 1069 13460 6.07 10519Guinea 153265 4379009 87665 65600 906100 1095.3 7325Guinea-Bissau 8865 154600 6700 2165 17270 583.67 1136Guyana 5440 105859 4300 1140 38757 142.4 843Haiti 2377 51578 798 1579 5797 16.66 7820Honduras 4584 61405 1650 2934 12728 13 5981Hungary 447500 8461600 380000 67500 4137070 186.79 10156Iceland 41684 529949 34945 6739 184700 70.9 274India 805000 15635500 105000 700000 2709000 36.31 966192Indonesia 10589984 62769500

03899784 6690200 129826950 2909.4 203380

Iran, IslamicRep.

12190000 277831000

5220000 6970000 72600000 1752.9 64628

Iraq 165021 3890629 97200 67821 70036 31.09 21180Ireland 3194 51822 2470 724 14400 0.66 3658Israel 28000 339992 21000 7000 163530 3.45 5860Italy 181246000 19506800

00103500000 77746000 985900000 1703.1 57377

Jamaica 13280 220556 7502 5778 84232 35.4 2516Japan 36180000 50785200

029000000 7180000 178770000 120.99 126038

Jordan 286 4946 172 114 2020 0.71 6126Kazakhstan 76277 1966000 48500 27777 469655 75.44 16373Kenya 28861 627436 18510 10351 168799 58.73 28446Kiribati 7.3 74 7.2 0.05 51.6 0.74 79.9Kuwait 301 9163 263 37.8 3129 0.3 1732Kyrgyzstan 1217 30686 847 370 8750 17.36 4619Lao Dem. Rep. 79700 2200000 50000 29700 579000 1260 5032Latvia 200 3276 122 77.9 1359 0.58 2461Lebanon 2230309 21997376 659266 1571043 8450000 1539.5 3143Lesotho 262 4715 190 72 1538 4.61 2016Liberia 75 2544 50 25 750 1 2402Libyan Arab J. 500 13284 230 270 8700 0.27 5210Lithuania 2471 38340 1871 600 13800 4 3705Luxembourg 38504 587000 35200 3304 270000 35.77 417Madagascar 382529 18046300 205781 176748 3113000 5090.9 14620Malawi 2404 41559 1423 981 10700 16.44 10067Malaysia 6467 281889 3727 2740 73000 2.81 20983Maldives 332 4027 212 120 1937 11.77 263Mali 60000 1431900 27500 32500 350400 583.67 10436Malta 81 1288 47.7 33.3 535 0.39 381MarshallIslands

15 164 11 3.8 84 1 58.4

Mauritania 9033 160618 2733 6300 41600 151.85 2461Mauritius 3015 86069 1595 1420 20850 20.56 1133Mexico 178877 3178954 73241 105636 1228600 7.91 94281Micronesia,Fed.

27 366 25 2.1 54 1 112

Monaco 240 3000 150 90.0 200 5.84 32.5Mongolia 31891 737039 26154 5737 196800 789.99 2537Morocco 16871 318350 6860 10011 106400 9.53 26890

Mozambique 1044690 17955000 745000 299690 8000000 11544 18443Myanmar 27457 1067522 3457 24000 93930 6.24 43936Namibia 1140 15115 590 550 5800 4.61 1622Nauru 6.5 128 6.4 0.064 70 1 10.9Nepal 10492 280582 2732 7760 51168 58.01 22316Netherlands 62182 703400 43972 18210 346800 1.95 15614New Zealand 8034 98247 5760 2274 45300 1.51 3761Nicaragua 1530 19116 815 715 6291 9.45 4679Niger 31296 889600 14598 16698 244000 583.67 9764Nigeria 68200 2200000 19240 48960 356262 21.89 103898Niue 0.274 5 0.24 0.034 20 1.51 2Norway 70993 1084788 58193 12800 481429 7.07 4396Oman 204 6075 130 74.2 2307 0.28 2305Pakistan 96533 2457400 22133 74400 772400 40.19 144047Palau 10 166 9 1 60 1 18.1Panama 657 8658 439 219 2310 1 2722Papua NewGuin

235 7342 183 51.4 2370 1.43 4499

Paraguay 1179340 20934300 420000 759340 2877500 2191 5088Peru 9704 173689 3849 5855 29700 2.66 24367Philippines 83433 2423640 40490 42943 561000 29.47 71430Poland 29022 469372 20787 8235 206900 3.28 38693Portugal 1461500 17859000 840000 621500 7809000 175.31 9864Qatar 2157 33464 1240 917 16387 3.64 569Rep of Korea 25666000 45327600

011500000 14166000 92510000 951.29 45731

Rep ofMoldova

715 8655 537 178 4330 4.62 4376

Romania 9533410 249750200

5743790 3789620 85793600 7167.9 22549

RussianFederat.

135347 2521942 103945 31402 454768 5.79 147656

Rwanda 24003 561600 12023 11980 68000 301.53 5962St Kitts &Nevis

44 724 22.5 21.2 216 2.7 40

Saint Lucia 62.2 1542 40.5 21.7 452 1.96 150St Vincent &Gren.

47.0 793 30.9 15.6 317 1.96 110

Samoa 24.4 540 18.4 6 202 2.56 172San Marino 98240 1312000 72200 26040 480000 1703.1 25.6Sao Tome &Prin

8000 200310 6000 2000 140174 4552.5 140

Saudi Arabia 21170 548620 16970 4200 181000 3.75 19479Senegal 119206 2639800 66400 52806 505000 583.67 8772Seychelles 171 2910 130 40.6 1547 5.03 80Sierra Leone 46500 959488 4500 42000 143293 981.48 4420Singapore 4458 142451 1596 2862 29222 1.49 3427Slovakia 56254 653900 46000 10254 327400 33.62 5372Slovenia 272924 2907300 220500 52424 1328400 159.69 1995SolomonIslands

28.2 886 28 0.2 535 3.72 404

Somalia 726264 47160000 518760 207504 100000 7250 8821South Africa 47945 683666 22300 25645 228800 4.61 38760Spain 6210859 77896600 4385597 1825262 32888000 146.41 39613Sri Lanka 26756 890272 12135 14621 234500 59 18274Sudan 551701 16012000 115493 436208 1202000 1575.7 27718Suriname 20150 266530 6850 13300 138000 401 440

Swaziland 207 6045 150 57.4 1827 4.6 925Sweden 160200 1813130 125000 35200 1089600 7.37 8856Switzerland 37500 371600 26000 11500 195000 1.45 7250Syrian ArabRep

18473 728794 6200 12273 211125 8.16 14948

Tajikistan 42700 560000 37500 5200 94712 650 5925Thailand 267927 4675500 83730 184197 1171000 31.36 59736Macedonia 12038 196000 10211 1827 65357 50 2000Togo 22832 817200 9782 13050 228000 583.67 4284Tonga 17.0 224 8.0 9.4 60.6 1.26 97.7Trinidad &Tobago

1571 36552 920 651 10412 6.25 1277

Tunisia 1127 20901 470 657 6575 1.11 9211Turkey 113516000

028836000

000840000000 295160000 774200000

0151865 63403

Turkmenistan 454500 10564000 391000 63500 2813980 4400 4233Tuvalu 1180 20000 1080 100 8500 1.34 10.8Uganda 342065 7531374 120000 222065 1213626 1083 20000Ukraine 5180 92480 3912 1268 40665 1.86 51062Un ArabEmirates

9419 181861 3330 6089 19400 3.67 2307

UnitedKingdom

46583 803890 45143 1440 316061 0.61 58544

Un RepTanzania

224000 4708630 136000 88000 499375 612.12 31417

United States 1088300 8300800 502200 586100 2721500 1 271772Uruguay 20363 188529 4125 16238 68704 9.44 3265Uzbekistan 40283 962140 32583 7700 318000 72 23212Vanuatu 965 29477 620 345 6485 115.87 177Venezuela 1734712 43211900 1125278 609434 10717659 489 22777Vietnam 15151000 31362300

03033000 12118000 68850000 11359 76387

Yemen 24998 740636 9485 15513 290571 129.28 16290Yugoslavia 8877 164421 5755 3122 5.5 10628Zambia 279745 5155800 106909 172836 1102000 1314.5 8585Zimbabwe 6810 99740 2957 3853 36454 11.89 11215

Notes: 1. AFR stands for the African region, AMR for the Americas, EMR for the EastMediterranean region, EUR for Europe and part of Central Asia, SEA for SouthEast Asia and WPR for the West Pacific region.2. Total Expenditure on Health is the measured level of public and privateoutlays in NHA-2000, calculated in millions of National Currency Units.3. The exchange rates are an annual average of daily observations .

Sources: WHO, NHA –2000 data files for expenditure on health; IMF, InternationalFinance Statistics for exchange rates; United Nations for population.