ESTIMATES OF NATIONAL HEALTH ACCOUNTS
(NHA) FOR 1997
Jean-Pierre Poullier
Patricia Hernández
GPE Discussion Paper Series: No. 27
EIP/GPE/FAR
World Health Organization
The authors are indebted to Chandika Indikadahena who has maintained
the data files on which the NHA-2000 have been constructed. This
construction would not have been possible without an input from several
dozen persons who have responded to data request and commented
preliminary versions of the data files; this input will be acknowledged in
a 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 disinfectants
Justice O.W. Holmes
Differentials in the health status of populations are considerable
(see World Health Report 2000, annex 5). There is a strong correlation
between health status and real income, more precisely the acquisitive
power that accompanies wealth. In the present state of measurement,
under a tenth of that acquisitive power is oriented towards goods and
services that directly enhance health. Non-medical as well as medicalpara-medical determinants are frequently referred to in policy analyses,
though only marginally captured by rigorous tools. As they attract
resources, a challenge of the next five years is the integration of neglected
determinants of health into the accounting framework and the
establishment of weights to attach to medical and to non-medical
determinants of health.
The basket of goods and services that directly enhance the health
status of the population experiences huge differentials in productivity and
in costs. Variations in the quantities consumed of these goods are large
within small areas, as well as across nations, or continents. The financing
paths adopted result in a wide array of incentives and disincentives, and
in greater (or lesser) patterns of citizens' equality irrespective of age, sex,
income and social status, disease and disability. A keener knowledge of
spending levels and trends, of the efforts deployed in each nation to
provide health enhancing services, of the costs and the use patterns of
determinants of health status improvements, of the incidence of health
care costs on the income status of the sick and disabled, appears thus to
be essential to a more effective deployment of resources. The major
unresolved policy puzzles of inappropriate allocation of resources tax the
ability of the statisticians called to monitor policy and their outcomes.
The search for a more effective use of the whole array of allocative
instruments towards social goals attainment, requires greater
transparency. Given the intertwined paths to deliver and to finance health
services, an extensive knowledge of privately funded health enhancement
transactions is further required.
National Health Accounts (NHA) aims to achieve a comprehensive
and consistent synthesis of health-related activities by enlightening the
main policy parameters of society. It can facilitate simulations that can
better reflect an increasing complex system of delivering and financing
care in light of a rapid evolution of medical technology and other
organizational determinants.
Only a tenth of the World Health Organization countries have
undertaken a financial synthesis respecting fully NHA standards,
including institutionalisation that supplies figures on a recurrent basis. In
order to accelerate the emergence of NHA in the rest of the world's
countries not yet equipped with a synthetic tool to monitor health
spending and finance, the WHO is providing a basic set of NHA
indicators for all of its 191 Member countries, hereafter referred to as
NHA-2000. The latter are not a compilation of existing country-specific
NHA; they respond to a methodology developed to ensure a comparable
synthesis across nearly 200 countries. Breaking down the 191 country
segments, the figures for two thirds of the countries are based on periodic
specialised international publications and one third is estimated based on
varying degrees of information available, completed using standard
estimation techniques.
NHA-2000 uses, as much as possible, a common framework that
places a greater emphasis on the financing side of the NHA triangle than
on its consumption or production sides. In the ideal National Accounts,
the three sides –– are in equilibrium as an equilateral triangle or, due to
statistical conventions, at least as an isosceles triangle. No National
Accounting system, nor any National Health Accounts, has to date
managed during its first iteration to capture the complex reality of the
macroeconomic relationships it seeks to describe. Successive iterations
should altogether transform NHA into a daily life managerial policy tool.
This note recalls in Part II some conceptual underpinnings of NHA
and the rationale of the WHO exercise for the World Health Report 2000.
Part III dwells on the methodological options adopted to estimate health
expenditure, and Part IV discusses the set of measured levels of health
expenditure (or sets, as different regions of the world and different areas
within each region exhibit altogether commonalties in spending patterns
and considerable heterogeneity in their delivery, financing and statistical
modalities). The quantitative observations in this discussion paper and in
the World Health Report 2000 refers to the 1997 calendar year (or
adjacent fiscal year). Like for any first undertaking, the essential lies,
however, not so much in the precision of the orders of magnitude
published as in the drive towards transparency.
II. What is the NHA tool
NHA may be defined as an integrated set of cross-classifications
purporting to measure health related activities and economic flows:
inputs, output and resource use, contributing to the enhancement of health
status.
NHA is a reductionist model of society, and caters to the
population at large. It lessens the myopia of a policy machinery tempted
to deal with problems in sequence and in isolation. It creates an informed
constituency of stakeholders around identified objectives and diverse
organisational arrangements. It distributes the gains of policy
interventions and of individual commitments across the entire spectrum
of the system.
Chart 1 illustrates the strategic convergence at which NHA is
located in a global information system monitoring interventions on the
system and health gain. The flowchart idealises real world conditions in
which NHA are often rudimentary and are not integrated in a cogent and
decision-prone information sub-system. A picture of the more ideal
setting provides a horizon of the potential of the tool, if not an ambition
and a target.
As developing country governments face the many challenges of
strengthening stewardship and managing health system reforms, the
implementation of NHA provides an opportunity to considerably expand
the monitoring of these systems. The strengthening of a health system’s
monitoring capacity constitutes an important step towards the
modernisation of its governance. Active stewardship requires interaction
between financial/non-financial information which would permit
decision-making in the face of diverse challenges caused by economywide constraining factors such as austerity programmes and their impact
on health needs and systems.
Irrespective of the financial formulas that prevail, poverty
reduction efforts require additional resources, a strengthening of capacity
building, and a more efficient deployment of resources. More effective
stewardship requires a greater focus on norms and a standard setting.
These are not easily translated into an accounting framework, but NHA
can provide a tool that permits a sharper and transparent focus on
structural change and on distribution issues ..
Chart 1. An Accounting Approach to the Production Flows in the
Health 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 health
sciences is allocated to the alleviation of around one tenth of the world’s
disease burden and, conversely, nine tenths of the world disease burden
attract around one tenth of the world R & D effort. The gap is barely
smaller in the total allocation of resources towards care and cure. The
measured input into the health systems of the world shown in Table 1 –
which summarises by mortality stratum the information captured in the
World Health Report 2000 – suggests that the high income countries
(AMR-A, EUR-A, WPR-A, together 15 % of the estimated world
population) capture three quarters of health spending while 85 % of the
world’s population has a quarter of the total resources devoted to the
alleviation of disease and disability. Expressed in a standard of living
equivalent currency, the three quarters – one quarter divide is marginally
less dramatic than the inequality indices depicted in Charts 2 and 3
whereby some 120 countries spend less than $ 20 per capita per month on
health 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). The
illustration shows one among many dispersions masked by regional or
sub-regional averages. These intra-regional disparities matter: inequalities
within low-income countries are often larger than those found in better
endowed countries and, at times, exhibit utilisation patterns that
constitute a social waste.
Table 1. Measured spending on health in the world, 1997
Mortality Number
Total
subof
expenditure on
region countries health at X-rate
($ million)
AFR-D
AFR-E
AMR-A
AMR-B
AMR-D
EMR-B
EMR-D
EUR-A
EUR-B
EUR-C
SEA-B
SEA-D
WPR-A
WPR-B
Total
26
20
3
27
5
13
9
26
19
6
3
7
5
22
191
6,461
14,097
1,143,480
75,895
5,312
25,247
12,965
766,765
26,232
28,897
12,637
29,208
339,450
59,407
2,546,054
Share of world
expenditure on
health
%
0.3%
0.6%
44.9%
3.0%
0.2%
1.0%
0.5%
30.1%
1.0%
1.1%
0.5%
1.1%
13.3%
2.3%
100.0%
Share of
world
population
%
4.7%
5.4%
5.4%
7.3%
1.0%
2.3%
5.7%
7.0%
3.9%
4.0%
4.8%
20.3%
2.6%
25.5%
100.0%
Per capita
spending at X
rate
(US $)
24
45
3,652
180
94
193
39
1,876
115
125
45
25
2,235
40
438
Notes:
1. The area sub-totals refer to total mortality levels, ranked from low (A) to high (E) level, a
scale developed at WHO on the basis of an analysis of the data file that collates mortality
figures by age-sex and ICD cause for all countries; clusters have been designed on the basis
of an analysis of the disease burden in the world (see World Health Report 2000, pp 204-5). A
stands for very low child and very low adult mortality, B low child and low adult mortality, C
low child high adult mortality, D high child and high adult mortality, E very high child and very
high adult mortality. AFR stands for the African region, AMR for the Americas, EMR for the
East Mediterranean region, EUR for Europe and part of Central Asia, SEA for South East
Asia and WPR for the West Pacific region.
2. Total Expenditure on Health is the measured level of public and private outlays converted
at 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 for
population.
A keener knowledge of the paths towards greater effectiveness is
acquired through a domestic planning and evaluation process.
Comparative analyses help to focus on strengths and weaknesses of
foreign experiences, thereby shortening the learning curve and generating
economies of scale. Modern policy analyses of health systems rely
increasingly 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 countries
seeking similar successes or desirous to avoid the same pitfalls. Policy
simulations, however, are not automatic as no two countries have the
same mix of instruments, incentives and regulations.
Chart 2. Inequality of opportunity revisited: Distribution of
measured per capita expenditure on health, 1997
100%
90%
Share of w orld
expenditure on
health
80%
70%
60%
50%
Share of w orld
PHE
40%
30%
Share of w orld
PvtHE
20%
10%
0%
< 700
700-1,300
1,300-40,000
Share of w orld
population %
GDP per capita strata
Source: WHO, NHA-2000 data files.
NHA are intrinsically flexible so as to apply to an ample spread of
alternative policy set-ups on the financing as well as on the delivery side.
Different models of NHA express, however, central features of the health
system to which they apply. The “Harvard model” (which has inspired a
majority of the NHA developments to date in Latin America, the East
Mediterranean Basin, South East Africa), stems from the multi-payer
HCFA (US Health Care Financing Administration) approach. The Dutch,
French, German and a number of other European models place more
emphasis on spending functions where a more limited number of payers
devote a larger part of its attention to the price-volume interface. A
smaller number of countries, such as Norway, have opted instead for
input-output models with emphasis on production; satellite Health
Accounts (satellite to the National Accounts) require this close level of
correspondence with value added. The ambitious OECD model, designed
to apply in a complex, multi-dimensional process environment, addresses
the 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 greatly
enhanced by achievements in the field of summary measures such as
Disability Adjusted Life Expectancy (DALE), Potential Years of Life
Lost (PYLL), and Disability Adjusted Life Years (DALY).
Chart 3. Distribution of countries by per capita expenditure on
health, 1997.
5
THE per capita
2 ,5 0 1 - 4 ,2 0 0
13
1 ,5 0 1 - 2 ,5 0 0
25
5 0 1 - 1 ,5 0 0
18
251-500
130
< 250
0
50
100
150
Nu mb e r o f c o u n tr ie s
Source: WHO, NHA-2000 data files.
Health policy analysts regularly stress the uniqueness of each
health system as it is instituted to respond to culturally determined
demands. To the uniqueness of the supply-demand interaction correspond
unique indicators. In business, however, the discipline to establish worldwide reporting norms make it possible for companies to compile one set
of books for investors everywhere. The International Accounting
Standard (IAS) blueprint is gaining increasing recognition. A similar
justification imposes homogeneous concepts, definitions and
methodological guidelines to model and trace the economy at large. The
System of National Accounts (SNA) is complemented in a number of
areas by specific statistical systems under the aegis of the United Nations
and its specialised agencies, the IMF, the World Bank, the OECD, the
Statistical Office of the European Union and numerous regional statistical
bodies.
As the economies moved more global, the reach of SNA extended
in depth and in width with satellite accounts in areas such as agriculture,
education, R&D, tourism and transport. A handful of countries have also
initiated a satellite account for health but most of these have been partial
achievements due to inaccessibility to needed data to build a full-fledged
satellite account.
The NHA-2000 has not adopted the path leading to a satellite
account, as this would have required full consistency with the framework
of the SNA and a more detailed cross-classification of transactions, of
providers and of income flows than what is available. The prospective
benefits are not commensurate with the costs entailed, not counting
considerably greater lead times before availability of usable results. With
disparities such as those shown in Chart 3, for comparative purposes the
greater accuracy of satellite accounts is perhaps not warranted.
NHA boundaries and NHA attributes
Conventionally confined to medical care and a few related
activities, the policy relevance criterion (listed below as a major attribute
of NHA) dictates that its boundaries should be extended to include a
range of non-medical interventions whose primary intent is the
enhancement of health status, and for which the implementation results
from interventions over which the health system is accountable for. As
for other areas of economics and social accounting, when a pro rata
allocation of joint products is not practical, the entirety of the joint
product is classified in the branch with the heaviest weight. As in
economic and social accounting, boundaries are set in respect of defined
classifications and with a degree of flexibility to accommodate “cultural
exceptions”.
Practical difficulties have impeded the implementation of these
principles in the NHA-2000. A lack of disaggregated data has often been
a roadblock, though they relate to areas in which an extension of the
conventional boundaries might have encountered only limited opposition.
The boundaries are often difficult to distinguish between the basic
survival function (which includes food, access to drinking water, and
shelter) with the health function (which includes community values, the
ability to perform in society without impairments, handicaps and
disability). In many sub-Sahelian and tropical countries, ministries of
health have the provision of safe drinking water within their
responsibility, and consider it a health related expenditure. In the
Americas and in Europe the sanitation function is distinct from the health
function. The primary intent moved from health enhancement to that of
securing a minimum level of environmental amenities and access to a
floor level of facilities.
Should there be different boundaries in different NHA around the
world? Should key amenities be included as an addendum item below the
health total? Should the “ancillary” services be only reported as
sanitation? The latter is the solution adopted by the classification of the
functions of government, COFOG, one of the pillars of the system of
national accounts. Should the production of seat-belts and airbags be
considered as serving more a primary health intent than a transportation
comfort? Does the removal and disposal of solid waste not contribute to
hygienic as well as to aesthetic values? The reduction in exposure to
pesticide contamination, chemical and industrial pollution, air pollution,
sewage, lead pollution, radioactive wastes, head a list of environmental
programmes designed to reverse neurological, respiratory, endocrine and
mental impairments of the affected populations.
There needs to be a periodic review of what it is that societies need
to monitor and where they classify the provision processes and the
consumption functions. Fluoridated toothpaste has strongly contributed to
receding tooth decay in the richer societies; in statistical records, these
purchases are not readily separated from cosmetics and toiletries whose
contribution is more of an olfactory nature. The need for flexibility in
classifications is highlighted further by epidemiological and technological
trends. Catastrophic illnesses, such as AIDS, consume increasing shares
of the total health bill. Countervailing strategies require conventional as
well as non-conventional strategies; it is important that the latter be fully
monitored. With computarisation, the level of disaggregation and the
geographical extension of alternative classification extends already to
middle income countries a statistical sophistication open yesterday to
higher-income countries.
Although country details have not been forthcoming to ensure an
itemised implementation in the NHA-2000, the latter has been notably
constructed using an implicit draft classification of public health
functions. The prevention and health promotion components of this
classification reach out to interventions, or the production of goods whose
primary intent is the enhancement of the health status of target groups in
the population. Education and the training of health personnel, research
and development, food hygiene and drinking water control, and
environmental health are some of the domains retained. Whereas curative
medicine and the relevant classification mainly deal with interventions on
the pathos (disease as a real event), public health mainly deals with nosos
(disease as a threat, a risk) that requires more evidently a wider
multidisciplinary approach and interventions. A System of Health
Accounts (hereafter referred to as the OECD Manual) shares much the
same approach.
The NHA matrices condense a complex reality made of a zillion
transactions around simplified classifications, depicting particular
attributes of these transactions. A comprehensive, systematic and
standardised quantification path of all financial resource variables, their
use and distribution is summarized in chart 4. Whilst NHA-2000
concentrated on providing aggregate information for 191 countries, future
editions will seek to supply more disaggregated information.
Chart 4. The main financial flows in a health system.
External resources
Households and Firms
Grants & loans
Voluntary contributions
Compulsory contributions
Sources of
Financing
(through public & private agencies):
Purchases, donations, copayments
(through public agencies):
Payroll taxes, social security premiums
Other public sources
(taxes, wealth)
Public health budget
Provider Agents
Social security budget
*
Direct payments
Private medical insurance &
other pooled payments
Health goods and services provision **
For non-insured population For insured population
Not-for-profit providers
For profit providers
Pharmaceutical &
therapeutic appliances
Other health care
services
Functions
Hospital services
Ambulatory services
* Includes mandated employer
** Includes collective consumption and investment, such as administration, R&D and public health.
As a statistical system, the NHA process entails respect of ten major
attributes. Their simultaneous pursuit is difficult because several are
seemingly contradictory. The essential attributes of NHA are:
•
•
•
•
Policy sensitivity: NHA seek to identify and quantify parameters, as
well as to focus on providing information describing components of
the health system susceptible of changes through interventions
designed to improve selected facets of the system's effectiveness;
Comprehensiveness: NHA strive to monitor all the health field
expenditure, provision, inputs and outputs, intermediate and final
outputs, financing flows of the institutions / and of the functions that
make up a health system;
Consistency: internal coherence and avoidance of contradictions are
achieved through standardised classifications, explicit identities and
exacting accounting rules;
Bookkeeping + imputations: an accounting system does not stop at
integrating dispersed data from a variety of institutional sources.
When an economic function performed by the system is not
quantified in the available sources of information, the relevant order
of magnitude must be simulated and entered alongside;
•
•
•
•
•
Standardisation: the application of identical rules is a requisite for
analyses over time and across countries. At individual country level,
this process yields economies of scale in supplying ready-made
concepts, definitions, nomenclatures and other methodological
devices;
Multidimensionality: the expenditure analysis is not relevant per se
but in terms relative to the population needs to be satisfied and to the
institutions to which they refer. This entails that expenditure
information needs to be complemented with non-financial
information of a demographic, epidemiological, service utilisation
nature, as well as by stocks of human, tangible and intangible
capital;
Accuracy: the levels and time series reflect arbitrages between
completeness and accuracy, since large data sets built for diverse
purposes, according to different methodologies and for different
dates/or periods have to be combined;
Timeliness: while survey data are structural information whose
behavioural relationships evolve only slowly, trends of selected
components of NHA may exhibit rapid and deep changes.
Opportunity to interact with policy decision is greater when a
preliminary NHA synthesis is completed within six to ten months
after the close of the fiscal year to which it relates (strenghtened,
whenever possible, by a projection of trends based on a no-policy
change scenario). The planning and budgetary process requires
preliminary data susceptible to be adjusted before formal publication
in a second round estimation. In the countries that release their first
estimates before the budget has to be voted on, a provisional release
of the macro-health aggregates offers a more reasoned base on which
the government and the parliament can act. The balance between
timeliness and accuracy may be struck by an arbitrage in which the
added value of new information is weighted against the
consequences of delayed action by policy-making bodies;
Recurrence: behavioural monitoring is assured only through a
continuous estimation. Continuity of estimates is the only way to
judge if results of estimates are exceptional or expected. Continuity
entails the benefits of a learning curve to improve the quality of the
estimates and diminish the costs of producing them: single year’s
syntheses are a financial survey or analysis, not a NHA..
•
Distributions: the amount of resources consumed or funds spent is
the initial synthesis established. An essential policy dimension is to
cater to strata of consumers of health goods and services, of health
functions, of care providers, as well as to balance inputs for the
production of health goods and services and to balance health
funding.
Selected identities of the NHA-2000
The NHA are a sequence of identities centred around:
Expenditure =
consumption +
investment ≡
provision of goods
and services ≡
Sources of financing
=
Taxes+Payroll
taxes+Private
disbursements
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 with
higher or lower attributes. To calculate expenditure trends, price levels
and volume indicators are required. Average prices are used for
opportunity costs analyses, medical-specific prices for productivity
analyses. 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 of
different elements.
THE = PHE + PvtHE
Public outlays on health (PHE) is defined as the sum of health enhancing
expenditure of the central-federal (CGHE), regional-state-provincial
(RGHE) and local-municipal governments (LGHE), of social security
institutions (SSHE) and of extra-budgetary outlays (EBHE). Public
expenditure includes the direct provision of services as well as indirect
payments, such as the subsidisation of providers or transfers to
households for the payment of their health bills, enterprise programmes
enhancing the health status of their employees (and, sometimes, their
relatives), non-profit institutions serving households health needs, direct
and indirect (notably through insurance) payments by households,
investment in private and public facilities. This can be formalised in the
following way
PHE = CGHE + RGHE + LGHE + SSHE + EBHE
A crude attempt has been made, based on the available sources, to
estimate in Annex table 8 of the World Health Report 2000 expenditure
on 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 be
essentially funded through contributions and not through income or
expenditure taxes. This is not the case in the real world. Social Security is
also partly funded in some countries through intra-government transfers.
TFHE includes other governmental resources, such as external borrowing
or grants, and wealth income (endowments, profits from public
corporations other than taxes accruing to the State budget). External
resources could only be singled out for a small number of countries so
that it is not shown as a distinct source in NHA-2000 but it is a strategic
value to highlight in future editions. External resources transiting via
PHE and/or PvtHE (mainly non governmental organisations, NGO) it has
been inferred in NHA-2000 that they are expenditures of government or
of NGO.
TFHE = GGEH - SSHE
Private outlays (PvtHE) integrate health insurance (PvtHI) and
prepayment schemes, mandated enterprise health expenditure (MEHE),
expenditures on health through non-profit health services (NGOHE) and
co-payments to public health services, as well as direct payments or outof-pocket expenditures in health goods (OOPS), which are mainly
pharmaceuticals, co-payments for ambulatory care, and expenditures by
for-profit agents, such as private investment expenditure on health
(PvtInvH).
PvtHE = PvtHI + MEHE + NGOHE + OOPS + other (including
PvtInvH).
Expenditure on health integrates the main components of the economic
classification:
PHE, PvtHE = consumption + investment
The financing of health expenditure comprises wages salaries, the
purchase of goods and services for the delivery of care and cure, subsidies
to producers, transfers to households, gross capital formation and capital
transfers contributing to private investment. In order to undertake
opportunity cost analysis, private investment must be recorded. Current
expenditure and health utilisation data do not reflect the level of private
investment that is responding to the rapid growth in demand for private
health care. A separate capital account is more necessary in the low- and
medium-income countries than it is in the higher income countries, as
investment (private and public) accounts there for two to five times the
relative levels observed in the OECD countries. Capital utilisation and
capital maintenance costs appear important variables to monitor.
Identities and conversion factors in NHA, as in most macroeconomic accounts, rest on fundamental assumptions such as someone's
expenditure is someone else's receipt or gross income. The first of these is
Value = Price * Quantity. Services being by nature difficult to stock,
expenditure identities applied to health typically omit (or exhibit only
minimal) changes in inventories. The paucity of detailed information on
therapeutic appliances leads typically to equate consumption data with
total expenditure, though conceptually this is not fully correct. That
assumption should, however, not be equated as the absence of delayed
provision. Like most distribution issues, presently ill-monitored by NHA,
delayed provision requires a special analysis and through distribution
flow charts can be integrated into an NHA framework.
III. Methodological considerations
NHA require that all agents transacting in health-related
commodities and all transactions be monitored, cross-classified, and
valued, i.e. purchases by ultimate user or beneficiary (households for
individual consumption, the population for collective consumption),
commodities by producing agents (hospitals, health centres, office-based
physicians and other professionals, specialised retailers of health
commodities such as children vaccination clinics, insurers and public
administrations regulating and monitoring health activity), by financial
status (public services, insurers, charities, foreign financial institutions,
households). This requires a careful mapping of all agents and all
transactions in health-related activities.
The NHA-2000 exercise has pursued two distinct aims. First, the
creation of a transitory expenditure financing statement for each WHO
Member country in order to provide a reasonable order of magnitude of
resources consumed to enhance the health status of its population.
Second, the stimulation of a large number of national administrations to
establish genuine NHA for their respective countries.
Each national segment has over two hundred health specific and a
hundred macro-economic and demographic variables. The information
gathered permits a basic analysis of the policy-relevant public and private
expenditure flows. The two sectors are further split into insurance and
alternative prepayment schemes and outlays funded from own sources
(taxation for government, mandated enterprise schemes and direct
payments or out-of-pocket for private flows).
Social security programmes compulsory for a sizeable segment of
the population are an integral part of public expenditure on health. For the
private segment, the intent has been to distinguish expenditure on health
from households as prepayment and private health insurance, from that of
direct out-of-pocket payments to purchase health goods and services
(including payments for pharmaceuticals), NGO and for-profit private
health services. Whilst conventional National Accounts treat occupational
health care provided by firms as intermediate outlays, the NHA-2000
classifies it as final expenditure.
Public Expenditure on Health
Public Expenditure on Health (PHE) in the context of the NHA2000 relates to outlays for which a government entity pays. The public
entities are those subject to governmental financial and/or political and/or
social control, whatever their legal status and whatever territory they
exert their power over. The sectoring adopted emphasises financial
transactions, not that of the legal status of the delivery agent.
General government includes central-federal authorities, regionalstate-provincial authorities, local-municipal authorities and social security
institutions whose affiliation is compulsory for a sizeable segment of the
population. In respect of the latter, discrepancies are found between
certain national classificatory rules and the international ones applied for
NHA-2000. On the grounds of legal status and of discretionary decision
powers vested in boards that act without government control, a number of
national statisticians have opted to treat Social Security distinctly from
territorial authorities.
Other extra-budgetary funds operate in the array of institutions
mapped in the WHO area. Their resources originating from a territorial
government, or on the basis of payroll or other taxes authorised by a
territorial government, are classified in NHA-2000 under General
Government.
Conceptually there is a fourth territorial level that can play a role in
health financing: supranational authorities. For instance, the European
Union has contributed to investments in the Irish or in the Greek health
system. The supranational route appears to have played a minor role in
the other regions of the world. In NHA-2000 they have not been treated
as a distinct sub-sector. External resources supply huge amounts of funds
to a few low-income countries, such as Bhutan and Nepal (which transit
mainly via general government budgets), or Lesotho (where NGOs –
notably religious missions – play an active role). These transactions are
recorded under government financing, non-tax revenue or under nongovernmental organisations income and outlays.
The economic transactions retained in NHA-2000 are those
classically found in the economic accounts of nations, differing in two
major ways from the bookkeeping conventions initially adopted by some
influential statisticians: the explicit incorporation of subsidies and transfer
payments, the imputation of real flows without overt financial
counterpart. An illustration may take the place of a formal justification. In
a country determined to set-up NHA, the institutions mapped as adding
up to the health share in the income and outlays of the nation summed up
to around 2.8% of GDP; when the subsidised enrolment of poorer citizens
was included, when a subsidy making up the shortfall of hospital revenue
based on an official nomenclature of fee-for-service compared to actual
costs was added (virtually doubling the revenue formally billed), and
when the deficit of the social protection schemes made up by a State
payment entered the pictured, that nation's health bill rose by two
percentage points.
In line with an SNA 93 recommendation in respect of subsidies to
non-market producers (e.g. government-owned hospitals) lowering the
prices charged or the costs reported, the OECD Manual rules that final
consumption values should be recalculated by adding subsidies to the
recorded costs. The implementation of this principle in NHA-2000 has
only been haphazard. Few national authorities publish subsidies classified
by function. As for imputations of real flows into a health system without
genuine financial counterpart, time constraints have prevented a
systematic consideration of the value of tax concessions (e.g. reduced
import tariffs for pharmaceuticals compared with tariffs on other
manufactured products) or in-kind donations (e.g. religious missions). In
NHA, subsidies should be entered as expenditure-equivalent values. This
principle matters particularly when the subsidies are non-cash
transactions for a government agency such as tax exemptions. An
intractable case consists in estimating the subsidy equivalent of a loan
guarantee that, usually, involves no cash payment, nonetheless
substantially lowers the borrowing costs associated to, say, the
construction of an hospital. The level of detail in the countries’ records
that have been accessed did not allow adjustments of this kind in NHA2000. Subsequent re-evaluations should at times thread on such a
territory.
The economic transactions in NHA are rigorously classified. The
bulk of the OECD Manual deals with an interrelated system of
classifications. Although each reporting system is based on classifications
of one kind or another, it has not been possible in the time allotted, to
implement in NHA-2000 a single classification, nor even to examine each
country’s detailed data. Even the OECD countries are only gradually
aligning their classifications. In Japan, for instance, eyeglasses and
selected appliances until recently were not classified as “medical goods”
because they are not part of the reimbursable benefits under the statutory
health insurance, etc. Classificatory exercises have taken place in several
countries. In Hong Kong, Lebanon, Sri Lanka, the classifications
proposed by OECD have served as benchmark and have been assessed as
providing a fairly good basis, largely adaptable to the reporting systems
of these countries. Other middle-income countries have seemingly used
the same classificatory principles, though many could implement them
only at a semi-aggregate level. While this is positive news for a NHA
Producers’ Guide being drafted under WHO, World Bank and PHR’s
auspices, the efforts required to reach harmonisation across a wide
spectrum of countries should not be underestimated. The current revision
of the International Standard Industrial Classification (ISIC), for instance,
is somewhat old for an activity in which medical manuals are out of date
every five years or so. On the other hand, the OECD classifications are
more exacting than what many countries (including some OECD
countries) are able to record in a systematic way in mid-2000, requiring
thus a simpler classification.
An operational challenge will be to reconcile the functional
classifications with the prevailing institutional and legal structures. The
conventional National Accounting rules, applied in most NHA
frameworks constructed to date, have been respected. For example,
territorial government levels (central-federal authorities, State-regionsprovinces-constitutional equivalent in other legal systems, local
authorities-municipal governments) and extra-budgetary arrangement
(among which social protection schemes not consolidated under central
government), which are often legally empowered to raise compulsory
premium akin to, but different from, universal taxation have been
explicitly categorised as public.
Public corporations which derive a substantial part of their
resources from the sale of commodities or services, such as mining,
utilities, transport, and communications, are a source of considerable
confusion in the build-up of NHA. Publicly owned facilities are
frequently classified as government outlays in budget statements. Under
SNA 93 rules, they are allocated to the income and outlays account of the
enterprises sector, aggregated with similar utlays of private business
enterprises. For a number of oil producing countries, the private-public
mix of expenditure on health exhibited in national sources (and in World
Bank reports) differs from the NHA-2000 subtotals mainly on
classification grounds of mandated business health programmes and/or
occupational health care, and not because of genuine differences in the
size of the estimates.
An underlying NHA-2000 principle is one of a distinct preference
for an economic rationale as opposed to a legal convenience. Unsettled
among professional health accountants is the issue of imputed
transactions. The direct costs to a health system of nursing services
supplied by members of a religious order are minimal but the services
rendered important. Should these services not be assessed at replacement
cost with an imputed transfer payment? When the under-priced service
vanishes the substitute arrangements are usually much dearer. The
conventional view is to leave most imputations to analysis, the
description 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 estimate
opportunity costs. Cases for potential imputations abound, such as
implicit-subsidies to pharmaceutical imports at below “normal” customs
tariffs.
How should foreign assistance be valued? At local wage rate plus a
scarcity premium incorporating part of the higher compensation of
foreign experts with only token overhead costs? Charging the full wage
supplements the foreign salary scale, plus travel costs, housing and local
transportation amenities, the financing agency’s administrative costs,
etc)? The limited accessibility to details has not facilitated a
homogeneous treatment in NHA-2000, which has leaned towards a
measure of the recurrent economic value to the health system of the
service with a separate entry for the transitory “import premium”.
A considerable practical hurdle – that may have led to under- or
over estimation – has been the determination of the level of expenditure
data. A number of regional or local authorities exert a discretionary
spending power but the underlying financing originated in intragovernmental transfers, not in an autonomous taxation capacity. In the
NHA-2000, the principal agent has been deemed to be the central
government whenever local authorities enjoyed no autonomous taxation
capacity in the health field. By exception to that rule, the national health
budget originating in external financial sources has been assumed to be
equivalent to a tax resource for the largest part (a share transits in some
countries via non government organisations and non-profit institutions
serving mainly households). When these data can be isolated, financing
flows originating from multilateral international agencies and bilateral
programmes are monitored in a complementary table of NHA-2000. The
quantity of information collected and the quality of the disaggregation
attained (grants, loans, direct costs) was not sufficient to report (the
external flows) in Annex Table 8 of the World Health Report 2000. The
share of grants that can be allocated to NGO has been included in private
expenditure and has likewise not been reported.
For convenience, the International Monetary Fund's Government
Finance Statistics (GFS), which supplies central government expenditure
by function for 73 WHO countries, has been used as a main source of
information (see Chart 4). Though the IMF guidelines are unambiguous, a
majority of countries report only part of their central government outlays
for health, usually those related to Ministries of Health. A few countries
add the outlays of Social Welfare Departments. Metadata on the actual
contents of the series are attached to the country segments. Only in the
case of Bulgaria and Yemen is the indication regarding the health
function crystal clear: for Bulgaria, according to GFS the outlays of all
ministries’ for the advancement of health are reported. For Yemen, the
post-reunification period (1990 onwards refers to one ministry only). For
some countries the data refer to consolidated central government
expenditures including social security, regional and local agencies (e.g.
Bolivia). Other countries only report general government expenditures
and social insurance funds (e.g. Luxembourg). Others report in addition
extra-budgetary expenditures (e.g Austria, Bahrain, Latvia, Macedonia
and Poland). Some countries changed the content of reporting categories
over time (e.g. Italy has not included autonomous agencies since 1993).
Occasionally, others exclude international grants in reporting extrabudgetary funds (e.g. Estonia). Others only report non-consolidated
central government expenditure (Paraguay and Singapore). These
examples are illustrative of the wide spectrum of institutional and
regulatory set-up.
IMF guidelines require the consolidation of Social Security with
central government. While this is frequently abided by, a number of
finance ministries or central banks skip a full consolidation,. For example
they report only social protection schemes whose main function is the
delivery or the funding of medical care at the exclusion of other schemes
(such as those of old age insurance, civil service insurance, railroad
workers insurance, workmen compensation act systems, which may have
a sizeable though not dominant medical care function). Underreporting of
this kind may have occurred in China, Iran, and other countries of Asia.
As more information is obtained, a more sophisticated institutional
mapping is expected for subsequent NHA syntheses. WHO Health
profiles are available for a third of WHO member countries. A country
wishing to set-up an NHA should consider mapping its health system
profile as a priority.
An effort has been made to collect health expenditure data in
Defence (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 insurance
schemes. The modest amount of data collated suggests that a fair number
of central government outlays cover a wide “health” territory but the
programmes included in the provisional NHA are only mildly
comprehensive. Further enquiries have been launched that may modify in
subsequent rounds of NHA some of the arbitrages made.
Private Expenditure on Health
The intent of the collection process to be comprehensive. In the
NHA-2000, the private sector data (PvtHE) comprise four groups of
stakeholders: enterprises purchasing medical care as part of the
remuneration package offered to their employees or because of a legal
mandate to do so, non-profit institutions serving mainly households
(NPISH), non government organisations (NGO), and the households
themselves. The diversity of the legal, institutional and behavioural
arrangements applicable to these four groups in each country and across
the spectrum of countries is large. Illustrations include legal or
contractual obligation by size of enterprise, nature of productive activity
or regulatory criteria. NPISH and NGO may be religious institutions and
charities, advocacy groups concerned with specific diseases or causes of
functional disability, and self-help associations. Direct purchase of
insurance by better-off segments of society and the use of payment-inkind or under-the-table payments, direct purchases of medicines etc., are
not easily traceable unless good household surveys are available.
The most sizeable component of private expenditure in middle- and
low-income countries is direct out-of-pocket spending (OOPS). It is often
obtained as a residual of private consumption on medical goods and
services net of private insurance. The United Nations National Accounts
Statistics 1995 provides for 45 countries an estimate of private
consumption on medical care for the period up to 1995. The health
expenditure to total expenditure ratio of the household survey has been
used to provide the appropriate multiplier to apply to total private
consumption for 31 countries. The estimates have been projected forward
to 1997 assuming a stable consumption pattern between 1995 and 1997.
Total private expenditure provides a control variable in four cases out of
five. To prevent double counting, government (social security or other)
transfers to households for medical care benefits (THH) and premiums
paid for private insurance or for prepaid health protection programmes
have to be deducted from private consumption on health (PCH). The
outlays of non-profit institutions or NGO when these benefits are not
separated from the household should also be deducted.
In a number of institutional settings households pay for medical
goods and services for which they are subsequently reimbursed. These
transfers, can be obtained up to 1995 from the UN National Accounts and
from consistent national sources. The 1997 level was projected assuming
a stable pattern since the mid-1990s. The mandated provision of medical
benefits by employers needs to be added to occupational health services
(treated under SNA rules as intermediate, not as final consumption). In
the NHA-2000 financing matrix, external resources are included as public
or as private spending; a supplementary set of detailed financing flows
records external resources as a specific rest-of-the-world transfer.
The NHA-2000 template
A selection of variables for which the NHA-2000 country segments
attempts to collate time series is presented in Tables 2 & 3. It illustrates
the complexity of operating with several data sources whose concepts and
definitions are not necessarily homogeneous. Rows 64 and 68 are
supplied by the IMF, rows 74 to 81 and 87 by the OECD and by the UN
National Accounts, and rows 86, 88, 89, 90 by OECD Health data.
Differences between consolidated general government outlays and
total government outlays are small except in 1997, an estimate subject to
a revision to be released later this year. Row 73 has been made equal to
row 86, the gap being outlays by communes, which in the country
concerned is funded by a combination of block grant intra-government
transfer between central and local governments, and local taxation. Row
73 has been made equal to row 86. In most of the 191 countries, row 81 is
equal to row 73. The reclassification of statistical data from SNA 68 to
SNA 93 introduces minor changes by lowering the levels shown (about 1
percent for those countries not yet reporting according to SNA93 rules).
Table 2. Measured expenditure on health in the country segments
(millions of NCU)
64
65
66
67
68
69
73
74
75
Consolidated Central Government Expend.
State, regional, provincial expenditure
Local government expenditure
Territorial Government Expenditure
Social insurance expenditure
Extra-budget/autonomous funds
Consolidated General Government Outlays
Government consumption
Compensation of employees
77
78
79
80
Subsidies to medical producers
Transfers to households
Investment
Capital transfers
1993
6211
1994
5935
1995
6242
1996
7017
1997
7426
5680
5489
5709
6489
6913
31262 30605 32136 34038 35195
24511 24177 25543 26865 27163
19619 19549 20550 21594 23900
5457
1180
5029
1069
5479
1170
5903
1228
6529
1471
81
86
87
88
89
90
91
93
97
98
99
Total Government Outlays
Public Expenditure on Health (=73)
Private consumption of medical care
Private insurance & other prepaid schemes
Out-of-pocket expenditure on health
Non-profit institution consumption (NGO)
Mandated entreprise health services
Other privately funded health care
Private investment
Private Expenditure on Health
Total Expenditure on Health (=86+98)
31262
31262
13998
1045
8170
1211
30605
30605
14376
1013
8269
1232
32136
32136
15420
1039
8717
1328
34038
34038
16598
1065
9039
1357
35195
35195
17400
1144
9211
1420
10426 10514 11084 11461 11775
41688 41119 43220 45499 46970
Notes:
1) The upper tier of rows corresponds to an institutional classification in a public
finance approach.
The second tier of rows corresponds to the economic classification in a National
Accounts approach.
The lower tier corresponds to an ad hoc economic classification of the spending
categories 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 reference
sources used do not publish the outlays by the communes, the largest public spending
agent. 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)
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
General Taxation, General Government
General Taxation, Central Government
General Taxation, States/Regions/Province
General Taxation, Local
Extra-budgetary funds
Social security
Employer contributions
Employee contributions
Government transfers to Social Security
Trust funds
Intra-government transfers from Cent.Govt.
Intra-government transfers from State Govt.
Intra-government transfers from Local Govt.
General .govt. transfers to NGO/NPISH
General Govt. transfers to households
Of which Social Security transfers to Households
External resources
International agencies
Bilateral assistance to Government
Bilateral flows to NGO
Bilateral, direct operations
Private to General Government
Private to NGO
Private, direct interventions
1993 1994 1995 1996 1997
25582 25116 26427 27549 28282
6211 5935 6242 7017
5680
612
5489
626
5709
607
5457
5029
5461
6489
6913
125
126
127
128
129
130
131
132
133
135
141
Enterprises
Mandated delivery
Direct delivery
Public corporations
NGO's & non-profit institutions
Private insurance & other prepaid schemes
For-profit
Non-profit
Net out-of-pocket expenditure
Private funds n.e.c.
Tax Expenditure for Health Care
1211
861
1232
832
1328
853
1357
866
940
2223
619
3486
639
3645
647
3932
701
4140
766
Notes:
An ad-hoc classification derived from a tally of frequently encountered financing
agents in the WHO area.
Source:
WHO, NHA-2000 data files.
An allowance has been made in several country segments for
private investment in health facilities (PIH) about which virtually no
direct information is gathered. Private investment is known to have
grown considerably during the 1990’s in many Latin American and in
some Asian countries. By and large, many statisticians do not report
private investment in health facilities because of inherent recording
problems and to avoid a risk of double counting (an allowance for capital
usage and depreciation is meant to be included in the fees perceived by
private producers for imaging, laboratory tests, hospitalisations, …).
Double counting is less of an issue when current and capital expenditure
may be separated and depreciation is deducted from gross receipts. The
significant amount of investment in health facilities observed in middleand low-income countries equipped with NHA confirms the importance
of adequate monitoring of assets and asset build-up. The notional value
attached to it for 1997 varies between 2% and 10% of direct households
payments.
When private consumption of medical goods and services (PCH) is
not accessible, OOPS has typically been calculated on the basis of
household budget surveys or level of living surveys. Out of pocket
spending comprises discretionary purchases of medical and paramedical
goods and services by patients and their families, as well as co-payments
in public schemes providing benefits-in-kind with some form of costsharing or user charge. The 'medical' care ratio obtained (including, where
relevant, “traditional” healing services) has been applied to the National
Accounts private consumption aggregate (PC). As household surveys are
only conducted intermittently, time series for OOPS have been derived
through statistical techniques and, when no household survey are
available, estimates have been necessary. Though inspired by the same
general approach across the spectrum of countries, household surveys
differ in the questions asked; they nevertheless provide acceptable
approximations or cross-checks of each PCH.
The private-public mix exhibited in the second and third columns
of annex table 8 in the World Health Report 2000 is also affected by
shifting statistical conventions, such as those resulting from the gradual
adaptation of SNA93 replacing SNA68 rules. In the original National
Accounts’ functional breakdown, expenditure was classified according to
its object (such as medical care) irrespective of the underlying financial
arrangements, at least within the main two sectors of the economy:
government and private. SNA-93 abolished the principle with respect to
goods and services co-financed by social security or another public
source and by households and private insurance (A System of National
Accounts, pp 194-6). While the NHA-2000 applies a similar divide expost, the heterogeneity of the data sources led to an effective allocation of
the social subsidy to the public share whenever the underlying
information was based on the new National Accounts, a more haphazard
one when the underlying information was based on the former National
Accounts (still the majority of countries in the first half of 2000).
A sizeable number of financing flows had to be estimated from
crude expenditure data. Conceptually, this procedure entails a risk of
double counting, as well as, paradoxically, a risk of not being
comprehensive. Examples cited above relate to central government
outlays by function. It is often the case that only the disbursements of
Ministries of Health are included at the exclusion of intervention by other
ministries whose primary intent is also the enhancement of the health
status of the population. Conversely, in many countries, the records
aggregate the co-payments received (a flow originating directly from the
households) with the share of general government revenue attributed to
the Ministry of Health, usually transferred from the Ministry of Finance.
A risk of double counting exists when the household surveys on which
the out-of-pocket outlays rest also include the value of co-payments. In
the initial development stages of an accounting system, involuntary
double counts are unavoidable. Most of household surveys do not register
the institution receiving the co-payments and often they do not include
reimbursements. In one country, the standards used by two state agencies
providing macro-economic data lead to a difference up to a factor of 6
when measuring private health consumption, that is 3% of GDP; for
NHA-2000 purposes, the arbitrage was made on a plausibility criterion.
Non-financial variables
In a full-fledged information system (see Chart 1 above), the
financial monitoring has to be complemented with several types of
quantitative monitoring instruments. They include:
• a needs assessment (mortality, morbidity and dysfunction of
population segments);
• resource and production information (amount of services and type of
functions covered, health services utilisation);
• a social and economic context (prices, production, income and
amenity distribution);
• a geographic and demographic distribution;
• a technology assessment (geared to better appreciate the
appropriateness and cost-effectiveness of medical procedures and
medical equipment);
• quality assurance programmes (focused on value for money at bedside
or regarding specific classes of interventions in the delivery and
financing of health care).
The underlying data for the WHR 2000
For several countries, the public expenditure measures underlying
the World Health Report-2000 - Annex table 8 may include an over-count
or undercount. For example no systematic evidence was available on
whether state/provincial/regional and local authorities spend money they
raise through taxes or whether they access their resources through
transfers from the central-federal authorities. Metadata accompanying the
country segments indicate the assumptions made. Many statistical
yearbooks, ministry of health and other official reports accessed fail to
provide information on the contents of the series they publish.
For total private consumption, aggregate national accounts should
be 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 surveys
supplied the basis for 31 countries (see Chart 5). Living Standards and
household budget surveys are frequently less comprehensive. For
example some of them exclude, imputed rent, which is a sizeable
component of private consumption. In many middle income countries up
to three quarters (even more) of dwellings are owner-occupied,
generating an undercount when using household and level of living
surveys as the base source. Chart 4 summarises the main sources tapped
to construct the NHA-2000.
Chart 5. Sources of information for the NHA-2000
(# of countries, State of the play end-March 2000)
W H O N H A e s tim a te s
180
16
17
H o u s e h o ld s u rv e y s
28
31
C o u n try s ta tis tic s
150
Number of countries
27
U N N a tio n a l A c c o u n ts
120
IM F -G F S
73
45
90
O th e r in te r n a tio n a l
re p o rts : W B , U N D P ,
U N IC E F , IL O
O E C D H e a lth D a ta
60
50
71
30
24
0
P u b lic E x p e n d itu re o n
H e a lth
P riv a te E x p e n d itu re o n
H e a lth
Source: WHO, NHA data files.
The NHA-2000 template provides a series of summary ratios. The
denominators of these ratios are macro-economic aggregates and
population. Both are at the root of much of the discrepancies found in the
international comparisons from different sources. The entries underlying
the ratios in annex table 8 of the World Health Report 2000 are found in
table A-1 at the end of this discussion paper. The United Nations, the
World Bank and the International Monetary Fund still release different
estimates of Gross Domestic Product (GDP). The IMF GDP, readily
available for all years, has been retained in the NHA2000 as the
denominator for the summary ratios. When International Financial
Statistics does not release national accounting aggregates (for countries
not member of IMF or countries that, for reason of war, civil strife,
breakdown of governance discontinued the supply of information to
IMF), other sources have been tapped. As part of the WHO countries
begin to report on the basis of SNA93 and other countries do not, a
transitory element of non-comparability has emerged.
Public Expenditure on Health (PHE) is shown as a share of total
General Government Expenditure (GGE). International Financial
Statistics releases estimates of central government disbursements (CGD).
The CGD series often equal the GGE series as intra-governmental
transfer payments or block grants cover or nearly so the outlays of the
regional/state/provincial and local/municipal authorities. The UN
National Accounts supplies an estimate of total current disbursements and
net savings for 73 countries through 1995. These have been extrapolated
through 1997 (for the OECD countries, the estimates are accessible in
OECD Health Data 99, reproducing series from OECD National
Accounts. When institutional data suggest that GGE is greater than CGD
and no direct information is readily available, ad hoc statistical techniques
are used to inflate the accessible CGD estimates to a plausible GGE level.
The population estimates are those produced by the United
Nations. The data in the annex table are reported in millions of national
currency units, except the series on spot exchange rates expressed in
national currency units, and population data, reported in thousand
persons.
An attempt has been made to use as much as possible the same
methodology and homogeneous sources for all WHO countries. Only the
primary or principal sources of data are listed in the meta-data files. As
they fill over a hundred pages equivalent, only a gross summary of the
main sources is supplied in chart 5.
IV. A tentative State-of-the-world message, 1997
A rigorous analysis of private and public expenditure on health
requires orders of magnitude. The contents of the exercise initiated by
WHO differs from previous studies first on comprehensiveness grounds:
a measure is achieved for all 191 Member countries. Second, there has
been a wider canvassing of the sources of funds (including the latent
ambition to survey the share of external resources). Third, there is a
unique temporal dimension (trends in the main aggregates are traced for a
period of one to three decades).
The first results of the exercise exhibit a level of expenditure that
is, on average, higher than the levels or ratios previously quantified. The
correlation between wealth and health frequently documented for highincome countries is strong also for medium and low-income countries.
The sizeable dispersion within the WHO regions invites an explanation
about the nature of these gaps. An expansion of NHA in the direction of
new distribution matrices on the expenditure side as well as on the
income side appears to be a necessary extension of the conventional
approaches to NHA. A distributional analysis has been developed in the
context of the World Health Report-2000 which could not be integrated
in the NHA-2000 but the interface between the two is strong (see Xu K et
al, 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 standard
indicators. The lowest total expenditure on health; calculated as shares in
GDP (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, reflecting
differences not only in income and wealth levels but also in sociopolitical organisation. These are more directly observable in the
THE/GDP and PHE/GDP ratios. Europe and the Pacific region exhibit
higher shares of public financing.
Chart 6. Measured levels of total expenditure on health, 1997
Total expenditure on health
per capita, % of GDP
Total ex penditure on health
per c apita, US dollars at X-rate
WORLD
W ORLD
WPR
W PR
SEA R
SEA R
EUR
EUR
EMR
EMR
A MR
A MR
A FR
A FR
0
0
5
10
500
1000
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 construction
of NHA and countries where that prospect has seemingly not yet been
evoked. Access to institutional and to public finance variables has been
haphazard at times. Nepal with an estimated US$ 8 per capita at exchange
rate and Thailand with an estimated $ 13 per head contribute to a regional
average of $48 per capita. The average public and private expenditure
shares (external resources included) are 41 and 59% respectively. The
role of private insurance and mandated employer schemes appear to be
modest in the region, suggesting that out-of-pocket spending plays a
relatively important role. The level of total expenditure on health in
Indonesia is lower than expected because no household survey providing
a plausible level of out of pocket health expenditure has been unearthed
(Table 5).
Table 5. Expenditure on health in the SEAR area, 1997.
THE OOPS
as % As % of
THE
of
GDP
Bangladesh
4.9
54.0
Bhutan
7.0
53.8 Indonesia
DR Korea
3.0
16.4 Maldives
India
5.2
84.6 Myanmar
Source: WHO NHA-2000 data files.
THE
as % of
GDP
1.7
8.2
2.6
OOPS
As % of
THE
47.4 Nepal
36.1 Sri Lanka
87.4 Thailand
THE
as % of
GDP
3.7
3.0
5.7
OOPS
as %of
THE
74.0
51.8
65.4
The East Mediterranean
For the East Mediterranean, the levels shown below reflect the
documentation readily accessible at the time of the World Health Report
2000 was drafted. It may underreport somewhat on average expenditure
levels according to new estimates obtained by intergovernmental agencies
operating in the EMR area. Sizeable expenditure programmes are notably
operated by the armed forces, or companies, public and non profit
institutions catering to refugees and displaced populations, whose records
are not readily accessible. Also, in some countries, the expenditure
programmes reported related to the resident population, the demographic
data including on the contrary the non resident population. Pending a
comparison of notes with those of an on-going NHA estimation exercise
in eight countries, the estimates collected suggest that the average
resident of that area spent US$ 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.
THE
as % of
GDP
Afghanistan
3.2
4.4
Bahrain
Cyprus
5.9
2.8
Djibouti
Egypt
3.7
Iran
4.4
Iraq
4.2
5.2
Jordan
3.3
Kuwait
Lebanon
10.1
Libyan Arab J.
3.4
Source: WHO NHA-2000 data files.
OOPS
as % of
THE
59.4 Morocco
37.7 Oman
63.1 Pakistan
27.1 Qatar
73.1 Saudi Arabia
57.2 Somalia
41.1 Sudan
32.8 Syria
12.6 Tunisia
53.8 U A Emirates
45.8 Yemen
THE
As % of
GDP
5.3
3.9
4.0
6.5
3.5
1.5
3.5
2.5
5.4
4.2
3.4
OOPS
as % of
THE
59.3
35.9
77.1
42.5
6.3
28.6
79.1
66.4
53.0
3.8
62.1
The Pacific
For the Pacific, the estimation process in a region that comprises
the world’s most populated nation and a number of island-nations that do
not report much about themselves, has constituted a true challenge. Low
Chinese expenditure reported translates in part the inaccessibility to an
important source of financing at the time the World Health Report 2000
went to print, the total and the public share of total expenditure are thus
expected 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 outlays
are classified as public (table 7) and one third as private.
Table 7. Expenditure on health in the WPR area, 1997.
PHE
THE
as % of as %
GDP of THE
Australia
7.8
72.0 Malaysia
Brunei Darus
5.4
40.6 Marshall I.
Cambodia
7.2
9.4 Micronesia
China
2.7
24.9 Mongolia
Cook Islands
7.4
76.7 Nauru
Fiji
4.2
69.2 N Zealand
Japan
7.1
80.2 Niue
Kiribati
9.9
99.3 Palau
Laos P.D.R.
3.6
62.7 Papua N G
Source: WHO NHA-2000 data files.
PHE
THE
PHE
THE
As % of as %
as % of as %
GDP of THE
GDP of THE
2.4
57.6 Philippines
3.4
48.5
9.0
74.3 Rep of Korea
6.7
37.8
7.4
92.3 Samoa
3.8
88.9
4.3
82.0 Singapore
3.1
35.8
5.0
99.0 Solomon Isl.
3.2
99.3
8.2
71.7 Tonga
7.8
46.0
5.7
87.6 Tuvalu
5.9
91.5
6.0
90.0 Vanuatu
3.3
64.3
3.1
77.6 Vietnam
4.8
20.0
Sub-Saharan Africa
Annual public expenditure by function could not be obtained for all
countries of Sub-Saharan Africa. Readily accessible information suggests
that only a handful of countries operate social security schemes. In some
countries the Ministry of Health has only a planning and evaluation
function, a Health Board is charged with the bulk of the implementation
function. It has been difficult to obtain information on mandated
corporate and private insurance schemes, such as those operating in
Zimbabwe. External resources (grants and loans to governments, but also
to NGO) play a sizeable role in a majority of the region countries but
information on them is scarce at best. Even the intergovernmental and
international aid agencies do not report this information in a consistent
manner. A careful meshing of information collated by teams reporting on
preliminary NHA should yield a genuine improvement of the estimates
prepared.
Expenditure on health is correlated to real incomes. Imperfection of
the data notwithstanding, the greater poverty of Africa is reflected in a
spending estimate of US$ 45 per person with important inter-country
variations: an estimated $ 4 per capita in Ethiopia and an estimated $ 424
per capita in the Seychelles. The PHE share reported in table 8 is likely to
overestimate in most countries the real state (except in the Democratic
Republic of Congo, an implausible figure even for a country beset by
public strife) because of the dearth of household expenditure surveys.
Table 8. Expenditure on health in the AFR area, 1997.
PHE
THE
as % of
as % of
THE
GDP
Algeria
3.1
50.8 Lesotho
3.6
59.6 Liberia
Angola
3.0
47.2 Madagascar
Benin
4.2
61.0 Malawi
Botswana
4.2
30.9 Mali
Burkina Faso
35.6 Mauritania
Burundi
4.0
5.0
20.1 Mauritius
Cameroon
2.8
63.8 Mozambique
Cape Verde
2.9
68.9 Namibia
Central African Rep
4.3
79.3 Niger
Chad
4.5
68.2 Nigeria
Comoros
Congo
5.0
36.6 Rwanda
3.2
38.4 Sao Tome & Principe
Côte d'Ivoire
3.7
0.9 Senegal
Dem Rep of Congo
3.5
57.2 Seychelles
Equatorial Guinea
Eritrea
3.4
55.7 Sierra Leone
3.8
36.2 South Africa
Ethiopia
3.0
66.5 Swaziland
Gabon
4.5
45.9 Togo
Gambia
3.1
47.0 Uganda
Ghana
3.5
57.2 United R. Tanzania
Guinea
5.7
75.6 Zambia
Guinea-Bissau
4.6
64.1 Zimbabwe
Kenya
Source: WHO, NHA-2000 data files.
THE
As % of
GDP
5.6
3.0
2.1
5.8
4.2
5.6
3.5
5.8
7.5
3.5
3.1
4.3
4.0
4.5
5.9
4.9
7.1
3.4
2.8
4.1
4.8
5.9
6.2
PHE
as % of
THE
72.6
66.7
53.8
59.2
45.8
30.3
52.9
71.3
51.7
46.6
28.2
50.1
75.0
55.7
76.2
9.7
46.5
72.3
42.8
35.1
60.7
38.2
43.4
A Latin American Perspective: Social Financing
The ratios presented seldom originate from a single source, notably
the distinction between social security and other public funds.
Considerable enhancements of the ratios should also be brought by a
more recurrent reporting of mandated employer schemes and private
insurance schemes. AMRO and the World Bank have released ratios of
Total and of Public Expenditure on Health to GDP, in the absence of
levels expressed in millions of national currency units, these could not be
compared with the levels and trends obtained through the NHA-2000
process. A reconciliation of differences between the two sets of ratios
could not be worked out before the World Health Report 2000 went to
print. The Americas are reckoned to have spent US$ 407 per capita with
naturally large disparities between the USA: an estimated $ 4,187 per
person, and Haiti: an estimated $ 18 per person. The rapid increase of the
private provision of health services accentuates a downward pressure to
spend publicly. On average, the Social Security share in the measured
public funding of health care reaches almost the half mark (Table 9).
Where tax funded health expenditure is given as 100, the indication is that
there is no nation-wide social insurance but not that all resources are taxbased; external resources contribute in several countries to the funding of
the health system, non-tax revenue (profits of state-owned firms) also.
Table 9. Expenditure on health in the AMR area, 1997.
TXFHE SSHE
THE
TXFHE SSHE
THE
as % of as % of as % of
as % of as % of as % of
PHE
PHE
GDP
PHE
PHE
GDP
6.4
100
… Guyana
5.1
100
…
Antigua & B
4.6
100
…
Argentina
8.2
39.6
60.4 Haiti
5.9
100
… Honduras
7.5
74.6
25.5
Bahamas
7.3
100
… Jamaica
6.0
100
…
Barbados
4.7
100
… Mexico
Belize
5.6
26.4
73.6
8.0
80.1
20.0
Bolivia
5.8
42.7
57.3 Nicaragua
6.5
100
… Panama
Brazil
7.5
44.5
55.5
5.6
49.8
50.2
Canada
8.6
98.9
1.1 Paraguay
Chile
6.1
24.0
76.0 Peru
5.6
44.2
55.8
6.0
100
…
Colombia
9.3
62.5
37.5 S Kitts & Nevis
4.0
100
…
Costa Rica
8.7
16.2
83.8 Saint Lucia
6.3
100
… StVincent & G.
5.9
100
…
Cuba
6.0
100
… Suriname
7.6
100
…
Dominica
4.9
73.0
27.0 Trinidad & Tob
4.3
100
…
Dominican R
Ecuador
4.6
59.4
40.6 United States
13.7
57.9
42.1
El Salvador
7.0
48.5
51.5 Uruguay
10.0
89.0
11.0
6.3
100
… Venezuela
Grenada
3.9
66.6
33.4
2.4
53.7
46.3
Guatemala
Source: WHO, NHA-2000 data files.
Europe & Central Asia after the Shemashko era
Long time series have proved to be elusive in countries that made
the transition from centrally planned system to a market economy and
little quantitative evidence could be used in the comparative framework
retained. The structural reforms under way have not generated yet in the
area a comprehensive and consistent information system, even in
countries with a longer tradition in reporting. Gaps in reporting of
selected schemes have been a cause of under-reporting. The average
outlay per capita, including the richer OECD-Europe and the Asian
Republics of the former Soviet Union, stands at US$ 920 per capita. In
Tajikistan, it is estimated to have been $ 11 and in Switzerland $ 3,564.
The temporary demise of public responsibility in a few countries overrepresents the permanent role of households in the health financing shares
shown in Table 10.
Table 10. Expenditure on health in the EUR area, 1997.
PHE
THE
as % of
as % of
THE
GDP
Albania
3.5
77.7 Lithuania
Andorra
7.5
86.7 Luxembourg
Armenia
7.9
41.5 Malta
Austria
9.0
67.3 Monaco
Azerbaijan
2.9
79.3 Netherlands
Belarus
5.9
82.6 Norway
Belgium
8.0
83.2 Poland
Bosnia &Herzegovina
7.6
92.6 Portugal
Bulgaria
4.8
81.9 Rep of Macedonia
Croatia
8.1
79.7 Rep of Moldova
Czech Republic
7.6
92.3 Romania
Denmark
8.0
84.3 Russian Federation
Estonia
6.4
78.9 San Marino
Finland
7.6
73.7 Slovakia
France
9.8
76.9 Slovenia
Georgia
4.4
8.6 Spain
Germany
10.5
77.5 Sweden
Greece
8.0
65.8 Switzerland
Hungary
5.3
84.9 Tajikistan
Iceland
7.9
83.8 Turkey
Ireland
6.2
77.3 Turkmenistan
Israel
8.2
75.0 Ukraine
Italy
9.3
57.1 United Kingdom
Kazakhstan
3.9
63.6 Uzbekistan
Kyrgyzstan
4.0
69.6 Yugoslavia
Latvia
6.1
61.0 OECD – Europe
Note: OECD-Europe is an arithmetic average of 22 countries.
Source: WHO, NHA-2000 data files.
PHE
THE
as % of
as % of
THE
GDP
6.4
75.7
6.6
91.4
6.3
58.9
8.0
62.5
8.8
70.7
6.5
82.0
6.2
71.6
8.2
57.5
6.1
84.8
8.3
75.1
3.8
60.3
5.4
76.8
7.5
73.5
8.6
81.8
9.4
80.8
8.0
70.6
9.2
78.0
10.1
69.3
7.6
87.8
3.9
74.0
4.3
86.0
5.6
75.5
5.8
96.9
4.2
80.9
4.5
64.8
7.8
76.0
Wealth and health
The strong correlation between disposable income and expenditure
on health, frequently demonstrated in the high-income countries, appears
to be a structural feature in the world as a whole. The association between
health expenditure and wealth in the 191 WHO countries is strong,
virtually linear when plotting total expenditure on health goods and
services (Chart 7 logarithmic scale, R2= 0.978). Values are shown in
national currency units (NCU) both for GDP per capita and total health
expenditure per capita. Because NCU are not “comparable” with standard
of living equivalent indices are, Chart 7 expresses only a relationship
between the two variables for each country, not the relative position that
each country would have in a measured based on universal currency.
Chart 7 does not have a normative or comparative value. Each dot
corresponds to measured per capita income and per capita health care
consumption, in that country’s own currency. Typically, a weak currency
is represented by large figures; some rich countries have, however, a large
figure 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. The
average per capita GDP mask, however, wide variations in the income
distribution of countries. Given large disparities between and inside
WHO regions, the implications of that correlation have to be considered
in greater depth.
Chart 7. Per capita expenditure on health and income flows, 1997.
(in National Currency Units)
100,000,000
10,000,000
THE per capita, NCU
1,000,000
100,000
10,000
1,000
100
10
1
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
Source: WHO, NHA data files.
Public commitment towards health goods and services, expressed
in Chart 8 for the same 191 countries, appears to be nearly as strongly
tied to income per capita as total expenditure is (logarithmic scale
R2=0.984). As for chart 7, this relationship does not qualify the position
of each plot. Because the logarithmic scale tends to compact the
dispersions around the plot, small variations in the association hide rather
wider real dispersions. Inequalities in risk pooling are not limited to
cross-national inequalities in wealth. The role and extent of this
commitment has been changing in many countries in the recent past and
is not as easy to capture as a string of numbers suggests. Specifically,
measured public expenditure on health hovers around half of measured
total expenditure on health. By region, the variation extends from 41% in
South East Asia to 74% in Europe and Central Asia. The world global
average, in its end-March 2000 calculation status, is 59.2% of total health
expenditure. Based on the countries for which data have been collated,
social security accounts for nearly a quarter of THE, and around half of
PHE. Because only part of the processes is transparent, the levels and
ratios provide a questionable picture for a few countries.
Chart 8. Public commitment towards health, 1997.
(in National Currency Units)
100,000,000
10,000,000
PHE per capita, NCU
1,000,000
100,000
10,000
1,000
100
10
1
1
10
100
1,000
10,000
100,000
1,000,000
10,000,000
100,000,000 1,000,000,000
GDPper capita, NCU
Source: WHO, NHA data files.
Private spending ratios are not immune from myopia. The
registration of private payments is one explanation. When compulsory
social insurance are channelling resources towards private practice, the
flows should remain nonetheless classified as publicly financed. In the
NHA-2000, the direct payments by the users of the system, labelled outof-pocket (OOPS) for convenience, have been estimated deducting from
the 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. This
chart includes two values with a very low estimate for OOPS. The
measured level of private spending encompasses more restrictions as not
all countries develop household surveys nor private providers expenditure
for health (Chart 9).
Chart 9. Household ability to pay for health: a close link to national
income, 1997
(in National Currency Units)
10,000,000
1,000,000
OOPS per capita, NCU
100,000
10,000
1,000
100
10
1
1
10
100
1,000
10,000
100,000
1,000,000
10,000,000
100,000,000
1,000,000,000
GDP pe r capita, NCU
Source: WHO, NHA data file.
Not all countries supply routinely enough information to allow a
comprehensive measure of direct household payment, often estimated
through a series of deductions from a private expenditure aggregate. In
countries with sizeable expenditure and NHA breakdowns, such as the
United States, OOPS are a relatively low share of THE because the
deductions could be made. Elsewhere, this was only crudely attainable.
The emerging picture is thus not fully transparent. A high private
expenditure share may not be a predictor of a sizeable out-of-pocket share
because of an extensive network of private insurers and managed care
schemes. Conversely a country with a medium-sized private sector may
turn out in a map or in a table to exhibit an oversized out-of-pocket
expenditure due to non-accountability of private insurance, mandated
employer schemes, and NGOs.
A map illustrates some strengths and weaknesses of the NHA-2000
exercise. The orders of magnitudes it exhibits relate to more variables and
to more countries than any previous attempt at measurement that precede
it. While important revisions are a certainty, a consolidation of the orders
of magnitude for a large number of countries is also likely.
An Unequal Health Care Burden of Households Around the World, 1997
Out-of-Pocket Outlays on Health as a Share of Measured Total Private Consumption
OOPS as % Pvt Cons Exp
0 - 1.59
1.60 - 2.89
2.90- 4.10
4.11 - 6.42
6.43 - 10.00
The boundaries and names shown and the designations used on this map do not imply the expr ession of any
opinion whatsoever on the part of the World Health Or ganization concerning the lega l status of any country,
te rritory, city or area or of its authorities, or concer ning 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 had
developed the backbone of a domestic NHA. The number has timidly
grown over time but, until the mid-1990s, the NHA developers have
mainly been confined to the high income strata of countries, contributing
-- without intent to do so -- to widening disparities across nations: when
applied to decision-making the countries with the highest access to
resources have the potential to allocate these resources more rationally on
account of greater transparency. The intelligence gap can, however, be
closed rapidly.
That gap is actually being reduced. Initiatives taken notably by the
United States Agency for International Development (USAID), the World
Bank, two of WHO's regional offices, the Interamerican Development
Bank (IADB), several International Development agencies of the Nordic
countries of Europe have recently contributed two dozen National Health
Expenditure 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, an
important consolidation effort has been launched. These NHA are,
however, not comparable with one another. The non-comparability
shortcoming diminishes the usefulness of NHA for policy analysis, as the
impact of alternative structures and of reforms undertaken by other
countries cannot readily be assessed. When national or regional
experiments are comparable, they act as a kind of real scale laboratories
on behavioural parameters.
Chart 10. Coverage of national health accounts by region
35%
30%
25%
20%
15%
10%
5%
0%
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)
Source: WHO, NHA-2000 data files.
The manufacturing of NHA at the centre (by WHO) has a meaning
only if the segments are repatriated in the appropriate national capitals.
Only at that level is there a guaranteed enrichment as their authorities
encounter policy challenges for which they have to produce monitoring
instruments. International organisations at best get involved in fragments
of the policy spectrum faced by a country.
By the nature of the tool, explicit or implicit NHA accompany
everywhere the reform process. An NHA thrives only when it is policy
relevant, thus only when its developmental process is tied to decisionmaking.
The country templates have deliberately been made simple so as to
be applicable to nearly 200 different environments, to be achievable by a
very small team within a year. Enlargement will be required and made
more rigorous as the burden of reconstruction and of maintenance passes
to ministries of health, ministries of planning and central statistical
institutes. Reconstruction at national level is compatible with a
maintenance and updating function of the variables contained in NHA2000 in order to ensure continuity.
The NHA-2000 exercise has made evident the dearth of statistical
information of all kinds in most WHO countries. The NHA-2000
framework may serve as a focal point to reorganise the observation and
quantitative analysis apparatus of those Member countries which will
want to immediately get a better grasp on the performance of their health
systems. The active preparation of producer’s guidelines (inspired from
the OECD manual) will facilitate the implementation of that target where
it is adopted.
Several of the conclusions derived from the first world NHA
exercise are not new: the fortune of interventions on health is closely tied
to the wealth of nations, and the wealth of nations depends on a better
health status of the workforce, of mothers and children, of the elderly.
The quantification of the resources required constitutes nonetheless a
prospective tool for the planners. Every country faces a distinct challenge.
Since its neighbours face some of the same hurdles policy makers may
learn from the mistakes of countries that have preceded their own country
on the path of reform. They can also learn from the success story of some
of their neighbours.
The implementation of reforms in more countries as well as the
development of a monitoring tool may, paradoxically, lead both to
statistical shortcuts as well as to greater analytical complexity.
The measurement of health expenditure remains an undeveloped
task. More detailed and comprehensive data need to be mined. More
relationships between the delivery and financing of health and its
economic environment have to be explored. Every country needs more
and better financial data to improve the health planing and assessment
processes. The WHO effort contributes to this aim, though the indicators
provided in the World Health Report-2000 are only rudimentary.
Imperfect information facilitates, comparative analyses and the promotion
of greater transparency of health financing across the world more than the
dearth of information. The supply of updated NHA is a public good. The
WHO contribution is, however, merely a means to incite local NHA
efforts, or an instrument that precede them.
V. Bibliography
Berman P (1997). National Health Accounts in Developing Countries:
Appropriate Methods and Recent Applications, Health Economics, Vol
6:11-30.
Hernández P, Poullier J-P, Brugiatti MA (2000). Cuentas Nacionales
de Salud. Manual del usuario. Opciones e instrumentos para la mejora del
sistema de salud en Panamá. MINSA - BID - CSS - Universidad Latina
de 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. Washington
D.C., IMF.
OECD. Economic and development review monographs. Several
countries. 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 its
accounts]. In: Edith Archambault and Oleg Archipoff (eds). La
comptabilité 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
ST/ESA/STAT/SER.M/84. UN. New York, 2000.
to
purpose.
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).
Afghanistan
Albania
Algeria
Andorra
Angola
Antigua
&
Barbuda
Argentina
Armenia
Australia
Austria
Azerbaijan
Bahamas
Bahrain
Bangladesh
Barbados
Total
Expenditure
on Health
GDP
1500
11937
74960
13380
38140
101
46872
341716
2457700
178000
1054000
1576
609
9273
38100
11600
22740
58.0
891
2664
36860
1780
15400
43.2
97472
783600
30160
125000
363
3000
148.93
57.71
146.41
22904
1.96
20893
3132
29394
66.8
11715
66.5
24090
292859
62900
798555
42624
549290
219961 2514400
451523 15352200
228
3850
105
2387
68740 1403050
318
4371
13852
26100
30700
151563
357875
114
61.2
31640
199
10238
36800
11924
68398
93648
114
43.5
37100
119
64200
199639
198700
1273200
2689600
829
640
348800
1458
1
490.85
1.34
12.2
2896.2
1
0.38
43.89
2
35671
3551
18333
8099
7642
291
583
122650
267
Public
Private
General Exchange
expenditure expenditure government
rate
on health
on health expenditure
Population
Belarus
Belgium
Belize
Benin
Bhutan
Bolivia
Bosnia
&
Herzeg
Botswana
Brazil
Brunei Darus
Bulgaria
Burkina Faso
Burundi
Cambodia
Cameroon
Canada
Cape Verde
Central African
Rep.
Chad
Chile
China
Colombia
Comoros
Congo
Cook Islands
Costa Rica
Côte d'Ivoire
Croatia
Cuba
Cyprus
Czech
Republic
Dem.
Rep.
Congo
Dem.
Rep.
Korea
Denmark
Djibouti
Dominica
Dominican
Rep
Ecuador
Egypt
El Salvador
Equator.
Guinea
Eritrea
Estonia
Ethiopia
Fiji
Finland
France
Gabon
21086208 35608000
0
694846 8712000
57
1222
37860 1249800
1015
14477
2411
41860
1342
17585
17425000
25964
10351
578000
29.6
17860
469
1423
1242
116846
27.8
20000
546
987
100
4387000
362
312450
4631
13750
2000
35.77
1.45
583.67
36.31
5.25
4.95
10127
224
5629
1945
7774
3520
741
1748
5612
864111
438
8051
825188 17103433
54310 1390200
13910
431037
647561 9025268
248300 5017400
74692
873950
1245
45101
16454
566000
452
27521
178
675580
16800
4950
60745
50020
53765
794
11344
289
28991
260
149608
37510
8960
586816
198280
20927
451
5110
7660
292000
4000
6742200
319100
74900
870000
6993600
352200
19037
177000
3.65
1.85
1.48
1676.5
583.67
352.35
2946.3
583.67
1.39
93.18
583.67
1541
163700
308
8393
11001
6362
10478
13924
30261
399
3420
27246
886900
1930687 31567300
202170 7489500
11279560 12170750
0
3812
85074
67025 1334600
11
150
196983 2260479
189913 6176200
9622
119053
1445
22952
254
4337
127699 1668800
21612
946900
50370
6141453
5633
983787
151800
5138107
163389
7013200
923356
35701313
583.67
419.3
8.29
1141
7086
14625
1244202
40043
2600
24517
8.6
151774
72913
7668
1265
89.0
117818
1212
42508
2.6
45210
117000
1954
180
165
9881
29776
530000
100
754000
2240000
34395
12663
1604
739600
437.75
583.67
1.51
232.6
583.67
6.1
1
0.51
31.7
640
2709
19
3748
14064
4484
11068
763
10301
11097000 30434200
0
1835
61400
97000
11000000
78953000
106000
47987
1535
300
20000
2.2
22610
1117800
88900
655
215065
75362
1800
25.5
4028
14000
670
13.8
6438
584100
31649
249
38500
6.6
177.72
1.96
14.27
5256
617
70.9
8097
3599273 79040013
9583
256250
6845
97428
10170
316290
1900000
2583
2545
5812
1699273
7000
4300
4358
21280000
78503
12028
73430
3998.3
3.39
6.36
598.81
11937
64731
5911
420
88.9
3232
570
90.0
35195
621739
61000
70.8
867
1003
40.0
11775
186821
30770
2589
30709
10017
1082
329600
4512800
988000
7.2
13.88
6.71
1.44
5.19
5.84
583.67
3433
1447
58218
786
5141
58472
1137
89362
2470
39
10466
160
4099
1573
130
46970
808560
91770
4713
64324
41465
3102
632880
8224900
3117400
3661208 175021601
Gambia
Georgia
Germany
Ghana
Greece
Grenada
Guatemala
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Hungary
Iceland
India
Indonesia
144
298
369000
430000
2612700
54.0
2709
153265
8865
5440
2377
4584
447500
41684
805000
10589984
286
76277
28861
7.3
301
1217
79700
200
2230309
262
75
500
2471
38504
382529
2404
6467
332
60000
81
15
3189
6798
3667200
14113400
33021800
850
107873
4379009
154600
105859
51578
61405
8461600
529949
15635500
62769500
0
27783100
0
3890629
51822
339992
19506800
00
220556
50785200
0
4946
1966000
627436
74
9163
30686
2200000
3276
21997376
4715
2544
13284
38340
587000
18046300
41559
281889
4027
1431900
1288
164
9033
3015
178877
27
160618
86069
3178954
366
2733
1595
73241
25
6300
1420
105636
2.1
41600
20850
1228600
54
151.85
20.56
7.91
1
2461
1133
94281
112
240
31891
16871
3000
737039
318350
150
26154
6860
90.0
5737
10011
200
196800
106400
5.84
789.99
9.53
32.5
2537
26890
Iran,
Islamic 12190000
Rep.
Iraq
165021
Ireland
3194
Israel
28000
Italy
181246000
Jamaica
Japan
Jordan
Kazakhstan
Kenya
Kiribati
Kuwait
Kyrgyzstan
Lao Dem. Rep.
Latvia
Lebanon
Lesotho
Liberia
Libyan Arab J.
Lithuania
Luxembourg
Madagascar
Malawi
Malaysia
Maldives
Mali
Malta
Marshall
Islands
Mauritania
Mauritius
Mexico
Micronesia,
Fed.
Monaco
Mongolia
Morocco
13280
36180000
65.9
25.6
299000
202000
1720000
25.1
1640
87665
6700
4300
798
1650
380000
34945
105000
3899784
77.6
900
272
750
70000
2028285
228000
2908900
892700 13620000
28.8
247
1069
13460
65600
906100
2165
17270
1140
38757
1579
5797
2934
12728
67500
4137070
6739
184700
700000
2709000
6690200 129826950
10.2
1.3
1.73
2050.2
273.06
1.96
6.07
1095.3
583.67
142.4
16.66
13
186.79
70.9
36.31
2909.4
1189
5121
82057
18656
10569
90
10519
7325
1136
843
7820
5981
10156
274
966192
203380
5220000
6970000
72600000
1752.9
64628
97200
2470
21000
103500000
67821
70036
724
14400
7000
163530
77746000 985900000
31.09
0.66
3.45
1703.1
21180
3658
5860
57377
7502
29000000
5778
84232
7180000 178770000
35.4
120.99
2516
126038
172
48500
18510
7.2
263
847
50000
122
659266
190
50
230
1871
35200
205781
1423
3727
212
27500
47.7
11
114
27777
10351
0.05
37.8
370
29700
77.9
1571043
72
25
270
600
3304
176748
981
2740
120
32500
33.3
3.8
2020
469655
168799
51.6
3129
8750
579000
1359
8450000
1538
750
8700
13800
270000
3113000
10700
73000
1937
350400
535
84
0.71
75.44
58.73
0.74
0.3
17.36
1260
0.58
1539.5
4.61
1
0.27
4
35.77
5090.9
16.44
2.81
11.77
583.67
0.39
1
6126
16373
28446
79.9
1732
4619
5032
2461
3143
2016
2402
5210
3705
417
14620
10067
20983
263
10436
381
58.4
Mozambique
Myanmar
Namibia
Nauru
Nepal
Netherlands
New Zealand
Nicaragua
Niger
Nigeria
Niue
Norway
Oman
Pakistan
Palau
Panama
Papua
New
Guin
Paraguay
Peru
Philippines
Poland
Portugal
Qatar
Rep of Korea
Rep
Moldova
Romania
of
Russian
Federat.
Rwanda
St
Kitts
&
Nevis
Saint Lucia
St Vincent &
Gren.
Samoa
San Marino
Sao Tome &
Prin
Saudi Arabia
Senegal
Seychelles
Sierra Leone
Singapore
Slovakia
Slovenia
Solomon
Islands
Somalia
South Africa
Spain
Sri Lanka
Sudan
Suriname
1044690 17955000
27457 1067522
1140
15115
6.5
128
10492
280582
62182
703400
8034
98247
1530
19116
31296
889600
68200 2200000
0.274
5
70993 1084788
204
6075
96533 2457400
10
166
657
8658
235
7342
745000
3457
590
6.4
2732
43972
5760
815
14598
19240
0.24
58193
130
22133
9
439
183
299690
24000
550
0.064
7760
18210
2274
715
16698
48960
0.034
12800
74.2
74400
1
219
51.4
8000000
93930
5800
70
51168
346800
45300
6291
244000
356262
20
481429
2307
772400
60
2310
2370
11544
6.24
4.61
1
58.01
1.95
1.51
9.45
583.67
21.89
1.51
7.07
0.28
40.19
1
1
1.43
18443
43936
1622
10.9
22316
15614
3761
4679
9764
103898
2
4396
2305
144047
18.1
2722
4499
1179340 20934300
9704
173689
83433 2423640
29022
469372
1461500 17859000
2157
33464
25666000 45327600
0
715
8655
420000
3849
40490
20787
840000
1240
11500000
759340
5855
42943
8235
621500
917
14166000
2877500
29700
561000
206900
7809000
16387
92510000
2191
2.66
29.47
3.28
175.31
3.64
951.29
5088
24367
71430
38693
9864
569
45731
537
178
4330
4.62
4376
9533410 24975020
0
135347 2521942
5743790
3789620
85793600
7167.9
22549
103945
31402
454768
5.79
147656
24003
44
561600
724
12023
22.5
11980
21.2
68000
216
301.53
2.7
5962
40
62.2
47.0
1542
793
40.5
30.9
21.7
15.6
452
317
1.96
1.96
150
110
24.4
98240
8000
540
1312000
200310
18.4
72200
6000
6
26040
2000
202
480000
140174
2.56
1703.1
4552.5
172
25.6
140
21170
119206
171
46500
4458
56254
272924
28.2
548620
2639800
2910
959488
142451
653900
2907300
886
16970
66400
130
4500
1596
46000
220500
28
4200
52806
40.6
42000
2862
10254
52424
0.2
181000
505000
1547
143293
29222
327400
1328400
535
3.75
583.67
5.03
981.48
1.49
33.62
159.69
3.72
19479
8772
80
4420
3427
5372
1995
404
726264 47160000
47945
683666
6210859 77896600
26756
890272
551701 16012000
20150
266530
518760
22300
4385597
12135
115493
6850
207504
25645
1825262
14621
436208
13300
100000
228800
32888000
234500
1202000
138000
7250
4.61
146.41
59
1575.7
401
8821
38760
39613
18274
27718
440
Swaziland
207
Sweden
160200
Switzerland
37500
Syrian
Arab
18473
Rep
Tajikistan
42700
Thailand
267927
Macedonia
12038
Togo
22832
Tonga
17.0
Trinidad
&
1571
Tobago
Tunisia
1127
Turkey
113516000
0
Turkmenistan
454500
Tuvalu
1180
Uganda
342065
Ukraine
5180
Un
Arab
9419
Emirates
United
46583
Kingdom
Un
Rep
224000
Tanzania
United States
1088300
Uruguay
20363
Uzbekistan
40283
Vanuatu
965
Venezuela
1734712
Vietnam
15151000
Yemen
Yugoslavia
Zambia
Zimbabwe
24998
8877
279745
6810
6045
1813130
371600
728794
150
125000
26000
6200
57.4
35200
11500
12273
1827
1089600
195000
211125
4.6
7.37
1.45
8.16
925
8856
7250
14948
560000
4675500
196000
817200
224
36552
37500
83730
10211
9782
8.0
920
5200
184197
1827
13050
9.4
651
94712
1171000
65357
228000
60.6
10412
650
31.36
50
583.67
1.26
6.25
5925
59736
2000
4284
97.7
1277
470
657
6575
840000000 295160000 774200000
0
391000
63500
2813980
1080
100
8500
120000
222065
1213626
3912
1268
40665
3330
6089
19400
1.11
151865
9211
63403
4400
1.34
1083
1.86
3.67
4233
10.8
20000
51062
2307
20901
28836000
000
10564000
20000
7531374
92480
181861
803890
45143
1440
316061
0.61
58544
4708630
136000
88000
499375
612.12
31417
8300800
188529
962140
29477
43211900
31362300
0
740636
164421
5155800
99740
502200
4125
32583
620
1125278
3033000
586100
16238
7700
345
609434
12118000
2721500
68704
318000
6485
10717659
68850000
1
9.44
72
115.87
489
11359
271772
3265
23212
177
22777
76387
9485
5755
106909
2957
15513
3122
172836
3853
290571
129.28
5.5
1314.5
11.89
16290
10628
8585
11215
1102000
36454
Notes:
1. AFR stands for the African region, AMR for the Americas, EMR for the East
Mediterranean region, EUR for Europe and part of Central Asia, SEA for South
East Asia and WPR for the West Pacific region.
2. Total Expenditure on Health is the measured level of public and private
outlays 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, International
Finance Statistics for exchange rates; United Nations for population.