Costs/Benefits Estimates for National Health Insurance

by Aug 16, 2009All Articles

A summary analysis submitted to

the Congress of SA Trade Unions

7 June 2009

1. Introduction

The South African government has made a commitment to National Health Insurance (NHI). How much would such a programme cost and what are the benefits?

An NHI is required to solve the problem of SA’s extreme inequality in health care access, as well as inefficiencies in multiple private-sector financing schemes, and tendencies towards private-sector over-treatment driven by perverse incentives. What are the cost and benefit implications, and can South African society afford an NHI?

A team consisting of Cosatu officials joined by academics from the Universities of KwaZulu-Natal (coordinated by Prof Patrick Bond), Witwatersrand and the Western Cape, the Johns Hopkins Bloomberg School of Public Health and George Washington University Public Health School, have made estimates of the fiscal costs and socio-economic benefits of NHI. Unless otherwise specified, estimates are based upon 2006 data, which provide reliable comparability (and hence any current estimates should be escalated by roughly 1/3rd in nominal terms to account for price inflation since 2006).

We first consider existing costs, followed by existing and anticipated utilisation rates. We then discuss a variety of savings associated with NHI, then the public-private services mix, then the social benefits in various categories, and finally the broader social justification for a higher level of state spending on NHI, amounting to a rise from 8.7% of GDP to 10.5%.

 

 

2. Existing costs and inequity

Current health expenditures show stark inequalities of access, whereby more than half the society’s resources are directed to just 15% of the population (Table 1). This correlates to dramatically higher private-sector health care costs/patient (Table 2). Although the growth of medical aid scheme membership was dramatic during the 1980s-90s, it has stagnated since, with no clear indication of strategies designed to draw in larger numbers of lower-income people, especially those suffering from ill health.

 

Table 1. Health Care Costs, 2006

 

Category

Public

Medical Aids AidsSchemes

Total

Total Expenditure

R57.3 bn

R59.6 bn

R116.9 bn

Total Population

40 263 686

7 127 343

47 391 029

Per person

R1 423

R8 361

R2 467

 

Table 2. Health Care Costs/Patient, 2006

 

Category

Public

Medical Aids

Hospital

R2 645

R9 349

Primary Care

R387

R725

Specialist

n.a.

R2 954

Dentist

R65

R1 004

 

3. Utilisation rates

The model estimates the percentage of South Africa’s population who would visit a health care provider if they had insurance. These estimates are based on the medical aids scheme member rates adjusted for age, gender and sickness rate using relative risk ratios (current members are on average older than the general population – and hence have higher average cost-of-services). These adjustments assume a decline in hospitalisation rates, due to improved primary and secondary care that patients would receive, compared to the present, as a result of NHI.

 

Table 3. Health Care Utilisation Rates (2006)[1]

Utilisation Rates

No Insurance at Present

Medical Scheme

Assumed NHI Utilisation

Hospital

28.32%

32.64%

25.54%

Private Doctor

20.50%

84.99%

67.90%

Specialist

7.27%

52.12%

44.00%

Dentist

8.10%

24.29%

18.51%

Public Clinic

59.28%

8.64%

66.99%

4. NHI Savings: Administration, gate-keeping, capitation

Assuming a single payer system with no duplicate coverage by the private insurance companies, what are the savings that can be expected?

 

  • For hospitals, the percentage of revenue spend on administration is assumed to be 26%, and savings are assumed to be 22% from NHI single-payer centralisation of administration (based on studies comparing the US and Canada).

 

  • For physician costs, the percent of revenue due to administration is assumed to be 30%, and savings are assumed to be 36%.

 

  • Overall administration of the NHI is assumed to be 3% of the total cost, which is similar to other countries with NHI.

 

NHI allows a reorganisation of health care delivery to reduce costs and improve quality of care.

 

  • Countries with capitation payment systems in ambulatory care spend 16% less than fee-for-service and countries with gate-keeping policies (Gerdtham et al, 1998), as health care providers are paid a contracted rate per member.

 

  • South Africa’s health consumers can be divided, roughly, into four clusters of patients with very different cost structure, with a difference between high-end users and low-end users of 33% (due to variations in prevalence rates of diseases, manifestation of these conditions, provider choice, and demographic factors), hence a percent difference of average cost of low-end users from the overall cost of 12%.[2]

 

Table 3: NHI Savings Assumptions

Proportion of Administrative Cost in Total Hospital Revenue

26%

Savings under NHI as a Percentage of Administrative costs

22%

Proportion of Administrative Cost in Total Physician Revenue

30%

Savings under NHI as a Percentage of Administrative costs

36%

Administrative Cost of NHI as % of Total Cost

3%

Savings due to Gate-keeping

16%

Savings due to Capitation in ambulatory sector

16%

Price adjustment using low-cluster group

12%

5. Additional costs and savings from NHI

At present, 14% of total health care expenditures are out-of-pocket payments by individuals, and the proposed NHI should cover all of those. Moreover, the model assumes that medical aid scheme members will receive a 15% discount on current payments. Both these concessions are political judgments which are reasonable and feasible.

 

6. The public-private delivery mix: three scenarios

The model has three options to illustrate the financing possibilities.

 

  • The first assumes all prices are based on current cost of services in the private sector (hence a higher-than-realistic cost estimate).

 

  • The second assumes all services are provided at the unit cost of public provision (hence a lower-than-realistic cost estimate).

 

  • The third is based on current public-private mix of health services provision (83% of hospitalisations and 16% of primary doctor visits occur in the public sector, as illustrated in Table 4).

 

Table 4. Public-Private Provider Mix: Percentage of Public Provision

 

Hospitals

83%

Doctor

16%

Specialists

n.a.

Dentist

65%

 

We do not know what the ultimate mix would be, because it is impossible to estimate a 2014 public-private mix. The extent of a shift from public to private providers would depend on the availability of services in the area and other costs of receiving services, such as transportation. But NHI would immediately increase funding for public services and hence improve the quality of services, which would retain patients and attract others. For our purposes in calculating estimated NHI costs, the existing ratios are retained.

7. NHI cost estimates

The annual cost of NHI – in the fifth year of phase-in, at 2006 prices – if the present public-private mix continues, is estimated at R153.8 billion. That sum includes a savings adjustment of 33% on existing costs escalated for full universal coverage. An additional R11.8 billion is anticipated in other public health care costs (HIV and AIDS, Health Facilities Infrastructure, Emergency Medical Services, Health Sciences and Training, Health Care Support, Coroner Services and Nutrition Programs), bringing total health spending to 10.48% of GDP. Table 5 outlines the core costs under the three scenarios, while Table 6 incorporates savings flagged in Table 3.

Table 5. Universal Health Care Costs Prior to Adjustments (R billion)

 

Category

using existing private sector rates

using existing public sector rates

using current public/private mix

Hospitals

113.1

32.0

45.6

Private Doctor (GP)

23.3

12.4

21.6

Specialists

61.6

32.8

61.6

Dentist

8.8

0.6

3.4

Public Clinics

1.3

1.3

1.3

Supplementary, Allied

24.7

9.8

16.6

Complementary Med.

2.2

0.9

1.5

Medicine

52.4

23.9

40.4

Administration

8.9

3.5

5.9

Out of Pocket Payments

48.1

19.0

32.1

Total Spending

344.5

136.3

230.1

 

Table 6. Adjusting Costs to Incorporate NHI Savings (R billion)

 

Category

using existing pvt sector rates

using existing public sector rates

using current public/private mix

Spending before Savings

344.5

136.3

230.1

Administrative Savings from Hospitals

6.5

n.a.

1.1

Administrative Savings from Physicians

10.1

n.a.

9.1

Gatekeeping

55.1

n.a.

36.8

Capitation

55.1

n.a.

16.5

Price diff. (low cluster)

42.5

n.a.

12.7

Total Savings

169.4

n.a.

76.2

As % of Total Spending

49%

n.a.

33%

Total Cost after Savings

175.1

136.3

153.8

 

Table 7. Additional and Total Health care Spending

 

Category

using existing private sector rates

using existing public sector rates

using current public/private mix

Other: HIV and AIDS, Health Facilities Infrastructure, Emergency Medical Services, Health Sciences and Training, Health Care Support, Coroner Services and Nutrition Programs

R11.8 bn

R11.8 bn

R11.8 bn

Total Health Care Expenditures

R186.9 bn

R148.1 bn

R165.2 bn

Total per capita

R3945

R3125

R3495

Total Health Care Spending as % of GDP

11.83%

9.37%

10.48%

 

 

8. NHI benefits: Macroeconomic, productivity, health

There are three sources of broad-based benefits to the society and economy that can be roughly estimated as offsetting the additional costs of NHI. These are in three categories: macroeconomic multiplier benefits of NHI (5% for each rand spent); labour productivity benefits (20% in the medium-term); and improvements in morbidity and mortality rates (up to 184 000 reduced premature deaths per year and 20% additional healthy days per person).

The introduction of an NHI program will reduce the cost of health care partly by reducing overall administrative costs, but also out-of-pocket costs to the consumer. As documented in a RAND Health Insurance Experiment (Newhouse, 1974) as well as a study on health care seeking behaviors in South Africa (McCoy, 1996), the less a person paid out-of-pocket for health care, the more health care services were utilized, or demanded. The increased demand for health care has spillover effects by stimulating growth for the economy. One measure of this is the Keynesian multiplier that estimates the impact of investments in stimulating demand on economic growth in the short run.[3] Based on Table 8, the Keynesian multiplier is 1.047, i.e. a 5% increase in overall economic activity associated with an additional investment in health care, such that R1000 investment results in a R1047 increase in GDP (Frogner 2009).

 

Table 8: Per Capita Health care Consumption and Income, 2000-05

Year

Health Care Consumption

Income

2000

R 1,415

R 36,314

2005

R 2,224

R 54,146

Difference (2005-2000)

R 809

R 17,832

Source: Statistics South Africa. 2000. Notes: Values deflated to year 2000 Rands based on the consumer price index. Income tax is assumed constant at 7% based on the 2000 survey data. Income tax data was not recorded in the 2005 survey. To ensure comparability of definitions of health care, 2005 data is the sum of “health” and “insurance connected with health” to be equivalent to the 2000 data category of “medical services and requirements.”

 

In addition, the health system affects the productivity of labour in the production process. The introduction of an NHI system must improve the efficiency of the health sector and increase the quality of the health service if it is to have long run effects on the growth rate of the economy. Improving the state of health of the labour force is not a short run consideration. Therefore if expenditure on this sector is contemplated, the true benefits that will accrue to the economy must be conceptualized from a long-run perspective. An increase in health spending now must shift long run economic growth upwards, so that the tax base expands in such a way that the resultant tax collections are enough to repay any additional public debt contracted plus interest accumulated. Cosatu modelling shows how this can be accomplished for the start-up period for NHI at different interest rates, building in a 20% labour productivity assumption (Malikane 2009). This corresponds to our estimates of potential Disability-Adjusted Life Years saved once disease reduction is calculated, below.

To calculate health benefits associated with lower morbidity and mortality rates, consider the top ten diseases responsible for registered deaths in South Africa (Table 9). To estimate the potential decline in premature deaths once NHI is established and hence health care is made universal, it makes sense to compare the benefits of rationalising health financing in South Africa with countries that have already adopted a single-payer NHI system and which also spend between 7.7% and 9.7% of their Gross National Income on health care: Australia, Canada, Denmark, Norway and Sweden (all of which have extensive private health care provision, publicly financed). These countries can not be easily compared given the very different socio-economic characteristics (and lack of a high AIDS rate), but avoidable mortality (Table 10) and Disability-Adjusted Life Year estimates (Table 11) are provided to show the vast differences in outcomes given the similar health/GDP ratios in the two types of systems.

While infectious diseases are the bulk of avoidable deaths, South Africa has a high chronic disease avoidable mortality rate that could benefit from a strong primary care system that includes gate-keeping in order to provide early preventive care and education, along with universal coverage and equal access to evidence based treatment. The second highest group of avoidable mortality in South Africa is circulatory disease including hypertensive disease and cerebrovascular disease (stroke), which is higher than the comparison countries. South Africans also have higher avoidable mortality rates of cervical cancer and diabetes, two other common chronic conditions targeted for care in industrialized countries (Table 9).

 

Table 9. Ten Leading Causes of Registered Deaths in SA, 2005

 

Cause of Death

Total Number

1. Tuberculosis of respiratory system

65,903

2. Pneumonia

44,882

3. Diseases of pulmonary circulation and other forms of heart disease

26,533

4. Cerebrovascular disease

24,408

5. Diabetes mellitus

18,416

6. Bronchitis chronic and unspecified emphysema/asthma

15,470

7. HIV disease

14,493

8. Accidents and adverse events

12,811

9. Hypertensive disease

11,851

10. Acute myocardial infarction

9,499

South Africa is fighting a two pronged attack against both infectious and chronic diseases. Almost half (48.6%) of all the deaths in South Africa are avoidable with prevention and treatment. The 286 307 avoidable deaths amount to 8.4 million life years (assuming South Africans could thus live to 75 otherwise). 84% of these life years are among working age adults (15 to 64 year olds). However, eliminating all avoidable deaths may not be the proper target. With a well-coordinated NHI, South Africa could potentially achieve 184 085 fewer deaths or 384 lives saved per 100 000 people (Table 10).

Table 10. Avoidable Mortality per 100,000 People, 2005

Disease

South Africa

Single Payers

Infectious diseases

285

4

Tuberculosis

151

0

Malignant neoplasms

53

115

Breast

4

10

Cervix uteri

5

1

Endocrine, nutritional, and metabolic diseases

18

3

Diabetes mellitus

4

1

Circulatory disease

112

73

Hypertensive disease

16

2

Cerebrovascular disease

34

14

Respiratory diseases

85

1

Pneumonia

59

0

Diseases of digestive system

30

13

Genitourinary diseases

13

3

Congenital CVD anomalies

1

1

Ischemic heart disease

18

39

Total

597

213

 

High disease rates have an effect on everyday living. In South Africa, even though the life expectancy is 51 years (in 2004), only 44.3 years were lived in a healthy state (WHO, 2009). Thus an alternative metric to mortality rate commonly used to describe the disease burden is Disability Adjusted Life Years (DALYs) which are a combination of years of life lost due to premature death and years of life lived within disability due to disease. South Africa suffers from more than 7 times as many DALYs per 100 000 people than the comparison countries (Table 11). Reflecting similar trends as avoidable mortality rates, the bulk of DALYs are due to infectious diseases including HIV that tend to be found most often in younger people and result in many potential life years lost. Once again, even if infectious diseases are treated, chronic diseases contribute to almost a quarter of the DALYs lost.

By adopting NHI, South Africa could potentially save 186 billion DALYs (29,471 DALYs per 100,000 people). Almost two-thirds of the South African population is of working age (15 to 65). Potentially assuming single payer system DALY rates, South Africa could save up to 18 861 DALYs per 100 000 among the working age population, which can alternatively be thought of as gaining 20% of a healthy year back per working person.

Table 11. Age-Standardized DALYs per 100,000 people, 2004

 

Disease

South Africa

Single Payers

Infectious diseases

22,646

158

Tuberculosis

2,484

4

Malignant neoplasms

1,503

1,353

Breast

156

163

Cervix uteri

146

25

Endocrine, nutritional, and metabolic diseases

2,284

450

Diabetes mellitus

839

229

Cardiovascular disease

3,559

1,085

Hypertensive disease

363

23

Cerebrovascular disease

1,284

272

Respiratory diseases/infections

2,314

804

Diseases of digestive system

936

317

Genitourinary diseases

427

68

Congenital CVD anomalies

270

232

Ischemic heart disease

990

513

Total

33,939

4,468

 

There is an additional set of factors associated with the current conjuncture. In 2007 the world economy began to suffer an unprecedented deflation of financial assets, which by late 2008 also adversely affected trade, investment, real estate, commodity prices and all forms of production. South Africa suffered a decline in GDP in late 2008, which degenerated into a severe crash of manufacturing leading to a 6.4% decline in annualized GDP in the first quarter of 2009.

The relevant implications for NHI costs/benefits include several factors which could have been avoided:

 

  • dramatic declines in the formal labour force will shrink the number of people on medical aid;
  • there are close correlations between unemployment and illness, and without medical aid, the state’s health system will come under further stress;
  • the financial assets kept by private medical aid schemes in reserves suffered huge losses (typically 25-40%) during 2008, which reduces their ability to cope with the increased disease burden that usually accompanies economic downturn;
  • employer cost-cutting during a time of declining profits and outright losses typically includes cuts to employee health benefits.

 

Hence the benefits of an NHI would include the mitigation of these problems. Moreover, a much larger health sector workforce associated with the increased NHI expenditure would also mitigate against the economic crisis. As noted above, the Keynesian multiplier includes spending associated with increased health care facilities, such as hospitals and clinics. So too do increased healthworker salaries translate into greater tax returns for the state.

As Figure 12 shows, there is enormous scope for bringing the numbers of healthworkers per person up to a level more closely corresponding to the peer group of countries that spend in the 7.7-9.7% of GDP range (Australia, Canada, Denmark, Hungary, Iceland, Ireland, Italy, Japan, Luxembourg, Netherlands, New Zealand, Norway, Spain, Sweden and the UK), given that presently South Africa hires only about 1/5th the relative numbers of health workers as those countries notwithstanding much lower-priced health care labour.

 

Table 12. Healthworkers per 10 000 People, 2005

 

Category

South Africa

Countries with similar spending

Physicians

8

30

Nurses

41

100

Other: dentistry personnel, pharmaceutical personnel, community and traditional health workers, environment and public health workers, laboratory workers, and other health services providers

20

190

Total

69

320

 

9. Political choices: health spending

What should be the overall social budget constraint for health care? The case has been made that South Africa should adopt NHI notwithstanding higher annual health spending, given the vast benefits that will arise. How high, then, should South Africa’s health spending be in relation to GDP? In 2002, South Africa’s health/GDP spending was 8.7%, the 32nd highest in the world. The model assumes it is in the realm of the possible to raise this to the 10.5% range, for various moral and efficiency-related rationales already analysed. This would put South Africa in 9th place overall.

 

Table 12. Relative health spending: Countries that spend more of their national income on health care than South Africa[4]

 

#1 United States:14.6%
#2 Cambodia:12.0%
#3 Lebanon:11.5%
#4 Switzerland:11.2%
#5 Sao Tome and Principe:11.1%
#6 Monaco:11.0%
#7 Germany:10.9%
#8 Marshall Islands:10.6%
#9 Togo:10.5%
#10 Uruguay:10%
#11 Iceland:9.9%
#12 Malawi:9.8%
#13 Niue:9.7%
#14 France:9.7%
#15 Malta:9.6%

#16 Canada:9.6%

#17 Norway:9.6%
#18 Greece:9.5%
#19 Australia:9.5%
#20 Portugal:9.3%
#21 Costa Rica:9.3%
#22 Jordan:9.3%
#23 Sweden:9.2%
#24 Bosnia and Herzegovina:9.2%
#25 Palau:9.1%
#26 Belgium:9.1%
#27 Israel:9.1%
#28 Argentina:8.9%
#29 Panama:8.9%
#30 Denmark:8.8%
#31 Netherlands:8.8%

#32 South Africa: 8.7%

 

There are a variety of other crucial factors that will affect political decisions on health spending, including the growing needs of society in sectors sometimes seen as ‘competing’ with health care – but that in reality should be considered complementary. But it is a fact that the health budget has shrunk in relative terms from 2000/01 to 2007/08: the percentage of the national budget devoted to health care fell from 11.5% to 10.9% (Figure 1).

Figure 1: Percentage of SA National Budget Devoted to Sectors

Source: McIntyre and Thiede, 2007

 

Finally, then, what are the available resources for financing health care, and how much additional will be needed beyond the existing spending. As Table 13 shows, the three differing assumptions about health care costs give very different results. The most realistic in the period 2010-14, i.e. a five-year phase in period, is the current public/private mix noted above. Using the costings associated with services as currently financed – but expanded to universal availability – the additional money required is R46.2 billion per annum. This amount comes from the total cost of health care with universal access, as estimated in 2015 (in 2006 rand): R165.2 billion, from which is subtracted the current state subsidies for medical aid schemes through tax deductions (R4 billion), the Government Employees Medical Scheme (R5.8 billion), the existing public health budget (R58.2 billion), and the existing medical aid schemes funding (less a 15% discount since members will pay less under NHI than they do today) (R51.0 billion).

The financing of the R46.2 billion should obviously come from two major sources, namely the extension of a payroll deduction to all current full-time workers who are presently not on a medical aid scheme, and higher general tax revenues which would require a higher rate for wealthier South Africans than is paid at present. The estimates on how to split these can proceed once political choices are made about relative burden-sharing. It is our contention that due to productivity improvements and Keynesian-stimulated growth through added health care spending, the R46.2 billion will be manageable for South Africa given the anticipated higher tax revenues that will enter the system. Regardless, the basic argument above is that the society and economy will benefit from the introduction of NHI in many objective and subjective ways. A fuller cost/benefit accounting can be carried out once updated official data are available and a full benefits package decided upon.

 

Table 13. Funding Required for Health care under NHI

 

Category

using existing private sector rates

using existing public sector rates

using current public/private mix

Total Health Care Expenditures

R186.9 bn

R148.1 bn

R165.2 bn

– State Subsidies for Medical Aids

4

4

4

– State Spending on Civil Servants

5.8

5.8

5.8

– Existing Public Health Budget

58.2

58.2

58.2

– Existing Medical Aid (15% discount)

51.0

51.0

51.0

Required revenue

77.9

29.1

46.2

 

 

10. Conclusion: New costs, big benefits

The model prepared for Cosatu suggests that with the current public-private mix but extended to universal health care access, and with the savings and costs indicated, a five-year roll-out period for the NHI will require, in 2015, less than R50 billion in additional state spending (per annum). In return for the increase in health care spending, the society will see potential improvements in health status that can easily be shown to have an economic multiplier impact, productivity merits (both for workers and broader society) and much lower moribidity/mortality rates.

 

References

 

Fish, T, et al. The Costing of Existing Prescribed Minimum Benefits in South African Medical Schemes in 2001, Cape Town, The Center for Actuarial Research Report, 2002.

 

Frogner, B. Preliminary Benefit Estimates of National Health Insurance: Disease Reduction and Macroeconomic Multipliers. Unpublished paper, Chicago, 2009.

 

Gerdtham, U.G., et al. The Determinants of Health Expenditure in the OECD Countries: A Pooled Data Analysis. Dev Health Econ Public Policy 6:113-34, 1998.

 

Malikane, C. National Health Insurance: Modeling Fiscal Implications of Initial Costs and Benefits. Unpublished paper. Johannesburg, 2009.

 

McCoy D, 1996, Free Health Care Policies for Pregnant Women and Children under 6 in South Africa: An Impact Assessment.” Health Systems Trust: Durban.

 

McIntyre, D. and M. Thiede, Health Care Financing and Expenditure, paper prepared for the Health Systems Trust, 2007.

 

Newhouse J. The Health Insurance Study: A Summary. Santa Monica: RAND Corporation (Pub. No. R-965-1-OEO), 1974.

 

Statistics South Africa. Income and Expenditure of Households: 2000: South Africa. Statistical Release P0111, Pretoria, 2000.

 

WHO. “WHO Indicators.” WHO Statistical Information System. Accessed 2009 May 20 at http://apps.who.int/whosis/data/Search.jsp, 2009.



[1] Source: CMS data. We consider this sufficient since we use aggregate rates without differentiating subspecialty. The model assumes that on average the number of visits per patient will be the same as current medical scheme members; this may be adjusted by 10% if overtreatment is widely accepted as a problem. Ideally, individual level data with cost information is required to make sound estimates.

[2] A report by the University of Cape Town Center for Actuarial Research estimating the cost of Chronic Disease List and Prescribed Minimum Benefit identifies four clusters of patients with very different cost structure. According to this study, the difference between high-end users and low-end users is 33%. The difference in the cost of services between clusters might be due to variations in prevalence rates of diseases, presentation or manifestation of these conditions, provider choice, and demographic factors. To adjust for these differences, we used the percent difference of average cost of low-end users from the overall cost, which is 12.34%. See Fish et al, 2002.

[3] The premise is that prices are ‘sticky’ and do not adjust quickly to a sudden stimulus to the economy, hence any changes in total expenditures (= price * quantity) is due to quantity changes, or changes due to demand. At its simplest form, the Keynesian multiplier assumes an economy (Y) is the sum of consumption from disposable (after tax, t) income (C), investment (I), government purchases (G) and net exports (NE). After some basic mathematical manipulation (see Appendix A for details),

.

This equation states that any 1 unit increase in , , , and  results in a:

 

increase in Y where b is the marginal propensity to consume (MPC). In other words, a $1 investment can be estimated to translate into $X increase in the economy based on the knowledge of the MPC. This equation is what is known as the Keynesian multiplier.

The MPC for health care can be calculated using the Income and Expenditure Survey, conducted every five years. The survey provides the average household income in South Africa as well as the breakdown of how much the average household spends on health care among other items. Values are deflated for proper comparison over time.

[4] http://www.nationmaster.com/graph/hea_tot_exp_on_hea_as_of_gdp-health-total-expenditure-gdp.

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