Summary Chapter 1, Introduction (Mattias Fritz)

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1 Introduction

The Objective of the article is to provide an answer to the question in the title, that is: Why do different countries spend different amounts on health care?

2 International comparisons

Newhouse (1977) used 13 developed countries’ data from 1971 and found two results which have later proven to be very robust:

  1. Aggregate income (GDP/capita) explains almost all of the variation in health care expenditure between countries (92% in his study)

  2. Income elasticity exceed one

The authors make a similar regression with data from 1998 and a larger number of countries. Their adjusted R-square is slightly lower (0.77) but that is changed (to 0.90) if the two “outliers” USA and Luxembourg are excluded. The results are shown in figure 1 where one can see that USA lies above – and Luxembourg below – the regression line. This implies that USA/Luxembourg spends relatively more/less on health care.

Gerdtham and Jönsson (2000) have reviewed the literature up to 1998 and found (most importantly):

  • Same finding on the significance of GDP/capita as above.

  • Income elasticity clearly larger than zero and close to or above one.

  • Age structure and unemployment usually insignificant

  • Lower health care expenditure related to: use of primary care “gatekeepers” ()

  • The Ratio of in-patient expenditure to total health expenditure is positively related to health expenditure.

  • Public sector provision is associated with lower health expenditure

Regarding the effect of GDP, Musgrove et al (2002) found for 191 WHO-members that health spending rises from around 2-3% of GDP at low income levels (<1000 USD/capita) to typically 8-9% at high incomes (>7000).

The authors use cross-sectional data from 1998 to see if the findings are still valid. They regress health care expenditure (variable name: HE) on the variables GDP/capita (GDP), share of total health expenditure publicly financed (PHE), percentage of population above 65 (Age65), number of in-patient beds per 1000 inhabitants (Beds) and a dummy variable on the existence of a gate-keeping function in the primary care. Successive elimination of insignificant variables left only GDP(+), PHE(-) and Age65 (+). However, the results are sensitive to the countries included (without USA PHE is not significant).

3 What can be learned from these comparisons?

That health expenditure share of income increase with income does not have to imply that rich countries consume more health care. This is so for two reasons:

  1. Rich countries may pay more per unit of health care. (However, studies using health care specific PPP produce the same income elasticities.)

  2. In several countries expenditure share has not increased with income per capita.

The fact that the US has a higher health expenditure share than the one expected from its GDP is mainly a result of expensive health care. For example physicians’ salaries are high. Newhouse et al (1988) find that US patients receive three times as much health care as Canadian patients without significantly better outcome.

By definition: health expenditure share = (price * quantity) / GDP per capita

So changing health expenditure share is the result of change in at least one of the three variables relative price of health care, quantity of health care produced and GDP per capita.

A critique of focusing on health expenditure share is that it neglects opportunity cost. For example in Sweden there has been an increase in the number of doctors and nurses at the same time as their salaries have declined. This change is missed when one focuses on the expenditure share alone.

The only potential lessons to be learned from investigating factors influencing the expenditure share are to identify factors with which increase expenditure but probably do not increase health consumption. This would point out inefficiencies in the system

4 The impact of age structure in Sweden.

There are difficulties involved in measuring the impact of age structure on costs.

  1. With “Ädelreformen” in 1992 the responsibility of the elderly care was moved to the municipalities. Problem for time-series.

  2. Part of the costs for elderly care is the cost of medical care (about 15% according to Swedish estimates).

  3. Arrangements for elderly care vary greatly between countries. In some countries the role of informal care is important.

  4. The impact of age is influenced by the correlation of age and mortality, so that there is an indirect effect of age on costs via mortality.

5 The output of health care

Health care is not only a cost. It contributes to economic growth.

In low-income countries WHO has fund that the effect of health on poverty reduction and long-term economic growth. Health care investments are therefore recommended as an aid and development strategy.

For richer countries the effect of healthcare on health are weaker connection. Bhargava et al (2001) estimated the effects of adult survival rate (ASR) on economic growth. They found that for low income countries 1% increase in ASR gave approximately 0.05% increase in growth rate. This can be compared with that 1 % increase in investment/GDP gave approximately 0.014% increase in growth rate. For highly developed countries the effect of ASR on growth seems to be negative.

That the health care production function is subject to the law of decreasing marginal returns is consistent with observations that the links between health indicators and growth are weak in rich countries.

In order to include improvements in health in the measurement of national income Nordhaus (2002) proposed the concept of health income.

6 Conclusion

Need for more theoretical models in order to make progress in assessing importance of different factors.

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Summary Chapter 1, Introduction (Mattias Fritz) iconExecutive Summary Introduction

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Summary Chapter 1, Introduction (Mattias Fritz) iconChapter 2 1 Introduction

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