Summary Lectures Economics of Health and Health Care
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Course
Economics Of Health And Health Care (GW4568M)
Institution
Erasmus Universiteit Rotterdam (EUR)
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The Economics of Health and Health Care
Lecture notes study book The Economics of Health and Health Care of Sherman Folland, Allen Charles Goodman - ISBN: 9781351595209, Edition: 8, Year of publication: - (-)
Summary Lectures Economics and Financing (2020-2021)
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Erasmus Universiteit Rotterdam (EUR)
Health Economics, Policy And Law
Economics Of Health And Health Care (GW4568M)
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Lecture 1: Production of health .......................................................................................................................1
Lecture 2: Demand for health ........................................................................................................................10
Lecture 3: Distribution of health (societal level) ............................................................................................23
Lecture 4: Funding health care expenditures .................................................................................................37
Lecture 5: Economics of COVID-19: Guest Lecture Xander Koolman ......................................................53
Lecture 6: Equity in health care finance .........................................................................................................56
Lecture 7: Measuring Universal Health coverage. ..........................................................................................66
Lecture 7: Financial Protection and Universal Health Coverage in low/middle income countries ..................67
Lecture 8: Equity in health care delivery ........................................................................................................76
Lecture 9: Explaining health inequalities (pro-rich or pro-poor) .....................................................................87
Lecture 10 & 11 : Efficiency ............................................................................................................................98
Efficiency: how to use the estimates? ............................................................................................................ 110
Lecture 1: Production of health
Students should be able to understand, assess and use
• An economic approach of health determination through production functions;
• Empirical (and econometric) evidence on marginal effect of income on health at macro level;
• The relationship between income inequality and health (inequality).
Empirically, we see that income and health are associated. Some studies even claim causal effect of
economic growth. But others claim that growth is neither necessary nor sufficient condition for health
improvement
- Health systems aim: improving health (the level) and health distributions (presented in means,
a lot of inequality is hidden behind those means). Both the level and distribution matter.
- Many different determinants of health, health care is only one of them
- Health and (economic) development are related
- Measurement of marginal health product of health care and income is hampered (gehinderd)
by:
o Population health measurement → hard to measure population health: which
indicator to use? Mortality, quality of life, combination is often problematic or not
available.
o Estimation of marginal contribution ≠ total contribution → estimate the marginal
contribution of additional investment in health care not the total
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, contribution/investment or the additional growth in income, not total income, which
is not the same thing.
o Reverse causality and confounding → it is a causal effect (income and health) - we
want to deal with confounding and reverse causality
- the marginal cost relates to the cost of producing one extra unit of output
Health production functions
Health production function: relationship between an outcome of population health (e.g. mortality/life
expectancy) and its potential inputs.
- Population health = f (health care, lifestyle, schooling,
environment, human biology, genes, …) population’s health is
affected by all these different things and they have to be controlled
for in order to say something about the marginal contribution of
medical care.
- Diminishing returns to scale: marginal product of health
investments decreases : higher levels of health care investment
will increase health status but at a decreasing rate. (see curve)
- Flat-of-the-curve medicine? ➔ meaning that further investments do
not lead to further improvements of the population’s health
depending on how it is measured.
- Correlation or causality? Reverse? Spurious? (onecht) ➔ healthy
populations could perhaps earn better incomes. the relationship
between income and health may be perhaps false (not drawing
conclusions too soon)
- 1st curve: The change in health status as a result of one unit of extra
health care. The very late units only generate very small marginal
units of health care compared to the first units. --> extra health generated by the first unit of
medical care is 11, difference of 32 to 43 in the right curve.
Health and development: demographic and epidemiological transition
Demographic transition (as populations become healthier, they also age): Mortality effect (longer lives)
and fertility effect (fewer births) leads to age-structure shift:
- Mortality declines: due to technological progress → development of medicine: as the health of
individuals improves, they live longer.
- Fertility declines: due behavioural change → fewer births, desire to have families with fewer
children.
→ In high-income countries: these effects generally occur simultaneously → dampens population
growth, typical annual growth is up to 2% pop growth
→ In developing countries: adoption of new technologies faster (mortality decline) than
behavioural shift (fertility decline), up to 4% pop growth. Consequence: much higher population
growth rates in less developed countries, but ageing consequences in other countries European and
OECD.
Epidemiological transition (the pattern of disease changes as development proceeds):
- Epidemiological transition: that causes of death or diseases are changing as well.
1. Expensive diseases drive out cheap diseases: cheap diseases that killed people at young
ages and the expensive diseases are the ones that don’t often kill individuals but have
requirements of life long treatments like diabetes and that goes hand in hand with an
increase in old age diseases.
2. Relative increase in old-age diseases: that one is familiar with. as individuals live longer,
diseases that only affect older individuals increase in absolute terms.
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,Consequence: shift in population structure. For example UK comparison. Shift of mortality from
agegroup 0-4 to 75+. And with this you have an equally distributed population. And life expectancy
of different age groups grew strongly (Mortality decline was not uniform by age: especially newborn
survival improved)
Main determinants of mortality decline / 3 phases:
1. Phase 1 (1750-1850): nutrition (with economic growth), people need healthy lives in order to be
productive.
- Agricultural yields increased significantly during the eighteenth century. Improved nutrition
and escaping hunger: Half of all mortality decline in late eighteenth century due to increased
caloric intake and growth in height, people were better fed and had a longer life spam.
2. Phase 2 (1850-1930): public health, mainly cleaner water in cities and better sanitation
• Public health? Water and food borne diseases (Preston) were really important and the water
purification explains half of mortality reduction in start of 20th century US: 23 dollars return
to 1 dollar investment.
3. Phase 3 (1930-2000): medical care, first vaccines and antibiotics, later ‘big medicine’
• Vaccinations? Many declines in infectious diseases mortality occurred before introduction of
effective vaccines. due to the public health measures a lot of the food and water borne
diseases were cut back, even before the introduction of effective vaccines.
• Medical treatment? Two-thirds of cardiovascular mortality decline due to medical advances.
Only in the last half of the century medical treatment has brought down cardiovascular
mortality.
› Countries’ life expectancies converge and diverge in different periods (depending on the level of
development they are in) Up until about 1980, life expectancies were converging across countries.
Convergence here is defined as a reduction in a measure of spread, such as the standard deviation
of life expectancies. Life expectancy is taken to be the same for everyone in a country.
4. Income and health in poor countries
Table: Death and poverty around the world that are preventable
- almost all of those are concentrated in low income countries
- difference in age distribution in low vs high. 75% of deaths occur in 60+
for high income
→ Main message: there is a dramatic association between income and health
Income and health relationship in poor(er) countries
What does that mean for policy? That one has to await income growth and development for improved
population health? Or that they go hand in hand for other (unobserved) reasons? (let economies grow
and almost by itself the population health will get better?, no because we assume only one causal
relation from income to health and not the other way around. Or other factors that might influence
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, both) Does all income growth result in better health? (there is variation at similar levels of income,
while in general higher income is associated with higher health) so in other words: is wealthier always
healthier?
- In other words: is wealthier always healthier? and if not, under what conditions are they?
→ data at the aggregate level of the entire population/region, see the extent to which income improves
health
Income and health linkages: early evidence
- Strong positive cross-sectional association income and health long observed since Preston ➔
the Preston curve. People tried to quantify the relationship to use it for policy.
- E.g. Gertler and van der Gaag (1990): 10% increase in GNP/capn was, on average, associated
with: 1 extra year of life expectancy, 8.3% lower infant (<1y) mortality rate, 14.2% lower child
(<5y) mortality rate, 1.5% lower crude death rate
- Concave structural relationship has shifted upward over last century. While there continued to
be a positive correlation between health status measured by life expectancy and income on a
cross-sectional basis throughout the twentieth century, this relationship shifted over time.
o There are two basic explanations for this shifting relationship between income and
health.
1. The first is that it has become easier, or cheaper, to attain and maintain given
levels of health over time because of technological innovations. Technological
improvements make health production cheaper
2. The second possible explanation for the shift in the relationship is that
individuals' preferences have changed over time, and that, for a given level of
income, individuals have become more concerned about health.
Graph: Life expectancy and income, 1900-1990: the Preston curve shifts upward.
Xaxis = income per capita , Y axis = life expectancy
Concave curve. Different dots in the curve indicate
different countries in different years, and for each of those
countries and years the researchers estimated the best
fitting concave model through these dots.
1) The curve always seems to be concave
2) There seems to be a shift upward
Countries are not only growing along this line but the
curve itself is shifting upwards.
Why is that curve shifting upwards? Technological
improvements make health production cheaper: at each level of income in later years,
higher levels of life expectancy can be obtained. So the upward shift of the curve is a clear
sign of technological improvement.
How does income generate health?
- Not directly, cannot buy health, but can use income for health-enhancing or other goods and
services, which can also be harmful (e.g. smoking, obesity) - it is not income per se that
improves health, but how that income is used → somehow convert ability to pay to health/better
care use
- Preston Curve: concave relationship means : average life expectancy (LE) across incomes <
life expectancy of those with average incomes (Jensen’s inequality).
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