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College aantekeningen

College aantekeningen Public Health Economics (GW4566M)

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Samenvatting van lectures en werkgroepen. 8.4 behaald.











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Documentinformatie

Geüpload op
26 juli 2023
Aantal pagina's
29
Geschreven in
2022/2023
Type
College aantekeningen
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Onderwerpen

Voorbeeld van de inhoud

PUBLIC HEALTH ECONOMICS

MEETING 1

Summary measures of population health (SMPH) allow a comparison of
different countries, different subgroups within countries, and of
countries over time.
- With the goal to measure progress over time, measure impact of an
intervention and measure disadvantaged populations.

Counting the dead: mortality rates, says something, but it does not tell the whole
story. It does not reflect time.
Life expectancy is a simple measure to compare mortality over time, across
countries. It translates mortality risks at different ages into time.
o It allows you to compare different countries, different subgroups
within countries and countries over time. (SMPH)

Life tables are a useful tool to summarize mortality probabilities.
 At the heart of modelling the impact of public health interventions
 A simple way to create survival curves and calculate life expectancy
 Can be extended to calculate DFLE/QALE and expected lifetime health care
expenditures.




Life-expectancy is the area under the survival curve.
Mortality rate is the probability of people dying within a certain period and the
amount of time lived.
- The mortality rate for each age is continuous.
The life table gives a collection of age specific mortality probabilities.

,It shows what the probability is that a person of that age will die before their next
birthday.
o The mortality rates can be converted into survival
probabilities
o Age specific yearly mortality to mortality probabilities:
 q(x)=1-exp (-m(x))




Functions of the life table;
- X = age in completed years
- Q(x) the probability to die between x and x+1
o Is input to the life table
- l(x) the number of survivors to age x
- D(x) number of people that died between ages x and x+1
- L(x) umber of life years lived between x and x+1
- T(x) number of life years lived after age x
- E(x) life expectancy at age x.
You perform half cycle correction.

Period versus cohort life expectancy
Cohort life expectancy
- The cohort is exposed to the current
mortality conditions. Cohort
longitudinally over time. Generation life
table.
- Across cohort the probability of dying
increases. To make a prediction: you
use future mortality rates.
- Cohort life expectancy exceeds period
life expectancy.
- Age and time move parallel.

Period versus cohort
 Suitability of period or cohort depends
on research question

, o Company who wants to sell you a life insurance needs to know
your actual life expectancy to set the premium cohort life
expectancy
o Period: less data needed
o Disadvantage of cohort is the need for historic data or
predictions
o Disadvantage of period is that life-expectancy is the
interpretation. It relates to a hypothetical cohort that is exposed
to the current mortality rates.

In a cohort: if we use in the birth cohort of 2020 the estimates of an 80-year-old
now overestimate the mortality probability of dying in the next year.

Trends in life-expectancy
Life expectancy is increasing. People are getting older.

- 1850-1930:
o Mainly achieved through reductions in infant mortality and child
mortality
- 1950-1980
o Fighting of welfare diseases (cancer treatment)
- Now:
o Reduction in mortality probabilities at high ages

Plenary meeting 1

The harvesting effect: covid mortality exceeds excess mortality.
The costs for some people (good, moderate, bad) health are equal. You are not
eliminating the poor health state if you are in a good health state. It is only
postponed. The costs are expected to be similar.

Understand basis concepts: mortality probability, mortality rate, life expectancy
Be able to calculate a period a lifetable
Understand the difference between period- and cohort-life-expectancy
Are able to critically apply your knowledge to relevant question such as “has the
inequality in life expectancy between the rich and the poor increased”

MEETING 2: CASE
Be able to work with cause deleted life table
Calculate the impact of a specific cause of death on the differences I life
expectancy between groups
Understand and be able to apply the concept of Years of Life Lost due to a
disease
o Suppose dx is the number of individuals aged x who died from Covid
o Then the YLL due to covid = dx*e(x)

MEETING 3: ADVANCED LIFE TABLES

Life expectancy increases, but what does that mean for health?
- It depends: how do we measure health? What perspective do we use?
Which methods?
You combine mortality and morbidity, why? There is more to life than death and
not all life years are spent in good health.

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