Samenvatting
Summary Economic Evaluation (AM_470828)
- Instelling
- Vrije Universiteit Amsterdam (VU)
summary of the course economic evaluation
[Meer zien]Voorbeeld 4 van de 48 pagina's
Voorbeeld 4 van de 48 pagina's
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Voorbeeld van de inhoud
Summary Economic Evaluation knowledge clips + working classes1. Research designs
Observational study: researchers observe the effect of
a risk factor/diagnostic test/treatment/intervention
without trying to change who is or isn't exposed to it.
*case control, cohort
Experimental study: a study in which conditions are controlled and manipulated by the
experimenter.
Observational study
Perks: relatively easy to conduct (data is already available), good reflection of usual practice, (a.k.
results have good generalizability)
Disadvantages: sometimes very large populations are required (*rare disease), there can be
confounding by indication (= selection bias!)
Selection bias= referral to treatment A or B may be biased by the referral procedure. Two groups are
most likely not comparable at the start of the study. Systematic differences in participant
characteristics at the start of a trial.
→ Are the found differences between the 2 groups because of the intervention or because of the
difference in characteristics?
Experimental study
Perks: randomization ensures allocation by chance, not by
indication (it prevents confounding)
Disadvantages: expensive to conduct, selective patient
population (results are not good generalizability to the
entire population)
So a RCT study is not very generalizable because
- inclusion and exclusion criteria creates a subset of the real population
- healthy individuals are more willing to participate at a RCT
- they are conducted in a relative stringed experimental conditions
- patient are measured at baseline and followed up and measured over time, all of those
measurements might also influence their response in an intervention (*increased good behaviour
while it does not occur in real life)
,Reliability and validity say something about the quality of a
study/measurement
→ Reliability (precision)= the degree of stability exhibited when a
measurement is repeated under identical condition. It refers to
the measuring procedure itself rather than the output. If we
repeat the measures, will we get the same result? -> than reliable.
→ Validity= the extent to which the study measures what it is
intended to measure. Are the values/ outcomes describing what
was supposed to be measured? Are we actually measuring what
we wanted to measure.
– Internal validity= the probability that the study design and conduct does not lead to biased
results (results are valid for research population)
– External validity= the probability that results are valid for other populations as well
(generalizability)
Threats to internal validity
a) Selection bias
b) Performance bias: there are systematic differences, besides the fact that the intervention-
and control group get different treatments, in the performance of care. It occurs due to
knowledge of interventions allocation, in either the researcher or the participant.
c) Detection bias: there are systematic differences in obtaining (measuring) outcomes. (to
prevent: blinding the researchers)
d) Selective outcome reporting bias: only a subset of the original outcomes measured and
analysed in a study are fully reported based on the magnitude of the treatment effect or the
statistical significance of selected outcomes. (to prevent: clinical trial registers &protocol)
Confounding by indication= When an exposure appears to be associated with
an outcome, the
outcome may, in fact, be
caused by the indication
for which the exposure
was used.
When you do not have
enough patients (*rare disease). You do not
divide them in control and intervention group.
The past of the group is the control.
Pre-post experiment
Drawback: you assume that nothing would happen over time (*Alzheimer= progressive)
, If we do not randomise, there is a possibility of
selection bias. People who are more risk averse are
more inclined take care as usual and people with a
very bad health will go with the intervention. This
makes the comparing more difficult.
Why economic evaluations?
There is an increase in healthcare costs due to
a. They greying of the population (→ people are getting older + there are relatively more older
people comparing to younger people)
b. Development of new technologies (*diagnostic or treatment→ they are generally more
expensive than usual care)
The demand of health care is much larger than the available budget, so we have to make decisions
about how to spend resources→ We want that health gains from that budget is maximized. We want
to make informed decisions on how to spend our budget, in such a way that we maximize the health
benefits within that budget. (aim: To maximize the health benefits from the available resources.)
Within economic evaluations you always make a trade-off. You compare the costs and health effects
of 2 or more interventions. The question that an evaluations needs to answer is whether the
additional investment that is needed for the new intervention are balanced by the additional health
effects obtained by the investment.
Types of evaluations:
Cost minimization: assumption that the
health effects of both treatments are
equal. In that case we are only interested
in costs, and which intervention is the most efficient because it is the cheapest. However, generally
the effects are not the same.
Cost-effectiveness analysis: we express the health effects in disease specific units *blood pressure
Cost-utility: In this type we express health effects in QALY’s. You can calculate it for every disease and
interventions, and the QALY always stays the same
Cost-benefit: Health effects are expressed in monetary units. This facilitates the comparison, but it is
difficult to convert health effects to monetary units. (also unethical)
Most encountered are cost-effectiveness analysis and cost-utility analysis.
, 1. Cost-effectiveness is not a dirty word
QALY takes into account how long you’re going to live+ the quality of that life.
(ICER) is often expressed as the cost per quality adjusted life year (QALY) gained
* A treatments for Moderate Seizure Disorder (MSD) costs €100.000
If you get fully treated today for MSD you gain 4 QALY’s.
The cost-effectiveness/ cost-benefit = €100.000/4 QALY= €25.000 per QALY
2. Design principles of economic evaluations
Often we use a RCT in economic evaluations. Problem: RCT is designed to show efficacy in new
interventions: can it work in highly controlled situations (High internal validity but low
generalizability).
→ we want to generate evidence on the costs & effects of an intervention in a scenerio that
resembles clinical practice as much as possible= pragmatic RCT
Pragmatic RCT
• Normally placebo in control group. This is not valid in economic evaluations focused on cost
effectiveness since placebo is not implemented in actual clinical practice. Control condition
should resemble current clinical practice *current treatment/guideline or doing nothing if
there is no treatment
• Protocol driven care: often in a normal RCT, to monitor patients more closely more blood
samples are taken/more outpatient visits are done/ more scans are taken (+ do patients
adhere to their treatments?). In economic evaluations, trials are designed to estimate cost-
effectiveness, you don’t want this protocol driven care. Normally this is not reality so when
you do so, this lead to an overestimation because of the higher costs.
• Blinding: In a normal RCT both patients and caregivers are blinded in the interventions.
However, in actual clinical practice which treatments someone gets will effect which type of
mandatory you apply. *If you know that a certain treatment can cause a higher blood
pressure you will monitor it more closely. If you don’t know which intervention your patients
receive you will do that additional monitoring for all patients. This will increase the costs
more than in clinical practice
• The study population included should be representative of the total population. Often in
RCT, study populations are highly selected: only highly healthy people without additional risk
factor+ who comply to the treatment. In reality the GP will encounter unhealthy people with
morbidity. It is important that the study population in your pRCT is an actual representation
of the people who the GP encounters in his practice.
• Study size: when you conduct a RCT that also aims to evaluate cost-effectiveness, you need
to make sure that all types of study sizes are included
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