Recap of Market Failure and Government Intervention:
We previously discussed how healthcare market is associated
with ‘market failures’ and that governments often take a
paternalistic approach to correct the failures.
We also learned that governments often attempt to alter
patients’ and healthcare providers’ behaviour through
various means, such as taxes, redistributions, laws and
regulations.
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This week’s topic:
We look at a more micro level, rather than at the societal level.
Just like social sub-optimal outcomes can arise from ‘market
failures’, private health outcomes can be sub-optimal due to
individual behavioural biases of both patients and health
providers.
Personal choices affect health, depending on the way an individual
allocates resources to its production.
Examples:
• The amount of TV time vs. jogging time, eat fatty vs. healthy
foods, water vs. soda, or to smoke or not.
• On the supply side, a doctor chooses whether to follow
established ‘knowledge’ or look for new evidence for
treatment. 3
This week’s topic
Also, note that the demand curve was derived on the basis of the
assumption that a consumer is ‘rational’ – that is s(he) will
accurately allocate resources to achieve the objective of
maximising his/her ‘benefit’ (or utility) function.
Then you may wonder why do people pay to smoke, ignore
medical advice, and drive drunk?
Are these choices rational?
In reality, the underlying classical assumption of ‘rationality’ is
violated all too often.
We will learn about some of these biases that are critical to
health decisions; and discuss an application.
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You know which one is healthier food – but would you always choose to eat it?
Why is this topic important?
Behaviour is a principal factor in the current epidemic of
chronic diseases
Coronary heart disease, Cardiovascular disease and Cancers are
commonest causes of death in many countries. Most can’t be
cured, but a majority of cases could be prevented by changing
health behaviour, e.g., exercise, diet, smoking.
Behaviour is also crucial for control of infectious diseases, e.g., TB,
HIV/AIDS and hepatitis.
Growing antibiotic resistance is a result of human behaviour,
including that of doctors.
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Lack of health knowledge Unhealthy behaviour?
• Health knowledge, or education, refers to the knowledge and
understanding people have about health-related issues.
• Knowledge is the first step to changing behaviour.
• It is important that people understand the causes of ill-health and
recognise the extent to which they are vulnerable to, or at risk
from, a health threat.
• However, knowing something can affect your health and
perceiving a health threat are not the same.
• In other words, knowledge is a necessary component of
behaviour change, but on its own, it is not sufficient to bring
about behaviour change.
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Why is Health Knowledge important?
To prevent disease people must change their hazardous behaviour.
Why do people behave in ways hazardous to their health?
Because most people don’t think of their health until it is
threatened.
Example: Even when smokers are shown the cancerous lungs of
other smokers removed postmortem, the decision to stop smoking
lasts only about 24-48 hours, after which the impact is not
noticeable in terms of their behaviour.
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Knowledge alone is not enough
Plenty of information about healthy diet and lifestyle.
It is likely that many people are aware of ‘what they are supposed
to eat’
Survey in UK:
• 99% knew fruit and vegetables very or fairly
important
• 94% said eating less salt was important
• 92% said limiting foods high in saturated fat was
important
But, the high incidence of CHD and CVD belie this knowledge.
Source: Food Standards Agency, 2010 9
What factors influence behaviour? The COM-B system
Michie et al. 2011, Implementation Science 6:42
Physical Psychological
Includes knowledge & skills
Reflective
processes
(System 2)
Automatic
processes
(System 1)
Physical Social
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Human behaviour shaped by TWO systems
(Dual Process model)
SYSTEM 2
Reflective, goal oriented system
• Driven by our values and
intentions
• Requires cognitive capacity or
thinking space
• Many traditional approaches to
health promotion target this
system, i.e. designed to alter
beliefs and attitudes
SYSTEM 1
Automatic, affective system
• Requires little or no cognitive
engagement
• Driven by immediate feelings
and triggered by
environments
Strack and Deutsch 2004, Pers Soc Psychol Rev 8:220-47. 11
Behavioural Economics: An introduction
The workhorse of economic
modeling is homo-economicus, an
agent who:
- Optimally maximises his
expected utility - Optimally updates his beliefs
- Is selfish and without emotion,
or, more formally, does not get
intrinsic utility from consumption
and utility of others
This approach has yielded fantastic insight, but…
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The motivation behind Behavioural Economics
• Do people behave like homo-economicus?
• If not, what are the implications for economic theory and policy?
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What Behavioural Economics does…
It adds to the standard model of economics some reality about
how humans behave. In particular, it adds among other things:
• bounded rationality,
• biases in interpreting information,
• interdependent preferences,
• emotions,
• learning,
….
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A sketch of history
Behavioural economics naturally emerged with game theory in the
50’s and 60’s. The likes of Vernon Smith, Kahneman and Selten
showed its power.
From the 80’s onwards Behavioural
Economics has been the fastest
growing area of economics. Partly
due to dissatisfaction with the
‘standard model’.
But note that Behavioural
Economics is not new. The
forefathers of economics, including
Adam Smith, Keynes and Marshall
talked a lot about behavioural
tendencies more than 100 years
ago. 15
The methods of Behavioural Economics
Experiments:
- lab based
- in the field
- neuroscience
Theoretical: - game theory
- decision theory
- evolutionary theory
Simulation: - Agent based models
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Some interesting behavioural biases
Example 1: A Fine is a Price
A problem for primary schools and nurseries is parents picking
their children up late. The school must play the role of babysitter.
• Suppose that we impose a fine on parents for picking their
children up late?
• However, in reality, more parents may leave their children late
because the fine makes it ‘ok’ to put a burden on the school.
• The ‘rational’ parents should avoid a fine – because increases
in price/minute should lead to fall in quantity demanded
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The results of an experiment: A Fine is a Price
• Gneezy and Rustichini (J Legal Stud., 2000) report an
experiment in day care centres in Haifa, Israel in 1998. In week
4, a fine was introduced and in week 17 it was removed.
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0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Proportion late
Weeks of trial
Test group
Control group
Example 2: Fairness in Tipping
How much would you tip?
In a restaurant you visit frequently the mean
amount suggested was $1.28.
If you were rational, would you tip the same
way in another city?
In a restaurant in another city the mean
amount suggested was $1.27 (Kahneman,
Knetsch and Thaler, 1986)
Some interesting behavioural biases (contd…)
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What we observe
• Reciprocity: Many people seem to
desire reciprocity
‘If someone does good (or bad) to me then I want to do
good (or bad) to them.
• Fairness: people care about outcomes, relative to others
‘Why should I get less than him’, ‘Why should I get more
than him?’
• Why is this different to the ‘standard model’?
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Fairness and reciprocity matter
In the standard model, utility is a function of consumption, $10 is
as good as $10 does.
Behavioural economics emphasizes that it matters:
o where the $10 comes from; $10 stolen induces guilt and
shame while $10 earned induces pride.
o how much others are getting; $10 when others are getting
$20 might be annoying but $10 when others are earning $5
might induce guilt.
Note the important interaction between these two effects.
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A neuroscience perspective
• Unfair offers activate
areas of the brain
associated with
emotion (Panel A); and
activate areas of
cognition (Panel B)
relative to fair offers.
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Applications and policy
Fairness and reciprocity have wide-ranging applied and policy
consequences.
One area with important consequences is pricing of health
plans, Medicare rebates, and wage-setting.
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The Law of Small Numbers
People exaggerate how closely a small sample will represent the
population.
• A model inference with the law of small numbers (Rabin, QJE
2002) - A person observes a sequence of binary signals from some
i.i.d. process. - The person believes that they are generated without
replacement from an urn with N signals. - The urn is replaced every other period.
- The smaller is N the larger the bias.
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The Law of Small Numbers
Suppose you know (from published medical data) that recovery
rate from a disease is 80%.
Now, if 5 patients report that they have contacted the disease, how
many do you think would recover?
Based on the 80% recovery rate, you are likely to say 4 out of 5
patients will recover from the disease.
If you do, you are biased due to the Law of Small Numbers.
The actual probability of 4 out of 5 recovering from the disease is only
41% (using Binomial probability distribution).
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Consequences of the law of small numbers
• We overestimate the importance of small samples.
• We underestimate the importance of large samples.
• We read too much into long streaks of success or failure.
(There are no ‘hot hands’ in basketball).
• Sequence matters beyond averages.
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Confirmatory Bias
People tend to be too inattentive to new information that contradicts their
hypothesis. They can ignore contradictory evidence, and misread it as
supporting their hypothesis.
A model of confirmatory bias – Rabin and Schrag (QJE, 1999) - A person receives a series of signals a or b.
- The person perceives each signal as α or β.
- After each signal the person updates their belief about the hypothesis.
- He currently believes in the hypothesis he perceives to have received
more signals. - If he currently believes in hypothesis X then he:
- correctly perceives a signal supporting the hypothesis
- wrongly perceives a signal against the hypothesis with probability q >
0 (correctly perceives this ‘contradicting’ signal with probability (1-q)<1)
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Consequences of confirmatory bias
Information contradicting a hypothesis can be ignored or missinterpreted.
This is particularly the case if the information is
ambiguous.
Hypothesis based filtering. People can use filtered evidence
inappropriately.
A person who has recently
changed his mind can be underconfident
in a hypothesis.
Confirmatory bias may not be
eliminated by increasing
information.
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Relevance for Healthcare
Both patient and practitioner must form hypotheses based on
constantly changing information.
The law of small numbers and confirmatory bias could cause
biased decision making.
The evidence is that we do observe such biases – Frank (NBER,
2004).
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Confirmatory bias among medical practitioners
• Practitioners must choose drugs and referral services based on
information about the drugs and services.
• In treating conditions like Otitis Media, Diabetes, Depression
and Asthma physicians regularly depart from evidenced based
practice.
• Doctors in Miami (Florida) have been observed to rely on drugs
they become familiar with and not use newer more effective
drugs or lower cost versions of older drugs. In 1999 Medicare
spending in the US was $9,941 per enrollee in Miami and
Florida compared to $4,886 in Minneapolis and Minnesota.
• Risk adjusted mortality rates for Coronary artery bypass graft
fell from 4.17% in 1989 to 2.45% in 1992. Despite this fall in
mortality risk, there was no increase in demand.
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Confirmatory bias among patients
Patients must choose which doctor to see and, in some instances,
which treatment to have.
• The evidence suggests that patients do not use information
available about doctors or treatments. - 70% do not according to one survey.
- Instead, they are more comfortable with doctors who they are
familiar with, they trust. - 76% would choose a doctor they are familiar with over one
more highly rated by experts.
• Choices are typically made on the basis of factors not really
relevant to health care. - 70% rely on the advice of family and friends.
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Getting rid of bias: ‘Learning’
Many have suggested that biases should disappear with greater
experience.
This seems, however, to not be the case:
In many instances there is no time to learn from
experience.
When there is time, the person may not realise
that they are biased, so cannot correct.
Even if people do learn about their biases, and its
costs, they typically do not apply this learning.
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Status-quo bias
This bias arises when a person exhibits a preference for the current state of affairs, even
when it would be beneficial to change the status-quo. This behaviour obviously can lead
to bad decisions.
o Example: People routinely fail to increase contribution to retirement saving, even after promising to do
so at the ‘next pay raise’ (and even when the employer ‘match’ the individual contribution)
• In healthcare, medical noncompliance may also stem from sheer inertia – the
tendency to stay in the current state, even when that state is undesirable
o Example: Suri et al. (2013): participants were told that the research would involve receiving electric
shocks. One group was told that they were required to choose one of two options: They could press a
button to stop the shock 10 seconds earlier, or press another button to keep the waiting time the
same. As expected, most people opted to get the shock over with early. In contrast, those participants
who were told that they could press a time-decrease button if they wanted to were more likely to stick
with the status quo: Only about 40% chose to push the button in order to shorten the trial.
Those participants who had to make a proactive choice to press the button opted to leave it
untouched about half the time, even though it meant they had to withstand shocks they themselves
rated as highly undesirable.
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Loss aversion
People tend to overvalue losses and undervalue gains. A heightened
tendency to focus on avoiding losses, even if it makes them worse off.
Due to this bias it becomes critical how choice is framed – in terms of
gains or in terms of losses. The ‘framing’ influences people’s decisions
in ways that cannot be accounted for by traditional economic theory.
• In general, it costs less to self-insure against very likely events and/or when size of
the loss is small, rather than purchasing full insurance. With insurance one has to
pay not only the expected cost of the loss but also administrative costs (including
profits) and ‘loading charges’ to the insurance company. If someone still buys
insurance, paying a deductible should be preferable to full coverage. Nevertheless,
people do buy insurance for high probability events.
o One example in US health care is Medigap coverage for the cost of the Part B
deductible, which is only $140 per year and is generally exceeded by seniors.
Medigap purchasers are expected to avoid such plans and choose options that do
not cover this deductible, but they do not.
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Delay Discounting (time preference)
• A related phenomenon relates to how decisions are made between
the present and the future.
• Discounting is a necessary adjustment to compare the value of
future outcome with the current cost. More distant the future is
lower should be its current value if discounting is applied. However,
some people discount the future values excessively.
• Choice of smaller, immediate rewards over larger distant rewards is
generally driven by
o Disproportioned priorities or present-orientedness (present-bias).
o By lack of self-control – particularly when the present temptation
(that chocolate mousse on the dessert tray) is so salient, whereas
the future health implications are remote and incremental.
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Excess delay discounting
People seek immediate gratification at the expense of long-term gains
Example:
Drinking, Smoking, Illicit Drug Use, or Eating (overconsumption)
These behaviours are “enjoyable” in the short-term. Avoiding these has longterm
health benefits, the value of which is heavily discounted.
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Excess delay discounting
• People with overconsumption disorders know that larger
delayed outcomes – physical health and vocational success – are
very important to them
• Nonetheless tend to persist and potentially make the problem
worse.
Why?
• “Inability to delay gratification” (low self-control?)
• Overvaluation of immediate rewards, or undervaluation (deep
discounting) of the future benefits.
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Delay discounting, impulsivity, and self-control
You want to be a healthy body weight more than you want a piece
of cake (in the long run) – but if cake is immediately available, it
can be eaten without much effort, while maintaining a healthy
body weight will take more effort. An impulsive person would eat
the cake, a self-controlled one would resist temptation.
You swore off cigarettes 2 months ago, but would rather smoke
right now, than continue to maintain your non-smoking lifestyle –
which takes more effort and isn’t as immediately rewarding to you
as smoking. An impulsive person would smoke, a self-controlled
person would not.
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Research Findings
Various Research found that substance abuse and
overconsumption aren’t alone in regard to delay discounting.
Other health behaviours fit too!
Can anyone think of any other health behaviours?
Also, how does delay discounting apply?
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Thus,
Overvaluation of immediate outcomes at the expense of future
outcomes appears to play a role across a wide range of health
behaviours.
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Distorted risk perception
• From Loss Aversion bias we think in terms of gains and losses
with respect to our perceived and expected status quo. We fear
losses more than we like gains.
• But we also distort probability according to how a prospect is
framed (in terms of gains and losses). Our choices are highly
dependant on how ‘uncertainty’ is framed:
o We overvalue probability (risk) when thinking in terms of loss (risk seeking).
o We undervalue probability when thinking in terms of gains (risk averse).
• These heuristics may lead to irrational health choices by patients
and doctors alike.
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Consequence of distorted risk perception
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Fourfold pattern for risk aversion and risk seeking
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