Memorandum submitted by the Genetic Interest
The Genetic Interest Group is a national alliance
representing families and individuals affected by genetic disorders.
Members of GIG include those with existing conditions, relatives
of affected individuals, people at significant risk of developing
a genetic disorder in the future and those at increased risk of
having children with a genetic condition.
1.1 In the area of genetics and insurance,
as in many others, a clear understanding of what is meant by the
term "genetic information" is important. Most of the
public and policy discussion of the issue genetics and insurance
over the past five or six years in the UK has focused on the possible
use by insurers of predictive DNA test results on adults who are
currently free of the condition to which the test result is thought
to be relevant. However, another form of predictive genetic data,
family history, has been used by insurers for many years, often
resulting in increased premiums or a denial of cover. A further,
and most probably larger group who also lose out in the insurance
context is made up of people who have disabilities or are already
ill. They may face a shortened life expectancy or a greater need
for care than the average person. This may be for genetic reasons,
as in, for example, the case of a person with cystic fibrosis,
or it may not.
1.2 A realistic assessment of the predictive
power of genetics and of government and individual behaviour in
relation to predictive testing, suggests that those with a family
history and those with existing disabilities or illnesses are
likely to constitute the largest group who experience problems
in the insurance context for the foreseeable future. We should
not lose sight of this when examining the use of predictive DNA
1.3 The significance of genetic information
will also depend on the form of insurance sought and the wider
social context, including non-insurance-based means of support.
The situation in the UK differs markedly from the United States
in the latter regard. In the US, the centrality of insurance to
the delivery of healthcare, a clear social good, has dramatic
and clear implications for the use of genetic data by insurers.
Couple this with the fact that many employers cover their employees'
health insurance in group schemes, and the danger of exclusion
from cover and even work is a real one. In the UK, the existence
of the National Health Service removes this problem for most people.
If the UK Government were to follow the policy of the Scottish
Executive, the same would also be true of long-term care.
1.4 Currently, insurers seek information
that is already known to the individual. If a requirement for
genetic testing for insurance were to be introduced it would certainly
alter the situation dramatically. Should insurers seek to change
policy in this way the public and professional backlash would
be considerable. In GIG's view, the taking of samples without
clinical need would be unethical and if done without consent would
probably constitute an assault. In sum, it is a policy that GIG
and probably all other genetic support groups would resist strongly
were it even to be mooted. In reality however, there is little
evidence that the insurance industry is thinking along these lines,
and the Association of British Insurers has repeatedly stated
that no such requirement will be introduced. We would caution
against repeated hypothesising that such a policy might be introduced
in the absence of any serious evidence. There are real problems
to address as it is, and these are not best addressed by alarming
the public about what might be the consequences of such a volte
face by the insurance industry when there is no evidence it
2. What do you feel to be the main benefits
and disadvantages of insurance companies using genetic test results
in assessing policies?
2.1 Families with rare conditions such as
Huntington's disease and familial Alzheimer's are those for whom
the debate about predictive data on healthy individuals is currently
relevant. Materially more would probably gain than lose from the
use both ways of predictive DNA test results compared with not
using the results at all. For many people in particular insurance
contexts, the possession of a family history of such conditions
is sufficient to make the insurance product unaffordable. In such
cases the extra loading due to a DNA test result indicating a
higher risk is therefore immaterial. But on the other hand those
shown by a test to be at much lower risk could be offered normal
rates. Regulators and policy makers should take care to ensure
that they do not make things worse by simply banning the use of
data altogether, or by making changes that the insurance industry
then reacts to by protecting its own interests at the expense
of groups of genetic patients.
2.2 As a matter of social policy it has
been suggested that test results indicating that a person does
not possess the disease-causing gene variant should be used but
not those indicating the presence of the disease-causing gene.
Evidence suggests that, as long as standard family history data
and other medical information was still used, insurers would face
only a very limited amount of adverse selection now and most probably
in the future as well. Such a policy would benefit some individuals
today. But that would only come at the expense of those in the
family history "pool" if the rates offered to those
with a family history were adjusted upwards based on estimates
of how many might also be in possession of DNA test results indicating
a higher risk. If the policy of not using test results indicative
of the presence of the disease-causing gene is adopted, measures
should also be put in place to ensure that family history levels
are not adjusted upwards. Once again, regulators need to think
carefully about the knock on effects of their actions if people
are to benefit.
2.3 In GIG's view, a system of solidarity
should hold in health and other areas such as long-term care where
the needs of the individual are being met. In relation to life
insurance some form of disaggregation according to risk seems
inevitable. It is a question for debate and public policy how
far that should go. Currently risk pooling in the former areas
is achieved through the NHS and in a more limited way through
the state provision that exists for long-term care and through
forms of disability payments to those unable to work. In these
areas the insurance markets are quite small, though growing. If
insurance were to become the primary means through which individuals
secured the services they needed in these areas, GIG would press
for a system of non-disclosure of all health data.
2.4 Working on the assumption that some
form of genetic data (whether arising from DNA test results, family
history or other clinical symptomatology) will continue to be
used, the question arises as to the extent to which a company
can, in pursuit of its commercial strategy decide not to accept
a particular type of business, even after following a rational,
reasonable process. What would be the implication if a large number
or all insurance companies were to go down this same route? Would
there need to be an element of compulsion in order to make this
social good available, and if so, what form might it take? (See
section 3 below).
3. How effective do you feel the current
regulatory system is?
3.1 The issue of misinterpretation, specifically
the danger that data may be given a predictive power that it does
not merit, concerns GIG. The current regulation of predictive
tests results by the Genetics and Insurance Committee (GAIC) addresses
this in part. Specifically, the use of hurdles50 per cent
raised mortality and 25 per cent raised morbidityis a useful
barrier to the misuse of mild predisposition data. GAIC have only
approved tests in relation to one condition so far (Huntington's
disease, as of 1 February 2001), and do not expect to receive
applications for the approval of products in relation to more
than a handful of predictive DNA test results in the short to
3.2 However, the hurdle model does not address
the quality, that is the actuarial accuracy, of the data
that is actually used by companies. Couple that with the fact
that the hurdle only has to be cleared for one age group for the
condition to pass the regulatory test, and it is quite conceivable
that poor data could be used in assessing a number of conditions.
It should be noted that Huntington's disease crosses the hurdles
with considerable ease at all age groups.
3.3 The industry would argue that this is
not proof that data is commonly misinterpreted. It is also the
case that a hurdle model is the norm for the use of all data that
is typical of a free market system working on the basis of the
"freedom to underwrite". But, to maintain the focus
on predictive DNA test data on healthy individuals, if some of
this data were to be used in the future, the clear possibility
is that in the first instance associations with disease would
be generated rather than any other, possibly health giving, effects
of the same alleles. Similarly, if studying individuals with conditions
generates the data, the risk will be that the penetrance of the
allelic variants will be exaggerated (as happened initially with
3.4 This is an issue for the future, and
there are other factors that count against such a scenario, including
the implausibility of widespread testing in the clinical context
before measures can be taken to reduce what will in any case be
relatively small risks which may not cross the existing hurdles
used by GAIC. Presently, GIG's concern is that the rarity of
many genetic disorders can encourage insurers to adopt a cautious
attitude, one that protects their interests, when faced with genetic
information. This is because the numbers of people with such conditions
may be too small for companies to have an incentive to market
attractively priced products. Unless up-to-date medical information
is brought to bear on actuarial calculations, individuals will
be loaded on the basis of the risks run by people in the past,
or those in whom the phenotypic effects are clear and harmful.
3.5 There is anecdotal evidence that this
is what often happens in practice. It would be useful to research
this point further. In addition to studies using the experience
of GIG's member groups and other genetic charities, it would be
interesting to examine the models used by individual companies,
perhaps using applications by hypothetical individuals.
3.6 The concerns outlined above arise from
the rarity of the conditions rather than the nature of the information
used, whether it is medical data on someone already ill or disabled
with a genetic condition, family history data, or predictive DNA
test results on someone unaffected by an associated condition.
This reinforces the points made in 1.1 and 1.2.
3.7 To address these issues, GIG would like
to see an additional hurdle used within the regulatory process.
Companies that use genetic data of any type would need to be able
to show that the data they use is actuarially accurate in the
light of the most recent science. This would include an understanding
of therapeutic options as well as genetic, actuarial and epidemiological
data. What is accurate data may of course be a moot point. However,
a body such as the UK Forum for Genetic and Insurance could be
called upon to develop the best consensus available, based on
collaboration between academic actuaries, geneticists and the
condition-specific patient groups. The default position should
be that genetic data is not used until it has been examined in
3.8 To focus on predictive DNA test results
specifically, GIG takes strong exception to the possibility of
people not being able to be assessed as a standard risk as a result
of a test result that shows that they are free of the disease-causing
mutation. Currently, the insurance industry is operating according
to a principle of equivalence between positive and negative test
results. If they can't use one, they say, they will not use the
other. The result would be that someone with a family history
of an adult-onset dominant disorder, for example who has been
shown not to possess the mutated gene as a result of a DNA test
would nevertheless be assessed as if they hadn't had the test.
That would be absurd.
4. Do you feel that the use of genetic test
results could have an effect on medical research and progress
in your area?
4.1 We are not aware of any substantial
evidence of this, although it is of course a possibility. Samples
collected for research purposes should have no bearing on insurance
decisions, if for no other reason than that the information is
generally not fed back to the individual.
4.2 It has been suggested that the use of
genetic information by insurers might discourage people from taking
tests in the clinical context that have potential benefits. Again
though, there is little evidence of this, and some evidence to
the contrarydemand for genetic testing is rising across
the country and regional genetics centres are under pressure to
meet the increasing workload. Much of the debate about the consequences
of patenting the BRCA1 gene has focused on the assumed inability
of the NHS to afford to purchase the test for all those demanding
4.3 It could be that people are just unaware
of the possibility that test results may affect them in an insurance
context. There is anecdotal evidence that this is the case. But
there is also evidence that for those who are aware of the issue
the potential impact on insurability does not figure largely in
their minds when contemplating predictive testing for a serious
genetic disorderother issues, about health and their future
lives are more important.
4.4 To shed further light on this issue,
specific research looking at actual behaviour should be commissioned.
1 February 2001