The UK spends
£97 billion treating diseases but just £8 billion preventing them.
This imbalance is set to change according to government proposals. Under a
social prevention model, health advice would be tailored to an individual based
on several criteria including personal data, their lifestyle and demographics.
There are parallels to
insurance. The Association of British Insurers has reported that UK life
insurers paid out £5 billion in income protection, critical illness and
life assurance claims in 2017.1These claims payments represent
amounts paid when peoples’ health has failed. While not every diagnosis or
early death can be avoided, providers could offer more to help customers
mitigate risk and stay healthy.
This predicament is
fuelling interest in matching insurance programmes to fitness data. There are
multiple digital-based solutions available to help with ongoing engagement
post-underwriting - a white space for insurers to move into. Gen Re is
active in researching technology of this type which has led us to
collaborations with a network of established companies and startups in an
effort to create a prevention model.
One such company is
PAI Health. They offer a proprietary, science-based algorithm that uses
cardiorespiratory fitness (CRF) to provide personalised guidance on how
much exercise is needed for optimal health.
In a 2018 article,
Mandsager et al. confirmed CFR is a modifiable risk indicator of long-term
mortality that is quite independent of age, sex and comorbidities. CRF is also
associated with cardiovascular and other health benefits, including reductions
in coronary artery disease, hypertension, diabetes, stroke and even cancer. CRF
is inversely associated with long-term mortality with no observed upper limit
of benefit. Extremely high aerobic fitness was associated with the greatest
survival.2
That said, taking the
right dose of physical exercise is very important. Too much exercise means a
risk of adverse outcomes leading to the idea of a U-shaped dose-response
association between exercise and cardiovascular events.3 PAI Health
works by linking the individual to the dose.
This personalised
approach is critically important to ensure an insurance programme is built
around physical activity that appeals to the broadest range of people; and not
just those who live in Lycra. In other words, an insurance programme that
provides benefit to everyman based on achievable yet therapeutic levels of
everyday physical activity.
It can be challenging to
untangle large amounts of data and turn it into meaningful health insights.
It’s important that there is evidence to validate the algorithms and
"health scores" promoted in apps. All exercise is beneficial to
health but it's well known that steps lack scientific reasoning. A daily target
of 10,000 steps is daunting, even unrealistic, and lacks any calibration
to the individual and their physical capability.
PAI Health avoids
these problems. The Physical Activity Intelligence (PAI) algorithm was
invented by Ulrik Wisløff, head of the Cardiac Exercise Research Group and
professor at the Norwegian University of Science and Technology. External evidence
supports the conclusion that meeting a personal PAI target cuts cardiovascular
risk, significantly reduces other lifestyle-related diseases in men and women
of all ages, and increases life expectancy. This has been shown to also be true
in patients with established cardiovascular disease.4
Preventative medicine is
about ensuring people take greater responsibility for their health and
well-being. Most insurers could do more to engage policyholders in this way.
Research suggests consumers increasingly value experiences above physical
things. Can a new breed of protection products offer people more of an
experience? A policy that actively involves them in protecting their own health
could offer that.
For any national health
service to link care to personal data requires the highest standards of data
privacy, and insurance is no different. While a prevention approach to
healthcare is unlikely to be without controversy, the major barrier to a social
prevention model is diverting funds away from treatment. For insurers the
problems may be less knotty. Elegant solutions like PAI Health are ready
to be utilised. Contact your local Gen Re representative to find out more.
Endnotes
2. K. Mandsager,
et al. (2018) Association of cardiorespiratory fitness with long-term
mortality among adults undergoing exercise treadmill testing. JAMA Network
Open, 2018;1(6): e183605. doi:10.1001/jamanetworkopen.2018.3605.
3. A. Merghani,
et. al. (2016) The U-shaped relationship between exercise and cardiac
morbidity. Trends Cardiovasc Med. 2016;26(3):232-240.
doi:10.1016/j.tcm.2015.06.005.
4. Kieffer SK,
Zisko N, Coombes JS, Nauman J, Wisløff U, Mayo Clin
Proc. 2018 Sep;93(9):1191-1201)
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