Population Health or Personalised Health in Preventive Medicine

One of the common comments about modern healthcare is that we would do a lot better to focus on prevention of disease rather than treatment of disease. The argument goes that we could reduce the cost of healthcare by preventing diseases in the first place and through promotion of ‘wellness’. In principle this sounds like a fair approach but are we sure that this will be the case?

Many effective prevention strategies are already in place: clean water and food sources, fluoridation of water, vaccination against childhood illness, and screening for some forms of cancer. Many of these activities are also cost-effective. These are population level strategies.

But many for many other conditions the role for prevention is less clear. Populations turn out to be heterogeneous and many conditions, whilst common, are actually not likely to occur for any given individual. The way around this is to identify who should receive a preventive intervention by risk stratification. The simplest example is smoking. Smokers are approximately 25 times more likely to develop lung cancer than non-smokers. Lung cancer and other smoking related diseases contribute substantially to the economic burden of disease. So it makes sense to promote smoking prevention.

On the other hand – not every smoker develops lung cancer (‘uncle Eddy lived to 90 and wasn’t sick a day in his life’) and 10-15% of lung cancer patients are non-smokers. So as an intervention smoking prevention will not necessarily eliminate the development of new cases (like universal polio vaccination) but it will have a substantive impact.

One way to increase the chances of correctly identifying ‘at risk’ individuals for any given disease is to obtain more in-depth information about risk factors. For many diseases this will involve genotyping or knowing the genetic make-up of a person. It is now possible to sequence the whole genome of individuals and commercial ventures undertaking genetic screening for predisposition to common conditions such as Alzheimer’s disease already exist.

With the possible exception of public policy around obesity prevention is possible that most of the population health measures to prevent disease are already in place. The way to move forwards is to gather more information on genetic predisposition to disease in order to target efforts at prevention. Some of the genetic factors will provide targets for intervention. Some genetic factors will cluster together – e.g. a cardiac risk profile – and will help direct prevention. Whilst this is the is the logical approach it may not be as cost-effective as the population health approach, but then the population approach isn’t necessarily applicable to the problems not yet tackled.

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