You seem enthusiastic about studying how this new medical approach is being implemented, and the unique questions it’s raising. You are also looking at the risks that it could pose for our current healthcare system. From an economic standpoint, what are the stakes of personalised medicine?
It’s a new area of research for health economists. It challenges our traditional fields of study – that is, the doctor-patient relationship, access to healthcare and medical and economic evaluations of therapeutic approaches [which determine how social security resources are allocated, to provide the best care to the population].
For us, personalised medicine means three major changes. The first is the shift from a one-size-fits-all system to an individualised system, using a patient’s genetic information. The second is the shift from a reactive approach, on the basis of symptoms, to a proactive approach, which aims to anticipate and prevent diseases before they even occur. Finally, this kind of medicine uses mass data, produced by new tools for DNA analysis.
Doctors are wondering how to interpret these results and how they should be given to the patient, especially when they indicate a certain predisposition (i.e. a stronger risk of developing a disease in the future). It’s also an indication on the way patients, civil society, and professionals prefer to communicate genetic data.
How is this different from traditional medicine?
In large part because of secondary data, which has nothing to do with the reason the patient came in for a consultation in the first place. Genetic testing often produces secondary data indicating a patient’s predispositions to other illnesses, with varying degrees of certainty.
In some cases, testing shows a predisposition to a disease for which treatments or prevention protocols can be implemented or the patient’s clinical monitoring can be adjusted. But sometimes there is nothing to be done. A typical example is Huntington’s disease (a rare, hereditary neurodegenerative disease with no real treatment). These predispositions can also affect other members of the patient’s family.
Why are economists interested?
They want to know more about the unique doctor-patient relationship, how we decide who can benefit from this genetic testing as well as who cannot, and therefore the ways in which this medical approach can be accessed. In a paternalistic system, the doctor makes the decision. But in a system where decision-making is shared more evenly between the two parties, the doctor should allow the patient to choose their own preferences about what they want to know and what they would rather not know. This can be important for economic evaluation in genomic medicine.
But this secondary data is not necessarily useful from a clinical point of view?
Reporting a patient’s secondary predispositions can lead to the implementation of prevention protocols, or modification of therapeutic monitoring. For example, if we know that a patient is predisposed to a very aggressive kind of breast cancer, we can recommend preventive surgery. The American College of Medical Genetics and Genomics recommends advising patients of these kinds of predispositions, and keeps a regularly updated list of actionable genes, for which effective treatment is possible.
In this context, it’s clear that it is in the public interest for the regulator to provide access to this data. At the moment, it’s not authorised. But disclosing this information can affect an individual’s behaviour. From a medico-economic evaluation perspective, this involves going beyond clinical criteria. From the patient’s point of view, it can be valuable to access this secondary data, even when their genes are not actionable.
This is what’s called data’s personal utility – knowing can influence our choices. A diagnosis has a psychological, planning and clinical value. Psychological value means the intrinsic value of the information, the fact of knowing that you are predisposed to a certain disease. Planning refers to the way it can impact life choices, such as the decision to have another child or to buy a property.
And in financial terms?
Beyond results, genomic medicine is also shaking up the economic side of things. For example, with rare diseases, genetic profiling can replace a myriad of tests and avoid years of incorrect diagnosis, therefore resulting in savings.
It is very difficult to assess the average cost of personalised medical testing. Throughout the world, attempts are being made to put a figure on this kind of care. In France, we know that the National Health Authority (HAS) is trying to assess whether personalised medicine can be provided to patients for an acceptable cost. But the technology is expensive. Pursuing it may eliminate the possibility of adopting other strategies that are just as useful from a clinical point of view, as personalised medicine would take up a significant part of the limited public budget. It’s something one should keep in mind.
What shifts are you expecting to see from a healthcare pathway point of view?
Nowadays, genomic analysis is the last step. It occurs only when the patient has been diagnosed and is seeing a specialist. But according to the France Genomic Medicine Plan, in the future, this analysis could be used for common diseases. Does this mean that one will need their own genetic data to receive healthcare? That is not what geneticists are suggesting, but this is an important question.
Personalised medicine has already brought shifts. Multidisciplinary consultations had to be created, as well as new professions, specifically in biotech. This raises issues for education and training policy.
We might also see shifts in the insurance sector. Our insurance system is financed collectively and based on the fact that individual risk is masked by a veil of ignorance. If, with this data, each person’s risk is revealed, this could have consequences such as insurers refusing to cover some people. Insurers could also place individual responsibility on patients, mandating behavioural change if certain predispositions are identified. We already know that preventive behaviours depend on a patient’s social environment. This means there is a risk that social health inequalities could widen if this approach becomes widespread.
