mp_5_economie
π Health and biotech
Personalised medicine: custom healthcare on a national scale?

Will personalised medicine create problems for the economy?

Agnès Vernet, Science journalist
On February 2nd, 2021 |
4 mins reading time
5
Will personalised medicine create problems for the economy?
Aurore Pélissier
Aurore Pélissier
Lecturer in economic science at the University of Bourgogne
Key takeaways
  • Personalised medicine produces a lot of data, some of which is not directly connected to the original intended analysis and can even include data relating to the patient’s family.
  • This raises questions on how to communicate this information and its value for the doctor, the patient, and society at large.
  • It is also very difficult to accurately assess all the cost vs. benefits of personalised healthcare.
  • Lastly, this new health model involves ethical considerations, to ensure that access to these new treatments is equitable.

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.