llions of Internet users as is the case today. But in a more optimistic way, we can recall that there are also examples of success of an autonomous management of acts by the patient.
In the end, we can see in the emergence of this patient autonomy certain risks involved, and also many reasons for hope.
In any case, whatever the degree of dissemination, these connected tools will certainly restructure the medical landscape. One can especially imagine that they will make up for any shortages of doctors in the future.
The evolution of the insurer profession
The third trend concerns the insurance profession and its evolution. The latter may be interested, as we alluded to previously with the case of Kaiser Permanente, in becoming a care provider in search of efficiency by participating, in partnership or directly, in the development of integrated care networks. But above all, it appears that with the rise of ICT, the insurer will be increasingly confronted with questions of disease risk prevention. The impact introduced by ICT is in fact to give additional possibilities of information on the risks incurred in health individually by each insured, and to develop preventive actions accordingly. Connected tools provide capabilities for monitoring the health status of any individual up to now unthinkable (insofar as a data recording system is set up between the insurer and the insured).
This concerns the prevention of the disease, depending on the risk factors known to the person (history of cardiovascular disease, pre-diabetic state, for example), or even in principle by playing on the maintenance of a good state of health.
This concerns secondary prevention focused on known weaknesses: to an asthmatic person, we will send a warning signal if they are going to areas at high risk of crises; to an elderly person prone to falls, we will equip their floors with “magic carpets” capable of detecting suspicious movements and informing them of a deterioration in their mobility.
Finally, this concerns preventive approaches based on predictive medicine. With the conquest of the human genome, knowledge of the risk profile of developing certain diseases (in particular, cancer) becomes possible. On this observation, we can reasonably envisage preventive actions of a new type, knowing nevertheless that: at risk related to alcohol or tobacco consumption); (ii) the relationship between prediction and the onset of the disease is complex. In many cases, the genetic aspects mix with environmental factors. Furthermore, the state of knowledge is still partial. For example, we have known for the past fifteen years that the risk of developing Alzheimer’s disease is very high in people with the apoε gene. However, having this genotype is neither necessary nor sufficient to develop the disease. In other words, people with the apoε gene may never develop Alzheimer’s disease, and others without it, can. The reasons for the onset of the disease are still too unclear.
All these elements combined tend towards the development of individualized insurance cover, based on prevention measures which are itself personalized. Indeed,better knowledge of known risk factors, such as predictive factors revealed by better knowledge of the genetic heritage, should help to specify preventive actions according to the profile of each individual. The challenge that seems to be taking shape in the insurance sector is then that of developing insurance models based on personalized prevention programs in addition to curative care. It is a question of considering support services for the patient throughout his life, upstream of the illness, either directly with the insured, or via the employers, and the theme of health at work.
In this context, a first question aims to understand the role that members of the GAFA (Google-Amazon-Facebook-Apple) could play. These companies have the potential to collect data on the behavior of individuals (and therefore policyholders), and to process databases (in the context of predictive medicine) which can lead them to question their introduction 