In the healthcare industry, the digital revolution affects two major areas: big data and eHealth (digital tools applied to healthcare). The availability of massive volumes of data is a hard fact. This exponential rise has layed the foundation for the medicine of the future, caracterised by 5 Ps: preventive, predictive, participatory, personalized, pertinent.
Historically, the expression “4 Ps” comes from marketing. In the mid-20th Century, marketing experts promoted an approach to their business with four variables: product, price, place, promotion. With the digital revolution, the 4 Ps were used to describe a new form of public action that consolidated traditional public policy. This new public policy responds to four major principles, the 4 Ps: personalized, predictive, preventive and participatory. Algorithms are now at the core of public policy, but the real innovation is user feedback. Users participate and cooperate permanently. Public action becomes personnalized, predictive and preventive thanks to appropriate solutions based on the knowledge provided by big data. The “4 Ps” are also at work in healthcare. A fifth “P” should be added: the “P” of pertinence. Healthcare is assessed according to different criteria, but from the patient’s perspective, the matter ultimately boils down to the pertinence of the treatment history.
Healthcare becomes both predictive and preventive thanks to data often generated by the patients themselves. Medicine will be better able to predict the risk of developing a particular disease. The segmentation of the population, treatment and prevention programs will also be improved. With the exploitation of health data, medicine will be able to predict before preventing – in other words, target the people who need a specific preventive measure.
From an economical standpoint, prevention policies will be much more efficient, thanks to increasingly adapted and personnalized medicine. Predictability sheds a new light on the issue of prevention and that of personalization. Big data will also allow more participatory medicine. This rises the issue of the involvement of patients themselves in monitoring the treatment of their disease. Participatory medicine will be more pertinent because health data will deliver more accurate diagnoses then the brain of a single doctor facing a patient. Concretely, the ability to pool all available data worldwide and assess each precise case makes it easier to take appropriate and pertinent decisions. For health professionals, big data supports the increasingly sophisticated algorithms of clinical decision making and practitioners are now able to leverage the scientific literature of evidence-based medicine. These powerful capabilities herald promising prospects and the evolution towards increased prevention and personalization should further accelerate as the volume grows and data availability increases. Automated and individualized information systems will ensure a health offer that is both global (in time) and personalized (adapted to each patient and their unique pathologies).
However, predictability poses both a technical and ethical issue. A technical problem, already identified during the last twenty years: predictive medicine makes solidarity insurance even more difficult, if not impossible. And indeed, if individual pathologies become predictable, it becomes difficult to insure them collectively. The greater availability of information affects solidarity i.e. the sharing of risk. Tomorrow, individuals that have been genetically tested and predicted as healthy for the rest of their lives could, in the absence of regulation, disaffiliate from compulsory health insurance. The problem of insurability is further compounded by an ethical issue. Predictive medicine poses a moral and ethical problem that is yet to solve. How do we inform more or less healthy adults, parents, or even children, on how they are programmed to die? The issue of the place of predictive medicine is a problem that stretches far beyond the scope of science into the field of moral. Predictive medicine is a promising field. But it still needs clearly defined limits.
The second issue of the digital revolution focuses on digital tools, e-health. For health professionals, the old field of telemedicine will quickly evolve thanks to the exchange of data and files. At an individual scale, the smartphone will become the new health auxiliary. In this regard, access to mobile phones being much more widespread than access to clean water, the penetration of health technology is not only reserved to wealthy countries but reaches the entire planet.
First, we need to put in perspective the potential value of these connected devices. People will tend to believe they can manage their own health with personal sensors and receivers. But in a field such as health, like in any other digital field, we need to be careful about the consumerist, almost recreational dimension. The involvement of isolated or poorly trained patients may not be as useful as it seems. Loading a step counter into your smartphone is not necessarily the best solution. Who should the data be sent to? How should it be exploited? Without a rigorous organization and solid networks, these applications may not be of great value.
Many data streams will be useless. However, there is a much more organized and integrated approach to care pathways and health data generated by patients. For example, experimental programs have been launched a few years ago to monitor patients suffering from chronic renal failure. These patients are experiencing kidney failure in a pre-dialysis stage. They will inevitably be forced to connect to a machine several times a week, which is both invasive for patients and very costly in terms of health insurance. Patients were provided with a tablet on which they would record simple physiological data about weight, diet or edema, on a weekly basis. Once the information is sent to an expert center and analyzed by a nephrologist, it becomes possible to adapt the diet or medication seamlessly. This method allows to postpone dialysis by seven years. The benefits for the patient are huge, both in terms of costs and confort.
From a technological perspective, beyond our individual devices, big data fuels a big bang in the healthcare industry. When correctly processed, the collection and analysis of large data sets represents an opportunity for increasingly accurate diagnoses, while also cheaper, thanks to the limitation of interventions. In the field of healthcare, big data is helping big brother in controlling, diagnosing and treating patients. While this evolution may raise many suspicions, it also obeys a necessity. To improve the reliability of diagnostics and therapies, we need to provide computers and practitioners with both experiences and data. Processing capabilities and IT progress exponentially, thereby supporting the advances of medical treatment.
Opportunities call for challenges, and the deepening of the digital revolution has implications for the entire healthcare system. The five positive Ps of the digital revolution must avoid at all costs the additional P of “perdition”. While digital technology coupled with biotechnologies can certainly improve both diagnosis and treatment, it can also endanger the healthcare system. Faced with these technological and scientific developments, some believe that healthcare is facing the same situation as major labels of the music industry. These large companies were unable to foresee the revolutions at work and failed to adapt to their aftermaths. In the 1980s, these companies thought their job was to find talent and make CDs. They never saw the arrival of the Internet, Youtube, Napster, etc. and were swept away by technological progress.
In the world of healthcare, relationships with digital giants such as GAFA (Google, Amazon, Facebook, Apple) are complicated. Some digital giants invest dramatically in transhumanism and new technologies that support the strive to improve the human species. But this isn’t the crucial point. The universal digitization of the economy and lifestyle has an impact on our health and health data. Our consumption habits, our searches on the Internet, our emails, our exchanges on social networks give many clues about our health hygiene and affections to digital companies. Even without a direct access to our medical data, these companies can predict with fair accuracy our medical history, risk behaviors, drug, drinking or smoking habits. If well processed, the information collected on the Internet can turn into valuable health data. In other terms, the management of this data is the next major challenge. In this regard, the discussion – or even the fight – over the management and sharing of information has only begun.