Big data health: the 4 P’s of medicine

The creation of internal hospital warehouses makes it possible to collect data which is stored in multiple databases to make sharing and consulting easier for hospitals. The data can then be used to identify patients with defined characteristics for clinical research, to train groups in epidemiology and to generate new knowledge. Using this big data […]

The creation of internal hospital warehouses makes it possible to collect data which is stored in multiple databases to make sharing and consulting easier for hospitals. The data can then be used to identify patients with defined characteristics for clinical research, to train groups in epidemiology and to generate new knowledge. Using this big data opens up great prospects to develop the so-called 4 P’s of medicine:

  • Preventive
  • Predictive
  • Personalized
  • Participatory

However, let us not forget that quantity is not everything and that building useful and reliable algorithms for doctors means that we must first make sure the data itself is correct and that it is integrated properly.

The way scientists work is changing…

…due to how data is now shared, and we are seeing the emer­gence of data-driven research, or even ‘reverse’ research, algo­rithms and deep-learning technologies bringing about discove­ries which wouldn’t have been possible otherwise.

Expected developments cover a very wide range, from the de­velopment of new therapies and their adaptation to each in­dividual (precision medicine), the development of innovative diagnostic methods, to decision support tools or preoperative simulation, health surveillance, epidemiology and pharmaco­vigilance.