The Future of Education

In this paper we will focus on how education resources should be prepares for the current impressive increase of digital information produced in all aspects of social life (Big Data), and the exchange of Big data between cloud systems, mobile and fixed devices, in particular in the health context. Medicine is moving from reacting to disease to a proactive precision medicine or P4 medicine: personalized, predictive, preventive and participatory. The future foreseen is that computers will assist our health and disease conditions in more effective ways than nowadays but will use and produce more information: a medical check up will be supported by advanced artificial intelligence and personal patient-based modeling software designing a likely morbidity risk profile for different diets, exercise and behaviors of the patients. The P4 framework will need a radical change in mentality and will involve the integration of large amount of molecular and clinical data.

In this paper we first provide a quantitative estimate of the amount of molecular (genomic) and clinical data that is required by the P4 medicine program. Then we discuss the IT infrastructure that is required to sustain such amount. We believe there is an educational challenge that is important to consider in order to govern in an optimal way the transition to Big health data and P4 medicine.

Education will provide understanding of all aspects of P4 medicine, including molecular and clinical data privacy, for example awareness of the sources of leakage of sensitive molecular and social data, ethical and legal issues.

An important reason for the P4 and, simultaneously, an important educational challenge in medicine is the shift from single disease medicine (organ-centered) to comprehensive systems medicine focused on comorbidities (multi organ and multi process medicine). Comorbidity addresses the occurrence of different medical conditions or diseases, usually complex and often chronic ones, in the same patient. A common factor linked to comorbidity is aging and inflammation. Comorbidity studies have been based on chronic obstructive pulmonary disease, obesity, mental disorders, immune-related diseases, cancer, just to mention a few examples. This paradigm shift will change both the way physicians are educated and trained and patients are informed and self inform themselves through medical social networks such as patients like me or others.

The Big data conundrum and the implementation of the P4 medicine will expose patients to problems of privacy, anonymity and genomic data awareness. Given that participatory and collective engagement (say patients like me) will increasingly use new internet business models based on crowdfunding and crowdsourcing, these business models could find ways for sustaining better educational framework which are vital for the entire society sustainability.  Following this reasoning, we conclude the paper with models of future educational scenarios for Big health data.