TBI is an extremely complicated, non-uniform disease involving multiple inter-related pathophysiological mechanisms depending on the mechanism of trauma / injury, the type and location of brain damage, the local brain tissue inflammatory response, the systematic inflammatory response, individual underlying pathologies etc. Gender and pathophysiological diversity is another important but under-explored dimension in TBI. Precisionmanagement of patients with TBI is consequently ideal but currently elusive. In fact, except for antibiotics, health care professionals have few effective tools to prevent or manage the deadly evolution of oedema, haemorrhage, local and systemic inflammation (secondary brain injury) and multiple organ failure or the debilitating, chronic, psycho-cognitive dysfunction (chronic injury). Patient selection, targeting and timing of surgical interventions in TBI is an equally challenging task due to the above problems. Many randomised studiesof evidence based medicine, have yielded inconclusive and/or inconsistent results. Physiological monitoring of TBI patients in the ICU, produces a wealth of bio-signals locally (real time numerical data and waveforms), combined with images and stationary clinical data. All this data and resulting information are currently under-utilized, only partially stored and mostly being subjected to problem-driven use. Large TBI patients’ data-sets are being set up in the context of collaborative TBI research funding initiatives between the EU and the USA / Canada (https://intbir.nih.gov/), and in a number of FP7 funded networks (CENTER TBI https://www.center-tbi.eu/, CREACTIVE etc.), however, they do not store clinical data. Sharing of clinical data has also proven to be a challenging and elusive task, having to overcome a multitude of legal, ethical, technical and financial obstacles. In the context of this project, big data analytics technologies, which will also include patient specific information, can be used and to play a major role in explaining TBI's complex pathophysiology, in designing new bedside diagnostics and therapeutic interventions, in informing / enabling collaborative research, randomized trials and decision making, in shortening new drug development pipelines, thus improving patient outcomes and reducing cost. For the countries of the European South, and in Cyprus particularly, severe TBI constitutes a major public health issue and lack of specialized Health Analytics applications in general, another one.
