Büki András

Prof. András Büki


Digital Support Assistance for Prevention and Treatment of Brain Injuries​

In Hungary traumatic brain injury (TBI) is an “epidemic” affecting all age groups of the population, meanwhile there is no accurate clinical register available to provide basis for standardized protocols for treatment and prevention. At the same time, the modern health care systems generate a substantial amount of digital data practically impossible to process, limiting
efficiency and cost-effectiveness of health care providers. In addition, synchronization of various digital data resources is lacking.
It is an international requirement to provide real-time data sets and rapid analysis of them for decision making support. These data sets could provide the fundamental basis of the decision-making algorithms, which could be involved at all levels of healthcare systems from screening procedures and general practitioners to acute clinical treatment and rehabilitation processes.

Based on these facts, our objective is to establish a multimodal digital support system that helps:

  1. to develop a region-specific model for digitalizing and synchronizing data generated during medical therapy,
  2. to develop an interactive matrix (which can be later generalized to be applied t other medical fields) for supporting the communication between health care providers,
  3. to provide basis for the development of supporting applications for decision making based on digital data,
  4. by utilizing the digital data, to estimate outcome and risk stratification, as well as to highlight high-risk groups and to support individually personalized prevention.

For these purposes we obtain and collect patients data by applying the mentioned multimodal and multidisciplinary approach. In this manner we have reliable data covering the entire spectrum of the disease, including the indicative biomarkers for the pathomechanism and outcome of traumatic brain injury along with detailed information regarding the intensive care therapy until long-term outcome.

According to this, the subproject is built up as follows:

  1. Laboratory Medicine: to acquire laboratory parameters
  2. Biomarkers: to identify biomarkers that may be used for screening / prevention later on
  3. Digital system for intensive care unit bedhead board: to record and upload all of the obtained parameters during the intensive care therapy
  4. Neuromonitoring: to assess derived parameters that characterize the physiological and pathological function of the central nervous system
  5. Neuroimaging: data from scans, scoring systems
  6. Electrophysiology: real time electroencephalography and its correlations with the above data in traumatic brain injury
  7. Establishment of a neurotrauma database, pain database, dementia register to provide basis for the epidemiological database
  8. Monitoring patient transport routes, predictive models for outcome and communication with the community to develop an audit system
  9. Neuropsychological assessment, registration of outcome