Unapređenje koncepta medicinskih informacionih sistema u cilju smanjenja efekata i posledica epidemija i pandemija

The emergence and fast expansion of huge epidemics and pandemics besides the effect on everyday life of people through the change of health, economic, social and political routine, greatly influence the existing IT products, with a significant emphasis on large information systems which are exploited daily. The main issue which naturally arises is the effective decrease of the rapid spread of epidemics. The reduction of disease transmission is most effectively achieved by socially distancing people and reducing their contacts. In addition to engaging health resources in combating the epidemic, there is also a need for the intensive use of IT solutions that can help slowdown the spread of epidemics, enable continuous monitoring of the affected area, enable rapid and early diagnosis of diseases, reduce contacts between infected and uninfected people, predict trends of the spread of epidemics in order to act in a targeted and proactive manner, etc. This doctoral dissertation presents an improved concept of medical information systems which is aimed at the reduction of effects and consequences of epidemics and pandemics. It enables a better response of the medical information system to the challenges which will be posed by future epidemics and pandemics, not just the COVID- 19 pandemic, which was taken as a case study. The concepts proposed in this doctoral dissertation are applicable to all existing medical information systems both in the Republic of Serbia and in the region. The main objective of the scientific research is to improve the concept of medical information systems in order to reduce the effects and consequences of epidemics and pandemics. The most important objectives of this doctoral dissertation are: the improved concept of medical information system, improved level of collaboration of medical information systems with other information systems outside of the primary health care level, increased level of social distance by implementing new medical information system services, proposed machine learning model for the fast and early diagnosis of COVID -19 disease based on radiological images of lungs, timely and accurate reporting in order to provide conditions for the rapid and adequate response and planning of human and material resources allocation, confirmation of proposed concepts by the practical implementation of certain proposed services and functionalities built into the real medical information system MEDIS.NET which is used daily