INTEGRATED MEDICAL DATA MANAGEMENT SYSTEMS REVIEW

Abstract

In recent years we’ve seen breakthrough research success in medicine and computer science enabled by novel technology advancements, data analyses capabilities and learning techniques. Despite this, quality care doesn’t have full cove­ rage even in developed countries and access to care is recognised as one of the biggest challenges to the global healthcare system. Bound with population growth in remote areas in developing regions, which lack skilled professionals and medical resources, as well as aging in developed countries this caused a strong need for increasing healthcare effectiveness. Enabled by development of cloud technologies, quick expansion of mobile network coverage and internet access Clinical Information Management Systems integrated with decision support systems, Telemedicine (inclu­ ding distributed Virtual Healthcare Teams and medical imaging), Mobile Healthcare, medical Internet of Things (mIoT), Consumer Health Informatics with personal intelligent health assistants, Health Information Exchanges and deep learning techniques for diagnostics and knowledge extraction are among the state-of-the-art solutions which are more or less successfully used for coping with the problem mentioned above. This paper reviews current situation with implementing these novel informational systems, analyses their advantages, drawbacks, implementation impediments and outcome effectiveness suggesting platform for empowering their integration and maximizing output of each module. Such solution will have a synergy effect and result in a drastic increase of medical resource utilization effectiveness, service quality and providing bigger and fuller coverage with less spending at the same time empowering knowledge exchange process and laying foundation for future development and innovations in the whole healthcare domain.