Medical Internet of Things and Big Data in Healthcare

Dimiter V. Dimitrov
2016 Healthcare Informatics Research  
sors, and network connectivity, which enables these objects to collect and exchange data [1] . Its impact on medicine will be perhaps the most important, and personal, effect. By 2020, 40% of IoT-related technology will be health-related, more than any other category, making up a $117 billion market [2] . The convergence of medicine and information technologies, such as medical informatics, will transform healthcare as we know it, curbing costs, reducing inefficiencies, and saving lives. Figure
more » ... 1 illustrates how this revolution in medicine will look in a typical IoT hospital, in practice. A patient with diabetes will have an ID card that, when scanned, links to a secure cloud which stores their electronic health record vitals and lab results, medical and prescription histories. Physicians and nurses can easily access this record on a tablet or Objectives: A number of technologies can reduce overall costs for the prevention or management of chronic illnesses. These include devices that constantly monitor health indicators, devices that auto-administer therapies, or devices that track realtime health data when a patient self-administers a therapy. Because they have increased access to high-speed Internet and smartphones, many patients have started to use mobile applications (apps) to manage various health needs. These devices and mobile apps are now increasingly used and integrated with telemedicine and telehealth via the medical Internet of Things (mIoT). This paper reviews mIoT and big data in healthcare fields. Methods: mIoT is a critical piece of the digital transformation of healthcare, as it allows new business models to emerge and enables changes in work processes, productivity improvements, cost containment and enhanced customer experiences. Results: Wearables and mobile apps today support fitness, health education, symptom tracking, and collaborative disease management and care coordination. All those platform analytics can raise the relevancy of data interpretations, reducing the amount of time that end users spend piecing together data outputs. Insights gained from big data analysis will drive the digital disruption of the healthcare world, business processes and real-time decision-making. Conclusions: A new category of "personalised preventative health coaches" (Digital Health Advisors) will emerge. These workers will possess the skills and the ability to interpret and understand health and well-being data. They will help their clients avoid chronic and diet-related illness, improve cognitive function, achieve improved mental health and achieve improved lifestyles overall. As the global population ages, such roles will become increasingly important.
doi:10.4258/hir.2016.22.3.156 pmid:27525156 pmcid:PMC4981575 fatcat:sbrdapvaxzao5hmvcc5xk2vv2y