A Taxonomy of e-Healthcare Techniques and Solutions: Challenges and Future Directions

Abstract

Technology has intruded all spheres of our lives, whether it be communication, travel, work, or leisure. Industries have been quick to respond to our growing needs and have explored technological interventions to aid their aid. Healthcare, on the other hand, has been slow in adapting to the evolving technology. With the rapid increase in the world population and people's life expectancy and the uncertainty of global pandemics like COVID-19, there has been a massive shortage of healthcare workers across the world. It is of utmost importance for technology to come to the aid of the healthcare domain. The purpose of e-healthcare is to improve the quality of patient care and ease access to healthcare and prepare for the high demand in the healthcare sector that we are witnessing amidst the COVID-19 outbreak in 2020. The research work done in the e-healthcare domain is majorly focused on one or other specific aspects of e-healthcare. It fails to provide an overall picture. This survey paper is aimed at providing a broader view of the techniques used in the e-healthcare domain. The survey broadly classifies the e-healthcare techniques into four categories based on the analysis done on the existing e-healthcare proposals: Machine learning techniques, cloud computing techniques, privacy techniques, and data analytics techniques. It was observed that big data analytics and 5G technology can play a prominent role in shaping the future of e-healthcare. Big data analytics can be used for drawing useful insights from healthcare data. In contrast, 5G technology can be used for scaling purposes by achieving ultra-low latency, high density, and high bandwidth requirements. Besides, suggestions for improvement and future research directions in the e-healthcare domain have been explored for a better understanding of the readers and to motivate future work.