A Compression Technique for Electronic Health Data through Encoding
Subrata Kumar Das, Mohammad Zahidur Rahman · 2021 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) · 2021
Healthcare organizations currently use a large set of IoTs and other medical diagnostic equipment to collect patients' data, which results in a large volume of data. The continuous sharing and accessing of massive healthcare data are raising a concern either in data storage and transmission speed via telecommunication medium, especially in the slow-speed network. If the stored healthcare data is sent to users directly from the databases without any compression, the message will be heavy. These heavy messages increase the network overhead and take high latency to pass the data over the slow-speed networks. Those messages should be compressed and send in low latency through the slow-speed network to get better performance. Therefore, this paper aims to reduce the data size by encoding and compressing them prior to transfer to the users from healthcare databases. A novel compression technique is proposed through encoding that could reduce the medical data size before transmitting over the network and decode again on the end-users side. To validate the approach, we here use medical prescription data. The results show that the proposed method can compress data with encoding before sending and decode successfully and efficiently after receiving from the end-users.