IoT is making a possible new generation of medical solutions that significantly boost the core value proposition for healthcare sectors, and thus attract new partners and clients. Previously, medical device connectivity market was largely insignificant, but has now caught up rapidly and is expected to grow at CAGR of 38 percent in the next five years. This intense growth will lead to an increase in the connectivity of medical devices and patient health tracking devices in the market and, in turn, lead to an explosion in healthcare big data. IoT in healthcare is destined to grow along with demands in health organizations to ensure a seamless workflow. Bringing safety and health improvements through health-monitoring apps is the theme behind the penetration of IoT in the healthcare sector.
Hospital providers need to understand the detailed features (complications) of their network and how each device is operated within it in their IoT ecosystem. Focus on network functionality first and make sure the devices are in the right track and can co-exist with tools that are present in place. Most organizations don’t have device visibility and data analytics to understand whether the connected devices are in a continuous network and how they are functioning. Data analytics enables to monitor how the devices are working and behaving in the environment. Visibility and analytics implement corrections when a malicious change occurs with the devices.
Security in IoT is very crucial to preserve the privacy and safety of the patients. Segmenting and partitioning of the network into subnetworks add an extra layer of security, and in turn, device performance can be increased. Without segmentation of a network, the data is left open at a single point of vulnerability for hackers. Breaking up the data flow into segments assures that the complete data is not compromised if there is a breach. It is very important to lay a strong foundation for segmentation, and this is not a one-time exercise but a continuous task. For running the network seamlessly, regular maintenance and relative adjustments are needed.
Continuous tracking and observation of connected devices are important. Avoiding the disjointed approaches that are arising from multi-departmental initiatives can be successfully overcome by IoT. Core asset of IoT, the sensor data, generates large amounts of data; analyzing and deriving real-time intuition from this derived data has become a big challenge. A robust data analytics tool is needed to overcome this challenge.