IoT and the Changing Face of Healthcare
- Competitive Differentiation
Publication | Update: Jan 2020
Using IoT in Healthcare
IoT apps have been widely accepted as a way of monitoring safety personally. Figures show that there are 23.2 million Fitbit users who are currently wearing devices that collect data regularly, including the number of steps taken, the length of time the wearer has slept, and their rest and active heart rate. After collecting data, data is then uploaded to secure the cloud server where immediate access is given to the user.
It is the strength of Fitbits-like wristbands that the healthcare sector has started to harness. Nonetheless, in order to implement the technology effectively and make it fully available, medical practitioners recommend that there must be a standardization aspect through the early stages of implementation, which should enable better scalability and affordability in the long term.
The now-prominent use of Big Data in the healthcare industry is combined with this IoT transformation. With the detection of disease outbreaks, diagnosis of chronic conditions, treatments for diseases such as cancer, and safe storage of electronic health records, there have been huge advances in its use over the past decade. Implemented outside of a hospital scenario, interconnected IoT devices are becoming more common, collecting and exchanging data using embedded sensors, as well as being able to speak directly to users. Facilitated as a diabetes coach to monitor glucose levels, check heart rates, and track patients with dementia, advanced technology in each device enables them to transmit signals directly to a hospital in emergency situations. When operated within a hospital, devices provide the increased ability to monitor the vital signs of a patient in real time. This can result in quicker diagnosis, quick execution of treatment plans, and more rapid discharge. The data collected is analyzed using machine learning algorithms before further evaluation along with a database of solutions collated from predictive analytical techniques, with the primary objective of assisting doctors in their diagnosis.
IoT tools and data gathering research were also implemented to aid in the treatment of newborn babies. The system is also being incorporated into NICU departments to assist with the treatment and care of premature babies by linking wirelessly wristbands worn by the mother and baby to the hospital network in order to keep both of them healthy. Following the introduction of IoT and Big Data to a medical situation, the next step should be to employ a data scientist with experience in managing massive unstructured databases and relying on non-conventional data management methods. This professional's primary goal is to recognize patterns and trends that run through the data that should assist with patient care when stored in a database. The use of Electronic Health Records is becoming more common and the knowledge provided by modern medicine is increasing, leading to better treatments. But for that to happen, it's data scientists who need to decipher the information.
IoT Architecture and Structure
In order to successfully integrate IoT in the healthcare industry, systems must be grouped around different network architectures to ensure any piece of technology is implemented and maintained at a high standard, leading to a zero-communication breakdown between the network and devices in principle.
Device management is the first aspect of the architecture to be introduced in relation to IoT. Usually falling within the remit of a Security and IT team member, ensuring that security protocols are followed during the implementation phase of new devices and preserved during their lifetime is the task of this person.
Infrastructure management is next on the architectural framework list. The speed at which equipment is connected is essential for how effectively implemented. Often overlapping with device management processes. Due to its computing limitations, multiple IoT devices are updated to boost their effectiveness by increasing their Cloud connection.
The main objective when adding IoT devices to a network is to use data control. This can be done favorably by technological incorporation of data management. Using the skills of a data scientist to leverage all of the data available, it offers the chance to uncover dark data, allowing for further insights and the positive upkeep of all collected data.
Risks and Security
The introduction of any new technology or tools in a new environment and many of those centers around protection is a risk factor. In the course of the IoT system implementation process, concerns will arise as to the safe storage of' information' data, how it can remain secure from cyber attacks and how networks can be built and monitored to avoid infringements.
It has become a common practice to recruit professionals with expertise to track large networks and technical infrastructure prior to the introduction of IoT tools, in particular in healthcare. Working alongside the Data Scientist, who will identify threats to a system, a DevOps engineer will have the know-how to develop, incorporate and update network security protocols, to stop threats and add an extra layer of protection to the collected data.
When the data obtained from IoT devices is connected to the network, it is compiled and stored in a hybrid cloud environment, which incorporates private cloud on-site servers and public cloud infrastructure such as AWS. Close devices to this infrastructure in which data can be safely stored ensure compliance with the safety protocols of the network and also allow data to be monitored continuously, as well as the network itself.
The data collected from each device, however, is not only a risk sensitive system but a primary objective for hackers who seek to infiltrate a healthcare system to get patient information. Preventing network breaches is a key part of the role of a DevOps engineers, and to ensure that data is kept completely safe from outside sources. From the first use of a device, engineers are able to enforce encryption on all collected information, which can then only be decrypted by a member of the data team.
Ultimately, furthering the use of the Internet of Things in the healthcare industry to improve treatment, develop cures and monitor health records, can only stand to improve performance overall. But in order to make the transformation successful, infrastructure and security should be the top priorities for providers looking to make the change.
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