Embracing the evolution of real-time data analytics in healthcare

Embracing the evolution of real-time data analytics in healthcare

Healthcare Tech Outlook | Thursday, December 06, 2018

Real-time analytics, also known as dynamic analysis is the use of, or the capacity to use data and related sources as soon as the data becomes available. It allows business to react without delay and prevent problems before they come in. Users can get insights immediately after the data enters the system. Implementing real-time data analytics will help in crisis management, an increased company vision, quick and less costly changes, better resource allocation and money management, effective application and website management. These applications of real-time data analytics help the companies in their long run. Industries like banking and finance, mainstream advertising, retail and consumer shopping, and healthcare are embracing real-time data analytics. They are gathering data from market trends to tracking customer purchases and everything in between.

Healthcare, in particular, is making use of the application of dynamic analysis. The collected data can provide deeper penetration by identifying trends, and healthcare providers can have an actionable awareness up to the minute. Smart wearable is already enabling healthcare vendors to monitor patients both during their hospital stays and discharge. There is an increase in the population of people with chronic illness, so is healthcare costs as the patients are found with greater needs.

Real-time data will be an added asset as the industry is trying to tackle these pain points. It can give a deeper comprehension of patients at the point of care by assuring a proactive care individually. Combining the data can help identify the high-risk patient who may need an extra care. Companies which provide valuable indications to medical staff about conditions of the patients and giving advice are already in the run.

The potential of such a robust technology is used in early diagnosis of diseases too. Voice communication with the medical staff can be considered the best example of this application. Where the medical staff asks questions based on the voice communication of the patient and gathers information for diagnosis. Apart from this with the help of an electrocardiogram enabled wearable device, the patient can track their heartbeat that will help in identifying undiagnosed conditions.

Dynamic analysis has to play a role in detecting medical frauds too. With the analytics embedded in the software of voice analytics technology trickery in the call could be pinpointed.

 Unless the past, the current generation is trivializing the use of real-time analytics as it can power nearly every industry and profession including healthcare. Where in the past it was reserved for governmental applications and heavy industries.

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