How healthcare analytics can ensure delivery of high quality patient care


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Healthcare vertical can leverage big data analytics to achieve better prognosis, effectively do remote patient monitoring and dig into combined clinical and genomics research data to suggest personalized treatments for patients


In a bid to deliver high quality healthcare care and improve patient satisfaction, public and private sector hospitals are today looking at streamlining workflow processes, integrating healthcare related data and securing information exchange. Like many developing nations, India too is exploring all ways and means in providing good, cost effective healthcare to its citizens. In doing so, healthcare organizations are increasingly realizing that IT solutions can actually help them meet this challenge by optimising resource allocation and plugging inefficiencies that cause delay in treatment. 

One of the technology solutions that can be leverage quite effectively by healthcare organizations is big data analytics which can go a long way in reducing the cost of healthcare care and improving patient outcomes which in turn could pave the way for a new age in healthcare. Let us look at some of the ways in which healthcare vertical could leverage big data and analytics for providing high quality of patient care both for inpatients and outpatients. 

Healthcare analytics

The healthcare industry is fast moving away from a paper based systems to Electronic Medical Record (EMR) systems. So far, much of this data was locked in a system designed to treat patients on an episodic fashion, and may not have contained the full longitudinal health record of the patient. But with the maturing of some solutions based on big data architectures, the ability to unlock and analyze this information is now possible. The Chief Medical Information Officer or Chief Research Officer  at many healthcare organizations are using these tools to derive scientific evidence that will help them validate the treatment being given to a patient as the most effective and efficient care at the best cost.

Remote patient monitoring 

In many countries, technology is enabling healthcare providers to closely monitor patients in their home on a real time basis. The care givers are monitoring home devices such as glucometers, weight scales, pedometers and others to understand how the patient is faring day to day. For example, if a patient is suffering from a chronic disease such as diabetes or congestive heart failure, the ability to monitor him for weight gain, blood sugar levels and exercise attempts will allow the care team to proactively contact the patient and provide help or recommend his report to an emergency room for immediate treatment if need be.

Another example where real time in-home devices can be used is, for independent living. Just because many countries are experiencing an ageing population, does not mean that the people will want to give up the ability to live alone. In such a situation having the ability to covertly monitor the person, with their permission, provides a level of safety to determine if someone has fallen, not gotten out of bed, or has been missing meals. 

The facilities to extend the healthcare system into the home of a person allows for a much better quality of life for the patient as well as to reduce operational cost for hospitals. However the volume and velocity of the data being collected, as well as the real time nature of the analysis and action require health care organisations to put in place a big data solution. 

Tapping into clinical and genomics research data for personalized treatments

Advances in medical technology have changed the way doctors monitor and treat patients. With the cost of DNA sequencing becoming affordable in many parts of the world, the emergence of personalized medicine is becoming a reality. There are many drug therapies that have been found to be effective for a certain group of patients with specific gene expressions. The ability to determine if a patient has the genetic gene expression before treatment begins allows for a better prognosis. 

Many research institutes, academic medical centres, drug makers and contract research organization are looking for technology solutions that will help them combine clinical and genomics research data in order to determine the effectiveness of personalized treatments.  In order to achieve this, many hospitals will be looking at adopting solutions such as big data analytics, over the next few years.

No-where is the transformative power of big data analytics more meaningful than in the health care sector. The need is to identify the potential that big data analytics holds in itself to transform the way healthcare vertical has been traditionally responding to the patients needs, so far.

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