There’s no bigger business than the business of saving lives and there hasn’t been a more pertinent time for businesses in healthcare to think out of the box to find solutions to pressing problems. As Centres for Disease Control and Prevention reported, in 2012, about half of all adults (nearly 117 million people) worldwide, had chronic diseases and conditions such as heart disease, stroke, cancer, type 2 diabetes, obesity and arthritis. The need is to prioritize prevention as much as finding cures for diseases as this is the only way to check their rampant spread.
In a short span of ten years, there has been a tremendous generation of data and the use of technology to analyse the same has given birth to a new industry, Big Data. By effectively using Big Data, healthcare businesses have found newer ways of reducing the number of preventable deaths, curing disease and improving quality of life, while cutting their business overheads and increasing profitability. Treatment modalities have transformed and that has a lot to do with the way healthcare professionals are using Big Data to make informed decisions about patient care. Now, the impetus is on understanding patient information better and quicker to predict the onset of illnesses and to stall them in the early stages.
START AT THE VERY BEGINNING
One of the most tangible ways data has changed healthcare is in the method used to collect it. Electronic Health Records (EHR) are now a reality across most hospitals in the U.S. (94 per cent adoption rate) and by 2020, a centralized European Health Record System is likely to come into being. EHRs have eliminated the need for paperwork, reduced data duplicity and also allowed for better treatment tracking. Today, the novelty of EHRs has worn off as technology has gotten way more avant-garde.
Telemedicine has been around for no less than four decades but mobile technology has changed the face of it with video conference tools and wireless devices. Remote yet personalized treatment has been made possible and this has significantly cut costs in healthcare. Patients save money on repeat visits to hospitals and doctors save on valuable time as remote treatment has made some facets of medical treatment location agnostic. Smart wearables have also made their way into daily life and it isn’t uncommon for friends and peers to exchange personal data that is collected by means of these devices. Industry experts predict that there will soon come a time when doctors rely on Big Data as step one in charting treatment plans.
The very fact that some companies are looking to collect and analyze an intangible variable such as stress is a testament to difference Big Data can make. The adoption of preventive analysis as opposed to traditional statistical analysis is a clear sign of things to come. Prediction modeling, the basis of preventive analysis, creates a prediction algorithm or profile of an individual using techniques such as artificial intelligence to analyze data. This can better individual outcomes, improve the accuracy of predictive research and lead to pharmaceuticals creating more effective drugs.
The common thread that runs through the applications of Big Data is the ability to provide real-time analysis of data. When it comes to making a decision on health, time is definitely of essence and further use of Big Data will help professionals and patients take quick calls without compromising on accuracy.