Using Data Analytics to Save Lives
The latest database analysis tools and techniques cannot just benefit businesses – when used in a healthcare setting, they can actually save lives.
Everyone knows that this is the age of big data. The technological revolution has brought with it more information that anyone could have imagined 20 or 30 years ago, and it is all right there at our fingertips.
The benefits from a business perspective are obvious – by having better email data at our disposal, we can create a far more targeted and effective digital marketing campaign, leading to an improved return on investment and a stronger bottom line. Data analytics can also provide insights that have a fundamental impact on your overall strategy, giving you the ability to better anticipate and meet customer demands, and providing a genuine competitive edge.
When the implications of big data are considered in the healthcare sphere, however, the possibilities go beyond mere business results. When it comes to medical data, the internet is even more awash with information than in other sectors, and the phrase “at your fingertips” becomes somewhat ephemeral – for sure, the information you need is there, but can you find it and put it to the best possible use to benefit those who need it most?
Predictive Data Analysis
Doctors are intelligent people, in whom we place our trust and our lives. But they are not walking encyclopaedias, and the advice they give is based on years of documented research and knowledge that has been accumulated by their contemporaries, and those who have gone before them.
The information they rely on is broad and complex, and the inevitable variability in the results of numerous treatments provides a textbook recipe for complex data analysis. Even if doctors had the mathematical skills to perform this kind of analysis and compare it with their own patient’s circumstances, they would be spending more time performing data analysis that patient consultations.
This is where modern data analytical tools can make such a difference to healthcare, and related disciplines, such as the insurance industry and the pharmaceutical sector. The methodology uses the latest technology and mathematical methods to trawl the vast amounts of medical information, finding what is relevant and analysing it to accurately predict outcomes for specific patients. The data might include information relating to past treatments on a variety of patients, or cutting edge research papers published online in a variety of databases, journals and other repositories.
Analysis of this sort helps predict the best course of treatment for a specific patient exhibiting specific symptoms, but that is only the start. It can also flag up correlations and associations that we would never spot with the naked eye.
These include parallel patterns such as hospital readmission rates, responses and side effects to specific medications and correlations relating to long term wellness.
It is important to remember that data analysis is a discipline that is developing every day, and over the coming years, the implications could be staggering. Pharma giant Bayer recently ran an ad campaign in which a woman receives a note saying “Your heart attack will arrive in two days,” with a strapline that actually, we do not get a warning like this.
In the brave new world of data analysis, such warnings might not be such a far fetched proposition.