Which tangible changes can data analytics make to the healthcare sector?

There’s a lot of buzz going around concerning the potential impact the widespread implementation of data analytics would have on the healthcare sector – with many exciting opportunities set to be explored. That being said, a large amount of media coverage surrounding this topic has focused on the use of data analytics in telehealth services, neglecting to highlight some of the key ways in which this technology can benefit other branches of the medical sector. In this blog post, I talk about some of the ways in which data analytics can affect tangible change in real-world settings outside of the digital health sphere.

There’s an endless list of possibilities when it comes to the potential of data analytics, and narrowing it down to a select few innovations isn’t an easy feat. One of the most exciting and substantial changes to be made can be seen in research and development, with artificial intelligence algorithms breaking new ground every day. New insights drawn from mountains of data are enabling researchers to better understand their subject matter – be that patient opinion and preferences, or drug efficacy and human response to a product candidate.

There are countless aspects of the research and development process set to benefit from the introduction and employment of data analytics – and perhaps none so comprehensively as the clinical trial process. Drug development is an expensive, time-consuming and effort-intensive endeavour, with a standard successful trial costing an average of $2 billion. 

Much of this cost is incurred through failed product candidates, wherein potential combinations are explored but ultimately proved to be insufficient, ineffective or unsuccessful. It’s a long and frustrating process, and results in pharmaceutical companies upping their prices in order to recoup their losses – something that directly affects the quality of life of patients and their pockets.

This is where data analytics steps in: by using artificial intelligence algorithms, data analysts are able to whittle down a large pool of potential combinations to a small group that hold a higher probability of success. By reducing the number of trials actually taking place, researchers are able to focus on the experiments that might result in a successful end product. Aa result, research and development teams are able to sidestep trials that have low chances of success, avoiding the cost of multiple failed trials and the need to recoup these losses.

This is a win-win situation for everyone, but especially the patient. When dealing with huge amounts of information and money over the course of many years, the people who matter most can sometimes get lost in everything: the patients.

By harnessing the power of data analytics, shaking up the biotech and pharmaceutical industries and adopting a patient-centric approach, we’re looking at a future in which one-size-fits-all blockbuster treatments are rejected in favour of personalized medicine. Every individual has their own unique set of preferences and requirements, and by considering these wants, needs, and opinions throughout the drug development process, the healthcare sector is opening the door to a more compassionate way of living.

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