Data Science and Analytics have been the backbone of society, both nationally and internationally, during the past 18 months. Detailed analysis of huge data sets has helped businesses of all shapes and sizes overcome some of the largest challenges the pandemic has created.From enabling staff to work from home to predicting the next potential strain of the COVID-19 virus – Data & Analytics has undoubtedly been the difference between survival and failure. According to research by McKinsey, digital or digitally enabled products used by executives have accelerated by seven years in order to respond quickly and efficiently to the crisis. One industry that has seen vast change in terms of embracing Data Science & Analytics tools and methods is healthcare. Traditionally, this industry has been slow to implement any sort of technological change however, over the past year and a half, it has become clear that it must evolve, and fast. Responding to crises, such as the pandemic, has been no easy feat for anyone within the healthcare sector, but those who had previously invested in, or rapidly turned to, data science trends such as AI and DevOps have reaped the rewards. Here are three movements we have seen creeping into our healthcare systems in recent times, and ones which we will undoubtedly see more of over the next six to 12 months. Increased use of AI to help make care more efficientThere is huge potential for AI and Data Science to have a sizeable, positive impact in healthcare soon. One example is using machine learning to optimise patient procedures, ensuring they’re in and out as efficiently as possible consequently freeing up bed space and allow for more operations to be undertaken – a problematic issue for the NHS currently. AI is also being used to help diagnose illnesses. Using computer vision and deep learning to understand images from scans, those illnesses that can be harder to detect, such as certain types of cancers, can be found and treated a lot earlier, meaning a much higher rate of survival for patients.In many cases and tests that have been done, AI has been more successful than using a doctor with several years’ experience.Implementation of the cloud for clinical trialsIt can take up to 10 years for a new drug to come to market, and the longest part of the process is often the clinical trials.However, certain elements of Data Science, such as the use of the cloud for data collection, can improve the efficiency of this process ten-fold. When used alongside technology such as wearable devices and electronic diaries, the collection and analysis of crucial data, such as a trial participants vitals, can be done in real-time from anywhere and everywhere. Adopting DevOps for cost reductionThe healthcare industry is heavily regulated to ensure that the drugs created do not cause harm, and this includes monitoring its software and hardware components as much as anything else.Using Computer System Validation (CSV) is the most common way of companies being regulated by the FDA, but there’s no denying that this system is time-consuming and expensive. Using DevOps for this process allows businesses to autonomously reduce the risk of bugs and avoid bottlenecking all without damaging productivity and reliability. Not only do all these elements within DevOps mean the regulation process becomes far more streamlined, but regulations are more likely to be adhered to and products are able to be taken to market much faster, improving ROI and revenue.Data Science tools have been, and will continue to be, the main driver of change within healthcare. From making medical processes more efficient to reducing the cost of HealthTech, improving productivity, and anticipating big potential changes within the sector, the importance of Data & Analytics has never been clearer.If you’re looking for your next role, or are looking to build out your Data Science team, Harnham can help. Take a look at our latest data science jobs or get in touch with one of our expert consultants to find out more.
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