insideAI News Guide to Healthcare & Life Sciences

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The healthcare and life sciences industries historically have generated vast amounts of data. These large volumes of data hold the promise of supporting a wide range of medical and healthcare tasks, including clinical analytics and decision support, patient profiling, disease surveillance, regulatory and compliance requirements, scientific research, and many others. Data in healthcare and life sciences is expected to grow exponentially in the coming years and will be beyond the capability of the traditional methods of data management and data analytics. It is vitally important for organizations in these industries to acquire the available infrastructures, methodologies, and tools to leverage this vast amount of data effectively to ensure the highest possible standard of patient care, as well as risk significant revenue and potential profits.

This technology guide provides an overview of the utilization of big data technologies as an emerging discipline in healthcare and life sciences. It explores the characteristics of this business strategy and the benefits of leveraging big data technologies within these sectors. It also touches on the challenges and future directions of big data and analytics in the healthcare and life sciences industries.

Despite the fact that some data in the healthcare sector is still stored in hardcopy form, most is in electronic form. One issue, however, is that this data is now stored in electronic silos with more and more data produced every day from new devices. Big data in the healthcare industry promises to support a diverse range of healthcare data management functions, however the industry is still in the early stages of getting its feet wet in the large scale integration and analysis of big data. Life sciences research continues to evolve rapidly in conjunction with an increasing focus on analytics and the more effective use of data. The race to understand patients and diseases at the molecular level to achieve precision medicine is fueling this shift. The figure on page three encapsulates many of the demand drivers coupled with new business models where outcomes and real-world data are providing health data and transforming what is possible. It’s clear that the race to find the cause and subsequent treatments and cures is paramount.

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