Big data is helping every industry become more efficient and productive with respect to the way in which data is collected and analyzed – and healthcare is no exception.
Not only is the worldwide spend on IT infrastructure, including data centers, expected to rise to nearly $3 billion by 2020, but the sheer volume of healthcare data is growing at an exceptional rate. 153 exabytes were produced in 2013 with this expected to rise to an estimated 2,314 exabytes in 2020, equating to an overall rate of increase of nearly 50% per year.
The internet is at our fingertips and patients are increasingly turning to self-diagnosis as a 24/7 alternative to hospital waiting times and lengthy appointment booking processes, with WebMD receiving 212 million unique monthly visitors, leaving the healthcare industry no choice but to further integrate technology and data analysis into daily hospital life.
With the relationship between data and healthcare set to become even more significant in the near future, we examine just a few of the ways in which big data can be used in healthcare:
- A sizeable part of the data produced in the healthcare sector can be attributed to imaging technology. As the technology advances and grows, the size of the files produced is growing in accordance, with the average size of a standard MRI image doubling since 2005.
- Big data has begun to play a crucial role in facilitating the research and development of new drugs and potential cures with it currently being used to try and identify new treatments for Parkinson’s disease.
- NHS England is planning to invest even more of its £120 billion-plus budget into artificial intelligence (AI), accelerating tasks such as planning radiotherapy where a neuro-oncologist might need to study more than 100 images of the brain then carefully mark out the entire brain to ensure sensitive areas aren’t touched by the radiotherapy beams. This process can take hours but is a crucial step before commencing radiotherapy. With AI, this task can be completed in minutes, analyzing the scan and creating a 3D model in a fraction of the time.
- Arguably, Electronic Health Records (EHRs) are the most popular and widely adopted application of big data in healthcare, the premise of which being that every patient has their own digital record detailing medical history, allergies, treatment received, results, etc. Whilst the merits of EHRs are undeniable, their implementation can vary substantially from country to country with the US leading the way with 94% of hospitals having adopted EHRs. Unfortunately, the EU is still playing catch-up, however, thanks to an EU directive, a centralized European health record system should be a reality by 2020.
- Real-time alerting is a further benefit of big data analytics in healthcare. Wearable technology can collect patients’ health data continuously and send this data to the cloud for medical professionals to access as well as issuing an alert when data is out of the ordinary or dangerous. For example, if a patient’s blood pressure increases alarmingly, the system can send an alert in real-time to the doctor who can then take action to reach the patient and treat the problem.
With the amount of data being produced within the healthcare sector on the rise at an extraordinary rate and patients calling out for medical provisions to move into the digital age and be more readily available, data centers will be crucial in providing the backbone infrastructure for this growth, facilitating the implementation of pioneering technology and ground-breaking data analytics, thus transforming the landscape of healthcare as we know it worldwide.
With decades of expertise in the design and manufacture of network solutions, AFL Hyperscale has the capabilities and infrastructure to support evolving healthcare networks, from network design to a full connectivity solution.
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