Harnessing Modern IT to Power Life-Saving Medical Advances
In recent years, the medical research and health care industries have witnessed revolutionary breakthroughs driven by life-saving technological advancements such as genomic sequencing and AI-enabled medical applications. However, these new technologies are generating hundreds of terabytes of genomic data per month for medical organizations. Genomics alone is expected to generate up to 40 exabytes of data per year by 2025, equal to nearly a billion DVD movies. As a result, data infrastructure requirements are highly likely to continue to grow as AI is deployed at a larger scale to analyze data for population health and predictive diagnostics.
At the same time, those working in medical environments know that speed matters, especially when it comes to delivering life-saving insights and results. Medical organizations looking to leverage new technologies need modern infrastructure and advanced storage to quickly analyze data and achieve groundbreaking results. Modern IT infrastructure allows the scalability and high-speed data processing capabilities that enable researchers to succeed.
Empowering Data Breakthroughs in Genomic Testing
Unprecedented outbreaks like COVID-19 pressure-test data management and performance. When facing a global pandemic, bottlenecks in accessing data are simply not an option because accelerating genomic pipelines can lead to life-saving breakthroughs. Take for example McMaster University’s McArthur Lab, which curates data, models and algorithms associated with threats to human health. The emergence of COVID-19 caused a dramatic uptick in genome sequencing at McArthur, placing tremendous stress on the lab’s computing infrastructure. Already massive genomic data sets doubled every three months, making it difficult for the team to keep up with the demands of its technology.
With the adoption of a modern IT storage system, the lab team created and operated a tool to identify how COVID-19 spreads and evolves with near-real-time processing times. Previously, it would have taken the team two days to gather critical insights, but transforming the lab’s storage infrastructure reduced that time to only three hours. Because this IT transformation was so successful, the McArthur Lab team was able to participate in a group that isolated the live virus, a critical breakthrough in understanding how it is transmitted.
Similarly, the Health 2030 Genome Center in Switzerland also adopted powerful and efficient storage solutions to enhance the speed of DNA sequencing analysis for rapid diagnosis. To successfully sequence and analyze DNA samples, the center required IT infrastructure that could provide the flexibility and scale to process high levels of data, especially considering that a single sample can reach 200GB. After transforming its infrastructure, the Health 2030 Genome Center not only enhanced the speed of DNA sequencing analysis but also gained unprecedented computing power and access to real-time data to simplify and accelerate research and patient diagnostics.
Supporting AI for Better Patient Outcomes
Healthcare organizations generate a staggering amount of data daily, but data is valuable to physicians only with proper storage and management. This is where AI and analytics can play a role in enabling stronger patient care and better outcomes. Not only does AI promise new medical technologies that can aid in early disease detection, personalized care, treatment risk analysis and diagnostic error prevention, but it can also be critical in improving the quality of data. Coupled with a modern infrastructure, large data sets can be more accessible and seamlessly integrated across different systems to advance data quality.
St. Joseph’s Health, a renowned hospital and healthcare network, recognized the need to become a data-driven organization. Its legacy system fell short, causing daily frustrations for both IT admins and clinicians, leading to performance issues, delayed lab results and slow patient admissions. Following an IT infrastructure overhaul, St. Joseph’s Health successfully implemented AI technology within its clinical applications, elevating patient care and reducing waiting times. Its radiology department now uses AI and data analytics to read medical images, identify anomalies and provide recommendations to specialists for expert evaluation. With a modern data storage system in place, the center’s AI-driven tools have improved read accuracy and expedited patient treatment. St. Joseph’s also uses live data queries to track revenue trends, hospital utilization rates and patient status throughout the day, which reduces email backup time by 98%.
Effectively managing patient data can become just as difficult for growing hospitals with limited space. For the University Hospital Centre (CHU) of Saint-Etienne, patient data was historically managed through disk storage. However, as the hospital grew, the IT team required a modern IT infrastructure to support all hospital systems with a small footprint that could easily be maintained by a smaller IT staff. The transformation increased CHU Saint-Etienne’s data capacity, offering more flexibility to increase demand and save energy through a smaller footprint. It also dramatically improved application performance, reducing latency from 17 milliseconds to under 1 millisecond in most cases.
Harnessing Technology for Better Patient Care
Behind the curtain, successful healthcare organizations have harnessed the potential of innovative new technologies through powerful and scalable IT infrastructures that can support large and fluctuating data volumes. By enabling faster data processing, increased storage capabilities and advanced accessibility, the health care industry can stay ahead of the curve, whether it’s providing progressive patient care or fighting global threats to human health.