For understandable reasons, data storage conversations tend to take on a bit of a “gearhead” feel, at times, as stakeholders kick around a variety of technical terms to try to understand the products and services that best fit their needs.
In healthcare, however, it’s never too hard to “humanize” those conversations by looking at the real-world implications of new and enhanced storage options.
For example, writing recently at Healthcare Innovation, Dr. Mark Burby, Health and Life Science Director at Intel APJ, takes a look at what’s going on around the globe on the frontiers of precision medicine.
“In precision medicine,” Burby explains, “doctors will study patients’ data, created through medical techniques that are becoming rapidly adopted such as genomics and life sciences, and create a targeted course of treatment designed specifically based on the needs and unique genetic make-up of each patient. This data, coupled with the collective data of patients with similar diagnoses and backgrounds generated in the healthcare system, is the key to unlocking a new, exciting, personal way of delivering healthcare, which has the potential to be more effective and less toxic than traditional methods.”
There are a few keys to this new approach to medicine, revolving generally around the capacity to collect, store and analyze massive amounts of data. For example, Burby notes that “countries like Japan, Korea, Taiwan and China are already digitizing medical records, with massive amounts of research and investment going into genomics, genomic sequencing and data analytics. Oncology and paediatrics could see the early implementations of precision medicine in these countries.”
Similarly, AI is being applied to an array of healthcare data challenges to help drastically reduce research time. “What took years in the past, may now be achieved in months, or even weeks. Significant developments in AI technology by leading technology companies, including Intel, will help bring about a seismic shift in diagnosis, treatment, predication and prevention.”
He points to the Mayo Clinic as “a healthcare organization that is using AI to turn the massive data that they’ve collected over the years into clear, actionable information that doctors can apply. Previously disparate medical data, such as X-rays or MRI images, lab test data and e-medical records, are collated into a single place, allowing doctors to have a broad picture of what the patient is facing and make better treatment decisions.”
In short, given easier access to the right tools, including fast and efficient storage options, research processes can be shortened and made cheaper, and healthcare organizations and researchers can spend less time analyzing results and more time creating tangible breakthroughs.
“Technology already in-hand can help change how diseases are understood, diagnosed and treated,” Burby says, “and help medical professionals stay one step ahead of mutating diseases like cancer, while driving progress for the healthcare industry.”