Many of us still remember seeing our doctors using handwritten notes and analog films for medical scans, but this has now changed (or transformed in trendy parlance) – so let’s look at some of the major drivers of that, and specifically the data behind what is pushing healthcare data growth.
There are clearly all kinds of digital data in healthcare now. Patient records are the perfect kind structured data of data that can be stored and maintained by database systems. The other large part of healthcare data is unstructured or non-record oriented data, represented as files for medical images, genomics data files and many other types of devices and scanner data. Imaging data is managed by Picture Archiving and Communication System (PACS) and Vendor Neutral Archive (VNA) applications, and by comprehensive Enterprise Image Management solutions that can manage all of the different modalities found inside a hospital or healthcare system. Ultimately, unstructured data is where the growth is.
Healthcare Cloud Storage Explained
UNDERSTANDING MEDICAL DATA’S EXPLOSIVE GROWTH, REGULATIONS & COMPLEXITY
This data growth issue is now very prominent. If we look at medium-to-large hospitals (those over 250 patient beds, which is common in cities with 100,000 people), in most cases there is now a petabyte scale data problem – or even beyond. There are really multiple reasons why this data is growing so fast, but we can highlight a few key ones.
We should first look at the number of patient studies, and the size of imaging studies. In radiology alone there are multiple types of diagnostic imaging modalities such as MRIs, CTscans, X Rays, ultrasound and of course there are digital images generated in pathology, angiography and oncology as well. This data is managed by software solutions from vendors such as Sectra, GE Healthcare, Fujifilm, Agfa, Philips, Change (McKesson), Hyland, Inspirata and others. As the scanners and imaging techniques have evolved and provide increasing resolution and fidelity, the file sizes generated by them grow as well – in some cases a single patient study can be tens of gigabytes in size. Think about all the studies for all the patients in a medium or large hospital over the course of a year – there is really a multiplier effect in the data growth from that alone.
Another key driver is the value of this data, since extracting insights and patterns from historical studies has massive benefits in how patients are treated over the course of decades and lifetimes. This is on top of regulatory compliance requirements (such as HIPAA in the US), which also forces providers to retain data for the long term, even patient lifetimes.
And finally, the need to store other types of data in hospitals, backups of patient databases, video surveillance data – and mountains of documents. Since this is all growing so fast – the cost of medical image storage is becoming a much more prominent part of budgets. So finding new and more efficient ways to store and protect this data is critical. The good news is these IT folks are finding ways to save millions in time and resources.
This is exactly why software-based, scale-out storage solutions such as Scality RING are seeing increased adoption in these industries. A recent survey of Scality’s hospital and genomics customers, conducted by IDC – demonstrates major advantages in time-to-deploy, scaling to address data growth, access time to image data, and ultimately major reductions in TCO.
To learn more, join us for the first episode of our SOLVED TechTalk with Amita Potnis, IDC Research Director, who will share the unique business value of scale-out, on-prem storage architectures.
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