When it comes to information technology (IT), the “whether and why” discussion about cloud use is pretty much over. As noted in some recent analysis from Accenture, “The last two years have laid bare the power and agility of cloud… and a new understanding that cloud at scale is essential for operations maturity, and ultimately, value.”
Even in the slow-to-digitize healthcare sector, contemporary estimates indicate around 90% of the industry has leveled-up to using some degree of cloud computing for some functions and in various incarnations (private-, public-, hybrid-, multi- cloud).
Supercharging IT with cloud power may now be essential, but that doesn’t necessarily mean it’s simple. Despite an accelerated cloud adoption curve over the past couple of years, a huge swath of healthcare organizations still rely on infrastructure predating the advent of the iPhone. And as everyone knows, hordes of valuable data remain confined to countless racks of servers siloed in hospital basements and assorted colocation data centers far and wide.
Working with assemblages of those very old systems and very new cloud deployments can get very, very complicated.
It’s difficult to rectify the sheer magnitude of differences in both fundamental operation and capability between legacy on-premise infrastructure and cloud infrastructure. Picture someone from the horse-and-buggy age being presented with access to a rocket ship and trying to conceptualize whether it will fit in the barn or what to feed it. That’s kind of where healthcare finds itself.
The world of technology moves at lightning speed. For a host of reasons, the healthcare sector has struggled to keep pace. What lies between is a gulf of IT complexity that stymies even the most sophisticated organizations. Thus a host of promising models and solutions are continuously evolving to help bridge the gap. The latest of these is the supercloud.
The “supercloud” term dates back to a 2016 Cornell University project describing an architecture that enables application migration as a service across different availability zones or cloud providers. The supercloud provides interfaces to allocate, migrate, and terminate resources such as virtual machines and storage and presents a homogeneous network to tie these resources together…[and] span across all major public cloud providers… as well as private clouds. ”
Much of the current excitement about the concept is centered around making everything portable across existing hyperscalers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, and the big business potential in building specialized clouds on top of them. Trendy examples of this model can be found in Snowflake’s recently launched Healthcare & Life Sciences Data Cloud and Databricks’ new Lakehouse for Healthcare and Life Sciences.
The central value of the supercloud concept really hinges on provisioning the best cutting edge technology available while simplifying the way the organization interacts with it. The real magic of cloud power today isn’t really in portable IT workloads; it’s in the vendor-specific cloud-native services that the big hyperscalers supply. For example, Amazon Web Services has some really cool database and stream management technology. Microsoft Azure has some really cool storage technology. Google Cloud has some really cool machine learning technology. But your average healthcare business can’t afford to staff a huge IT department that:
- Keeps up with all of those developing services;
- Manages strict compliance and security requirements;
- Keeps the proverbial lights on for all their internal systems; and
- Finds innovative ways to utilize nifty new technologies for the business.
It’s just not feasible.
However, cloud resources are now incredibly varied and accessible, with a large ecosystem of industry-specific cloud-based managed services specializing in these complexities. Which means the average healthcare organization can, indeed, afford to tap into supercloud power – they just get it as a service.
Essentially, healthcare organizations can get a service layer designed for their industry with sets of application programming interfaces (APIs) that are called to implement best-of-breed cloud services in a hybrid fashion amongst the appropriate hyperscalers. The right cloud is picked for particular use cases, and a mesh service layer covers all of it. Unique compliance and security requirements are automated, and the underlying implementation complexities are hidden from the business users of those services. So the healthcare organization’s IT department can pretty much offload tasks 1 through 3 and focus entirely on innovating ways to help the business.
You’ll sometimes see a similar ideal touted as “industry cloud.” As recently noted by Brian Campbell of Deloitte Consulting in HealthITSecurity, “Industry clouds are a portfolio of business transformation-focused solutions, assets, and accelerators that ultimately help to reinvent and transform the business side of that specific industry,” supplying an excellent option for healthcare organizations looking to “keep pace with the changing digital landscape.”
Regardless of how a healthcare organization goes about increasing IT agility, reducing complexity, and reinventing business processes, the cloud should be central to the effort. A simple fact has been established: Cloud power increases healthcare power.
To demonstrate, consider a recent six-month study where a team of researchers shattered the record for diagnosing rare genetic diseases with DNA sequencing, and set a new Guinness World Record of 5 hours and 2 minutes to sequence a patient’s genome. At Stanford Hospital, the team dedicated specialized flow cell sequencing hardware to try to speed sequencing a single patient’s genome. But the amount of data being produced overwhelmed the lab’s computational systems.
According to Stanford study team member Euan A. Ashley, “We weren’t able to process the data fast enough. We had to completely rethink and revamp our data pipelines and storage systems. ” Team member Sneha Goenka “found a way to funnel the data straight to a cloud-based storage system where computational power could be amplified enough to sift through the data in real time.”
They were able to sequence and diagnose a genetic illness in 7 hours and 18 minutes, which is about twice as fast as the previous record. For one teenaged patient in their study, their sequencing data showed his condition was rooted in genetics within a matter of hours, and he was immediately placed on a heart transplant list. He received a new heart three weeks later, and as of January this year, his mom says he’s doing “exceptionally well.”
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