The importance of intelligent storage and big data analytics in a healthcare environment cannot be understated. Renowned for vast stores of data that go chronically under-interrogated, healthcare providers have reached a true inflection point: Intelligent analytics and high-quality cloud storage have never been more widely available, the hospital ecosystem has never been more dependent on intelligent data management and integrated technologies, and the pandemic has exacerbated existing challenges with revenue shortfalls, compressed margins, talent shortages, and overreliance on manual processes.
The EMR is the foundational piece of technology in modern healthcare delivery and while the positive impact with respect to information delivery and consolidation is indisputable, these massive investments incur significant, ongoing costs and dominate the attention of both IT and system leadership with tactical maintenance and re-configuration concerns. Furthermore, improper implementation, lack of internal expertise, or an under-powered infrastructure can render the EMR slow, inefficient, and cumbersome to the detriment of clinical and financial outcomes. Exacerbating this reality, more than 80% of healthcare data is unstructured and continues to explode as digitization increases, new methods change the way we think about the human body and diseases states, and new technologies improve the way we examine, interrogate, and assess information. EMR technology, as it stands now, is not capable of accommodating these trends and continues to come up short in terms of delivering bottom-line improvements to provider finances.
Adopting an advanced cloud storage infrastructure accelerates native applications to improve analytics and deliver more meaningful insights in less time, expedites time to delivery of all patient records, eliminates the need for constant tactical adjustments to improve EMR performance, and provides the backbone for a more efficient – and less visible – operating environment. Furthermore, patients increasingly desire personalized and customized care options, as well as visibility into their costs and outcomes. New mobile and wearable devices are constantly generating data, and users are demanding that analytics make sense of it all. Faster, more accurate data means more efficient patient care, happier physicians, and healthier patients. Cloud-based infrastructure allows providers to accelerate clinical innovations, handle hefty radiomics and genomics requirements, identify similarities and patterns across data points in patients suffering from a particular disease and overlay it across the standard population to uncover potential signs of predisposition or initial symptoms.
While the most successful providers have already moved towards integrated data infrastructures and invested in ensuring the transfer and analysis of clean, consistent information across systems and departments, the costs of storing this data are becoming a significant challenge. Many hospitals still adhere to the outmoded belief that on-premises storage is more secure and reliable than the cloud, and are thus willing to accept the increased cost, resource, and space commitments that this requires. The lack of downtime risk, local server connection, and the psychological preference for physical proximity are all drivers of this mentality, and given the incredible importance of preserving highly sensitive personal information – as an ethical, legal, and financial concern – the willingness to sacrifice efficiency for security is both admirable and understandable. However, cloud technology has advanced to a stage where it no longer represents the security risk it once did, and the numerous material rewards it offers are becoming too clear and well-defined to ignore. This is largely accomplished through advanced automation, more advanced tooling, and an overall maturing of best practices and preventative security measures. Cloud storage is also more dynamic, with automated predictive analysis and machine learning algorithms that are constantly searching for bugs and performance shortcomings, in many cases resolving them independently before they become issues.
The move to value-based care, the emphasis on sophisticated population health analysis, the need for advanced automation, IoT monitoring, advanced digital records sharing, and even more advanced considerations like genomics and precision medicine, will all be accelerated and enhanced by investment in cloud storage. Fundamentally, as more data is created, more space is required, and in many hospitals, space is either at an absolute premium or simply not available within the confines of the existing facility. In some markets, the costs of physical expansion are effectively prohibitive. Furthermore, maintaining these systems, from actual physical maintenance to ensuring a proper power supply to keeping the hardware safe represents a tremendous resource drain that goes directly to OPEX. And while local networks are in some ways the most secure, they are still heavily dependent on the efforts of the provider’s own internal IT and cybersecurity teams, incurring additional personnel and resource costs and introducing the risk of human error. There are also regular, upfront investments in hardware with a finite lifespan that will eventually require replacement and upgrading; the more advanced the provider becomes with respect to its digital infrastructure, and the more sophisticated it needs to be with respect to analysis and reporting, the greater the demands on its storage investment. The cloud offers easy scaling, faster and more secure data delivery across the network and to patients and accommodates more devices and tools more easily.
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