One of the most significant technology-related challenges in the modern era is managing data growth. As healthcare organizations leverage new data-generating technology, and as medical record retention requirements evolve, the exponential rise in data (already growing at 48 percent each year according to the Dell EMC Digital Universe Study) could span decades.
Let’s start by first examining the factors contributing to the healthcare data deluge:
- Longer legal retention times for medical records – in some cases up to the lifetime of the patient.
- Digitization of healthcare and new digitized diagnostics workflows such as digital pathology, clinical next-generation sequencing, digital breast tomosynthesis, surgical documentation and sleep study videos.
- With more digital images to store and manage, there is also an increased need for bigger picture archive and communication system (PACS) or vendor-neutral archive (VNA) deployments.
- Finally, more people are having these digitized medical tests, (especially given the large aging population) resulting in a higher number of yearly studies with increased data sizes.
Healthcare organizations also face frequent and complex storage migrations, rising operational costs, storage inefficiencies, limited scalability, increasing management complexity and storage tiering issues caused by storage silo sprawl.
Another challenge is the growing demand to understand and utilize unstructured clinical data. To mine this data, a storage infrastructure is necessary that supports the in-place analytics required for better patient insights and the evolution of healthcare that enables precision medicine.
Isolated Islands Aren’t Always Idyllic When It Comes to Data
The way that healthcare IT has approached data storage infrastructure historically hasn’t been ideal to begin with, and it certainly doesn’t set up healthcare organizations for success in the future.
Traditionally, when adding new digital diagnostic tools, healthcare organizations provided a dedicated storage infrastructure for each application or diagnostic discipline. For example, to deal with the growing storage requirements of digitized X-rays, an organization will create a new storage system solely for the radiology department. As a result, isolated storage siloes, or data islands, must be individually managed, making processes and infrastructure complicated and expensive to operate and scale.
Isolated siloes further undermine IT goals by increasing the cost of data management and compounding the complexity of performing analytics, which may require multiple copies of large amounts of data copied into another dedicated storage infrastructure that can’t be shared with other workflows. Even the process of creating these silos is involved and expensive because tech refreshes require migrating medical data to new storage. Each migration, typically performed every three to five years, is labor-intensive and complicated. Frequent migrations not only strain resources, but take IT staff away from projects aimed at modernizing the organization, improving patient care and increasing revenue.
Further, silos make it difficult for healthcare providers to search data and analyze information, preventing them from gaining the insights they need for better patient care. Healthcare providers are also looking to tap potentially important medical data from Internet-connected medical devices or personal technologies such as wireless activity trackers. If healthcare organizations are to remain successful in a highly regulated and increasingly competitive, consolidated and patient-centered market, they need a simplified, scalable data management strategy.
Simplify and Consolidate Healthcare Data Management with Data Lakes
The key to modern healthcare data management is to employ a strategy that simplifies storage infrastructure and storage management and supports multiple current and future workflows simultaneously. A Dell EMC healthcare data lake, for example, leverages scale-out storage to house data for clinical and non-clinical workloads across departmental boundaries. Such healthcare data lakes reduce the number of storage silos a hospital uses and eliminate the need for data migrations. This type of storage scales on the fly without downtime, addressing IT scalability and performance issues and providing native file and next-generation access methods.
- Eliminate storage inefficiencies and reduce costs by automatically moving data that can be archived to denser, more cost-effective storage tiers.
- Allow healthcare IT to expand into private, hybrid or public clouds, enabling IT to leverage cloud economies by creating storage pools for object storage.
- Offer long-term data retention without the security risks and giving up data sovereignty of the public cloud; the same cloud expansion can be utilized for next-generation use cases such as healthcare IoT.
- Enable precision medicine and better patient insights by fostering advanced analytics across all unstructured data, such as digitized pathology, radiology, cardiology and genomics data.
- Reduce data management costs and complexities through automation, and scale capacity and performance on demand without downtime.
- Eliminate storage migration projects.
The greatest technical challenge facing today’s healthcare organizations is the ability to effectively leverage and manage data. However, by employing a healthcare data management strategy that replaces siloed storage with a Dell EMC healthcare data lake, healthcare organizations will be better prepared to meet the requirements of today’s and tomorrow’s next-generation infrastructure and usher in advanced analytics and new storage access methods.
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Tags: Big Data, cloud, Data Lake, data management, digitization, tiering