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Health IT Analytics Demands Flexible Storage Infrastructure

Health IT analytics is growing rapidly, but with the influx in clinical data, organizations need to establish flexible and scalable storage infrastructure.

Health IT analytics challenges storage infrastructure

Source: Thinkstock

- The health IT analytics market is expected to rise along with the need for healthcare organizations to cut spending while improving patient outcomes.

A recent Research and Markets report predicted the healthcare analytics market to grow at a CAGR of 27 percent through 2021.

The health IT analytics market is driven by the increase of government initiatives encouraging EHR adoption. Health IT analytics are also needed to decrease spending and improve patient outcomes, according to the report.

Increased availability of healthcare big data solutions, recent technological advancements with machine learning, and the rise of venture capital investments in analytics technology give organizations more options, driving market growth.

The pressure to reduce healthcare costs is the main contributing factor to the clinical assessment segment of the health IT analytics market. Analytics allows clinicians to focus on personalized care by providing insight into patient conditions and making connections based on data.

Healthcare organizations are gaining much insight from applying analytics solutions. However, many entities lack the infrastructure technology to support a full implementation of the technology.

Analytics need massive amounts of storage space to be successful for healthcare organizations in the long term. Entities are faced with choosing what kind of storage will best suit their needs as they prepare for a future of data analytics.

Quickly retrieving patient data is one of the biggest motivators for healthcare organizations to adopt analytics. Clinicians want to have access and visibility of a patient’s entire medical record, plus data discovered via analytics without having to search for it. This allows clinicians to spend more time interacting with the patient and less time searching databases for information.

The biggest decision organizations need to make is on-premises versus cloud storage. Traditionally, healthcare organizations prefer on-premise storage because of the control they have over their data environment. Storing data on-premise worked well enough in the past, but analytics and other data intensive workflows are too much for traditional servers to handle efficiently.

The general stigma of cloud technology has dissipated over the past several years. Cloud vendors are getting better at securing cloud data in a HIPAA compliant manner and organizations see that the benefits of cloud far outweigh the risks especially when it comes to analytics demands.

Cloud computing is flexible in a way that traditional on-premise solutions are not. Organizations can store clinical data in different ways to make it more retrievable.  

One way organizations can store data in the cloud at high volumes is using object storage.

Key Information Systems Director of Cloud Service Clayton Weise sees potential in object storage to benefit the healthcare industry and move organizations away from dated legacy solutions. Weise also noted it can help organizations seeking more elastic solutions for analytics data.

“Object storage provides an inexpensive way to store vast pools of data, multiple petabytes up to exabyte scale within a single space,” Weise explained to HITInfrastructure.com. “The data stored using object is always accessible, unlike tape where I have to know the serial number, track the tape, and physically retrieve it.”

“Data in object stores is always accessible,” he continued. “Object storage makes data retrieval far more convenient.”

Object storage manages data as objects instead of files or blocks. Objects are kept in a storage pool that does not have a hierarchical structure. This means that data is stored anywhere in the storage pool marked by unique identifiers, making data retrieval faster.

Healthcare organizations will continue to deploy data intensive analytic solutions which put strain on storage infrastructure. Different, more flexible ways of retrieving data are needed as the amount of data accessed grows.

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