Virtualization News

What the Growth of Data Virtualization Means for Healthcare

Healthcare organizations face unique challenges when implementing virtualization as part of their health IT infrastructure.

By Elizabeth O'Dowd

As part of an evolving health IT infrastructure, data virtualization offers a number of benefits from mobilizing access to clinical health data to organizing clearance parameters. Virtualization can also pose challenges for maintaining HIPAA compliance and managing budget restrictions.

Challenges facing health IT virtualization

At its most basic, data virtualization enables convenient storing and viewing of data. With the help of abstraction layers, data is viewable to the user in a cohesive and easy way to view even despite the information being stored using a variety of methods.

Adoption of enterprise data virtualization is growing. According to Gartner analysts, more than one-third of organizations (35%) will have implemented a form of data virtualization by decade’s end. Gartner’s predictions include data virtualization adoption across all enterprise industries.

While that figure represents a minority, Gartner analysts have observed that data virtualization offerings are “maturing at a steady pace in terms of connectivity options, performance, security and near-real-time data delivery” and that major industries have already begun deploying the technology.

Embracing virtualization does not require virtualizing an entire infrastructure environment.The report outlines vendor verticals, with many vendors claiming healthcare as a major industry served. However, very few environments have yet to be fully virtualized and according to the Gartner analysts, no healthcare environment has been fully virtualized.

The report’s market analysis outlines operational use cases that support business operations and data retrieval including:

  • Virtual operational data store (ODS): A data service layer is used to retrieve data and integrate user views across multiple databases.
  • Reusable data services in service-oriented architecture: Interfaces are deployed via virtualization that allow developers to build service-oriented data access.
  • Simplify application data access or exchange: Virtualization builds an access layer that recognizes different access requirements from different apps.
  • Legacy system migration: Virtualization can be used to access data consistency when systems are being migrated to a new storage method.
  • MDM (master data management): Master data stored using different storage methods is integrated for cohesive retrieval and viewing.

Some of these virtualization implementations should appeal to the healthcare industry in particular. MDM and simplifying data access or exchange align well with information sharing efforts and initiatives between organizations. Affiliated organizations would have the ability to grant permissions for consolidated master record keeping virtually, thereby maintaining the most up-to-date and informed record of each mutual patient’s visits (i.e., the single source of truth)..

The report addresses four major physical barriers affecting data virtualization functionality:

  • Source system access connections
  • Data volume
  • Network capacity
  • Query complexity

Given that healthcare organizations in remote regions often struggle with limited internet connectivity and IT resources, deploying data virtualization is likely untenable. Coupled with these limitations are concerns about health data security and privacy which health systems, hospitals, and physician practice must address before going virtual.

The advancement of virtualization depends greatly on the technology’s ability to mature in a way that will eliminate these barriers. Gartner analysts see progress on these fronts:

Modern data virtualization tools exploit technology-driven approaches to address these issues concerning the physics of, and access to, data. Techniques such as multitiered caching (including incremental tier-to-tier updates), process distribution (some as simple as query predicate push-down to the connected source; others are more complex, such as temporary data redistribution across sources), as well as enhanced utilization of memory grids and processing grids, can all potentially be deployed to varying degrees by the different data virtualization offerings in the current market. These techniques have not only increased the efficiency of existing data virtualization tools in the market, but have also increased adoption and implementation of these tools for mission-critical workloads.

Continued advancements in virtualization technology have clear benefits for the healthcare industry as far as data retrieval and file sharing are concerned. The benefits of data virtualization, however, do not come without their challenges which these organization would need to consider before deploying the technology in a healthcare environment.   

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