Health IT Infrastructure Sees Growth in Cognitive Computing

January 03, 2017 - As healthcare organizations explore the future of big data analytics, cognitive computing presents a viable addition to health IT infrastructure to assist organizations in processing the structured and unstructured data collected from medical devices and other connected systems.

According to a recent Grand View Research report, the global cognitive computing market is expected to reach $49.60 billion by 2025 across all major industries, including healthcare.

The report cites a need among organizations to incorporate advanced data analytics technology into their business processes as the main growth factor for cognitive computing. As organizations collect more data via mobile and wearable devices, cognitive computing will assist existing infrastructure technology in analyzing and sorting data.

“The incorporation of features, such as artificial intelligence and Internet of Things (IoT) that enables automated integration between software, hardware platform, and the consumer, is energizing the industry growth prospects,” report authors stated.

Researchers found that an increased focus on research and development encouraged the growth of cognitive computing. Cloud systems are also expected to gain momentum as they facilitate secure and integrated data storage solution, encouraging the growth of cognitive learning solutions.

Healthcare organizations have recognized the potential of cognitive computing and its impact on the quality of patient care.

Cognitive computing stands out as a big data analytics tool which mimics the way the human brain makes connections between data in addition to recognizing patterns and connections that goes beyond the ability of a human brain.

The report found that the natural language processing technology segment of cognitive computing accounted for the majority of the market share as organizations demanded the need for advanced pattern recognition.

Integrating natural language processing has significant uses in healthcare as many clinicians enter unstructured free text into their EHR system when speaking to patients.

“When physicians are recording information, they’ll just prefer to type everything in one place into the notes section of the EHR,” Paul Hake, who worked for the IBM Smarter Care Analytics Group told EHRIntellegence.com. “And so this information is kind of lost.  It’s then almost a manual process to map this unstructured information back into the EHR system so that we can then use it for analytics. We can run natural language processing algorithms against this data and automatically extract these features or risk factors from the notes in the medical record.

Cognitive computing can be implemented into an IT infrastructure for the purpose of enhanced intelligent security in addition to analytic uses.

“The cognitive computing solution has the potential to perform analysis and support business decision making against a huge amount of data generated daily across various industries,” report authors found. “It also has the potential to identify anomalous behavior in the data by inspecting usage patterns to block the cyber-attacks.”

IBM Watson is a well established player when it comes to cognitive computing in big data analytics, but they have also recently launched an AI cybersecurity beta program to address the security challenges organizations face as IT infrastructures grow more advanced.

The organizations currently participating in the beta program are leveraging Watson to build an intelligent security solution to give them better insight to determine suspicious behavior. Watson provides additional context for user activity outside of the most common suspicious behavior, which aid IT staff in determining whether certain behavior is malicious.

The University of Rochester Medical Center is one of the 40 organizations currently participating in the Watson for Cyber Security Beta Program. The organization began using IBM Watson to advance their care and research in 2013.

While big data analytics is the main focus for healthcare organizations seeking cognitive learning solutions, the technology is beginning to prove useful for other infrastructure initiatives as well as automated and intelligent solutions continue to grow across health IT.  

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