The stage is set. The IT giants are each targeting healthcare with analysts projecting that, by 2018, 30 percent of providers will run cognitive analytics on patient data. With artificial intelligence making its presence felt in healthcare, a Healthcare IT News report asks what the greater risk is for providers; to invest too soon or too late?

Much implementation of AI is still years away but many cases are very much in the here and now and making providers sit up and take note, the report says.

It refers to Regenstrief Institute and Indiana University School of Informatics and Computing which recently studied open source algorithms and machine learning tools in public health reporting. Using pathology reports, the tools showed superior results in terms of speed and accuracy to human efforts.

Many key health systems are now investigating how to take advantage of the power of AI, cognitive computing and machine learning.

Non-profit health research organisation, Sutter Health says that development would be driven by healthcare’s “acute need to gain efficiency”.

Market intelligence provider, International Data Corporation (IDC) has said that by 2018, healthcare will access cognitive solutions for close to 50 percent of cancer patients, resulting in reduced costs and mortality rates.

Meanwhile, the hurdle ahead for healthcare and Informatics vendors is data, the report says.

“Data is always going to be an issue for both healthcare providers and technology vendors. Collecting it, storing it, normalising it, tracing its lineage and the critical – if not particularly sexy – matter of governance, are all necessary so providers can harness cutting-edge software and hardware innovations to glean insights that enhance patient care.”

Harnessing the potential of AI will mean a radical change in approaching how providers embrace technology and acquire their teams.

Other key pieces of the AI puzzle include business intelligence, enterprise data warehouse, infrastructure, privacy and security.

While AI, cognitive computing and deep machine learning are technologies that are still in their infancy, consultancies are indicating that healthcare needs to start to work with them now instead of playing a waiting game.

"The risk of investing too late in smart machines is likely greater than the risk of investing too soon," according to one information technology research report.

Sutter says it has no doubt that "sophisticated learning and AI algorithms will find a place in healthcare over the coming years…..it's coming."

 

Source: Healthcare IT News

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