INDUSTRY WATCH
DURING THE PANDEMIC , HEALTHCARE ORGANISATIONS ACCELERATED THEIR USE OF DIGITAL TOOLS AND SOLUTIONS OUT OF NECESSITY .
As healthcare organisations scrambled to cope with huge surges in patient numbers in the wake of the pandemic , the past year has seen a major step change in the adoption of technology and digital services . But any progress they have made in their Digital Transformation risks being washed away by the deluge of resulting data .
According to research by Aruba , a HPE company , as of last year the healthcare sector was among the furthest ahead in terms of its adoption of advanced technologies and the sense of urgency it felt around this .
Around three quarters of healthcare IT leaders had started to implement trials or applications in areas such as Artificial Intelligence ( AI ) ( 74 %), Internet of Things ( IoT ) ( 76 %) and Machine Learning ( 71 %).
But it was also one of the sectors struggling most with the data this new technology is producing . A third ( 33 %) of IT leaders in healthcare said there was too much data for their systems to handle and that they could not process the data they collected quickly enough to act ( 32 %).
To get a handle on all this data and underpin long-term Digital Transformation in healthcare , a new eBook by Aruba , ‘ Taking healthcare to the Edge ’, lays out three key areas of focus for healthcare organisations – providing a clear roadmap to setting up the right network for future success . to implement integrated systems to handle data at the Edge of the network as urgent , 71 % are already using or trialling Edge technologies and 74 % are delivering new outcomes as a result . These include equipping healthcare providers with improved tools and applications , ensuring continuous availability of patient data at the point of care and using IoT sensors to continuously monitor patient data in real-time and generate early-warning notifications at bedside .
Step 2 : Analysing data intelligently
Capturing all that data is one thing , but being able to act on it is something else entirely . That is why there is a growing role for AI to help convert disparate data point into insights for diagnosis , patient care and pharmaceutical development – but also support IT teams with network troubleshooting and issues resolution to avoid any costly downtime or damage the user experience . Even before the pandemic around three quarters ( 74 %) of IT leaders in healthcare were either trialling or running AI applications on their network to deliver powerful insight .
Step 3 : Storing data securely
Against a backdrop of rising IoT use in hospitals and homes , healthcare organisations are having to police growing levels of device and app connectivity . And this is a big worry for healthcare IT leaders , with 61 % saying that connecting IoT devices at the Edge would make their business more vulnerable . Aruba believes
Morten Illum VP EMEA , Aruba
Step 1 : Processing data efficiency
In order to process data efficiently healthcare organisations must follow it to the Edge of the network , capturing it in real-time at its source versus transferring it back to a centralised hub . Our research showed that 86 % of health IT leaders identified the need
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