- Artificial intelligence (AI) is one of the most talked about healthcare technologies of the past year, and is poised to play a significant role in the future of healthcare to improve patient care and meet value-based care initiatives.
The healthcare industry has a real need for AI, as the volume of available medical knowledge has overgrown the ability of physicians to reasonably evaluate it and draw conclusions. However, without a health IT infrastructure that can support an increase in the number of connected devices and store that influx of data, an AI solution cannot function effectively.
AI is expected to significantly impact health IT infrastructures in the coming year by adding strain to wireless networks and clinical data storage. As the healthcare industry embraces AI-driven analytics technology, wireless networks need to support the devices collecting data and organizations need to have scalable repositories to store the collected data.
The more data AI solutions can access, the more successful its implementation will be. Organizations considering future AI initiatives need network visibility and control to ensure that EHR systems and other data points such as environmental, socioeconomic, and genetic data are able to communicate and work together before AI solutions are considered.
“When we look at healthcare IT, we’re focused on the applications that the clinicians are gonna use,” Bob Zemke. Director of Healthcare Solutions at Extreme Networks told HITInfrastructure.com. “It's always focused around the initiative that the clinicians are going to interface with and I think a lot of hospitals are caught off guard on the requirements on that back end to ensure the performance and delivery of those systems.”
In order to support future AI solutions, a healthcare network’s backend needs to support EHR systems and applications so they can deliver accurate information to clinicians.
“It seems like the network infrastructure is often neglected until the eleventh hour when there's a realization,” Zemke continued “Organizations need to focus on network infrastructure and it's visibility into applications. There is going to be that key foundation for the successful delivery of newly connected digital systems.”
Legacy wireless solutions cannot support the amount of data constantly moving through a network as more applications and systems are added. Wider bandwidths and access points (APs) that can support the increase of devices accessing data using applications along with scalability for system connections is required for a future AI solution.
Healthcare organizations need to determine the best storage strategy to support future AI analytics initiatives. Cloud-based storage is a flexible storage solution and often provides healthcare organizations with a more cost-effective storage solution over traditional on-premise deployments. When organizations begin to consider the future costs of scaling up based on the increased amount of data, budget concerns come to the forefront of the decisionmaking process.
On-premise storage solutions require organizations to purchase hardware and only offer a finite amount of space available before additional hardware needs to be added. Cloud services act as a utility with organizations paying monthly or yearly fees based on what they are using. As organizations need more space, they scale up their cloud service requirements and increase payments accordingly.
Healthcare IT decision-makers are growing to trust the cloud with EHRs and clinical data, according to a recent HIMSS survey.
“Cloud solutions are an extension of a healthcare organization’s communications infrastructure and connecting to the cloud is as mission critical as the platform itself,” survey analysts found. “Connectivity should easily ‘scale up,’ as more applications are moved to the cloud or more compute cycles are accessed for analytics.”
AI is still a young technology when it comes to enterprise IT infrastructure implementation, but it is expected grow significantly worldwide over the next several years. As healthcare organizations look to implement an AI solution in the near future, ensuring the organization’s health IT infrastructure can support it is key to deploying a successful AI analytics solution.