AI-enabled healthcare
Navigating the Digital Deluge
Since the COVID-19 pandemic, a surge of innovation has emerged in the health and social care sector. Stimulated by a necessity to do things differently, the sector has continued to collaborate with technology partners to revolutionise the way UK health providers manage and interpret troves of unstructured data. The biggest challenges are volume and context. The sheer quantity of digital information generated by healthcare systems is massive. Data from governmental entities, medical practices, and patients themselves all needs to be brought together, but crucially, actionable insights need to be extracted from it in order for patient outcomes to be improved. This is where the power of applied artificial intelligence (AI) can step in.
AI's Role in Data Contextualisation
At Cloud Gateway, we are fortunate enough to work with organisations who design and deploy AI technologies such as natural language processing and knowledge graphing, to add context and coherence to unstructured data. By harnessing AI, these platforms transform fragmented information into cohesive, optimised datasets, facilitating a more holistic understanding of patient information and how they fit into a wider healthcare context.
Streamlining Clinical Processes with AI Automation
One such example of applied AI in healthcare is Dyad AI’s solution to streamline clinical processes. Through AI-driven automation, their systems identify pertinent information from clinical correspondence, categorising it into diagnoses, medications, results, or actionable items. By minimising the need for manual intervention, AI accelerates workflows, enabling healthcare providers to navigate patients towards appropriate care pathways in a fraction of the time it would take a human.
The Crucial Link: Reliable Connectivity as the Backbone
The efficacy of AI solutions hinges on reliable connectivity to critical healthcare infrastructure. While the promise of applied AI is exciting, solutions cannot operate effectively without a reliable network underlay to enable them. In Dyad’s case, their AI would not work without access to the very data they are contextualising, specifically, vital services like EMIS and SystmOne which are reachable solely via the Health and Social Care Network (HSCN). Foundational infrastructure must be capable of bridging the gap between these data sources and the cloud-built applications that implement artificial intelligence.
Partnering for Progress: Selecting Connectivity Providers
Selecting the right connectivity partner is a crucial step. They must be capable of quickly connecting many / any endpoints together - from clouds, to users and sites, as well as closed third party networks like the HSCN. Connections must be secure and scalable, with in-built flexibility to accommodate fluctuations in data demand, and support new AI innovations when they are ready to launch. In many cases, using the internet as this backbone is not appropriate, taking into account the sensitivity of patient data, and the lack of availability or uptime guarantees with this approach.
A Data-Driven Future in Healthcare
The marriage of applied AI with robust network connectivity marks a pivotal moment in healthcare innovation. The transformative potential of AI is clear, but this potential can only be fully realised with the support of reliable infrastructure. By forging strategic partnerships and leveraging advanced technologies, the healthcare sector stands poised to revolutionise patient care delivery, and can reap the benefits for years to come.
Visit Cloud Gateways website to find out more.
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