Skip to main content

Network Visibility for the Delivery of Quality Healthcare

Michael Segal

Healthcare, in common with many other industries, is undergoing a significant digital transformation. As resources and purse strings become ever tighter, healthcare providers are becoming increasingly dependent on advancements in digital technology to enable them to do more with less.

The ability for healthcare practitioners and patients alike to securely access to electronic medical records (EMR) in real time, for example, not only improves an organization's operational efficiency, but can also enable more accurate diagnosis of a patient's condition, and inform their ongoing treatment plan.

Similarly, the introduction of e-prescriptions and the expansion of Wi-Fi connectivity throughout hospitals and doctors' surgeries have led to a reduction in administrative burden, freeing up frontline operatives to allow them to focus more on delivering high-quality services to their patients.

What's more, the ongoing adoption of the Internet of Things (IoT), and the use of connected wearable devices in particular, has opened up new, innovative ways of monitoring patients' health and measuring the effect of their treatment.

However, while the health and efficiency benefits of this digital transformation are clear, it is having an impact on the IT networks that power today's healthcare providers. The increased complexity that comes with the introduction of these new technologies is responsible for performance issues and potential vulnerabilities, leading to a need for greater visibility into the data crossing these networks, and for a view of how better to manage the technology itself.

Protecting Patient Care

Healthcare providers never have a "typical" business day. Given the organic nature of a hospital, for example, where patients, staff and visitors are continuously moving in and out of the campus, and a wealth of different devices are being added and removed on an ongoing basis, the demand on its network and services will be unpredictable at best. It's vital, therefore, to have better insight into the performance of services across the network.

Protecting patient care in today's hyper-connected world largely depends on protecting and optimizing a healthcare provider's wired and wireless networks, and the services that run through them. Much of the functionality — the key services and applications — upon which healthcare organizations rely, tends to be multi-vendor, requiring IT teams to ensure that everything is working together without friction. Achieving visibility into this environment is complicated by the fact that these services will be running across both physical and virtualized environments as well as private, public and hybrid cloud environments, which only adds to the levels of complexity.

High Availability

While challenges around network complexity and multi-vendor, siloed technologies may not, at first glance, appear to have much bearing on delivering high-quality patient care, any issues with either the network or applications will have a knock-on effect. Delays in accessing information, for example, such as appointment times, medical images, diagnostic data or drug interactions, can have a negative impact on a patient's experience of the service.

Network downtime is a challenge for healthcare providers, even when it's scheduled. Problems can be further amplified when an outage is unscheduled due to an application error or a breach, especially when you consider that hospitals and health systems are currently being targeted by cybercriminals at a rate of almost one a day. With one in five healthcare organizations claiming to have at least 5,000 devices connected to its network, each of which represents an endpoint that could be exploited for criminal gain, any outage resulting from such an attack could potentially put patient lives at risk.

Healthcare providers will continue to adopt innovative new digital services in a bid to improve efficiency and quality. With each of these services dependent on high availability, not only to ensure the seamless delivery of care, but also the protection of patients, the need for network visibility and service assurance before, during and after their implementation has never been more critical.

Hot Topics

The Latest

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

Network Visibility for the Delivery of Quality Healthcare

Michael Segal

Healthcare, in common with many other industries, is undergoing a significant digital transformation. As resources and purse strings become ever tighter, healthcare providers are becoming increasingly dependent on advancements in digital technology to enable them to do more with less.

The ability for healthcare practitioners and patients alike to securely access to electronic medical records (EMR) in real time, for example, not only improves an organization's operational efficiency, but can also enable more accurate diagnosis of a patient's condition, and inform their ongoing treatment plan.

Similarly, the introduction of e-prescriptions and the expansion of Wi-Fi connectivity throughout hospitals and doctors' surgeries have led to a reduction in administrative burden, freeing up frontline operatives to allow them to focus more on delivering high-quality services to their patients.

What's more, the ongoing adoption of the Internet of Things (IoT), and the use of connected wearable devices in particular, has opened up new, innovative ways of monitoring patients' health and measuring the effect of their treatment.

However, while the health and efficiency benefits of this digital transformation are clear, it is having an impact on the IT networks that power today's healthcare providers. The increased complexity that comes with the introduction of these new technologies is responsible for performance issues and potential vulnerabilities, leading to a need for greater visibility into the data crossing these networks, and for a view of how better to manage the technology itself.

Protecting Patient Care

Healthcare providers never have a "typical" business day. Given the organic nature of a hospital, for example, where patients, staff and visitors are continuously moving in and out of the campus, and a wealth of different devices are being added and removed on an ongoing basis, the demand on its network and services will be unpredictable at best. It's vital, therefore, to have better insight into the performance of services across the network.

Protecting patient care in today's hyper-connected world largely depends on protecting and optimizing a healthcare provider's wired and wireless networks, and the services that run through them. Much of the functionality — the key services and applications — upon which healthcare organizations rely, tends to be multi-vendor, requiring IT teams to ensure that everything is working together without friction. Achieving visibility into this environment is complicated by the fact that these services will be running across both physical and virtualized environments as well as private, public and hybrid cloud environments, which only adds to the levels of complexity.

High Availability

While challenges around network complexity and multi-vendor, siloed technologies may not, at first glance, appear to have much bearing on delivering high-quality patient care, any issues with either the network or applications will have a knock-on effect. Delays in accessing information, for example, such as appointment times, medical images, diagnostic data or drug interactions, can have a negative impact on a patient's experience of the service.

Network downtime is a challenge for healthcare providers, even when it's scheduled. Problems can be further amplified when an outage is unscheduled due to an application error or a breach, especially when you consider that hospitals and health systems are currently being targeted by cybercriminals at a rate of almost one a day. With one in five healthcare organizations claiming to have at least 5,000 devices connected to its network, each of which represents an endpoint that could be exploited for criminal gain, any outage resulting from such an attack could potentially put patient lives at risk.

Healthcare providers will continue to adopt innovative new digital services in a bid to improve efficiency and quality. With each of these services dependent on high availability, not only to ensure the seamless delivery of care, but also the protection of patients, the need for network visibility and service assurance before, during and after their implementation has never been more critical.

Hot Topics

The Latest

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...