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Safeguard Healthcare Innovations with AIOps - Part 1

Sean McDermott
Windward Consulting Group

You've likely heard it before: every business is a digital business. That saying is increasingly true; however, some businesses and sectors digitize more quickly than others. Healthcare has traditionally been on the slower side of digital transformation and technology adoption, but that's changing.

A vast majority (81%) of worldwide healthcare executives say digital transformation is accelerating within their organizations, according to Accenture's Digital Health Technology Vision report. And 93% say they're innovating with urgency.

Even as a regular consumer, healthcare's digital transformation isn't hard to see. Readily available telehealth platforms connect patients and providers for more convenient and accessible healthcare services. And some caregivers use innovations like wearable devices to track patient health from afar.

Technology is also working behind the scenes to modernize healthcare organizations. Smart technologies can help this data-heavy industry modernize its internal systems, providing fast, accurate information on things like the number of available beds, patient status and supply inventory. Artificial intelligence (AI) can also do the heavy lifting typically involved in mundane administrative processes like paying bills, maintaining patient databases and scheduling appointments.

Many digital-first healthcare organizations are finding a new challenge as they embrace technology: businesses must guarantee seamless digital experiences. In other words, they must keep their apps and services always on and performing well.

Too often, there is so much attention on buying or developing apps and services that sustaining these innovations is overlooked. But system downtime can be costly for any business and particularly harmful for those in the healthcare industry.

As healthcare organizations roll out innovations at increasing velocity, they must build a long-term strategy for how they will maintain the uptime of their critical apps and services. And there's only one tool that can ensure this continuous availability in our modern IT ecosystems. Artificial Intelligence for IT Operations (AIOps) can help IT Operations teams ensure the uptime of critical apps and services.

How AIOps Helps Healthcare Systems

There's a common misconception: someone flips the technology "on" switch, and apps and services stay online and operate at peak performance. Unfortunately, this isn't the case.

Human IT Operations teams must operationalize healthcare technologies and then maintain them to provide reliable systems for patients, providers and other employees. After all, the systems, applications and networks behind the technologies that make our lives easier tend to be complex.

Maintaining uptime in these complex environments rides on monitoring and catching service-disrupting incidents before they impact the user. But humans can no longer perform this monitoring and detection alone because there is simply too much data for humans to process. Our modern systems prove too layered, interdependent and ephemeral. On top of this complexity, modern systems also spit out so much data that it's virtually impossible for human operators to handle, no matter how big the IT team.

The cadence of technology deployments and updates also makes uptime assurances more challenging. The very changes to the production environment that provide bigger and better technologies can also spark the service interruptions that lead to outages.

In short, the IT Operations teams charged with maintaining our modern IT ecosystems need help. And that's where AIOps comes in.

AIOps helps IT Operations teams simplify the management of ever complex and evolving IT systems. Through big data, automation and machine learning, a holistic AIOps solution detects potential service-disrupting incidents, identifies the problem and provides teams with the actionable insights they need to fix the problem — and keep it from happening again. If implemented correctly, these tools also automate the entire incident workflow to enable rapid responses that can catch issues early, before they impact the business.

Preventing outages is essential, but AIOps tools provide another advantage. With time added back into their days, engineering teams can focus on developing the kind of innovations that deliver tangible business value.

Go to: Safeguard Healthcare Innovations with AIOps - Part 2

Sean McDermott is the Founder of Windward Consulting Group and RedMonocle

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Safeguard Healthcare Innovations with AIOps - Part 1

Sean McDermott
Windward Consulting Group

You've likely heard it before: every business is a digital business. That saying is increasingly true; however, some businesses and sectors digitize more quickly than others. Healthcare has traditionally been on the slower side of digital transformation and technology adoption, but that's changing.

A vast majority (81%) of worldwide healthcare executives say digital transformation is accelerating within their organizations, according to Accenture's Digital Health Technology Vision report. And 93% say they're innovating with urgency.

Even as a regular consumer, healthcare's digital transformation isn't hard to see. Readily available telehealth platforms connect patients and providers for more convenient and accessible healthcare services. And some caregivers use innovations like wearable devices to track patient health from afar.

Technology is also working behind the scenes to modernize healthcare organizations. Smart technologies can help this data-heavy industry modernize its internal systems, providing fast, accurate information on things like the number of available beds, patient status and supply inventory. Artificial intelligence (AI) can also do the heavy lifting typically involved in mundane administrative processes like paying bills, maintaining patient databases and scheduling appointments.

Many digital-first healthcare organizations are finding a new challenge as they embrace technology: businesses must guarantee seamless digital experiences. In other words, they must keep their apps and services always on and performing well.

Too often, there is so much attention on buying or developing apps and services that sustaining these innovations is overlooked. But system downtime can be costly for any business and particularly harmful for those in the healthcare industry.

As healthcare organizations roll out innovations at increasing velocity, they must build a long-term strategy for how they will maintain the uptime of their critical apps and services. And there's only one tool that can ensure this continuous availability in our modern IT ecosystems. Artificial Intelligence for IT Operations (AIOps) can help IT Operations teams ensure the uptime of critical apps and services.

How AIOps Helps Healthcare Systems

There's a common misconception: someone flips the technology "on" switch, and apps and services stay online and operate at peak performance. Unfortunately, this isn't the case.

Human IT Operations teams must operationalize healthcare technologies and then maintain them to provide reliable systems for patients, providers and other employees. After all, the systems, applications and networks behind the technologies that make our lives easier tend to be complex.

Maintaining uptime in these complex environments rides on monitoring and catching service-disrupting incidents before they impact the user. But humans can no longer perform this monitoring and detection alone because there is simply too much data for humans to process. Our modern systems prove too layered, interdependent and ephemeral. On top of this complexity, modern systems also spit out so much data that it's virtually impossible for human operators to handle, no matter how big the IT team.

The cadence of technology deployments and updates also makes uptime assurances more challenging. The very changes to the production environment that provide bigger and better technologies can also spark the service interruptions that lead to outages.

In short, the IT Operations teams charged with maintaining our modern IT ecosystems need help. And that's where AIOps comes in.

AIOps helps IT Operations teams simplify the management of ever complex and evolving IT systems. Through big data, automation and machine learning, a holistic AIOps solution detects potential service-disrupting incidents, identifies the problem and provides teams with the actionable insights they need to fix the problem — and keep it from happening again. If implemented correctly, these tools also automate the entire incident workflow to enable rapid responses that can catch issues early, before they impact the business.

Preventing outages is essential, but AIOps tools provide another advantage. With time added back into their days, engineering teams can focus on developing the kind of innovations that deliver tangible business value.

Go to: Safeguard Healthcare Innovations with AIOps - Part 2

Sean McDermott is the Founder of Windward Consulting Group and RedMonocle

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...