Three ways analytics are improving clinical outcomes – Microsoft Industry Blogs

hospital management listening to doctor

According to Accenture Digital Health Technology Vision 2017, 84 percent of healthcare executives believe artificial intelligence (AI) will revolutionize the way they gain information. And many health organizations are already taking advantage of technologies such as AI and advanced analytics to gain insights that help them improve clinical treatment processes and outcomes. In fact, there’s a broad spectrum of use cases for clinical analytics.

Anticipating patient needs

Some of the first ways that health organizations have applied clinical analytics: looking for gaps in care and better predicting patient needs.

That’s becoming especially important with managed care models where health organizations receive reimbursement based not just on episodic health services but also on factors like length of stay (LOS) and readmission rates. Health systems are taking advantage of analytics to help them correlate staffing with anticipated patient needs and better coordinate care so they can improve patient outcomes and reduce LOS and readmission rates.

For example, Steward Health Care analyzed multiple types of data—such as CDC, flu, seasonality, and social data—using Microsoft Azure Machine Learning to predict patient volume so they could staff accordingly.

The results have been impressive. The private hospital operator can predict volumes one to two weeks out with 98 percent accuracy. And it reduced the average LOS for patients by one and a half days. In other words, improved nurse scheduling is helping patients get better faster. It has also increased patient satisfaction. All this, plus: Steward Health Care is saving $48 million per year.

Empowering care teams with predictive care guidance

The next level up in clinical analytics is predictive care guidance. A great example comes from Ochsner Health System—where they’ve integrated AI into patient care workflows.

Care teams there get “pre-code” alerts through an Azure-based platform (from our partner Epic) so they can proactively intervene sooner to help prevent emergency situations. The AI tool analyzes thousands of data points to predict which patients face immediate risks.

“It’s like a triage tool,” says Michael Truxillo, Medical Director of the Rapid Response and Resuscitation Team at Ochsner Medical Center, in this article. “A physician may be supervising 16 to 20 patients on a unit and knowing who needs your attention the most is always a challenge. The tool says, ‘Hey, based on lab values, vital signs, and other data, look at this patient now.’”

During a 90-day pilot project with the tool, Ochsner reduced the hospital’s typical number of codes (cardiac or respiratory arrests) by 44 percent. That incredible number demonstrates the impact AI-driven predictive care guidance can have on clinical outcomes.

Accelerating rare disease diagnoses

Yet another example on the clinical analytics continuum is the work we’re doing with Shire and EURORDIS to accelerate the diagnosis of rare disease. Together, we’ve formed The Global Commission to End the Diagnostic Odyssey for Children with a Rare Disease. As part of the commission’s efforts, phenotypic data (the physical presentation of a person) and genomic data are analyzed to gain insights that could help physicians identify and diagnose patients with a rare disease more quickly.

On average, it takes five years before a rare disease patient—of which approximately half are children—receives the correct diagnosis. Harnessing the power of AI-driven clinical analytics, the alliance aims to shorten the multi-year journey that patients and families endure before receiving a rare disease diagnosis. And that’s one of the most important issues affecting the health, longevity, and well-being for those patients and families.

Those are just a few examples of how AI and advanced analytics can transform healthcare and improve clinical outcomes.

Together with our partners, we’re dedicated to learning and growing alongside our customers and helping them achieve the quadruple aim through clinical analytics and other cloud-based health solutions. We’re also committed to helping them meet their security needs and safeguard the privacy of PHI. And our customers have peace of mind when innovating with us thanks to our Shared Innovation Principles that provide clarity around co-creating technology. We value our customers and partners’ expertise and don’t seek to own it. Rather, we help them monetize their technology assets.

However your health organization wants to use—or advance your use of—clinical analytics, you can learn how to take advantage of AI tools and see more real-world use cases in the e-book: Breaking down AI: 10 real applications in healthcare.

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Author: Steve Clarke

F5-Nginx deal reflects mainstream trend toward microservices

This week’s F5-Nginx deal heralds the arrival of widespread enterprise microservices use, and enterprises will soon see a bounty of products, from traditional vendors to startups, that address the convergence of networking and app components.  

F5 Networks Inc. makes application delivery controllers (ADC) that were originally hardware-based but more recently delivered as virtual appliances. Nginx Inc., which F5 acquired this week for $670 million, started out as an open source project in 2004 that resulted in a software-based web and application server now in widespread use, and more recently a paid subscription version, Nginx Plus.

Nginx generated revenue of $26 million in 2018, which represented 65% growth over 2017, and has 1,300 paying customers for its Nginx Plus subscription, F5 execs said in a conference call. The open source Nginx has much wider reach, and is used by 60% of the busiest 100,000 sites on the web, they said.

“F5 had a hard time cracking DevOps, as their brand is associated with traditional IT and network operations buyers,” said Brad Casemore, analyst at IDC. “Now they have no choice but to figure it out.”

DevOps and modern application architectures, including microservices, force traditionally separate network operations and application development teams to collaborate. Their first order of business is usually to mitigate the strain from microservices, which generate heavy “east-west” traffic between application components, on corporate networks designed for hierarchical intermachine “north-south” patterns.

“Worlds are colliding,” Casemore said. “There’s always been a clear demarcation of responsibility between network operations and application teams, but now developers and DevOps teams need visibility and some ability to operate the network.”

Things like discovery and east-west load balancing are network-borne. … As people scale [distributed microservices] environments for production runtime and scale, the network really comes into play.
Brad Casemoreanalyst, IDC

Containers and container orchestration, the computing infrastructure of choice for microservices, demand software-defined approaches to network devices, which is where Nginx virtual ingress controllers and API gateways come into play for F5.

“Nginx basically provides the same services for distributed apps that F5’s portfolio provides for traditional enterprise apps,” said Torsten Volk, analyst at Enterprise Management Associates. “Now F5 is able to cover both sides of the story, the 80% of remaining traditional apps and the 20% of web apps, some of which are microservices-based.”

The fact that F5 bought Nginx to speed up its microservices network development indicates that cloud-native applications are headed for the IT mainstream, since networking often trails innovations at the application and compute layer.

“Things like discovery and east-west load balancing are network-borne and need to be considered,” Casemore said. “There’s been a realization that as people scale these environments for production runtime and scale, the network really comes into play.”

Microservices musical chairs will force an industry reckoning

As network and application management worlds collide in IT, a wide array of vendors scrambles to target developers. Thus, as with container management and IT monitoring, DevOps pros will have a bounty of choices among microservices network management products that attack the problem from multiple angles.

Network management competitors to F5, such as Cisco, also offer software-defined network tools and microservices management platforms that incorporate Kubernetes container orchestration. Server virtualization bellwether VMware plans to join its NSX software-defined network IP with Heptio’s ingress controller and service mesh capabilities. Meanwhile, DevOps software players such as HashiCorp already offer multi-cloud network abstraction tools that F5 said it plans to deliver through Nginx.

Nginx is also something of an outsider in service mesh, which has generated strong buzz among DevOps early adopters. Nginx released its own service mesh product with its Application Platform in October 2018, but it was overshadowed by other projects, such as Istio, Linkerd and HashiCorp’s Consul Connect.

Widespread service mesh adoption is still a ways off, and probably wasn’t the main driver for the F5-Nginx deal, Volk said.

“Even if you want to adopt Istio as an enterprise, you still require most of the components that are included in Nginx already to complete your distributed microservices app architecture,” he said.

However, as microservices networking moves beyond the ingress controller and into the container cluster itself, it will challenge the new F5-Nginx entity to evolve along with customers, according to IDC’s Casemore.

“[F5] needs to address both a distributed model for technical architecture and a buying center and influencer challenge,” he said. “Networking ultimately needs to be closer to applications, within [Kubernetes] pods.”

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For Sale – HP Desktops and Acer Monitors for Sale

8 Units- HP Desktop Computer Elite 8000 Core 2 Duo E8400 (3.00 GHz) 4 GB DDR3 160 GB HDD Windows 7 Professional 64-Bit

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All were purchased refurbished and were never used thereafter. All computers come with keyboard and mouse.

Whole Lot Available for $1200, pm if interested.

– Andrew

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Price and currency: 1200
Delivery: Goods must be exchanged in person
Payment method: venmo, cash
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Advertised elsewhere?: Advertised elsewhere
Prefer goods collected?: I prefer the goods to be collected

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By replying to this thread you agree to abide by the trading rules detailed here.
Please be advised, all buyers and sellers should satisfy themselves that the other party is genuine by providing the following via private conversation to each other after negotiations are complete and prior to dispatching goods and making payment:

  • Landline telephone number. Make a call to check out the area code and number are correct, too
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DO NOT proceed with a deal until you are completely satisfied with all details being correct. It’s in your best interest to check out these details yourself.

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Three ways analytics are improving clinical outcomes – Microsoft Industry Blogs

hospital management listening to doctor

According to Accenture Digital Health Technology Vision 2017, 84 percent of healthcare executives believe artificial intelligence (AI) will revolutionize the way they gain information. And many health organizations are already taking advantage of technologies such as AI and advanced analytics to gain insights that help them improve clinical treatment processes and outcomes. In fact, there’s a broad spectrum of use cases for clinical analytics.

Anticipating patient needs

Some of the first ways that health organizations have applied clinical analytics: looking for gaps in care and better predicting patient needs.

That’s becoming especially important with managed care models where health organizations receive reimbursement based not just on episodic health services but also on factors like length of stay (LOS) and readmission rates. Health systems are taking advantage of analytics to help them correlate staffing with anticipated patient needs and better coordinate care so they can improve patient outcomes and reduce LOS and readmission rates.

For example, Steward Health Care analyzed multiple types of data—such as CDC, flu, seasonality, and social data—using Microsoft Azure Machine Learning to predict patient volume so they could staff accordingly.

The results have been impressive. The private hospital operator can predict volumes one to two weeks out with 98 percent accuracy. And it reduced the average LOS for patients by one and a half days. In other words, improved nurse scheduling is helping patients get better faster. It has also increased patient satisfaction. All this, plus: Steward Health Care is saving $48 million per year.

Empowering care teams with predictive care guidance

The next level up in clinical analytics is predictive care guidance. A great example comes from Ochsner Health System—where they’ve integrated AI into patient care workflows.

Care teams there get “pre-code” alerts through an Azure-based platform (from our partner Epic) so they can proactively intervene sooner to help prevent emergency situations. The AI tool analyzes thousands of data points to predict which patients face immediate risks.

“It’s like a triage tool,” says Michael Truxillo, Medical Director of the Rapid Response and Resuscitation Team at Ochsner Medical Center, in this article. “A physician may be supervising 16 to 20 patients on a unit and knowing who needs your attention the most is always a challenge. The tool says, ‘Hey, based on lab values, vital signs, and other data, look at this patient now.’”

During a 90-day pilot project with the tool, Ochsner reduced the hospital’s typical number of codes (cardiac or respiratory arrests) by 44 percent. That incredible number demonstrates the impact AI-driven predictive care guidance can have on clinical outcomes.

Accelerating rare disease diagnoses

Yet another example on the clinical analytics continuum is the work we’re doing with Shire and EURORDIS to accelerate the diagnosis of rare disease. Together, we’ve formed The Global Commission to End the Diagnostic Odyssey for Children with a Rare Disease. As part of the commission’s efforts, phenotypic data (the physical presentation of a person) and genomic data are analyzed to gain insights that could help physicians identify and diagnose patients with a rare disease more quickly.

On average, it takes five years before a rare disease patient—of which approximately half are children—receives the correct diagnosis. Harnessing the power of AI-driven clinical analytics, the alliance aims to shorten the multi-year journey that patients and families endure before receiving a rare disease diagnosis. And that’s one of the most important issues affecting the health, longevity, and well-being for those patients and families.

Those are just a few examples of how AI and advanced analytics can transform healthcare and improve clinical outcomes.

Together with our partners, we’re dedicated to learning and growing alongside our customers and helping them achieve the quadruple aim through clinical analytics and other cloud-based health solutions. We’re also committed to helping them meet their security needs and safeguard the privacy of PHI. And our customers have peace of mind when innovating with us thanks to our Shared Innovation Principles that provide clarity around co-creating technology. We value our customers and partners’ expertise and don’t seek to own it. Rather, we help them monetize their technology assets.

However your health organization wants to use—or advance your use of—clinical analytics, you can learn how to take advantage of AI tools and see more real-world use cases in the e-book: Breaking down AI: 10 real applications in healthcare.

Go to Original Article
Author: Steve Clarke

How do you build Windows Server 2019 cluster sets?

Windows Server 2019 cluster sets bring traditional clustering to a new level to improve workload mobility and protect applications from interruptions. But it takes some work to build the high availability fabric.

First, administrators must configure a management client and install the failover cluster tools on the management server. Next, administrators create the member clusters, which should consist of at least two clusters with at least two Cluster Shared Volumes on each cluster. Finally, administrators make a separate management cluster that oversees the member clusters. Microsoft designed Windows Server 2019 cluster sets with a separate management cluster to keep its services alive in the event of a node failure.

Administrators must then run a series of PowerShell commands to create the Windows Server 2019 cluster set. Microsoft provides detailed instructions on its documentation site, but the overall process is summarized below.

First, construct at least two clusters consisting of at least two nodes, as well as a management cluster. Next, use PowerShell to create the cluster set, give it a name and then add the member clusters.

Once the cluster set is built, administrators can use PowerShell cmdlets to list the member clusters and nodes:

Windows Server 2019 cluster sets produce debugging logs for member clusters and the management cluster.

  • Get-ClusterSetMember lists the nodes and properties of each node within the cluster set.
  • Get-ClusterSet lists the member clusters, including management cluster nodes. Additional command-line switches can tell the command to list resource groups across the cluster set.
  • Get-ClusterSetNode lists all the nodes from the member clusters.

Windows Server 2019 cluster sets produce debugging logs for member clusters and the management cluster. Use the Get-ClusterSetLog cmdlet to gather these logs for review, auditing and troubleshooting.

Establishing security in member clusters is an important part of this deployment. Administrators typically configure Kerberos constrained delegation for member clusters and also use Kerberos authentication for cross-cluster VM live migration among member clusters in the cluster set.

A final step is often to add the management cluster to the local administrators group on each member cluster.

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Automate, customize CI/CD pipelines with Bitbucket Pipes

With its Bitbucket Pipes technology, Atlassian gives developers a way to automate their CI/CD pipelines, with integrations to more than 30 DevOps tools and services.

Bitbucket is Atlassian’s Git-based tool for professional development teams. Bitbucket Pipes, released in late February, enables developers to customize their CI/CD pipelines to meet their specific needs.

Developers responsible for building and managing CI/CD pipelines typically have to use multiple tools and manually write pipeline integrations. However, Bitbucket Pipes eliminates that manual process, said Harpreet Singh, head of products for Bitbucket Cloud at Atlassian.

Building pipes

Atlassian worked with vendors, including Google, Microsoft, Slack, AWS and others, to build integrations — or “pipes” — to automate CI/CD pipelines, Singh said.

Bitbucket Pipes is analogous to plumbing that interconnects pipes to bring water into a house, he said. In a similar manner, when developers build CI/CD pipelines, they have to interact with a number of tools to build integrations. And these integrations are manually written as scripts within pipelines — a process that can be error-prone, Singh said.

This can result in “duct tape DevOps,” where these scripts are haphazardly connected, he said. Bitbucket Pipes automates this process, enabling developers to build sophisticated pipelines and avoid duct tape DevOps scenarios. It integrates with a set of DevOps tools that developers can just drop into their configuration, and Pipes will connect to the tool.

“It is a great step — the ability to simplify how you plug in the various components you want to use as you build and deploy software,” said Thomas Murphy, an industry analyst at Gartner.

Atlassian’s Bitbucket Pipes provides a service-oriented approach that has become a common thread in software development, he said. This approach involves providing pluggable tools that are flexible enough to fit developer needs and adaptable enough to withstand changes in technology, Murphy said.

“We want to help you connect with the tools that you use today and take away the onus of writing these complex configurations,” Singh said.

This can reduce the time it takes for developers to move code to production.

Code script before and after Bitbucket Pipes
Code script before and after Pipes

Integrating pipelines

Two of Atlassian’s core philosophies are to make development teams work together better, and there is no one-size-fits-all tool for developers.

“Developers use all kinds of tools, and we want to meet them where they are,” Singh said. Thus, Atlassian worked with 20 different vendors to provide 30 pipes to connect to products and services, such as Azure Web Apps, Google Cloud, AWS Elastic Beanstalk, Datadog, JFrog and others.

JFrog’s DevOps tools help development teams release at high velocity, continuously updating from code commit through to production.

“Integrating our DevOps tools with coding and collaboration tools from Atlassian — including Bitbucket Pipes — is a development that will bind many companies’ entire complete delivery pipelines together efficiently,” said Kit Merker, vice president of business development at JFrog.

Other tools in the market with similar capabilities to Bitbucket Pipes include CircleCI Orbs from Circle Internet Services in San Francisco. CloudBees has done some work to simplify the pipeline, and there is some relation with GitHub actions — though they are not a CI provider, Murphy said.

Fewer lines of code

Moreover, DevOps pipelines rely on a lot of different components, many of them open source, and the pieces change all the time.

Developers spend a lot of time just keeping their build and deploy scripts up to date — not just for their code changes, but for changes to other components that the build relies on, Murphy said.

The bottom line is, if you have to write fewer lines of code, you are more insulated from changes, he said. And if the pipes are well-supported by third parties, it is all beneficial to developers.

It is a great step — the ability to simplify how you plug in the various components you want to use as you build and deploy software.
Thomas Murphyindustry analyst at Gartner

“Does this mean that Atlassian is jumping out in front of others? Not so much,” Murphy said. “But they are continuing to build a strong solution, and I think this is, in some ways, just a beginning for them and what they announce this year.”

The challenge with a product like Bitbucket Pipes is whether the provider, Atlassian, has to create something special to support each of these vendors that is building “simplification,” Murphy said.

Bitbucket is free to small teams of up to five users. Standard pricing for larger teams is $2 per user, per month, and starts at $10 a month. The Premium plan is a new pricing tier for larger teams that require granular admin controls, security and auditing capabilities. Premium pricing is $5 per user, per month, and starts at $25 a month. Each plan includes build minutes for Bitbucket Pipelines ranging from 50 minutes in the free plan to 1,000 minutes in the Premium plan.

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For Sale – Virtualisation PC /media PC

Hi mate I may have low feedback jut this would be the third time I have sent something before I have received payment.. The last stuff was over 450 pounds worth of stuff and then I had to chase for two days to get payment. So I would prefer not too
I also stated that that the price doesn’t include delivery so will have to work something out there..
The case is in good condition I have just didn’t put it on properly for the first pic, third was to show how the ssd was seated lol

Forgot to mention its got an Intel pci e Nic card too.

One back panel is missing

No warranty except the ssd which I bought a few months back from Cex which should have two years and I’m happy to help with that.

Where abouts are you based as I travel alot for work

PayPal would work too.. I will get the post up for the last big sale too, I just haven’t received feedback for that yet

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