This article is contributed. See the original author and article here.
Hello everyone, I’m Basel Kablawi, PM on the Azure Edge and Platform – Core Networking team, here to announce the latest updates to the physical network switch requirements!
Our ecosystem of physical switches is designed to help ensure the compatibility and reliability of network switches with Azure Stack HCI, Microsoft’s hyperconverged infrastructure solution. By participating in this program, vendors can validate that their physical switches meet the network requirements for rock-solid interoperability with Azure Stack HCI solutions.
In this blog, we’ll discuss how we’re reclassifying the physical network switches that meet the requirements of Azure Stack HCIto answer the following questions, such as:
“Do I need a datacenter switch for every deployment architecture?”
“Does my management and compute switch need storage capabilities?”
“Are all 22H2 requirements needed for switchless configurations?”
And other related questions…
One of the core benefits of this program is helping you have a seamless deployment and operational experience. This eliminates the risk of switch compatibility issues that increase deployment and troubleshooting times. You know that when you select a physical switch, Azure Stack HCI has everything it needs for the highest quality experience.
Our previous approach required all devices to support each network requirement, regardless of the type of traffic the switch was used for. We heard your feedback, and this led us to update how we think about physical switches connected to Azure Stack HCI nodes.
What are we changing?
As with the recent change we made to network adapters, physical switches will now be aligned based on the traffic type that they carry. This means more, low-cost and high-quality devices will be available for selection over time. The traffic types are as follows:
Management traffic
Compute traffic – This can be broken down into two categories:
Standard virtual machine traffic
SDN enabled virtual machine traffic
Storage traffic
Here’s an example of the new structure which shows how the specific requirements map to a device carrying a certain type of network traffic:
For an updated mapping of the requirements, please see the documentation on our requirements page.
What does this mean for me?
This change is intended to expand our switch ecosystem by adding more validated switches.With this new approach, there is no more “one size fits all”. You simply pick a switch that has the required capabilities for your specific role types.
What if my switchisn’t listed in the catalog?
If you are utilizing a switch that currently is not on the list, please contact your physical switch vendor.
Is my device still validated for Azure Stack HCI?
All devices listed (21H2/22H2) at the time of this blog are still validated for Azure Stack HCI. Previously certified devices met all the requirements for each role type and as a result remain validated with these changes. All future devices will be validatedaccording to our updated requirements and testing tool results.
Summary
With the changes to our switch program, you can use the new validation structure to identify the best switches for your intended workloads, configuration, and more.
As always, if you have feedback, please leave a comment in the chat below.
This article is contributed. See the original author and article here.
With the rapid advance of Generative AI, as demonstrated by Microsoft, understandably folks are excited! Generative AI has tremendous promise in workload reduction in content creation. For folks working on company Intranets, organizational knowledge management, and more, the need for help is great. Oftentimes these are teams that have part-time roles and are often understaffed.
In this HLS Show Me How video I show how organizations can begin to leverage Microsoft Bing Generative AI with Microsoft Viva… today! Specifically, I show enhancing a Microsoft Viva Topics page with Generative AI content that can then be reviewed and edited. Although I show this action within Topics the same method is applicable in any aspect of Microsoft Viva, such as news in Connections, where content authoring is done.
*During the making of this video I show using the Developer Edition of Microsoft Edge. Literally as soon as I finished and went to post this using my production instance of the Microsoft Edge browser that edition was updated and now includes the Bing component with Generative AI!
This article is contributed. See the original author and article here.
It’s the dawn of a new era in customer experience where AI is transforming the way businesses connect with their audiences. Microsoft is proud to be at the forefront of this shift, using Azure OpenAI Service to empower marketers with new levels of efficiency and effectiveness. With Copilot in Microsoft Dynamics 365 Marketing and Dynamics 365 Customer Insights, marketers can now take advantage of the latest next-generation AI-powered tools to learn more about their customers, create targeted customer segments, and generate personalized content. These cutting-edge features increase productivity that could have taken hours or weeks to produce, empowering anyone on your team to uncover new data insights and create high-quality email content.
At Microsoft, we believe every business should have the ability to harness the power of next-generation AI. That’s why we’re excited about Copilot in Dynamics 365 and Azure OpenAI Service enabling our customers to do more with less by using these new technologies to be more productive. This is just the beginning, and we can’t wait to see where this technology will take us in the future. Here are just a few of the Copilot capabilities we will release in public preview in the coming weeks within Dynamics 365 Marketing and Customer Insights.
Discover more about your customers, faster
Today, customers expect hyper-personalization from the brands they interact with, which requires marketers to have a deep understanding of their customers. However, this knowledge is often locked away in data platforms and managed by data and analytics teams. Accessing this data and analyzing it using SQL queries can take weeks, delaying marketers from delivering the personalized experiences that customers demand.
The exciting new Copilot feature in Dynamics 365 Customer Insights allows data analysts and marketers to engage directly with customer data using natural language. This saves time for data analysts, allowing them to type the query in their own words instead of identifying the query in SQL. This feature democratizes access to insights, allowing marketers to ask questions using everyday language and receive instant answers, without needing to have the knowledge of SQL programming. With simple prompts, marketers can explore, understand, and predict customer preferences and needs in near real time, reducing the reliance on the data and analytics team to provide them with the customer insights they need.
Copilot enables marketers to create targeted customer experiences and interactions that are informed by data-driven decision making. With access to the natural language data discovery feature in Customer Insights, they can build confidence by validating and discovering customer insights for their marketing strategies. For example, a marketer can ask Copilot how many of their customers fit the profile of currently residing in Washington, DC, who are over the age of 25, who have also attended a promotional event in the last six months. With just a few clicks, Copilot will present the results of their query, including the number of customers that match the attributes or behaviors, as well as other useful information such as the customer lifetime value, product preferences, or average purchase price. Copilot in Dynamics 365 Customer Insights removes the barrier of needing to craft queries in SQL to get a deeper understanding of customers, enabling marketers to speed and scale the delivery of hyper-personalized experiences that customers expect.
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But that’s not allthe work to target the right audience just got easier for marketers, as they can now bypass the time-consuming process of manually building customer segments. With query assist, a new Copilot feature in Dynamics 365 Marketing, marketers can take the guesswork out of targeting the right audience by simply describing the segment in their own words. From there, query assist builds the segment that meets the marketers’ request and enables them to quickly review and modify the list before their next email campaign.
Previously, marketers had to rely on that one person in the company who understands data models and queries to create the target segment. With generative AI targeting, marketers can now quickly go from planning to execution.
Craft captivating content with ease
Finally, we are excited to share the release of our other Copilot in Dynamics 365 Marketing capability, content ideas, which harnesses next-generation AI to offer unparalleled assistance to marketers in their content creation efforts. Content ideas uses AI to generate content, allowing marketers to save time while still providing engaging and relevant emails for their target audience.
To create this powerful capability, we spent more than 10 months working with hundreds of preview customers, gathering and analyzing marketing emails from the public domain to tune our AI model. The result is a highly accurate and reliable content idea engine that uses Azure OpenAI Service to generate content ideas that marketers can easily edit, personalize, and send to their customers. With the Copilot content ideas feature, marketers can spend less time on copywriting and more time on strategic marketing efforts.
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The benefits of using Copilot in Dynamics 365 Marketing and Customer Insights are clearreduced time spent on marketing tasks, improved efficiency, and higher quality content that connect marketing teams with their customers. And let’s not forget the excitement of working with cutting-edge technology that’s paving the way for a new era of marketing.
Join the waiting list for the Copilot in Dynamics 365 Customer Insights preview today. And visit Dynamics 365 Customer Insights to learn more about our customer data platform and sign up for a free trial.
Finally, to learn more about the depth and breadth of all the new Copilot features that are bringing next-generation AI to every line of business across Dynamics 365, please check out our announcement blog.
This article is contributed. See the original author and article here.
Today we are excited to announce the public preview of near real-time custom detections in Microsoft 365 Defender. This new frequency will allow you to respond to threats faster with automated responses and gain valuable time in stopping attacks and protecting your organization.
Automation is key to keeping up with attackers
While Microsoft’s eXtended Detection and Response (XDR) solution helps prioritize response activities and provides a unified experience that allows for more effective investigation at the incident level, the increasing volume and speed of sophisticated attacks remains challenging.
That’s why automation is becoming an increasingly important tool in optimizing the SOC process. Automating response actions for common alerts can help you stay on top of threats, protect your organization more effectively, and reduce response times. If you want to get started in Microsoft 365 Defender, check out this post.
For effective protection, most organizations have custom detection mechanisms in place that are unique to the requirements of their environment, but in order for these automations to be as effective as possible, the speed of detection is critical.
Detect in near real-time, respond in near real-time
To address the need for faster detections and response, we are thrilled to announce that you can now create custom detection rules that run in near real-time, in addition to existing frequencies ranging from every 24 hours to every hour. These detections can be integrated with the broad set of Microsoft 365 Defender across email, endpoint, and identity, leading to faster response times and faster mitigation of threats.
This means your custom logic will run and evaluate all available signals and alerts faster than ever before and will trigger your predefined response action immediately, once a match is detected.
This new frequency will be available in Microsoft 365 Defender as Continuous (NRT). Image 1 shows the configuration wizard for custom detection rules in Microsoft 365 Defender and the various frequency options you can choose from, including near real-time (NRT).
Image 1: Custom detection wizard with the frequency dropdown opened, new frequency of Continuous (NRT) is available.
When you configure a rule using the Continuous (NRT) frequency, the query is compared to every single event that gets into the service, and if there is a match, an alert is triggered. You can use the continuous frequency for queries referencing one table and using operators from the list of supported KQL operators.
Top use cases for custom detections and automated response actions
Monitoring for recent vulnerabilities
A common use case for a near real-time custom detection rule that we see with customers is monitoring for events that might indicate threat activity related to a recently disclosed vulnerability. For instance, you can use the DeviceProcessEvents table to look for the malicious string needed to exploit the Log4j vulnerability and configure remediation actions to run automatically on targeted devices, like initiating investigation on the device:
DeviceProcessEvents
| where ProcessCommandLine matches regex @'(?i)${jndi:(ldap|http|https|ldaps|dns|rmi|iiop)://(${([a-z]){1,20}:([a-z]){1,20}})?(([a-zA-Z0-9]|-){2,100})?(.([a-zA-Z0-9]|-){2,100})?.([a-zA-Z0-9]|-){2,100}.([a-z0-9]){2,20}(/).*}'
or InitiatingProcessCommandLine matches regex @'(?i)${jndi:(ldap|http|https|ldaps|dns|rmi|iiop)://(${([a-z]){1,20}:([a-z]){1,20}})?(([a-zA-Z0-9]|-){2,100})?(.([a-zA-Z0-9]|-){2,100})?.([a-zA-Z0-9]|-){2,100}.([a-z0-9]){2,20}(/).*}'
Detect and remove unwanted emails
Another use case is to look for unwanted emails, that may not necessarily be malicious but have been defined by the organization as unwanted and need to be automatically removed as soon as they are delivered. This empowers security admins to more easily manage mail flows from a security lens and can be done by configuring a Soft Delete remediation action:
EmailEvents
| where Subject contains "This account has been suspended!"
| where SenderFromAddress == "malicious@sender.com"
| where UrlCount > 0
An example of another scenario is to look for messages that spoof the recipient from a particular IP subnet and blocking this activity.
EmailEvents
| where SenderIPv4 startswith "xx.xx.xx." and SenderFromAddress == RecipientEmailAddress
Automation is critical to creating efficiencies in your SOC, but the speed of detection is fundamental to an effective response and keeping your organization safe.
The ability to define custom rules for near real-time detections is in public preview starting today and will enable your defenders to create effective response mechanisms with the breadth of Microsoft 365 Defender’s XDR signal across endpoints, email and more.
Learn more
Check out our documentation and explore how near real-time custom detections can enhance your SOC’s detection and response processes
Wondering which tables are supported by near real-time detections? Find them here.
Near real-time detections are available in public preview starting today. We would love to know what you think. Share your feedback with us in the Microsoft 365 Defender portal or by emailing AHfeedback@microsoft.com.
When:Wednesday, March 22, 2023, 9:30 AM – 2:00 PM (GMT+02:00)
Where:Johannesburg, Gauteng, South Africa
Microsoft Student Summit is an event designed for students and rising developers who are passionate about technology and eager to learn new skills and meet like-minded individuals. Attending the Microsoft Student Summit can provide students with a number of benefits, including:
Exposure to the Latest Technologies: The Microsoft Student Summit provides students with an opportunity to learn about and experience the latest Microsoft technologies, such as cloud computing and artificial intelligence.
Microsoft Learn: Microsoft Student Summit Cloud Skills Challenge are hands-on, allowing students to apply their knowledge and skills to real-world learning and challenges. This can be a valuable experience for students and rising developers who are looking to build their portfolios and demonstrate their abilities to future employers.
Career development: The Microsoft Student Summit can be a valuable resource for students who are interested in pursuing careers in technology. By attending the event, students can gain insights into the latest trends and innovations in the industry and connect with potential employers and recruiters.
Overall, the Microsoft Student Summit provides students and rising developers with a unique opportunity to learn and grow as individuals and technology professionals. Whether you are a beginner or an experienced technologist, the Microsoft Student Summit is a valuable investment in your future.
What is Student Summit?
Are you exploring a career in technology? Or looking to accelerate your technical career? Want to know what a “day in the life of” is really like before you dive in? Or get a jumpstart understanding the skills needed for success? Whether you are just starting your undergraduate degree or a seasoned professional curious about the tactical steps needed to accelerate your career, Microsoft Student Summit will help you discover how to gain expertise in today’s cutting-edge technology needed for your career.
What Will I Learn?
Tech Discover the cutting edge of Application Development and Developer Tools, Low Code/ No-Code / Fusion Development, and AI, Data and Machine Learning and how to build your expertise start your learning journey with our Student Summit Cloud Skills Challenge.
Community Tailored learning paths, upcoming networking events in your region, and invitations to join technical communities to help you deepen your technical expertise learn more at Microsoft Learn Student Hub.
Career Career advice about how to start and accelerate your technical career from industry experts.
This article is contributed. See the original author and article here.
Hello hello, everyone! Happy Friday!
Here’s a recap of what’s been going on in the MTC this week.
MTC Moments of the Week
To start things off, we want to first give a huge shoutout to this week’s MTC Member of the Week – @Kidd_Ip! Kidd is a MCT (Microsoft Certified Trainer) and full time IT pro who has made great contributions to a variety of Tech Community forums across Azure and M365. Way to go, Kidd!
Then on Thursday, we had our second AMA all about Windows Server – from upgrading older versions and the importance of regular updates, to the security features in the latest versions of Windows Server (2022). We received a lot of questions, which were answered by our panel of speakers from the Windows Servicing and Delivery team as well as Windows Server engineers and security product managers. Shout out to @Artem Pronichkin , @Rick Claus, @Scottmca, @Ned Pyle, @Rob Hindman, and the rest team for a great session!
And over on the Blogs, in honor of Women’s History Month, the Marketplace Community kicked off a series of interviews with women leaders in the ISV community. The first edition of this series features an interview between @justinroyal and Harmke Alkemade, AI Cloud Solution Architect at Microsoft and Co-Founder at Friendly Flows. We love to see it!
Did you know that the concept of what we know today as “Spring Break” (in the US, at least) began in 1938, when a college swimming coach, Sam Ingram, brought his team down from New York to Fort Lauderdale, Florida in 1936 to train? When the word got around to other swim coaches, they followed suit, and it began an annual pilgrimage for swimmers from across the US to enjoy the sun – and have some fun. The more you know!
Have a great weekend, everyone, and don’t forget to spring forward on Sunday!
This article is contributed. See the original author and article here.
Welcome to the conclusion of our series on OpenAI and Microsoft Sentinel! Back in Part 1, we introduced the Azure Logic Apps connector for OpenAI and explored the parameters that influence text completion from the GPT3 family of OpenAI Large Language Models (LLMs) with a simple use case: describing the MITRE ATT&CK tactics associated with a Microsoft Sentinel incident. Part 2 covered another useful scenario, summarizing a KQL analytics rule extracted from Sentinel using its REST API. In Part 3, we revisited the first use case and compared the Text Completion (DaVinci) and Chat Completion (Turbo) models. What’s left to cover? Well, quite a lot – let’s get started!
There is some incredible work happening every day by Microsoft employees, MVPs, partners, and independent researchers to harness the power of generative AI everywhere. Within the security field, though, one of the most important topics for AI researchers is data privacy. We could easily extract all entities from a Microsoft Sentinel incident and send them through OpenAI’s API for ChatGPT to summarize and draw conclusions – in fact, I’ve seen half a dozen new projects on GitHub just this week doing exactly that. It’s certainly a fun project for development and testing, but no enterprise SOC wants to export potentially sensitive file hashes, IP addresses, domains, workstation hostnames, and security principals to a third party without strictly defined data sharing agreements (or at all, if they can help it). How can we keep sensitive information private to the organization while still getting benefit from innovative AI solutions such as ChatGPT?
Enter Azure OpenAI Service!
Azure OpenAI Service provides REST API access to the same GPT-3.5, Codex, DALL-E 2, and other LLMs that we worked with earlier in this series, but with the security and enterprise benefits of Microsoft Azure. This service is deployed within your Azure subscription with encryption of data at rest and data privacy governed by Microsoft’s Responsible AI principles. Text completion models including DaVinci have been generally available on Azure OpenAI Service since December 14, 2022. While this article was being written, ChatGPT powered by the gpt-3.5-turbo model was just added to Preview. Access is limited right now, so be sure to apply for access to Azure OpenAI!
ChatGPT on Azure solves a major challenge in operationalizing generative AI LLMs for use in an enterprise SOC. We’ve already seen automation for summarizing incident details, related entities, and analytic rules – and if you’ve followed this series, we’ve actually built several examples! What’s next? I’ve compiled a few examples that I think highlight where AI will bring the most value to a security team in the coming weeks and months.
As an AI copilot for SOC analysts and incident responders, ChatGPT could power a natural language assistant interfacing with security operators through Microsoft Teams to provide a common operating picture of an incident in progress. Check out Chris Stelzer’s innovative work with #SOCGPT for an example of this capability.
ChatGPT could give analysts a head start on hunting for advanced threats in Microsoft 365 Defender Advanced Hunting by transforming Sentinel analytic rules into product-specific hunting queries. A Microsoft colleague has done some pioneering work with ChatGPT for purple-teaming scenarios, both generating and detecting exploit code – the possibilities here are endless.
ChatGPT’s ability to summarize large amounts of information could make it invaluable for incident documentation. Imagine an internal SharePoint with summaries on every closed incident from the past two years!
There are still a few areas where ChatGPT, as innovative as it is, won’t replace human expertise and purpose-built systems. Entity research is one such example; it’s absolutely crucial to have fully defined, normalized telemetry for security analytics and entity mapping. ChatGPT’s models are trained on a very large but still finite set of data and cannot be relied on for real-time threat intelligence. Similarly, ChatGPT’s generated code must always be reviewed before being implemented in production.
I can’t wait to see what happens with OpenAI and security research this year! What security use cases have you found for generative AI? Leave a comment below!
This article is contributed. See the original author and article here.
We’re entering the era of next-generation AI that is driving new levels of productivity and efficiency, unleashing new innovations in the customer service space. AI is profoundly changing how customers engage with businesses and how agents provide exceptional service to them.
From a service perspective, customers expect fast, accurate answers to their questions, and personalized help when they contact a business. Meanwhile, businesses are under pressure to provide exceptional customer service with fewer resources. Legacy ways of integrating multiple-point solutions for customer service do not work. The time to embark on a digital transformation journey is now. Choosing the right AI-powered customer service solution for that journey, empowering customer service agents with AI, and reducing costs has never been more important.
We’re excited to launch Copilot in Dynamics 365 Customer Service, which provides agents with real-time AI-powered assistance, developed in alignment with our responsible AI principles and standards. Copilot helps agents resolve issues faster, handle cases more efficiently, and automate time-consuming tasks so they can focus on delivering high-quality service to their customers. In a nutshell, Copilot can help every agent to become your best agent.
With just a click of a button, Copilot empowers any agent to obtain the most relevant answer to any complex question that a customer may have and deliver a tailored response to the customer in real time using chat messages and emails. Copilot is available to agents as part of their natural flow of solving problems using Customer Service workspace. It’s like having an expert at your fingertips, always ready to assist.
Let’s take a closer look at the ways Copilot revolutionizes customer service and enables agents to deliver fast and relevant resolutions to customer problems.
Make every customer service agent a superagent
Today, when agents get a question from a customer that they can’t answer immediately, they typically search multiple internal knowledge sources or try to find an internal expert to consult with. The amount of time it takes to read through search results, find the right solution, compose a response back to the customer, and resolve the case is often lengthy.
Now, agents can chat with the next-generation AI-powered Copilot in Dynamics 365 Customer Service right within Customer Service workspace. Copilot can diagnose customer problems, use the organization’s internal knowledge and vast amounts of data from trusted websites, and supply the agent with an appropriate solution to give to the customer.
Copilot analyzes customer data to identify patterns, anticipate customer needs, and make suggestions to the agent on how to best handle each interaction. With this powerful tool at their disposal, agents can handle more queries in less time, increasing efficiency and improving the overall customer experience. Since agents are always in the loop every step of the way, they are in full control of using AI to drive their productivity. Agents can verify the responses, check the resources, and personalize the message to match the customer’s specific needs to ensure their satisfaction and optimal experience.
Answer customer questions fast across channels
In today’s fragmented contact center solution space, agents are often inundated with multiple messages on different channels of engagement. They are overwhelmed by multitasking and context switching, often wondering how they can keep up with overflowing incoming requests.
With omnichannel capabilities in Dynamics 365 Customer Service, customer service agents get a streamlined view of incoming chats from a variety of channels (such as Apple Messages for Business, Google Business Messaging, text messages, and WhatsApp) integrated with case management. Agents can now use Copilot in Dynamics 365 Customer Service, which intelligently parses information from the conversation and contextualizes it with organizational and customer data. Furthermore, Copilot keeps track of historical interactions, and uses all of that information to recommend a tailored, helpful answer that agents can review before they respond. Customers get the best service, regardless of their choice of channel.
Send expertly crafted customer service emails
For agents who receive questions via email, Copilot in Dynamics 365 Customer Service can help create relevant and personalized email responses in seconds. Copilot provides agents with predefined prompts based on what the agent is trying to do, such as “suggest a call”, “request more information”, “empathize with feedback”, or “resolve the customer’s problem.” Agents can also provide their own custom prompt for more complex issues.
Normally, agents may spend many minutes or hours researching and composing a detailed email with all the necessary information. With Copilot, agents get a composed email response in an instant that they can review and send.This model drives unparalleled productivity for the agent and delivers personalized service for the customer.
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Enrich self-service with AI-powered conversational assistance
Dynamics 365 Customer Service now offers a powerful conversational experience with Power Virtual Agents, boosted by next-generation AI capabilities. Customers can get relevant answers to their questions immediately from intelligent conversational bots that use trusted websites and internal data. Enterprises also have the choice of using Nuance as an on-ramp for their digital transformation journey. Nuance announced new AI capabilities in Nuance Mix. Dynamics 365 Customer Service, together with Microsoft Teams, Microsoft Power Platform, Nuance, and Microsoft Azure, deliver truly transformative experiences for both agents and customers through the contact center.
Next-generation AI that is ready for enterprises
Azure OpenAI Service offers a range of privacy features, including data encryption and secure storage. It also allows users to control access to their data and provides detailed auditing and monitoring capabilities. Dynamics 365 is built on Azure OpenAI, so enterprises can rest assured that it offers the same level of data privacy and protection.
AI solutions built responsibly
We are committed to creating responsible AI by design. Our work is guided by a core set of principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. We are putting those principles into practice across the company to develop and deploy AI that will have a positive impact on society.
Try Copilot in Dynamics 365 Customer Service
Sign up for the limited preview of Copilot in Dynamics 365 Customer Service. This preview is available for instances in North America using the English US language.
Microsoft Business Applications Launch Event
On April 4, discover innovations across Microsoft Dynamics 365 and Microsoft Power Platform at a digital event.
This article is contributed. See the original author and article here.
Processing health insurance claims can be quite complex. This complexity is driven by a few factors, such as the messaging standards, the exchange protocol, workflow orchestration, all the way to the ingestion of the claim information in a standardize and scalable data stores. To enable operational, financial, and patient-centric data analytics, the claims data stores are often mapped to patient health records at the cohort, organization, or even population level.
What is X12 EDI?
Electronic Data Interchange (EDI) defines a messaging mechanism for unified communication across different organizations. X12 claims based processing refers to a set of standards for electronic data interchange (EDI) used in the healthcare industry to exchange information related to health claims. The X12 standard defines a specific format for electronic transactions that allows healthcare providers, insurers (payers), and other stakeholders to exchange data in a consistent and efficient manner. This cross-industry standard is accredited by the American National Standards Institution (ANSI). For simplicity, we will refer to ‘X12 EDI’ as ‘X12’ throughout this article.
What is FHIR?
FHIR® (Fast Healthcare Interoperability Resources) is a standard for exchanging information in the healthcare industry through web-based APIs with a broad range of resources to accommodate various healthcare use cases. These resources include patient demographics, clinical observations, medications, claims and procedures to name a few. It aims to improve the quality and efficiency of healthcare by promoting interoperability between different systems.
Azure Health Data Services is a suite of purpose-built technologies for protected health information (PHI) in the cloud. The FHIR service in Azure Health Data Services enables rapid exchange of health data using the Fast Healthcare Interoperability Resources (FHIR®) data standard. As part of a managed Platform-as-a-Service (PaaS), the FHIR service makes it easy for anyone working with health data to securely store and exchange Protected Health Information (PHI) in the cloud.
Why Convert X12 to FHIR?
FHIR is a modern, developer-friendly, born-in-the-cloud data standard compared to the aging X12. Converting from X12 to FHIR has many merits; (1) take advantage of FHIR interoperability and adoption to exchange claim information across various systems using modern and secure protocols, (2) unification of patient health and claim dataset into a single FHIR service in the cloud (3) enjoy a larger community of developers and evolving ecosystem at the global healthcare stage.
The Azure Solution
In essence, this article describes how to orchestrate the conversion of X12 claims to FHIR messages using Azure FHIR Service (with Azure Health Data Services), Azure Integration Account and Azure Logic Apps. Azure Logic Apps is a service within the Azure platform that enables developers to create workflows and automate business processes through the use of low-code/no-code visual and integration-based connectors. The service allows you to create, schedule, and manage workflows, that can be triggered by various events, such as receiving an HTTPS request or the arrival of a new file in an SFTP service. The Azure Integration Account is part of the Logic Apps Enterprise Integration Pack (EIP) and is a secure, manageable and scalable container for the integration artifacts that you create. The X12 XML Schema will be provided through the Azure Integration Account. The complete implementation of the X12 to FHIR conversion in Azure is available on GitHub.
Orchestration of X12 to FHIR Conversion
Azure Logic Apps orchestrates the conversion process from X12 to FHIR resources, allows for additional data quality checks, and then ingests the FHIR resources in the Azure FHIR Service as depicted in the following 4 steps:
X12 to FHIR
First, we ingest the X12 file content into the Azure Logic Apps workflow. In this sample, we submit the X12 file content in the body of an HTTPS Post request to the HTTPS endpoint exposed by Azure Logic Apps.
Initial data quality check and decoding is done using the Azure Logic Apps X12 connector leveraging the X12 XML schemas associated with the transaction sets. This step will verify that the sender is configured and enabled in the system and pick the correct agreement that is configured with the X12 schema. This schema is used to convert the X12 data to XML.
Once the X12 file is validated and decoded into the XML format, the XML content can then be converted to FHIR using the Azure Logic Apps XML to JSON Liquid connector. This uses DotLiquid templates to map the XML content to the corresponding FHIR resources.
The output of the workflow is to store the data in Azure FHIR Service (with Azure Health Data Services) to support a unified view of the patient’s record. The FHIR service supports an HTTP REST endpoint where individual resources can be managed or sent as an atomic transaction using a FHIR bundle.
FHIR Resources
Various FHIR resources can be generated from an X12 transaction set. Depending on business requirements and entities participating in the integration, these resources will vary.
Metadata bout the X12 message including the raw message.
Liquid Template Sample
A sample liquid template is provided showing how to extract data from the decoded X12 file. In the following snippet, the elements under ‘content’ correspond to XML elements in the decoded X12 file. The XML elements are being mapped to the ‘total’ attribute of the ‘Claim’ FHIR resource.
Patient and provider identifiers in the transaction set may not correspond directly to the FHIR identifiers for those matching resources. A lookup approach may be needed to map the data such as an EMPI (enterprise master patient index) and Provider Registry. These mappings can exist in a separate data store or using the FHIR Identifier data type for the corresponding FHIR resource.
Various X12 EDI schemas may need to be managed across your provider base. Each version of the transaction set will have a corresponding Liquid template which will also need to be versioned to convert the correct XML to FHIR. An approach around modularizing templates will be crucial to find the right balance for reusability.
Depending on the scale of the provider base and security requirements the architecture can be revised accordingly:
One instance of Azure Logic Apps can be created per provider providing full compute isolation.
Azure Logic Apps also support parallelization allowing for a batch of X12 files to be submitted and then processed in parallel.
One instance of Azure Logic Apps and Azure FHIR Service can be associated with a certain geographic region which may be needed if data sovereignty is required.
Depending on business scenario, the ingestion process can be trigger from an SFTP event. Health organizations and providers can be associated with an Azure Storage Account enabled with SFTP where they can securely connect and manage their X12 artifacts.
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