Recent Discussions
How Emerging Opportunities team at Microsoft uses Azure DevOps for project management
We want to share how we created a project management system with Scrum practices based on Azure DevOps. We chose the Scrum template from Azure DevOps that supports Work Items - Epics, Features, Product Backlog Items (PBIs) and Tasks as shown below. Epic represents the overall Project. Features are used to organize specific objectives within the project. To build the features, we need User Stories that group work into logical collections of activities. Tasks captures the actual work that needs to be done to satisfy the User story. During the planning of Sprint, each PBI in the current Sprint is given an estimated effort. Effort is defined as a relative estimate of the amount of work required to fully implement a PBI. To set the effort, you can use any numeric unit of measurement. e.g., powers of 2 (1, 2, 4, 😎 and the Fibonacci sequence (1, 2, 3, 5, 8, etc.). How do we know we are progressing in a Sprint and Sprint-over-Sprint? Sprint Burndown - By reviewing a sprint burndown report, we can monitor how much work remains in a sprint backlog, understand how quickly our team has completed tasks, and predict when our team will achieve the goals of the sprint. We defined it by the number of Tasks under each PBI. To achieve this, the measurement to do a task should be consistent. In our case, Task should be a work that can be completed in a day or less. If a Task, was not marked as Done in 3 days, it was classified as a blocker. This enabled us to easily find any blockers and focus on resolving them to keep the project moving forward. Velocity - We track the velocity to determine how much work we can perform sprint-over-sprint. Velocity provides an indication of how much work a team can complete during a sprint based either on a count of work items completed or the sum of estimates made to Effort (PBIs). By using Azure DevOps for project management, the built-in reporting for burndown charts and Sprint planning allows us to analyze progress, have reasonable expectations from the team, focus on prioritizing and keep everyone fully informed. Resources: Implement Scrum, track work in sprints - Azure Boards | Microsoft DocsCan Remote Patient Monitoring address many challenges in healthcare?
People who are old might need medical care and observation more often than younger people. That is to be expected as seniors are more prone to diseases and physical injury. Regular diseases aside, elders are also prone to long-term illnesses like dementia or Parkinson's disease. Moreover, lots of them even find it difficult to drive to a clinic or use smartphone applications to order a cab. It is estimated that the end of this decade will see tens of millions of people reach or surpass eighty years of age. The frailty increases drastically as one crosses eighty and they need constant support and care. Experts have warned that the United States is about to reach a tipping point in the area of eldercare, and the country is grossly unprepared. That is mainly because of the rapidly increasing cost of care, coupled with a dearth of home caregivers. In light of this looming problem, https://www.osplabs.com/remote-patient-monitoring-system/ technology has been touted as a promising solution to address the problem of senior care. As the name suggests, remote patient monitoring systems enable caregivers and providers to monitor a patient’s health situation outside clinical settings. The idea of a https://www.osplabs.com/remote-patient-monitoring-system/ based device is to collect the health information of a patient in real-time and transmit it to a physician. The physician can view the health vitals and know about the patient’s health situation. In other words, the doctor and patient need not even be in the same city. If the doctor sees abnormal health data, he or she can immediately notify the patient about it and have an in-person visit arranged. This is an excellent way for a single physician to observe the health vitals of multiple seniors from a remote location and ensure timely care. Recent innovations in remote healthcare monitoring have given immense hope to many physicians and people alike. Let’s look at some innovative remote health monitoring systems that help with senior care - Fall Detector As mentioned earlier, seniors who are of 80 years and above are frail and are at greater risk of accidents and physical injury. A little slip and fall could have catastrophic results. So, a fall detector installed at home alleviates this risk and allows family members to breathe easy. A fall detector is like a camera but without the usual video feed. It detects movement patterns of people in the room and knows if someone fell. It is powered by an advanced artificial intelligence algorithm and knows the difference between a person who fell, and someone who performs activities like bending over, squatting, or anything else. If it detects a fall, it automatically notifies people from a pre-determined list through push notifications or alerts. Moreover, since it doesn’t have a regular video feed, it ascertains privacy for the person being observed. This type of home health monitoring system also ensures peace of mind to the families of elders who might not live with them. Wearable Diagnostic Band This is a band to be worn on the wrist. It detects vitals like body temperature, heart rate, blood pressure, and electrocardiogram at regular intervals throughout the day. In case of deviation from established benchmarks of normalcy, the device automatically notifies the families of the user and also a designated caregiver. This type of patient monitoring software is excellent for seniors who can’t afford home care, and whose family doesn’t live with them. This device could also work as a kind of hospital monitoring system and enable physicians to track patient health in real-time.Working as a CNA
I am working as a CNA at a facility that is half long term care for elderly people and half temporary placement after surgeries, hospital stays etc. I am having a very hard time getting anyone to attend any activities. Most residents have a phone or a tablet are there any safe games or puzzles on the web they could do as a group or by themselves? Any help would be appreciated!Introducing Scalable and Enterprise-Grade Genomics Workflows in Azure ML
Genomics workflows are essential in bioinformatics as they help researchers analyse and interpret vast amounts of genomic data. However, creating a consistent and repeatable environment with specialized software and complex dependencies can be challenging, making integration with CI/CD tools difficult, too. Azure Machine Learning (Azure ML) is a cloud-based platform that provides a comprehensive set of tools and services for developing, deploying, and managing machine learning models. Azure ML offers great repeatability and auditability features natively that not many workflow solutions offer. It provides a highly integrated and standardised environment for running workflows, ensuring that each step is executed in a consistent and reproducible manner. This feature is particularly useful for genomics workflows that require the use of multiple tools and software packages of certain versions with specific dependencies. In this blog post, we will show how Azure ML can run genomics workflows efficiently and effectively, in addition to being an end-to-end platform for machine learning model training and deployment. Figure 1 illustrates an example of such a workflow. Figure 1: A sample genomics workflow running in Azure ML, consisting of 3 steps. A reference genome input dataset flows into the indexer step, while the sequence quality step gets its data from a folder of DNA sequences (".fastq" files). Azure ML has comprehensive audit and logging capabilities that track and record every step of the workflow, ensuring traceability and repeatability. One of the critical features of Azure ML to achieve these capabilities is its support for users to be able to specify Docker and Conda environments for each workflow step, which guarantees consistent environment execution. These environments can be versioned and centrally shared. Workflow steps within pipelines then can refer to a particular environment. Figure 2 shows one such environment, bwa, version "5". As we make modifications in the environment definition, the new version will be registered as "6", however, we will still be able to continue to use older versions. Figure 2: An example Azure ML environment, defining a Docker image containing the BWA bioinformatics software package. This is the 5th version of this environment registered under the name, "bwa". Like environments, Azure ML supports user created pipeline components that can be centrally registered for reuse in other pipelines, also versioned, and with an audit log of their usage. Runs are logged together with standard out and error streams generated by the underlying processes, automatically. MLflow logging and adding custom tags to all assets and runs are supported, too. This feature ensures that the results are consistent and reproducible, saving users’ time. An example versioned component is shown in Figure 3. Figure 3: An Azure ML component named "BWA Indexer". It is a self-contained, re-usable, versioned piece of code that does one step in a machine learning pipeline: running the bwa indexer command, in this instance. Versioning is not limited to environments and pipeline components. Another essential feature of Azure ML is its support for versioning all input datasets and genomic data, including overall pipeline input, and as well as intermediate step and final outputs, if needed. This feature enables users to keep track of dataset changes and ensure that the same version is used consistently across different runs of the workflow, or in others. There are many genomics workflow engines which are very good with multiple parallel execution when it comes to processing files in parallel. However, Azure ML parallel steps support parallel running both at the file-level (one by one, or 3 files at a time etc) and at the file chunk-level (50 MB of data per process, or 20 KB of text per node etc) where appropriate as supported by the consuming application, enabling the processing of large genomic datasets efficiently across elastic compute clusters that can auto-scale. Pipelines can even also run locally on your laptop for test/development phases, and of course support powerful CPU and GPU-based VMs, low priority or on-demand compute clusters, Spark engines, and other compute targets such as Azure Kubernetes, making it flexible for different use cases. Azure ML has integrations with Azure DevOps and GitHub Actions for CI/CD, making it easy to deploy and manage genomics workflows in a production environment, which in turn makes GenomicsOps possible. Well established pipelines ready for "production use" can be published, and called on-demand or from other Azure services including the Azure Data Factory and Synapse. This means we can create a schedule for running pipelines automatically, or whenever data become available. Thanks to its Python SDK, command line utility (az cli, ml extension), REST-API, and user-friendly UI, it makes it possible to develop pipelines and initiate pipeline runs from any preferred means, also providing easy monitoring and management of workflows. That said, event-based triggers and notifications are also supported. For instance, one can set up an email alert that will be triggered whenever a genomics pipeline finishes execution. As compute and storage are de-coupled, any pipeline input or output stored in an Azure ML datastore or blob storage can also be accessed by Azure ML’s Jupyter Notebooks for any upstream or downstream analysis. Azure ML is a managed PaaS service, making it an accessible and easy to set up platform for genomics researchers and bioinformaticians. Additionally, it has a Visual Studio Code integration for local development and has a workspace concept for managing pipeline projects, enabling collaboration, and Azure role-based access control (RBAC). In conclusion, Azure ML comes with advanced security features, including AD authentication, public & private endpoints, subscription-based event triggers, storage backed by the Azure Storage Service that comes with encryption at rest and in transit, and application insights, making it a reliable and already proven enterprise platform that can also be natively used for genomics research. For a more detailed tutorial that shows how to set up and run the example workflow shown in Figure 1, as well as for all the source code for creating the aforementioned sample environments and components, please check out this GitHub repository: truehand/azureml-genomics (github.com)
Microsoft Cloud for Healthcare: please help!
Hello, I have a client a (Healthcare System) who reached out and wants to utilize Microsoft Cloud for Healthcare. Yet, the Microsoft Account Manager I am working with says he doesn't know how to sell it and there's pretty much nothing we can do except consult with the Azure team? And they have pushed me back for weeks. This client wants to see a demo and have a final build by end of August but for the past three weeks I have made little progress due to my "contacts" at Microsoft. I fear this client is going to jump ship if I do not have an update- as you can see I am desperate. We are in a bad spot right now, so any help is good help. Thank you
5 ways Healthcare Organizations are leveraging Microsoft Azure for Cybersecurity
Healthcare organizations across the globe face mounting challenges when it comes to safeguarding sensitive patient data against cyber threats. In this digital age, leveraging advanced technology has become imperative for ensuring robust cybersecurity measures. Microsoft Azure, a cloud computing service, has emerged as a powerful ally for healthcare entities in fortifying their cybersecurity frameworks. Here are five ways healthcare organizations are utilizing Microsoft Azure to bolster their cybersecurity measures: Advanced Threat Protection: Microsoft Azure offers advanced threat protection capabilities that enable healthcare organizations to proactively detect and respond to potential security threats. Leveraging Azure's sophisticated tools like Azure Security Center and Azure Sentinel, healthcare entities can gain real-time insights into their network, identify anomalies, and swiftly mitigate potential risks before they escalate. Secure Cloud Infrastructure: With Azure's robust infrastructure, healthcare organizations can securely store and manage vast amounts of patient data in compliance with stringent regulatory requirements such as HIPAA. Azure's built-in security features, including encryption, firewalls, and access controls, ensure that sensitive healthcare information remains protected while stored or transmitted across the cloud. Compliance and Governance: Healthcare organizations are bound by strict regulatory standards concerning data privacy and security. Microsoft Azure aids in ensuring compliance with industry regulations by providing specialized compliance offerings and adherence to international standards. Azure's compliance certifications, including HIPAA and HITRUST, offer healthcare entities peace of mind by aligning with industry best practices. AI-Powered Security Analytics: Azure's integration with artificial intelligence and machine learning equips healthcare organizations with powerful tools for predictive analytics and threat intelligence. By harnessing AI-driven insights, healthcare entities can anticipate potential security breaches, identify patterns in cyber threats, and enhance their overall cybersecurity posture. Continuous Monitoring and Incident Response: Azure enables healthcare organizations to implement continuous monitoring mechanisms and robust incident response protocols. Through Azure's automated monitoring tools and centralized logging, healthcare entities can continuously assess their security posture, detect vulnerabilities, and promptly respond to security incidents, thereby minimizing potential damages. In conclusion, Microsoft Azure offers a comprehensive suite of cybersecurity solutions tailored to the unique needs of healthcare organizations. By leveraging Azure's advanced capabilities in threat detection, secure cloud infrastructure, compliance adherence, AI-driven analytics, and incident response, healthcare entities can significantly fortify their defenses against evolving cyber threats. Embracing these strategies not only enhances patient data protection but also instills trust and confidence among stakeholders in the healthcare ecosystem.Some Significant Advances of Azure Cloud in Healthcare
Healthcare AI and Machine Learning: Azure offers a robust set of AI and machine learning tools, enabling healthcare organizations to develop and deploy advanced analytics and predictive models. This can be used for tasks like diagnostics, personalized medicine, and population health management. Secure and Compliant Data Management: Azure provides a secure and compliant platform for healthcare data. It complies with various industry standards and regulations, such as HIPAA (Health Insurance Portability and Accountability Act), ensuring that sensitive patient information is handled securely and in accordance with legal requirements. Hybrid Cloud Solutions: Azure's hybrid cloud solutions are particularly valuable for healthcare organizations that may need to maintain some of their data on-premises due to regulatory or practical considerations. Azure's hybrid capabilities allow seamless integration between on-premises infrastructure and cloud services. IoT in Healthcare: Azure IoT services have been used in healthcare to connect and manage medical devices, wearables, and sensors. This facilitates real-time monitoring of patients, enables remote healthcare services, and enhances the overall efficiency of healthcare delivery. Telemedicine and Remote Patient Monitoring: Azure has been instrumental in supporting telemedicine solutions, allowing healthcare providers to offer remote consultations and monitor patients outside traditional healthcare settings. This has become especially crucial in times of global health crises. Healthcare Analytics and Insights: Azure's analytics and big data services empower healthcare organizations to derive insights from vast amounts of data. This can help in understanding patient trends, improving operational efficiency, and making data-driven decisions for better healthcare outcomes.Pioneering system protecting healthcare staff from surgical smoke secures place on NHS Wales.
A smoke evacuation system developed to keep operating theatres smoke free has successfully won a place on the NHS Wales framework agreement. Cardiff-based manufacturer Eakin Surgical is one of the suppliers appointed by NHS Wales Shared Services Partnership to the national framework agreement. The contract award means the company – a distributor for the CIMPAX® C-PURE 750™ Smoke Evacuation System – can help the NHS across Wales to better protect its staff from the dangers of surgical smoke. Developed by Danish manufacturer CIMPAX ApS, the CIMPAX® C-PURE 750™ Smoke Evacuation System is widely recognized as the gold standard in smoke evacuation. Since the early 1980s surgical smoke has been known to be a significant chemical and biological hazard and has been shown to be as mutagenic as cigarette smoke. Electrosurgery devices which use high-frequency current to cut and coagulate tissue are the most common at producing surgical smoke plumes. One study found that on average the smoke produced daily was equivalent to the amount produced by 27-30 cigarettes. Despite this discovery 40 years ago, the adoption of measures to remove the smoke plume from the surgical environment have been slow and inconsistent. More recently, research has shown that smoke inhaled by theatre staff during procedures can contain over 40 different hazardous chemicals and can lead to complications from viral infections through to respiratory illness with further links to pregnancy complications and cancers. While other products may only disperse the smoke plume, the CIMPAX® C-PURE 750™ has been developed to deal with the problem and keep surgical teams safe from smoke inhalation. Its unique 3-port filter offers a variety of flexible options for tubing and accessories to meet clinical needs and sets new precedents for quiet operation. The system can be operated with a Remote Sensor Activator, control panel, or a foot pedal. Also available on the framework is the CIMPAX® C-VAC TORNADO™ electrosurgical pencil. Offering the ultimate combination of Electrosurgery and removal of hazardous smoke in one instrument, the device has been developed to minimize risk of smoke exposure to the OR team and patient. The unique triangular design combined with the silicone cover offers the surgeon an ergonomic and safe grip, while a special adaptor ensures the device can be fitted to any smoke evacuation system in the market. With the NHS committed to reducing its carbon footprint, the eco-friendly material of the device also means it has the added benefit of a smaller environmental footprint. Jon Blastland, Commercial Director said: “Following a tender for the supply of electrosurgical instrumentation across NHS Wales, we are thrilled to announce that our company has successfully secured a place on the NHS Welsh framework agreement. As the UK distributor for the pioneering CIMPAX Smoke Evacuation System, we are pleased to be able to support the NHS in its goal to better protect its staff from the well-known dangers of surgical smoke. With Eakin Surgical is being a Welsh company, we are also particularly delighted to be able to serve the Welsh community and provide revenue into the Welsh economy.” Eakin Surgical is committed to improving the outcomes of surgery for both patients and theatre staff; and as such, promote the use of ‘best practice’ on tip extraction of surgical smoke for every instance in which it is generated.
"Enhancing Service Delivery at NSFAS through Microsoft Technologies"
By integrating Microsoft technologies, https://applyfornsfas.co.za/ can streamline application processes, enhance communication with applicants, and automate administrative tasks, resulting in improved efficiency, transparency, and service delivery to students in need.AI and Machine Learning Revolutionizing Healthcare
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming the healthcare landscape, bringing about a new era of personalized, efficient, and data-driven care. These technologies are revolutionizing various aspects of healthcare, from diagnosis and treatment to drug discovery and patient management. Diagnosis and Treatment: AI and ML algorithms are being used to analyze medical images, such as X-rays, CT scans, and MRIs, with unprecedented accuracy. This allows for earlier and more accurate diagnosis of diseases like cancer, heart disease, and neurological disorders. Additionally, AI-powered systems can analyze patient data, including medical history, lab results, and genetic information, to predict the risk of developing certain diseases and recommend personalized treatment plans. Drug Discovery and Development: AI and ML are playing a crucial role in accelerating drug discovery and development. These technologies can analyze vast amounts of data to identify potential drug targets and predict the efficacy and safety of new drugs. This can significantly reduce the time and cost of bringing new drugs to market. Patient Management and Monitoring: AI-powered chatbots and virtual assistants are being used to provide patients with 24/7 support and information. These systems can answer patients' questions, schedule appointments, and even monitor their health status remotely. Additionally, AI algorithms can analyze patient data to identify those at risk of complications or readmission, allowing for early intervention and improved outcomes. Administrative Tasks and Workflow Optimization: AI and ML can automate many administrative tasks in healthcare, such as scheduling appointments, processing claims, and managing medical records. This frees up healthcare professionals to focus on providing direct patient care. Additionally, AI-powered systems can analyze data to identify inefficiencies in workflows and suggest improvements, leading to increased efficiency and cost savings. Challenges and Ethical Considerations: Despite the numerous benefits, AI and ML in healthcare also present challenges and ethical considerations. Data privacy and security are critical concerns, as AI systems rely on vast amounts of patient data. Additionally, ensuring fairness and avoiding bias in AI algorithms is crucial to prevent discrimination and ensure equitable access to healthcare. Conclusion: AI and ML are revolutionizing healthcare, offering the potential to improve patient outcomes, reduce costs, and increase efficiency. However, it is important to address the challenges and ethical considerations associated with these technologies to ensure their responsible and equitable implementation. As AI and ML continue to evolve, the future of healthcare promises to be more personalized, data-driven, and accessible than ever before.
IOMT and FHIR configuration
My name is Shuhaib from India, I was referring to a video to configure my IOMT and FHIR server configuration. It was helped me to learn basic things about the configuration of IOMT and FHIR, since this video is for very limited minutes and skipped many steps I could not complete my integration with my mobile application. I referred to other couples of links to complete this connectivity, all are explaining different ways of the same topic. I am totally confused about how I can accomplish my project. Any advice or help can be provided to complete this project. https://www.youtube.com/watch?v=_mrUWYhQV5c&t=416s https://docs.microsoft.com/en-us/azure/healthcare-apis/azure-api-for-fhir/iot-fhir-portal-quickstart
How are healthcare organizations using Microsoft Azure capabilities?
Healthcare organizations have been increasingly adopting Microsoft Azure due to its versatile capabilities, enabling them to enhance patient care, streamline operations, and optimize data management. Azure's features cater to various facets within the healthcare sector: Data Storage and Management: Azure provides secure and compliant storage solutions for healthcare data. It ensures data integrity, scalability, and accessibility, facilitating the management of electronic health records (EHRs), medical images, and patient information. Analytics and AI: Leveraging Azure's robust analytics and artificial intelligence (AI) tools, healthcare providers can derive valuable insights from vast amounts of patient data. AI algorithms aid in disease prediction, personalized treatment plans, and the identification of patterns for better diagnostics. Telemedicine and Remote Care: Azure enables the creation of telemedicine platforms and remote patient monitoring systems. These solutions support virtual consultations, remote diagnostics, and continuous patient monitoring, improving accessibility and patient engagement. Security and Compliance: Healthcare organizations prioritize data security and compliance. Azure offers comprehensive security features, including encryption, access controls, and compliance certifications (such as HIPAA and GDPR), ensuring patient data confidentiality and regulatory adherence. Internet of Medical Things (IoMT): Azure's IoT capabilities empower the integration and management of medical devices, enabling real-time monitoring of patients and equipment. This facilitates proactive healthcare interventions and predictive maintenance for devices. Collaboration and Communication: Azure's collaboration tools facilitate seamless communication among healthcare professionals, enabling secure sharing of patient data and fostering interdisciplinary cooperation for better care delivery. Healthcare Research and Development: Azure's high-performance computing capabilities support healthcare research endeavors, such as genomics, drug discovery, and clinical trials, by providing computational power for complex analyses. Scalability and Cost Efficiency: Azure's scalable infrastructure allows healthcare organizations to adjust resources according to demand, ensuring cost efficiency and flexibility in managing IT infrastructure. In essence, healthcare organizations are leveraging Microsoft Azure's versatile suite of tools and services to transform patient care, enhance operational efficiency, ensure data security and compliance, and drive innovation across various domains within the healthcare industry.Azure’s Impact on Telemedicine: Bridging Divides and Revolutionizing Patient Care
Microsoft Azure’s influence goes beyond mere convenience. It is fundamentally altering how healthcare is perceived and approached. By providing innovative tools and platforms, Azure is making healthcare more accessible than ever before. A prime example is a scenario where a rural community, previously underserved due to geographical constraints, now has access to top-tier medical consultations. Azure’s cloud infrastructure enables healthcare providers to deliver quality care to remote and marginalized areas, effectively bridging the healthcare divide that has long plagued our society. Healthcare today is just a click away, and it’s available when and where it’s needed. Let’s delve into some of the key ways Azure is making a difference: Real-Time Data Streaming: Azure’s IoT Hub and Event Hubs have redefined the integration of real-time health data from wearable devices. A patient with a chronic condition can now monitor their health in real-time and transmit this data to their healthcare provider. Azure’s capabilities empower healthcare professionals to continuously track patients’ health status, detect anomalies, and intervene as needed, resulting in improved health outcomes, reduced hospital admissions, and lower healthcare costs. A study published in the Journal of Medical Internet Research found that real-time monitoring of chronic conditions using IoT technology can reduce hospital admissions by up to 35% and lower healthcare costs by 26%. AI-Powered Diagnostics: Azure’s machine learning capabilities have ushered in a new era of AI-powered diagnostics. Picture a scenario where an AI algorithm, trained on vast medical datasets, assists radiologists in swiftly and accurately identifying anomalies in medical images. Azure’s machine learning tools are driving the development of AI models for medical image analysis, diagnostic support, and predictive analytics, leading to quicker and more precise diagnoses, reducing the burden on healthcare professionals, and improving patient outcomes. Research conducted by the American College of Radiology indicates that AI-powered diagnostic tools have increased radiologists’ accuracy in identifying anomalies by 20% and reduced the time required for diagnoses by 30%. Predictive Analytics: Azure’s big data and analytics tools have become indispensable in predictive healthcare analytics. Consider a healthcare system that can predict disease outbreaks or identify high-risk patient groups with incredible accuracy. With Azure’s support, organizations can harness the power of predictive analytics to anticipate health trends, allocate resources efficiently, and reduce the strain on healthcare systems, ultimately improving the quality of care. The Centers for Disease Control and Prevention (CDC) reported that predictive analytics tools can anticipate disease outbreaks with a lead time of up to 2 weeks, allowing for more timely and effective interventions. Virtual Reality (VR) Healthcare: Azure’s capabilities extend to virtual reality (VR) applications for healthcare, offering immersive experiences with significant therapeutic potential. For instance, a patient recovering from surgery can use VR therapy to manage pain and aid rehabilitation. Azure’s mixed reality services, including HoloLens, are instrumental in developing VR applications for pain management, physical therapy, and behavioral therapy, enhancing patient engagement, and expediting recovery. A study published in the Journal of Pain Research found that VR therapy can reduce pain scores by an average of 30% and decrease the need for pain medication in post-surgery patients. Secure Blockchain Integration: Data security in healthcare is paramount, and Azure’s blockchain services have entered the fray. Think about the critical need for the secure and immutable storage of electronic health records (EHRs). Azure’s blockchain capabilities are paving the way for tamper-proof EHRs, ensuring data integrity and patient privacy in an era where data breaches are a prevalent concern. According to a survey by the Healthcare Information and Management Systems Society (HIMSS), healthcare organizations that have implemented blockchain for electronic health records (EHRs) have reported a 30% reduction in data breaches. Tele-Pharmacies: Azure’s cloud services aren’t limited to clinical care alone; they also support the growth of tele-pharmacies, a sector poised for substantial expansion. Imagine the convenience of consulting with a pharmacist remotely, ensuring accurate medication management and healthcare education. Azure’s role in bolstering tele-pharmacies is invaluable, especially in a world where patient-centric care and convenience are of utmost importance. The American Telemedicine Association reports that tele-pharmacies have grown by 200% in the past five years, and patients using tele-pharmacy services have reported an average satisfaction rating of 4.8 out of 5. AI Chatbots for Triage: Azure’s Cognitive Services, driven by AI, power chatbots for patient triage, making healthcare interactions more efficient and patient-centric. Consider a scenario where a patient initiates a conversation with an AI chatbot to describe their symptoms. The chatbot, powered by Azure’s natural language processing capabilities, intelligently assesses the patient’s condition, streamlines the intake process, and directs them to the appropriate healthcare resource, ensuring swift and accurate care. A case study conducted by a major healthcare provider showed that AI chatbots reduced the average patient triage time by 50%, resulting in faster access to care and improved patient satisfaction.Microsoft Fabric and Azure AI Innovations Redefining Patient Care
Microsoft Fabric: With AI infused into every layer in Microsoft Fabric , they are committing to a future where every data professional can get more done faster. For healthcare organizations, it is empowering them with a comprehensive suite of capabilities that amalgamates data from previously segregated sources within the organization—spanning electronic health records (EHRs), Picture Archiving and Communication Systems (PACS), lab systems, claims systems, and medical devices. This solution harmonizes structured, unstructured, imaging, and medical device data into the Fabric data lake, employing open data standards like FHIR, DICOM, and MedTech services, thereby establishing a unified architecture. Further enhancing its flexibility, connectors, and converters simplify data transformation between formats and facilitate the creation of specific pipelines. This multimodal data foundation serves as a platform for standardized, scalable solutions, expediting the discovery of impactful clinical and operational insights to elevate patient care. Fabric cultivates a consolidated data environment conducive to building and deploying AI models and extracting valuable insights. Moreover, it offers standard capabilities such as Observational Medical Outcomes Partnership (OMOP) analytics, enabling clinical research, patient outreach analytics, and personalized patient engagement. Introducing a novel de-identification service, Fabric ensures the privacy of patient-protected health information (PHI) by employing machine learning models to extract, redact, or surrogate identifiers, enabling insight extraction from unstructured data like medical documents and clinical trial studies. Additionally, healthcare-specific pre-built classification rules, labels, and data glossaries within Microsoft Purview enable healthcare organizations to effectively govern, protect, and manage their entire data estate. Azure AI Health Insights: Azure AI Health Insights, a cognitive service, furnishes clinicians and researchers with prebuilt models designed to analyze data and offer insights pivotal for informed decision-making during critical healthcare scenarios. Among these, three new models—currently in preview—come to the forefront. Patient Timeline: This leverages generative AI to extract crucial events like medications, diagnoses, and procedures from unstructured data, arranging them chronologically. This meticulous timeline offers clinicians a clearer, more accurate understanding of a patient’s medical history, enhancing the precision of care plans. Clinical Report Simplification: Utilizing generative AI, this model transforms intricate medical jargon into easily understandable language without compromising the clinical essence. This allows clinicians to communicate complex clinical information effectively, even with patients and others, facilitating comprehensive understanding. Radiology Insights: Offering quality checks, this model flags errors and inconsistencies within clinical documentation, ensuring accuracy. Moreover, it identifies follow-up recommendations and clinical findings, including measurements, recorded by radiologists, streamlining the interpretation process. Azure AI Health Bot: Azure AI Health Bot furnishes readily available healthcare intelligence that can be tailored and seamlessly integrated into current workflows. It draws on responses sourced from a healthcare organization’s internal content while also utilizing generative AI to offer information from reputable sources like the National Institutes of Health and the U.S. Food and Drug Administration. Text Analytics for Health: Text Analytics for Health, a language service within Azure AI, employs machine learning capabilities to extract and categorize crucial medical data from diverse unstructured texts. Recently unveiled industry open-source templates encompass population health, patient queries and answers utilizing Azure OpenAI Service, clinical trial patient cohorts, and large-scale historical data processing.Researcher takes another step toward discovering how a brain molecule could halt MS
Multiple sclerosis is an autoimmune disease in which the myelin, or fatty lining of nerve cells, is eroded, leading to nerve damage and slower signalling between the brain and the body. MS symptoms range from blurred vision to complete paralysis, and while there are treatments, the causes are not fully understood and nothing exists to reverse the disease process. More than 90,000 Canadians live with MS, according to the MS Society. In new research published in Stem Cell Reports, Anastassia Voronova, an assistant professor and Canada Research Chair in Neural Stem Cell Biology, injected fractalkine into mice with chemically induced MS. She found the treatment increased the number of new oligodendrocytes -- vital brain and spinal cord cells that produce myelin in both embryonic and adult brains -- which are damaged during the MS autoimmune attack. "If we can replace those lost or damaged oligodendrocytes, then they could make new myelin and it is believed that would halt the disease progression, or maybe even reverse some of the symptoms," Voronova says. "That's the Holy Grail in the research community and something that we're very passionate about." Voronova's earlier research tested the safety and efficacy of fractalkine in normal mice and found similar beneficial effects. Other researchers have demonstrated that fractalkine may provide protection for nerves in mouse models before the disease is induced, but this is the first time it has been tested on animals that already have the disease. Voronova and her team observed new oligodendrocytes, as well as reactivated progenitor cells that can regenerate oligodendrocytes, in the brains of the treated animals. Remyelination occurred in both the white and grey matter. The researchers also observed a reduction in inflammation, part of the damage caused by the immune system. Next steps for the treatment include testing it in other diseased mouse models, including those with neurodegenerative diseases other than MS.
How does Azure ensure the security and privacy of sensitive patient data in the cloud?
In the healthcare industry, where privacy and security are paramount, storing sensitive patient data in the cloud can feel like a gamble. But Microsoft Azure employs a multi-layered approach to ensure your information stays safe. Here's how: Encryption at Rest and In Transit: Imagine your data wrapped in multiple layers of security. Azure encrypts patient data at rest (when stored) using industry-standard 256-bit AES encryption, which is practically uncrackable. And when data travels between Azure datacenters, it's encrypted again using secure protocols for additional protection. Compartmentalization: Azure uses a multi-tenant model, meaning various customers share the physical infrastructure. But worry not! Logical isolation keeps your data segregated from others, like placing your files in a separate folder on a shared server. Customer Control: You hold the reins! Azure Key Vault empowers you to manage the encryption keys that unlock your data. This ensures only authorized personnel can access sensitive information. Confidentiality Through Confidential Computing: For an extra layer of security, Azure offers confidential computing environments. These are like secure fortresses within the cloud that encrypt data even while it's being processed. This makes it virtually impossible for unauthorized users, even within Microsoft, to access your data. Compliance with Regulations: Azure adheres to a wide range of healthcare data privacy regulations, including HIPAA and HITRUST. This gives you peace of mind knowing your data security meets industry standards. By implementing these robust security measures, Azure ensures your patient data remains confidential, compliant, and protected in the cloud.Five Ways in which Microsoft Azure is Accelerating Healthcare Transformation
The healthcare industry has seen an accelerated transformation ever since the outbreak of the pandemic. Keen observers in the industry are a catalyst by recommending ideas to improve the system, such as care access, critical care, the safety of the patients and caregivers, and more. Check out these Five crucial ways in which Microsoft Azure is Accelerating Healthcare Transformation; Enhance patient and provider engagement – Microsoft Azure ensures the secure flow of data through all data points, virtual and in-person, that helps elevate the patient’s experience, easy diagnostics, and improve health conditions. Accelerate research and development innovation – Azure helps in driving faster advancements by modernizing discovery, development, and quality system process to support rapid modeling, improve clinical trial management, and accelerate innovation. Enhance collaboration – Azure accelerates the adoption of digital technologies that drive collaboration among healthcare team members for secured coordination and simplified workflow management. Help protect health information – Azure helps ensure the protection of sensitive data, to enhance the security and privacy of the customers. It also helps in managing evolving compliance regulations while improving data governance. Improve clinical and operational insights – Azure integrates the data across various systems to provide one single source of truth that is leveraged to extract insights for predicting risks and improving patient care, quality assurance, and operational efficiencies.Survey opportunity | Data governance, compliance and risk management requirements
With the ever-increasing number of regulatory standards (like GDPR, HIPAA, FISMA) along with the increasing threat to backed-up data and the process of recovery, data governance & risk management for backup and DR has become an area to be focused on. The Azure BCDR product group has been exploring various use cases in this area and would appreciate any and every input from stakeholders who have worked with customers in regulated industries such as healthcare and life sciences. If you or your end customers have been involved in processes around data governance, compliance or risk management (for Azure in general), we would love to connect with you and learn more about these processes, challenges faced and overall experience of various stakeholders. Please help us out by filling up this short survey! Your inputs would greatly help us prioritize the right set of product investments. Link to survey: https://aka.ms/DataGovernanceAndComplianceSurvey
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