To view recording of this webinar please use the below link:
https://wso2.com/library/webinars/2015/02/connected-health-reference-architecture/
The key focus areas of this session are
Overview of healthcare IT landscape
Standards and protocols widely used in healthcare platforms
SOA is healthcare domain
Quality of services in healthcare platforms
A connected healthcare reference model
A technology company that provides state-of-art Web-based Healthcare Ecosystem platform, first of its kind. We are not just a software company — rather, we provide technology-enabled services that are changing healthcare from a combination of innovative technologies.
There are variety of different software solutions available on the market that provide separate and individual solutions. Aptuso Health is the first Healthcare Ecosystem. Web based, fully-integrated, easy to use, scalable Turn Key Solution.
This describes a conceptual model approach to designing an enterprise data fabric. This is the set of hardware and software infrastructure, tools and facilities to implement, administer, manage and operate data operations across the entire span of the data within the enterprise across all data activities including data acquisition, transformation, storage, distribution, integration, replication, availability, security, protection, disaster recovery, presentation, analytics, preservation, retention, backup, retrieval, archival, recall, deletion, monitoring, capacity planning across all data storage platforms enabling use by applications to meet the data needs of the enterprise.
The conceptual data fabric model represents a rich picture of the enterprise’s data context. It embodies an idealised and target data view.
Designing a data fabric enables the enterprise respond to and take advantage of key related data trends:
• Internal and External Digital Expectations
• Cloud Offerings and Services
• Data Regulations
• Analytics Capabilities
It enables the IT function demonstrate positive data leadership. It shows the IT function is able and willing to respond to business data needs. It allows the enterprise to meet data challenges
• More and more data of many different types
• Increasingly distributed platform landscape
• Compliance and regulation
• Newer data technologies
• Shadow IT where the IT function cannot deliver IT change and new data facilities quickly
It is concerned with the design an open and flexible data fabric that improves the responsiveness of the IT function and reduces shadow IT.
Security in Clouds: Cloud security challenges – Software as a
Service Security, Common Standards: The Open Cloud Consortium – The Distributed management Task Force – Standards for application Developers – Standards for Messaging – Standards for Security, End user access to cloud computing, Mobile Internet devices and the cloud. Hadoop – MapReduce – Virtual Box — Google App Engine – Programming Environment for Google App Engine.
Interactive data visualization products focused on business intelligence. Data Visualization and Communication. Tableau is considered a leader in the field of data discovery.
Tableau products are designed and built to meet the critical needs of the digital forensic community world-wide.
Watch full webinar here: https://bit.ly/2N1Ndz9
How is a logical data fabric different from a physical data fabric? What are the advantages of one type of fabric over the other? Attend this session to firm up your understanding of a logical data fabric.
A technology company that provides state-of-art Web-based Healthcare Ecosystem platform, first of its kind. We are not just a software company — rather, we provide technology-enabled services that are changing healthcare from a combination of innovative technologies.
There are variety of different software solutions available on the market that provide separate and individual solutions. Aptuso Health is the first Healthcare Ecosystem. Web based, fully-integrated, easy to use, scalable Turn Key Solution.
This describes a conceptual model approach to designing an enterprise data fabric. This is the set of hardware and software infrastructure, tools and facilities to implement, administer, manage and operate data operations across the entire span of the data within the enterprise across all data activities including data acquisition, transformation, storage, distribution, integration, replication, availability, security, protection, disaster recovery, presentation, analytics, preservation, retention, backup, retrieval, archival, recall, deletion, monitoring, capacity planning across all data storage platforms enabling use by applications to meet the data needs of the enterprise.
The conceptual data fabric model represents a rich picture of the enterprise’s data context. It embodies an idealised and target data view.
Designing a data fabric enables the enterprise respond to and take advantage of key related data trends:
• Internal and External Digital Expectations
• Cloud Offerings and Services
• Data Regulations
• Analytics Capabilities
It enables the IT function demonstrate positive data leadership. It shows the IT function is able and willing to respond to business data needs. It allows the enterprise to meet data challenges
• More and more data of many different types
• Increasingly distributed platform landscape
• Compliance and regulation
• Newer data technologies
• Shadow IT where the IT function cannot deliver IT change and new data facilities quickly
It is concerned with the design an open and flexible data fabric that improves the responsiveness of the IT function and reduces shadow IT.
Security in Clouds: Cloud security challenges – Software as a
Service Security, Common Standards: The Open Cloud Consortium – The Distributed management Task Force – Standards for application Developers – Standards for Messaging – Standards for Security, End user access to cloud computing, Mobile Internet devices and the cloud. Hadoop – MapReduce – Virtual Box — Google App Engine – Programming Environment for Google App Engine.
Interactive data visualization products focused on business intelligence. Data Visualization and Communication. Tableau is considered a leader in the field of data discovery.
Tableau products are designed and built to meet the critical needs of the digital forensic community world-wide.
Watch full webinar here: https://bit.ly/2N1Ndz9
How is a logical data fabric different from a physical data fabric? What are the advantages of one type of fabric over the other? Attend this session to firm up your understanding of a logical data fabric.
Introduction to Cloud Computing and Cloud InfrastructureSANTHOSHKUMARKL1
Introduction, Cloud Infrastructure: Cloud computing, Cloud computing delivery models and services, Ethical issues, Cloud vulnerabilities, Cloud computing at Amazon, Cloud computing the Google perspective, Microsoft Windows Azure and online services, Open-source software platforms for private clouds.
A Reference Architecture for Digital Health: The Health Catalyst Data Operati...Health Catalyst
There are essentially four strategic options to address the enterprise data platform requirements of today’s healthcare systems: (1) build your own, (2) buy from EHR vendors, (3) look to a Silicon Valley high-tech startup, and (4) partner with Health Catalyst or a handful of similar companies.
In this webinar, Health Catalyst’s CTO, Dale Sanders, comments on all four approaches, hoping to help you to assess your organization’s strategy against the options and vendors in each category.
It’s been exactly three years since Health Catalyst embarked on a major investment in its next-generation technology, the Data Operating System (DOS™) and its applications. This webinar is an update on the progress, less about marketing the technology, but rather offering DOS as a reference architecture that can support analytics, AI, text processing, data-first application development, and interoperability, as an all-in-one agile cost-savings architecture.
In addition to the successes, Dale comments on the challenges that Health Catalyst has faced under a very ambitious DOS development plan. In its current state, DOS has made some significant improvements to overcome early mistakes, and is now a very solid enterprise data platform. In the interests of industry-wide learning, Sanders will talk transparently about those mistakes and how those learnings are being applied to the DOS platform, positioning it to evolve gracefully over the next 25 years.
View the webinar to learn how the DOS reference architecture:
- Helps manage the 2,000+ compulsory measures in US healthcare
- Enables applications as varied as a real-time patient safety surveillance system, and an activity-based costing system in one platform
- Can ingest data of any type or velocity from over 300 healthcare source systems and growing
- Bundles tools, applications, and analytics that would cost 3-6x more to build on your own
- Compares to EHR vendors as an option to serve as an enterprise data and analytics platform
- Is a performant, sustainable, and maintainable platform for deploying AI models in the natural flow of the healthcare data pipeline
- Provides curated data content and models while still allowing for the agility of a late binding design option
- Functions as a reference architecture that all healthcare organizations and vendors will ultimately have to build in their pursuit of digital health
Building a Logical Data Fabric using Data Virtualization (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3FF1ubd
In the recent Building the Unified Data Warehouse and Data Lake report by leading industry analysts TDWI, we have discovered 64% of organizations stated the objective for a unified Data Warehouse and Data Lakes is to get more business value and 84% of organizations polled felt that a unified approach to Data Warehouses and Data Lakes was either extremely or moderately important.
In this session, you will learn how your organization can apply a logical data fabric and the associated technologies of machine learning, artificial intelligence, and data virtualization can reduce time to value. Hence, increasing the overall business value of your data assets.
KEY TAKEAWAYS:
- How a Logical Data Fabric is the right approach to assist organizations to unify their data.
- The advanced features of a Logical Data Fabric that assist with the democratization of data, providing an agile and governed approach to business analytics and data science.
- How a Logical Data Fabric with Data Virtualization enhances your legacy data integration landscape to simplify data access and encourage self-service.
Data Warehousing in the Cloud: Practical Migration Strategies SnapLogic
Dave Wells of Eckerson Group discusses why cloud data warehousing has become popular, the many benefits, and the corresponding challenges. Migrating an existing data warehouse to the cloud is a complex process of moving schema, data, and ETL. The complexity increases when architectural modernization, restructuring of database schema, or rebuilding of data pipelines is needed.
With the expansion of big data and analytics, organizations are looking to incorporate data streaming into their business processes to make real-time decisions.
Join this webinar as we guide you through the buzz around data streams:
- Market trends in stream processing
- What is stream processing
- How does stream processing compare to traditional batch processing
- High and low volume streams
- The possibilities of working with data streaming and the benefits it provides to organizations
- The importance of spatial data in streams
Informatica Cloud Services deliver purpose-built data integration cloud applications to allow business users to integrate data across cloud-based applications and on-premise systems and databases. Informatica Cloud Services address specific business processes (customer/product master synchronization, opportunity to order, etc.) and point-to-point data integration (e.g. Salesforce.com to on premise end-points).
Healthcare Interoperability: New Tactics and TechnologyHealth Catalyst
Every provider agrees on the need for healthcare interoperability to achieve clinical data insights at the point of care. The question is how to get there from the myriad technologies and the volumes of data that comprise electronic medical records. It’s been difficult to organize among participants that have had little incentive to cooperate. And standards for sending and receiving data have been slow to develop. This is changing, but the key components that are still vital to realizing insights are closed-loop analytics and its accompanying tools, an enterprise data warehouse and analytics applications. This article defines the problems and explores the solutions to optimizing clinical decision making where it’s needed most.
Modern Data Architecture for a Data Lake with Informatica and Hortonworks Dat...Hortonworks
How do you turn data from many different sources into actionable insights and manufacture those insights into innovative information-based products and services?
Industry leaders are accomplishing this by adding Hadoop as a critical component in their modern data architecture to build a data lake. A data lake collects and stores data across a wide variety of channels including social media, clickstream data, server logs, customer transactions and interactions, videos, and sensor data from equipment in the field. A data lake cost-effectively scales to collect and retain massive amounts of data over time, and convert all this data into actionable information that can transform your business.
Join Hortonworks and Informatica as we discuss:
- What is a data lake?
- The modern data architecture for a data lake
- How Hadoop fits into the modern data architecture
- Innovative use-cases for a data lake
Data Integration is a key part of many of today’s data management challenges: from data warehousing, to MDM, to mergers & acquisitions. Issues can arise not only in trying to align technical formats from various databases and legacy systems, but in trying to achieve common business definitions and rules.
Join this webinar to see how a data model can help with both of these challenges – from ‘bottom-up’ technical integration, to the ‘top-down’ business alignment.
Saama Presents Is your Big Data Solution Ready for StreamingSaama
Amit Gulwadi and Karim Damji presented at Panagora's IoT in Clinical Trials Summit in Boston in November 2018. Using the right analytic solution that can incorporate your unstructured IoT data provides tremendous benefits including faster time to commercialization and better business and patient outcomes.
3 Phases of Healthcare Data Governance in AnalyticsHealth Catalyst
Healthcare data governance is a broad topic and covers more than data stewardship, storage, and technical roles and responsibilities. And it’s not easy to implement. It’s necessary, though, for health systems that are entering the world of analytics because the governance structure will enable the organizations to drive higher-quality, low cost care. In order for healthcare data governance to be most effective however, it needs to be adaptive because real healthcare data governance is much more fluid than any plan laid out on paper. Typically there are three phases that characterize successful analytics implementations: the early stage, the mid-term stage, and the steady state. As health systems begin to determine the effectiveness of their data governance strategy, it’s important to look at key metrics from their analytics implementations that will either trend up, remain solid, or trend down.
A successful data governance capability requires a strategy to align regulatory drivers and technology enhancement initiatives with business needs and objectives, taking into account the organizational, technological and cultural changes that will need to take place.
Health device makers, to date, have primarily targeted consumers who are either fitness focused or chronically ill. But between these two extremes sits a large, fragmented and often overlooked population who seek better information to effectively manage their health. Our research suggests that successful solution providers will approach this market opportunity as an ecosystem of partners – with an integrated solution that extends beyond the device itself. By plugging the information gap for these consumers, solution providers can help fuel healthcare innovation.
Introduction to Cloud Computing and Cloud InfrastructureSANTHOSHKUMARKL1
Introduction, Cloud Infrastructure: Cloud computing, Cloud computing delivery models and services, Ethical issues, Cloud vulnerabilities, Cloud computing at Amazon, Cloud computing the Google perspective, Microsoft Windows Azure and online services, Open-source software platforms for private clouds.
A Reference Architecture for Digital Health: The Health Catalyst Data Operati...Health Catalyst
There are essentially four strategic options to address the enterprise data platform requirements of today’s healthcare systems: (1) build your own, (2) buy from EHR vendors, (3) look to a Silicon Valley high-tech startup, and (4) partner with Health Catalyst or a handful of similar companies.
In this webinar, Health Catalyst’s CTO, Dale Sanders, comments on all four approaches, hoping to help you to assess your organization’s strategy against the options and vendors in each category.
It’s been exactly three years since Health Catalyst embarked on a major investment in its next-generation technology, the Data Operating System (DOS™) and its applications. This webinar is an update on the progress, less about marketing the technology, but rather offering DOS as a reference architecture that can support analytics, AI, text processing, data-first application development, and interoperability, as an all-in-one agile cost-savings architecture.
In addition to the successes, Dale comments on the challenges that Health Catalyst has faced under a very ambitious DOS development plan. In its current state, DOS has made some significant improvements to overcome early mistakes, and is now a very solid enterprise data platform. In the interests of industry-wide learning, Sanders will talk transparently about those mistakes and how those learnings are being applied to the DOS platform, positioning it to evolve gracefully over the next 25 years.
View the webinar to learn how the DOS reference architecture:
- Helps manage the 2,000+ compulsory measures in US healthcare
- Enables applications as varied as a real-time patient safety surveillance system, and an activity-based costing system in one platform
- Can ingest data of any type or velocity from over 300 healthcare source systems and growing
- Bundles tools, applications, and analytics that would cost 3-6x more to build on your own
- Compares to EHR vendors as an option to serve as an enterprise data and analytics platform
- Is a performant, sustainable, and maintainable platform for deploying AI models in the natural flow of the healthcare data pipeline
- Provides curated data content and models while still allowing for the agility of a late binding design option
- Functions as a reference architecture that all healthcare organizations and vendors will ultimately have to build in their pursuit of digital health
Building a Logical Data Fabric using Data Virtualization (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3FF1ubd
In the recent Building the Unified Data Warehouse and Data Lake report by leading industry analysts TDWI, we have discovered 64% of organizations stated the objective for a unified Data Warehouse and Data Lakes is to get more business value and 84% of organizations polled felt that a unified approach to Data Warehouses and Data Lakes was either extremely or moderately important.
In this session, you will learn how your organization can apply a logical data fabric and the associated technologies of machine learning, artificial intelligence, and data virtualization can reduce time to value. Hence, increasing the overall business value of your data assets.
KEY TAKEAWAYS:
- How a Logical Data Fabric is the right approach to assist organizations to unify their data.
- The advanced features of a Logical Data Fabric that assist with the democratization of data, providing an agile and governed approach to business analytics and data science.
- How a Logical Data Fabric with Data Virtualization enhances your legacy data integration landscape to simplify data access and encourage self-service.
Data Warehousing in the Cloud: Practical Migration Strategies SnapLogic
Dave Wells of Eckerson Group discusses why cloud data warehousing has become popular, the many benefits, and the corresponding challenges. Migrating an existing data warehouse to the cloud is a complex process of moving schema, data, and ETL. The complexity increases when architectural modernization, restructuring of database schema, or rebuilding of data pipelines is needed.
With the expansion of big data and analytics, organizations are looking to incorporate data streaming into their business processes to make real-time decisions.
Join this webinar as we guide you through the buzz around data streams:
- Market trends in stream processing
- What is stream processing
- How does stream processing compare to traditional batch processing
- High and low volume streams
- The possibilities of working with data streaming and the benefits it provides to organizations
- The importance of spatial data in streams
Informatica Cloud Services deliver purpose-built data integration cloud applications to allow business users to integrate data across cloud-based applications and on-premise systems and databases. Informatica Cloud Services address specific business processes (customer/product master synchronization, opportunity to order, etc.) and point-to-point data integration (e.g. Salesforce.com to on premise end-points).
Healthcare Interoperability: New Tactics and TechnologyHealth Catalyst
Every provider agrees on the need for healthcare interoperability to achieve clinical data insights at the point of care. The question is how to get there from the myriad technologies and the volumes of data that comprise electronic medical records. It’s been difficult to organize among participants that have had little incentive to cooperate. And standards for sending and receiving data have been slow to develop. This is changing, but the key components that are still vital to realizing insights are closed-loop analytics and its accompanying tools, an enterprise data warehouse and analytics applications. This article defines the problems and explores the solutions to optimizing clinical decision making where it’s needed most.
Modern Data Architecture for a Data Lake with Informatica and Hortonworks Dat...Hortonworks
How do you turn data from many different sources into actionable insights and manufacture those insights into innovative information-based products and services?
Industry leaders are accomplishing this by adding Hadoop as a critical component in their modern data architecture to build a data lake. A data lake collects and stores data across a wide variety of channels including social media, clickstream data, server logs, customer transactions and interactions, videos, and sensor data from equipment in the field. A data lake cost-effectively scales to collect and retain massive amounts of data over time, and convert all this data into actionable information that can transform your business.
Join Hortonworks and Informatica as we discuss:
- What is a data lake?
- The modern data architecture for a data lake
- How Hadoop fits into the modern data architecture
- Innovative use-cases for a data lake
Data Integration is a key part of many of today’s data management challenges: from data warehousing, to MDM, to mergers & acquisitions. Issues can arise not only in trying to align technical formats from various databases and legacy systems, but in trying to achieve common business definitions and rules.
Join this webinar to see how a data model can help with both of these challenges – from ‘bottom-up’ technical integration, to the ‘top-down’ business alignment.
Saama Presents Is your Big Data Solution Ready for StreamingSaama
Amit Gulwadi and Karim Damji presented at Panagora's IoT in Clinical Trials Summit in Boston in November 2018. Using the right analytic solution that can incorporate your unstructured IoT data provides tremendous benefits including faster time to commercialization and better business and patient outcomes.
3 Phases of Healthcare Data Governance in AnalyticsHealth Catalyst
Healthcare data governance is a broad topic and covers more than data stewardship, storage, and technical roles and responsibilities. And it’s not easy to implement. It’s necessary, though, for health systems that are entering the world of analytics because the governance structure will enable the organizations to drive higher-quality, low cost care. In order for healthcare data governance to be most effective however, it needs to be adaptive because real healthcare data governance is much more fluid than any plan laid out on paper. Typically there are three phases that characterize successful analytics implementations: the early stage, the mid-term stage, and the steady state. As health systems begin to determine the effectiveness of their data governance strategy, it’s important to look at key metrics from their analytics implementations that will either trend up, remain solid, or trend down.
A successful data governance capability requires a strategy to align regulatory drivers and technology enhancement initiatives with business needs and objectives, taking into account the organizational, technological and cultural changes that will need to take place.
Health device makers, to date, have primarily targeted consumers who are either fitness focused or chronically ill. But between these two extremes sits a large, fragmented and often overlooked population who seek better information to effectively manage their health. Our research suggests that successful solution providers will approach this market opportunity as an ecosystem of partners – with an integrated solution that extends beyond the device itself. By plugging the information gap for these consumers, solution providers can help fuel healthcare innovation.
Creating Interoperable Medical Devices that fit into Hospital Enterprise IT E...Shahid Shah
Creating connected medical devices is challenging but doing so in an interoperable manner that can easily and flexibly fit into modern hospital IT environments is even more difficult. This presentation provides sage advice on how to design connected life-critical medical devices so that they work well within modern hospital environments.
Personal connected health is currently characterized by limited thought leadership, insufficient coordination and collaboration, and a lack of awareness and understanding of the full potential by all stakeholders: public, providers, policymakers, industry and patients. The Personal Connected Health Alliance is defining the the field of personal connected health to inspire market and policy innovation, research and collective action for sustained adoption of personal connected health technology. The vision is better health and well being for all through increased personal responsibilities and connectivity as well as improved care delivery enabled by technology.
Slipp dataene min fri - Innovation@Altinn - Altinn-dagen 2014Steinar Skagemo
Hvordan kan brukerstyrt deling av personopplysninger gjøre at vi raskere får realisert gode digitale tjenester som tilpasser seg brukerens situasjon? Effekten er at brukeren slipper å legge inn informasjon, og mottageren slipper å kontrollere den. Presentasjonen viser skjermbilder fra Altinn/Accentures prototyp av et slikt grensesnitt bygget oppå dagens Altinn.
Software 2017: Tjenesteplattform som del av digitaliseringsstrategien i Oslo ...Steinar Skagemo
(Last ned som ppt for å få manus til hvert lysark.) Byrådet har store ambisjoner for digitaliseringen av kommunen. En tjenesteplattform skal sikre at de digitale løsningene gir innbyggerne helhetlige og effektive tjenester og at den informasjon som kommunen allerede har blir gjenbrukt. Ved å koble plattformen til fellesløsninger (FIKS, Altinn, Id-porten, grunndata) vil kommunen kunne lansere raskere. Plattformen vil bygge videre på kommunens ITAS.
Bidragsytere: Per Kjetil Grotnes, Trine Lind, Jan Henrik Gundelsby, Arne Berner, Kristin Hallandvik, m.fl.
A presentation showing the conversion of a html+css template to a simple Drupal theme. Theme files can be found at http://groups.drupal.org/node/23694#comment-83107
Can a custom Drupal 8 Theme be created in 40 minutes? The results might not be pretty but we're going to create a theme from start to finish. In the process you'll get to see all the components that make up a theme and get acquainted with tools that get the job done.
In this session, we will explore the how the recent explosion of devices has disrupted the process of designing a website that we've crafted over the past decade.
When designers only have one instance of website (i.e., desktop) to design, the layout is uniform. The header, content area, sidebar, and footer all remain static. Furthermore, the elements are relatively uniform as well. Buttons, navigation, typography, and images are all basically the same across across the various pages. But if you are designing a responsive website – one whose look and feel adapts depending whether you're using a phone, laptop, or tablet – then these elements and especially the layout begin to diverge.
After this session, you should leave with the confidence to argue the importance of responsive design to your client or boss – and that the with the proper strategy, the extra effort and costs can be justified (and hopefully minimized).
Minimalist Theming: How to Build a Lean, Mean Drupal 8 ThemeSuzanne Dergacheva
Back in the Drupal 7 days (aka last year), we came across some pretty large, hard-to-maintain Drupal 7 sites. The theme was often responsible for a lot of the cruft. We saw themes with excess code, too many template files, and not enough documentation.
The Drupal 8 theme layer provides new features like libraries and Twig blocks that can help us to build cleaner, better-organized themes. So now is a good time for themers to re-visit which theming techniques to use to create themes that are smaller, maintainable, and well organized.
[Srijan Wednesday Webinars] Drupal 8: Goodbye to 10 Years of Theming HeadachesSrijan Technologies
Drupal 8 has many new and exciting features, but none are as radical and essential as the changes made to the theme system. For over 10 years, Drupal's front end was designed and built by developers who tried their very best to figure out what the front end needed. The lack of dedicated front-enders in core resulted in a less than ideal front end architecture.
In this webinar, our speaker would share how Drupal 8 and Twig have changed it all. He would cover what’s new in Drupal 8 theme system, and how to use Twig to relieve the headache that you, as a themer, have been suffering from.
You can watch the complete webinar recording here: https://youtu.be/PxEpnGI5z6w
WSO2Con ASIA 2016: WSO2 Integration Platform Deep DiveWSO2
The world has become a system of connected components. Whether you are going to have breakfast at your favourite restaurant, watch a movie or book a sports event, everything is connected to provide you the best service. Connecting or integrating different systems has been a challenge for the IT industry for the last decade and it will be the same for coming decades. WSO2 provides the world’s fastest open source integration solution – the WSO2 ESB – to connect heterogeneous systems with each other.
This tutorial focuses on
An in-depth knowledge of the high performance integration platform
Its upcoming features
Customer use cases to give you real life insights into the capabilities of the product
It’s effect on your business.
Approach to enable your IT systems for FHIR (HL7 standards) complianceShubaS4
This summary deck discusses a practical, step-by-step approach to transform your IT systems for FHIR (HL7 standards) compliance, API-enablement of your legacy for an accelerated go to market using a library of tools and frameworks under the DigitMarket umbrella. It outlines different integration challenges such initiatives encounter and equips you to plan your compliance roadmap for FHIR.
Healthcare IT Systems Interoperability Market Industry Analysis and Forecast ...PriyanshiSingh187645
The global demand for healthcare IT systems interoperability was valued at USD 3658.50 Million in 2023 and is expected to reach USD 10560.29 Million in 2032, growing at a CAGR of 12.5% between 2024 and 2032.
Utilizing Interoperability Standards to Exchange and Protect Healthcare DataChetu
Technical standards have become exceedingly integral to healthcare processes and workflows. They increase interoperability amongst disparate EHRs and other systems. Standardization also reduces errors and risks, supports value-based and patient-centric care, etc.
https://www.chetu.com/healthcare/hie.php
Addressing the Healthcare Connectivity ChallengeTodd Winey
In healthcare, information accessibility can impact the outcome of a medical decision, or the success of a bundled payment initiative. To ensure that the right information is available at the right place and time, healthcare organizations typically have used HL7® interface engines to share data among clinical applications. But the demands on healthcare information technology are changing so rapidly that these simple engines are no longer sufficient.
Carl Kesselman and I (along with our colleagues Stephan Erberich, Jonathan Silverstein, and Steve Tuecke) participated in an interesting workshop at the Institute of Medicine on July 14, 2009. Along with Patrick Soon-Shiong, we presented our views on how grid technologies can help address the challenges inherent in healthcare data integration.
Healthcare and AWS: The Power of Cloud in Patient Care and Data ManagementSuccessiveDigital
Digital transformation in healthcare has encouraged patients to seek more personalized experiences from their providers. The customer experience evolution has changed how healthcare organizations deliver care forever.
Healthcare Integration | Opening the Doors to CommunicationBizTalk360
Integration plays the central role in connecting health systems to effortlessly communicate and share data, ultimately improving the quality and outcomes of health services. With an integration system in place, healthcare organizations can improve communication within their enterprise, connect to external entities, such as HIEs, laboratories, and long-term care facilities, and to patient platforms, such as Microsoft HealthVault. With established and evolving standards, such as HL7 v2 & v3, CDA, XDS, and FHIR, healthcare organizations now more than ever need a robust interoperability solution to meet and support these requirements.
Innovation in Enterprise Imaging: Clinical Context is What's NextTodd Winey
Clinicians have one word for what they want from your next generation enterprise imaging solutions. Context. A recent study in the Journal of Digital Imaging suggests that nearly 60% of radiology orders have no mention of important chronic conditions, calling it “an alarming lack of communication” that “may negatively impact interpretation quality.” Imaging orders such as “chest pain” or “lower abdominal pain,” for example, are essentially context free, giving clinicians little information to work with. Access to a complete clinical history behind those orders can help clinicians provide richer input for more accurate diagnoses and more effective care plans, along with results of the imaging study.
FHIR Vs Blockchain (capminds) 21 july.pptxkumarB54
In today’s digital world, health data management remains to be one of the ongoing challenges worldwide.
The healthcare data transmission has lagged behind the trend due to its complexity and sensitivity. This limits the healthcare providers’ ability to coordinate care, perform data analytics, and cost-effectively integrate IT environments.
learn more : www.capminds.com
CDSS implementation with CDA generation and integration for health informatio...ijtsrd
Electronic health record helps to improve the safety and quality care of every individual patient details, that to be stored in various hospital through health information exchange. The clinical document architecture(CDA) developed by Health level seven(HL7) is core document standard that ensure interoperability of the document. Hospitals are reluctant to adopt interoperable hospital information system due to its deployment cost except for in a handful countries. A problem arises even when more hospitals start using the CDA document format because the data scattered in different documents are hard to manage. CDA document generation and integration Service based on cloud computing through which hospitals are enabled to conveniently generate CDA document per patient into a single CDA document and physician and patients can browse the clinical data in chronological order. To improve the accuracy and speed of diagnosis, health care system is important to provide the faster and efficient way. A clinical decision support system (CDSS) is a health information technology system that is designed to provide physicians and other health professionals with clinical decision support (CDS), that is assistance with clinical decision “making tasks. The system is designed by using various data mining techniques to assist the diagnosis of patients symptoms. Our system is designed with the help of Naïve Bayesian classification technique which has overcome the various data mining technique to diagnose the patient symptoms. The Naïve Bayesian classification technique provide the diagnosis of disease with the help of symptoms occurs to the patient .œClinical decision support systems link health observations with health knowledge to influence health choices by clinicians for improved health. Our system implement (CDSS) clinical decision support system looking towards the system CDSS clinical decision support system diagnose the diseases of the patient and also the CDA is generated which will be in XML form and also it can be integrated through various platforms. With the help of this system the time of patient would be saved and accurate diagnoses of the patient is done. Pooja N. Umekar | Dr. H R. Deshmukh | Prof. O. A. Jaisinghani | Prof S.V. Khedkar"CDSS implementation with CDA generation and integration for health information exchange in cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14127.pdf http://www.ijtsrd.com/engineering/computer-engineering/14127/cdss-implementation-with-cda-generation-and-integration-for-health-information-exchange-in-cloud/pooja-n-umekar
Significant Advantages of Cloud Computing.pdfShelly Megan
Cloud computing in healthcare offers numerous benefits like easy collaboration, seamless interoperability, new avenues of Big data implementation, data analytics, medical research, reduced data storage, and operational costs, elevated patient experience, enhanced scalability, and improved data security.
DIGITAL HEALTH: DATA PRIVACY AND SECURITY WITH CLOUD COMPUTING Akshay Mittal
Emerging Threats and Countermeasures - Digital health is the convergence of digital technology in healthcare. The emerging technology and the use of innovations are needed in healthcare for advancements and better outcomes. With the use of innovations, new threats and challenges are emerging in the industry which needs to be managed for efficient operations.
Healthcare Interoperability: The Key to Leveraging Health TechMityung
Despite some setbacks, the digitalization of healthcare holds great promise for global health improvements. Health information technology (HIT) systems are taking over the healthcare industry.
For further information click here
https://www.mityung.com/
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Accelerate Enterprise Software Engineering with PlatformlessWSO2
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Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Less Is More: Utilizing Ballerina to Architect a Cloud Data PlatformWSO2
At its core, the challenge of managing Human Resources data is an integration challenge: estimates range from 2-3 HR systems in use at a typical SMB, up to a few dozen systems implemented amongst enterprise HR departments, and these systems seldom integrate seamlessly between themselves. Providing a multi-tenant, cloud-native solution to integrate these hundreds of HR-related systems, normalize their disparate data models and then render that consolidated information for stakeholder decision making has been a substantial undertaking, but one significantly eased by leveraging Ballerina. In this session, we’ll cover:
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Ballerina’s role in multiple evolutionary steps to the current architecture
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In this keynote, Asanka Abeysinghe, CTO,WSO2 will explore the shift towards platformless technology ecosystems and their importance in driving digital adaptability and innovation. We will discuss strategies for leveraging decentralized architectures and integrating diverse technologies, with a focus on building resilient, flexible, and future-ready IT infrastructures. We will also highlight WSO2's roadmap, emphasizing our commitment to supporting this transformative journey with our evolving product suite.
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The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
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Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
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Bob Boule
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https://alandix.com/academic/papers/synergy2024-epistemic/
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5. What drives Connected Health
Governments
Citizens
Healthcare organizations
Health insurance organizations
World health care institutions
Research entities / Universities
7. Goals in healthcare business
Providing the best possible service through accurate and timely
information sources
Decrease latencies in connected services
Reduce manual executions to reduce human errors (i.e data entry etc.)
High availability of medical information
Intelligence via information sharing
Big data analytics for healthcare research
10. Technology landscape in healthcare
Heterogeneous devices / applications / data formats /
protocols (i.e hospital information system)
heterogenous integrations in a hospital
12. Protocols & Data formats
HL7 (v2 / v3 / FHIR) over HTTP
HL7 (v2) over MLLP
SOAP / XML over HTTP
REST / JSON over HTTP
Messaging over JMS
XML, CSV over FTP
Custom binary protocols (certain HC devices)
Legacy CORBA based systems
14. Data storage and transformation
In a distributed HCIS data can reside in multiple different
locations
Data would be stored in different formats
There would be data which is common across several entities
Some data needs to be consolidated before consumption
Aggregation of data can be a function of data federation and
service mediation
16. Data accessibility and integrity
Distributed transactions (maintaining the ACID
properties in health data)
Who can access the data
From where the data is accessed
Entitlement policies
17. Data governance & entitlement
data bus
HCSB
cloud services
identity&entitlementbus
18. Health events
Admission, discharge and transfer events
Scheduling of surgeries / patient care / lab activity
Readings of healthcare devices (HC telemetries)
Alerts and events of registered patients
Insurance claim management
Disease control and vaccination related alerts
Hospital inventory management
Equipment maintenance alerts
19. Complex health event processing
HC cloud
complexeventsprocessor
HCSB
event queue
email / alerts
dashboards
22. The connected reference architecture
data bus
healthcare cloud
HCB
HC API gateway
securitygateway
eventprocessor
bigdataanalytics
event queue
data queue
cloud services
services workflows
23. The connected reference architecture
data bus
healthcare cloud
HCB
HC API gateway
securitygateway
eventprocessor
bigdataanalytics
event queue
data queue
cloud services
services workflows
external ecosystem
internal ecosystem
24. WSO2 view on the reference model
data bus
healthcare cloud
HCB
HC API gateway
securitygateway
eventprocessor
bigdataanalytics
event queue
data queue
cloud services
services workflows