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.
Cloud computing promises to fundamentally transform the global healthcare industry. But most healthcare providers have only just started to understand the power of cloud to not only drive efficiency, but also to redefine collaboration, partnering, and business models. The IBM Institute for Business Value point-of-view explores the opportunities and implications of cloud computing to help global healthcare companies meet new competitive pressures and ever-expanding consumer expectations.
Analytics is a key enabler for life sciences and healthcare organizations to create better outcomes for patients, customers and other stakeholders across the entire healthcare ecosystem. While almost two-thirds of organizations across the healthcare ecosystem have analytics strategies in place, our research shows that only a fifth are driving analytics adoption across the enterprise. The key barriers are a lack of data management capabilities and skilled analysts, as well as poor organizational change management. To develop and translate insights into actions that enhance outcomes, organizations will need to collaborate across an expanding ecosystem.
Your cognitive future: How next-gen computing changes the way we live and workIBM in Healthcare
The healthcare industry is undergoing significant change driven by six disruptive forces - rapid digitization, changing consumer expectations, regulatory complexities, increasing healthcare demand, shortage of skilled resources and elevating healthcare costs. To meet the implication of these forces, healthcare organizations must excel in engaging with consumers, discovering new ideas and taking effective decisions
Currently, traditional analytics capabilities are unable to exploit maximum value from the ever increasing data resource constraining organization’s achievements and performance. But cognitive computing has the ability to bridge this gap and can open up fresh opportunities for the healthcare industry. It is already helping healthcare organizations to provide personalized care, effective decisions and more innovative solutions.
Cloud computing promises to fundamentally transform the global life sciences industry. But most life sciences organizations have only just started to understand the power of cloud to not only drive efficiency, but also to redefine collaboration, partnering, and business models.
Life sciences organizations are hungry for the capabilities that cloud can deliver, to meet new competitive pressures and ever-expanding consumer expectations.
This new IBM Institute for Business Value (IBV) Cloud point-of-view (POV) for the life sciences industry explores the opportunities and implications of cloud computing for global life sciences companies. It provides a roadmap to formulate and execute cloud strategies.
The evolution of life science ecosystems: Five effective innovation approache...IBM in Healthcare
The life sciences industry, like many others, faces broad disruption and challenges on fronts ranging from technology to regulation to product resourcing. Traditionally, innovation has been a key driver of success for life sciences organizations, and it will continue to play a critical role for an industry that seeks to sustain this momentum.This report, the third of the Innovating Life Sciences series, identifies five strategies that differentiate the more successful academic life sciences institutions from the rest.
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
Platforms and Partnerships: The Building Blocks for Digital InnovationHealth Catalyst
Virtually all service-oriented industries have experienced massive disruption and transformation, resulting from the confluence of digital, mobile, cloud, data, and consumerization. And then there’s healthcare…
In this webinar Ryan Smith, executive advisor at Health Catalyst, shares practical insights gained from his combined 25 years of IT and digital leadership roles at Banner Health and Intermountain Healthcare. He explores why our industry is struggling to provide the tools and self-service experiences that patients and consumers have come to expect in every other aspect of their lives. To attract and retain patients and members, healthcare organizations need to “shift gears” and go on the digital offensive to sustain brand loyalty; however, decades of siloed, monolithic approaches to implementing technology and managing data continue to hamper industry progress.
During this session, Ryan shares his approach for building business support to enable digital transformation.
By viewing this webinar, you will learn key digitization concepts:
- How to conceptualize a digital enablement framework.
- Ten strategic guiding principles for technology leaders.
- Why it’s vital to create business-driven technology governance.
- Why building strategic vendor partnerships really matters.
- How to apply case studies to bolster digital investments.
Cloud computing promises to fundamentally transform the global healthcare industry. But most healthcare providers have only just started to understand the power of cloud to not only drive efficiency, but also to redefine collaboration, partnering, and business models. The IBM Institute for Business Value point-of-view explores the opportunities and implications of cloud computing to help global healthcare companies meet new competitive pressures and ever-expanding consumer expectations.
Analytics is a key enabler for life sciences and healthcare organizations to create better outcomes for patients, customers and other stakeholders across the entire healthcare ecosystem. While almost two-thirds of organizations across the healthcare ecosystem have analytics strategies in place, our research shows that only a fifth are driving analytics adoption across the enterprise. The key barriers are a lack of data management capabilities and skilled analysts, as well as poor organizational change management. To develop and translate insights into actions that enhance outcomes, organizations will need to collaborate across an expanding ecosystem.
Your cognitive future: How next-gen computing changes the way we live and workIBM in Healthcare
The healthcare industry is undergoing significant change driven by six disruptive forces - rapid digitization, changing consumer expectations, regulatory complexities, increasing healthcare demand, shortage of skilled resources and elevating healthcare costs. To meet the implication of these forces, healthcare organizations must excel in engaging with consumers, discovering new ideas and taking effective decisions
Currently, traditional analytics capabilities are unable to exploit maximum value from the ever increasing data resource constraining organization’s achievements and performance. But cognitive computing has the ability to bridge this gap and can open up fresh opportunities for the healthcare industry. It is already helping healthcare organizations to provide personalized care, effective decisions and more innovative solutions.
Cloud computing promises to fundamentally transform the global life sciences industry. But most life sciences organizations have only just started to understand the power of cloud to not only drive efficiency, but also to redefine collaboration, partnering, and business models.
Life sciences organizations are hungry for the capabilities that cloud can deliver, to meet new competitive pressures and ever-expanding consumer expectations.
This new IBM Institute for Business Value (IBV) Cloud point-of-view (POV) for the life sciences industry explores the opportunities and implications of cloud computing for global life sciences companies. It provides a roadmap to formulate and execute cloud strategies.
The evolution of life science ecosystems: Five effective innovation approache...IBM in Healthcare
The life sciences industry, like many others, faces broad disruption and challenges on fronts ranging from technology to regulation to product resourcing. Traditionally, innovation has been a key driver of success for life sciences organizations, and it will continue to play a critical role for an industry that seeks to sustain this momentum.This report, the third of the Innovating Life Sciences series, identifies five strategies that differentiate the more successful academic life sciences institutions from the rest.
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
Platforms and Partnerships: The Building Blocks for Digital InnovationHealth Catalyst
Virtually all service-oriented industries have experienced massive disruption and transformation, resulting from the confluence of digital, mobile, cloud, data, and consumerization. And then there’s healthcare…
In this webinar Ryan Smith, executive advisor at Health Catalyst, shares practical insights gained from his combined 25 years of IT and digital leadership roles at Banner Health and Intermountain Healthcare. He explores why our industry is struggling to provide the tools and self-service experiences that patients and consumers have come to expect in every other aspect of their lives. To attract and retain patients and members, healthcare organizations need to “shift gears” and go on the digital offensive to sustain brand loyalty; however, decades of siloed, monolithic approaches to implementing technology and managing data continue to hamper industry progress.
During this session, Ryan shares his approach for building business support to enable digital transformation.
By viewing this webinar, you will learn key digitization concepts:
- How to conceptualize a digital enablement framework.
- Ten strategic guiding principles for technology leaders.
- Why it’s vital to create business-driven technology governance.
- Why building strategic vendor partnerships really matters.
- How to apply case studies to bolster digital investments.
The Dangers of Commoditized Machine Learning in Healthcare: 5 Key Differentia...Health Catalyst
Many vendors deliver machine learning models with different applications in healthcare. But they don’t all deliver accurate models that are easy to implement, targeted to a specific use case, connected to actionable interventions, and surrounded by a machine learning community and support team with extensive, exclusive healthcare experience.
These machine learning qualities are possible only through a machine learning model delivered by a vendor with a unique set of capabilities. There are five differentiators behind effective machine learning models and vendors:
Vendor’s expertise and exclusive focus on healthcare.
Machine learning model’s access to extensive data sources.
Machine learning model’s ease of implementation.
Machine learning model’s interpretability and buy-in.
Machine learning model’s conformance with privacy standards.
These five factors separate the high-value vendors and models from the crowd, so healthcare systems can quickly implement machine learning and start seeing improvement results.
EHR Integration: Achieving this Digital Health ImperativeHealth Catalyst
As the digital trajectory of healthcare rises, health systems have an array of new resources available to make more effective and timely care decisions. However, to use these data analytics, machine learning, predictive analytics, and wellness applications to gain real-time, data-driven insight at the point of care, health systems must fully integrate the tools with their EHRs. Integration brings technical and administrative challenges, requiring organizations to coordinate around standards, administrative processes, regulatory principles, and functional integration, as well as develop compelling integration use cases that drive demand. When realized, full EHR integration will allow clinicians to leverage data from across the continuum of care (from health plan to patient-generated data) to improve patient diagnosis and treatment.
Network Optimization: Why Physician Quality Should Drive Your Benefits StrategyGrand Rounds
Employers and payers are increasingly interested in narrow network or "high performance" networks to control healthcare costs. But there's a science to reshaping your physician network to cut costs while avoiding member blowback. Learn how to optimize networks for cost and quality, while reassuring your employees that they can still access the care they need.
Should healthcare be more digitized? Absolutely. But if we go about it the wrong way... or the naïve way... we will take two steps forward and three steps back.
In this 90-minute webinar, Dale Sanders, President of Technology at Health Catalyst describes the right way to go about the technical digitization of healthcare so that it increases the sense of humanity during the journey.
The topics Dale covers include:
• The human, empathetic components of healthcare’s digitization strategy
• The AI-enabled healthcare encounter in the near future
• Why the current digital approach to patient engagement will never be effective
• The dramatic near-term potential of bio-integrated sensors
• Role of the “digitician” and patient data profiles
• The technology and architecture of a modern digital platform
• The role of AI vs. the role of traditional data analysis in healthcare
• Reasons that home grown digital platforms will not scale, economically
Most of the data that’s generated in healthcare is about administrative overhead of healthcare, not about the current state of patients’ well-being. On average, healthcare collects data about patients three times per year from which providers are expected to optimize diagnoses, treatments, predict health risks and cultivate long-term care plans. Where’s the data about patients’ health from the other 362 days per year?
McKinsey ranks industries based on their Digital Quotient (DQ), which is derived from a cross product of three areas: Data Assets x Data Skills x Data Utilization. Healthcare ranks lower than all industries except mining. It’s time for healthcare to raise its digital quotient, however, it’s a delicate balance. The current “data-driven” strategy in healthcare is a train wreck, sucking the life out of clinicians’ sense of mastery, autonomy, and purpose.
Healthcare’s digital strategy has largely ignored the digitization of patients’ state of health, but that’s changing, and the change will be revolutionary. Driven by bio-integrated sensors and affordable genomics, in the next five years, many patients will possess more data and AI-driven insights about their diagnosis and treatment options than healthcare systems, turning the existing dialogue with care providers on its head. It’s going to happen. Let’s make it happen the right way.
What the ONC's Proposed Rule on Information Blocking Means for Your WorkHealth Catalyst
Information blocking has been a hot-button issue for years as it has impeded innovation and patient healthcare options for too long. The 21st Century Cures Act (Cures Act) sought to eliminate these problems but information blocking persisted. However, in February 2019 the Office of the National Coordinator for Health Information Technology (ONC) announced a proposed rule with consequences to non-compliance with the Cures Act that may finally force true interoperability. As a healthcare decision maker you have a real opportunity to build an innovation strategy around these changes. To learn how, view this webinar.
True data interoperability enables innovation and better patient experience. In aggregate, both of these activities have the potential to accelerate the shift away from fee-for-service and towards fee-for-value healthcare. Dan Orenstein has spent much of his career providing legal counsel to healthcare organizations on regulatory and risk management issues as well as how to implement growth initiatives that comply with healthcare laws and regulations. That experience has made him an expert in applying policy to healthcare strategy. He has studied the proposed rule and in this webinar he will provide a summary of the existing legislation, implications of non-compliance with the proposed rule as well as insight into putting it into practice.
View this webinar and learn:
- To identify information blocking practices
- Seven exceptions to the information blocking provision and how they may apply to your work
- Summary of the public comments about the proposed rule and the overall perception of it in the industry
- The potential impact to your healthcare organization
Big Data Analytics on Customer Behaviors with Kinect Sensor NetworkCSCJournals
In modern enterprises, customer data is valuable for identifying their behavioral patterns and developing marketing strategies that can align with the preferences of different customers. The objective of this research is to develop a framework that promotes the use of Kinect sensors for Big Data Analytics on customer behavior analysis. Kinect enables 3D motion capture, facial recognition and voice recognition capabilities which allow to analyze customer behaviors in various aspects. Information fusion on the network of multiple Kinect sensors can achieve enhanced insight of the customer emotion, habits and consuming tendencies. Big Data Analytic techniques such as clustering and visualization are applied on the data collected from the sensors to provide better comprehension on the customers. Prediction on how to improve the customer relationship can be made to stimulate the vendition. Finally, an experimental system is designed based on the proposed framework as an illustration of the framework implementation.
Population Stratification Made Easy, Quick, and Transparent for AnyoneHealth Catalyst
One of the fundamental tasks when creating a population health initiative is to identify the right patients for the right interventions. The challenge with identifying patients is two-fold—there isn’t a one-size-fits all stratification method; and, current stratification tools prove to be inflexible, “black box” solutions that require time-consuming, technical expertise to customize the algorithms. Many commonly used stratification methods also fail to take advantage of the whole-patient picture, using the limited data sources that are available.
To address these challenges, Health Catalyst developed the Population Builder™️: Stratification Module; a fast, adaptable tool that allows for rapid and transparent stratification of patient groups based on predefined, yet easy to customize, populations and then provides the architecture to integrate the stratified populations into the population health workflow.
Based on the existing Population Builder tool, the Stratification Module consists of several population health building blocks that users can mix and match to create purpose-driven, transparent, and customizable populations to fit their needs. The building blocks save users the time and effort of creating the raw materials required for effective stratification by providing industry standard, evidence-based definitions for over 6,000 value sets, 21 predefined chronic condition registries, ED utilization (combined claims and clinical data), transition of care, and predictive risk models all in one tool. In addition, the power of AI is made accessible and easy with Health Catalyst-developed risk algorithms that are targeted to specific interventions.
View the Population Builder: Stratification Module webinar to learn more about its functionality, understand the customization process, observe a unique framework that integrates claims and clinical data, and make it easy to consume customized data sources, so that your algorithms include all of your available patient data.
In this webinar you can expect to:
- Learn how Population Builder: Stratification Module is used to combine data from multiple data sources—including claims and clinical data—to stratify based on a “whole patient picture.”
- Get a glimpse of the predefined stratification content that is packaged within the Population Builder: Stratification Module.
- Understand how the Population Builder: Stratification Module allows non-technical experts to quickly and transparently create sophisticated stratification algorithms.
- See how “published” patient lists, or registries, are created within Population Builder: Stratification Module and accessible by the DOS ecosystem.
Artificial intelligence (AI) truly is a disruptive force across all industries. One such industry that has been transformed by AI technologies is healthcare. So, in this post, we discuss the many roles of AI in today’s healthcare industry.
Visit: https://www.ezdi.com/blog/the-role-of-ai-in-healthcare/
Cloud-Based Open-Platform Data Solutions: The Best Way to Meet Today’s Growin...Health Catalyst
Smartphone applications, home monitoring equipment, genomic sequencing, and social determinants of health are adding significantly to the scope of healthcare data, creating new challenges for health systems in data management and storage. Traditional on-premises data warehouses, however, don’t have the capacity or capabilities to support this new era of bigger healthcare data.
Organizations must add more secure, scalable, elastic, and analytically agile cloud-based, open-platform data solutions that leverage analytics as a service (AaaS). Moving toward cloud hosting will help health systems avoid the five common challenges of on-premises data warehouses:
1. Predicting future demand is difficult.
2. Infrastructure scaling is lumpy and inelastic.
3. Security risk mitigation is a major investment.
4. Data architectures limit flexibility and are resource intensive.
5. Analytics expertise is misallocated.
Six Proven Methods to Combat COVID-19 with Real-World AnalyticsHealth Catalyst
As data in healthcare becomes more available than ever before, so does the need to apply that data to the unique challenges facing health systems, especially in a pandemic. Even with massive amounts of data, health systems still struggle to move data from spreadsheets to drive change in a clinical setting.
These six methods allow health systems to transform data into real-world analytics, going beyond basic data usage and maximizing actionable insight:
1. Create effective information displays.
2. Add context to data.
3. Ensure data processes are sustainable.
4. Certify data quality.
5. Provide systemwide access to data.
6. Refine the approach to knowledge management.
Advancing data use in healthcare with real-world analytics arms health systems with effective tools to combat COVID-19 and continue delivering quality care driven by comprehensive, actionable insight.
The Foundations of Success in Population Health ManagementHealth Catalyst
From hospital systems to large employers, organizations are increasingly taking on financial risk for the health of populations. Drivers of this trend include the update to the MSSP model, the recent CMS Primary Cares Initiative announcement, the increasing prevalence of the Medicare Advantage model, innovative partnerships in the self-insured employer space, and the proliferation of Medicaid ACOs. Yet while market pressures push organizations toward population risk, they don't necessarily help them succeed: most organizations are struggling to attain or sustain the dual imperatives of high-quality care and cost containment. A primary reason? Short-sighted and tactical approaches that don't provide the flexible data infrastructure and tools to adapt to emerging trends in population health—or to support short-term contractual requirements while building toward long-term success.
View this launch webinar to learn about Health Catalyst’s Population Health Foundations solution, a data and analytics-first starter set aimed at optimizing performance in value-based risk arrangements and providing the data ecosystem that will flex and adapt to complex needs of risk-bearing organizations. Solution services ensure that the strategic value of data is maximized to improve performance in risk contracts—and provide side-by-side subject matter expert partnership for establishing short- and long-term goals for population health management (PHM).
Built on Health Catalyst’s foundational technology and supported by the nationwide experience and perspective of its experts, the Population Health Foundations solution helps organizations leverage multiple data sources to understand their patient populations and create meaningful views of financial and clinical quality performance. As a starter set that organizations can build on based on their needs, the solution is designed to compensate for the known limitations of “black box” population health applications that fail to reveal the “why” of analytic insights and exacerbate the challenges of transforming quality, cost, and care. The Population Health Foundations solution delivers the essential analytic tools needed for success under value-based risk arrangements.
In these slides you can expect to:
- Review recent changes to the field of value-based care, and reactions and insights from the market
- Discover how the Population Health Foundations solution can act as a comprehensive, data-first analytics solution to support your population stratification and monitoring needs
- Understand how this solution functions as a foundational starter set for value-based care success, enabling clients to leverage all their data and other relevant population health tools
More and more health economies across the globe are deploying Electronic Health Records with some countries reaching full adoption by 2017. This means we, as healthcare marketers, now have a vital new channel to reach and educate decision makers.
A Healthcare Mergers Framework: How to Accelerate the BenefitsHealth Catalyst
Health system mergers can promise significant savings for participating organizations. Research, however, indicates as much as a tenfold gap between expectation and reality, with systems looking for a savings of 15 percent but more likely to realize savings around 1.5 percent.
Driving the merger expectation-reality disparity is a complex process that, without diligent preparation and strategy, makes it difficult for organizations to fully leverage cost synergies. With the right framework, however, health systems can achieve the process management, data sharing, and governance structure to align leadership, clinicians, and all stakeholders around merger goals.
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.
Breakout Session: Cybersecurity in Medical DevicesHealthegy
Presentation by PwC at Medtech Conference 2016.
Participant:
Geoff Fisher, Director – PwC
Powered by:
Healthegy
For more healthcare innovation
Visit us at Healthegy.com
The Dangers of Commoditized Machine Learning in Healthcare: 5 Key Differentia...Health Catalyst
Many vendors deliver machine learning models with different applications in healthcare. But they don’t all deliver accurate models that are easy to implement, targeted to a specific use case, connected to actionable interventions, and surrounded by a machine learning community and support team with extensive, exclusive healthcare experience.
These machine learning qualities are possible only through a machine learning model delivered by a vendor with a unique set of capabilities. There are five differentiators behind effective machine learning models and vendors:
Vendor’s expertise and exclusive focus on healthcare.
Machine learning model’s access to extensive data sources.
Machine learning model’s ease of implementation.
Machine learning model’s interpretability and buy-in.
Machine learning model’s conformance with privacy standards.
These five factors separate the high-value vendors and models from the crowd, so healthcare systems can quickly implement machine learning and start seeing improvement results.
EHR Integration: Achieving this Digital Health ImperativeHealth Catalyst
As the digital trajectory of healthcare rises, health systems have an array of new resources available to make more effective and timely care decisions. However, to use these data analytics, machine learning, predictive analytics, and wellness applications to gain real-time, data-driven insight at the point of care, health systems must fully integrate the tools with their EHRs. Integration brings technical and administrative challenges, requiring organizations to coordinate around standards, administrative processes, regulatory principles, and functional integration, as well as develop compelling integration use cases that drive demand. When realized, full EHR integration will allow clinicians to leverage data from across the continuum of care (from health plan to patient-generated data) to improve patient diagnosis and treatment.
Network Optimization: Why Physician Quality Should Drive Your Benefits StrategyGrand Rounds
Employers and payers are increasingly interested in narrow network or "high performance" networks to control healthcare costs. But there's a science to reshaping your physician network to cut costs while avoiding member blowback. Learn how to optimize networks for cost and quality, while reassuring your employees that they can still access the care they need.
Should healthcare be more digitized? Absolutely. But if we go about it the wrong way... or the naïve way... we will take two steps forward and three steps back.
In this 90-minute webinar, Dale Sanders, President of Technology at Health Catalyst describes the right way to go about the technical digitization of healthcare so that it increases the sense of humanity during the journey.
The topics Dale covers include:
• The human, empathetic components of healthcare’s digitization strategy
• The AI-enabled healthcare encounter in the near future
• Why the current digital approach to patient engagement will never be effective
• The dramatic near-term potential of bio-integrated sensors
• Role of the “digitician” and patient data profiles
• The technology and architecture of a modern digital platform
• The role of AI vs. the role of traditional data analysis in healthcare
• Reasons that home grown digital platforms will not scale, economically
Most of the data that’s generated in healthcare is about administrative overhead of healthcare, not about the current state of patients’ well-being. On average, healthcare collects data about patients three times per year from which providers are expected to optimize diagnoses, treatments, predict health risks and cultivate long-term care plans. Where’s the data about patients’ health from the other 362 days per year?
McKinsey ranks industries based on their Digital Quotient (DQ), which is derived from a cross product of three areas: Data Assets x Data Skills x Data Utilization. Healthcare ranks lower than all industries except mining. It’s time for healthcare to raise its digital quotient, however, it’s a delicate balance. The current “data-driven” strategy in healthcare is a train wreck, sucking the life out of clinicians’ sense of mastery, autonomy, and purpose.
Healthcare’s digital strategy has largely ignored the digitization of patients’ state of health, but that’s changing, and the change will be revolutionary. Driven by bio-integrated sensors and affordable genomics, in the next five years, many patients will possess more data and AI-driven insights about their diagnosis and treatment options than healthcare systems, turning the existing dialogue with care providers on its head. It’s going to happen. Let’s make it happen the right way.
What the ONC's Proposed Rule on Information Blocking Means for Your WorkHealth Catalyst
Information blocking has been a hot-button issue for years as it has impeded innovation and patient healthcare options for too long. The 21st Century Cures Act (Cures Act) sought to eliminate these problems but information blocking persisted. However, in February 2019 the Office of the National Coordinator for Health Information Technology (ONC) announced a proposed rule with consequences to non-compliance with the Cures Act that may finally force true interoperability. As a healthcare decision maker you have a real opportunity to build an innovation strategy around these changes. To learn how, view this webinar.
True data interoperability enables innovation and better patient experience. In aggregate, both of these activities have the potential to accelerate the shift away from fee-for-service and towards fee-for-value healthcare. Dan Orenstein has spent much of his career providing legal counsel to healthcare organizations on regulatory and risk management issues as well as how to implement growth initiatives that comply with healthcare laws and regulations. That experience has made him an expert in applying policy to healthcare strategy. He has studied the proposed rule and in this webinar he will provide a summary of the existing legislation, implications of non-compliance with the proposed rule as well as insight into putting it into practice.
View this webinar and learn:
- To identify information blocking practices
- Seven exceptions to the information blocking provision and how they may apply to your work
- Summary of the public comments about the proposed rule and the overall perception of it in the industry
- The potential impact to your healthcare organization
Big Data Analytics on Customer Behaviors with Kinect Sensor NetworkCSCJournals
In modern enterprises, customer data is valuable for identifying their behavioral patterns and developing marketing strategies that can align with the preferences of different customers. The objective of this research is to develop a framework that promotes the use of Kinect sensors for Big Data Analytics on customer behavior analysis. Kinect enables 3D motion capture, facial recognition and voice recognition capabilities which allow to analyze customer behaviors in various aspects. Information fusion on the network of multiple Kinect sensors can achieve enhanced insight of the customer emotion, habits and consuming tendencies. Big Data Analytic techniques such as clustering and visualization are applied on the data collected from the sensors to provide better comprehension on the customers. Prediction on how to improve the customer relationship can be made to stimulate the vendition. Finally, an experimental system is designed based on the proposed framework as an illustration of the framework implementation.
Population Stratification Made Easy, Quick, and Transparent for AnyoneHealth Catalyst
One of the fundamental tasks when creating a population health initiative is to identify the right patients for the right interventions. The challenge with identifying patients is two-fold—there isn’t a one-size-fits all stratification method; and, current stratification tools prove to be inflexible, “black box” solutions that require time-consuming, technical expertise to customize the algorithms. Many commonly used stratification methods also fail to take advantage of the whole-patient picture, using the limited data sources that are available.
To address these challenges, Health Catalyst developed the Population Builder™️: Stratification Module; a fast, adaptable tool that allows for rapid and transparent stratification of patient groups based on predefined, yet easy to customize, populations and then provides the architecture to integrate the stratified populations into the population health workflow.
Based on the existing Population Builder tool, the Stratification Module consists of several population health building blocks that users can mix and match to create purpose-driven, transparent, and customizable populations to fit their needs. The building blocks save users the time and effort of creating the raw materials required for effective stratification by providing industry standard, evidence-based definitions for over 6,000 value sets, 21 predefined chronic condition registries, ED utilization (combined claims and clinical data), transition of care, and predictive risk models all in one tool. In addition, the power of AI is made accessible and easy with Health Catalyst-developed risk algorithms that are targeted to specific interventions.
View the Population Builder: Stratification Module webinar to learn more about its functionality, understand the customization process, observe a unique framework that integrates claims and clinical data, and make it easy to consume customized data sources, so that your algorithms include all of your available patient data.
In this webinar you can expect to:
- Learn how Population Builder: Stratification Module is used to combine data from multiple data sources—including claims and clinical data—to stratify based on a “whole patient picture.”
- Get a glimpse of the predefined stratification content that is packaged within the Population Builder: Stratification Module.
- Understand how the Population Builder: Stratification Module allows non-technical experts to quickly and transparently create sophisticated stratification algorithms.
- See how “published” patient lists, or registries, are created within Population Builder: Stratification Module and accessible by the DOS ecosystem.
Artificial intelligence (AI) truly is a disruptive force across all industries. One such industry that has been transformed by AI technologies is healthcare. So, in this post, we discuss the many roles of AI in today’s healthcare industry.
Visit: https://www.ezdi.com/blog/the-role-of-ai-in-healthcare/
Cloud-Based Open-Platform Data Solutions: The Best Way to Meet Today’s Growin...Health Catalyst
Smartphone applications, home monitoring equipment, genomic sequencing, and social determinants of health are adding significantly to the scope of healthcare data, creating new challenges for health systems in data management and storage. Traditional on-premises data warehouses, however, don’t have the capacity or capabilities to support this new era of bigger healthcare data.
Organizations must add more secure, scalable, elastic, and analytically agile cloud-based, open-platform data solutions that leverage analytics as a service (AaaS). Moving toward cloud hosting will help health systems avoid the five common challenges of on-premises data warehouses:
1. Predicting future demand is difficult.
2. Infrastructure scaling is lumpy and inelastic.
3. Security risk mitigation is a major investment.
4. Data architectures limit flexibility and are resource intensive.
5. Analytics expertise is misallocated.
Six Proven Methods to Combat COVID-19 with Real-World AnalyticsHealth Catalyst
As data in healthcare becomes more available than ever before, so does the need to apply that data to the unique challenges facing health systems, especially in a pandemic. Even with massive amounts of data, health systems still struggle to move data from spreadsheets to drive change in a clinical setting.
These six methods allow health systems to transform data into real-world analytics, going beyond basic data usage and maximizing actionable insight:
1. Create effective information displays.
2. Add context to data.
3. Ensure data processes are sustainable.
4. Certify data quality.
5. Provide systemwide access to data.
6. Refine the approach to knowledge management.
Advancing data use in healthcare with real-world analytics arms health systems with effective tools to combat COVID-19 and continue delivering quality care driven by comprehensive, actionable insight.
The Foundations of Success in Population Health ManagementHealth Catalyst
From hospital systems to large employers, organizations are increasingly taking on financial risk for the health of populations. Drivers of this trend include the update to the MSSP model, the recent CMS Primary Cares Initiative announcement, the increasing prevalence of the Medicare Advantage model, innovative partnerships in the self-insured employer space, and the proliferation of Medicaid ACOs. Yet while market pressures push organizations toward population risk, they don't necessarily help them succeed: most organizations are struggling to attain or sustain the dual imperatives of high-quality care and cost containment. A primary reason? Short-sighted and tactical approaches that don't provide the flexible data infrastructure and tools to adapt to emerging trends in population health—or to support short-term contractual requirements while building toward long-term success.
View this launch webinar to learn about Health Catalyst’s Population Health Foundations solution, a data and analytics-first starter set aimed at optimizing performance in value-based risk arrangements and providing the data ecosystem that will flex and adapt to complex needs of risk-bearing organizations. Solution services ensure that the strategic value of data is maximized to improve performance in risk contracts—and provide side-by-side subject matter expert partnership for establishing short- and long-term goals for population health management (PHM).
Built on Health Catalyst’s foundational technology and supported by the nationwide experience and perspective of its experts, the Population Health Foundations solution helps organizations leverage multiple data sources to understand their patient populations and create meaningful views of financial and clinical quality performance. As a starter set that organizations can build on based on their needs, the solution is designed to compensate for the known limitations of “black box” population health applications that fail to reveal the “why” of analytic insights and exacerbate the challenges of transforming quality, cost, and care. The Population Health Foundations solution delivers the essential analytic tools needed for success under value-based risk arrangements.
In these slides you can expect to:
- Review recent changes to the field of value-based care, and reactions and insights from the market
- Discover how the Population Health Foundations solution can act as a comprehensive, data-first analytics solution to support your population stratification and monitoring needs
- Understand how this solution functions as a foundational starter set for value-based care success, enabling clients to leverage all their data and other relevant population health tools
More and more health economies across the globe are deploying Electronic Health Records with some countries reaching full adoption by 2017. This means we, as healthcare marketers, now have a vital new channel to reach and educate decision makers.
A Healthcare Mergers Framework: How to Accelerate the BenefitsHealth Catalyst
Health system mergers can promise significant savings for participating organizations. Research, however, indicates as much as a tenfold gap between expectation and reality, with systems looking for a savings of 15 percent but more likely to realize savings around 1.5 percent.
Driving the merger expectation-reality disparity is a complex process that, without diligent preparation and strategy, makes it difficult for organizations to fully leverage cost synergies. With the right framework, however, health systems can achieve the process management, data sharing, and governance structure to align leadership, clinicians, and all stakeholders around merger goals.
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.
Breakout Session: Cybersecurity in Medical DevicesHealthegy
Presentation by PwC at Medtech Conference 2016.
Participant:
Geoff Fisher, Director – PwC
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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.
Breakout Session: Is Off-Label Promotion Lawful After the Howard Root/Vascula...Healthegy
Presentation by DuVal & Associates at Medtech Conference 2016.
Participants:
Mark DuVal, JD, President & CEO – DuVal & Associates
Howard Root, CEO – Vascular Solutions
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Infographic: Ask if Your EHR Offers Surescripts CompletEPA Electronic Prior A...Surescripts
Surescripts works with EHRs serving nearly half a million physicians. Ask your EHR if they work with us. Tell them you want CompletEPA to save your practice time and money.
Unlocking Technology Opportunities in Value-Based Healthcare | Parimal Shah |...UCICove
About UCI Applied Innovation:
UCI Applied Innovation is a dynamic, innovative central platform for the UCI campus, entrepreneurs, inventors, the business community and investors to collaborate and move UCI research from lab to market.
About the Cove @ UCI:
To accelerate collaboration by better connecting innovation partners in Orange County, UCI Applied Innovation created the Cove, a physical, state-of-the-art hub for entrepreneurs to gather and navigate the resources available both on and off campus. The Cove is headquarters for UCI Applied Innovation, as well as houses several ecosystem partners including incubators, accelerators, angel investors, venture capitalists, mentors and legal experts.
Follow us on social media:
Facebook: @UCICove
Twitter: @UCICove
Instagram: @UCICove
LinkedIn: @UCIAppliedInnovation
For more information:
cove@uci.edu
http://innovation.uci.edu/
EU cybersecurity requirements under current and future medical devices regula...Erik Vollebregt
Presentation delivered at Q1 MEDICAL DEVICE CYBERSECURITY RISK MITIGATION conference in Washington on 25 July 2016 concerning EU cybersecurity requirements under current and future medical devices regulation
Jake Williams - Navigating the FDA Recommendations on Medical Device Security...centralohioissa
In January, the FDA has draft recommendations for medical device security after the sale. Among other things, the recommendations tell manufacturers how to evaluate security risks, how to build a program for coordinated vulnerability disclosure program, and how to intake vulnerability reports from researchers. While the security of medical devices is especially important given the potential consequences, we can learn from the FDA recommendations regardless of our industry. Any recommendations adopted by the FDA for medical devices are likely to be implemented across other verticals for their IoT devices as well. Whether you manufacture, purchase, integrate, implement, or generally try to run away from IoT devices, there’s plenty to take away from this session while learning about the future of IoT device security.
Med Device Vendors Have Big Opportunities in Health IT Software, Services, an...Shahid Shah
If you’re in the medical device manufacturing or hardware sales business your revenue growth (CAGR) is under pressure like never before. You’re being asked to do more with less but you’re probably going to find that hard to accomplish because of one or more of the following challenges:
* Longer product development timelines caused by more FDA and other government regulations
* Increased demand by customers to have your devices deliver user experiences that are more like “consumer” devices such as cell phones and tablets
* Lower margins as a reaction to commodity competition (your sensor hardware business will be commoditized faster and faster over time)
* More complex and longer sales cycles because devices are now being approved for sale not by facilities and clinical executives alone but increasingly by CIOs and IT teams
* Increased cost of risk management and compliance caused by connectivity requirements
Any one of these challenges is difficult to meet but these days you’re probably being asked to meet more than one simultaneously. The solutions are not simple but the good news is that medical device manufacturers have many revenue generation opportunities today that can fund the new strategic imperatives you’ll need to put into place to meet the challenges listed above.
This briefing, presented by Netspective CEO Shahid Shah, describes some of the opportunities and how device vendors can take advantage of them.
2016 IBM Interconnect - medical devices transformationElizabeth Koumpan
Emerging technologies such as Internet of Things, 3D Printing are driving the creation of new business models and forcing the Industry for transformation. The product centric model where the Industry main objective was to develop the device, is moving to software and services model, with the focus on Big Data & Analytics, Integration and Cloud.
The maturation of technologies such as social, mobile, analytics, cloud, 3D printing, bio- and nanotechnology are rapidly shifting the competitive landscape. These emerging technologies create an environment that is connected and open, simple and intelligent, fast and scalable. Organizations must embrace disruptive technologies to drive innovation
Connecting Patient Monitoring Devices to EHRsAn electronic health .pdfeyebolloptics
Connecting Patient Monitoring Devices to EHRs
An electronic health record (EHR) is a computer-readable record of health-related information
on an individual. The compiled data in an EHR can include information about patient
demographics, medical history, family history, immunization records, labotary data, ongoing
health problems, progress notes, medications, vital signs, and radiology reports. Ideally, EHRs
incorporate data from all healthcare facilities a patient uses, making the data easily accessible to
healthcare professionals.
EHRs hold out the promise of improving health care and reducing costs, but for now, many
hospitals are struggling to automate the capture of raw data from the various patient monitoring
devices - such as vital sign monitors, ventilators, and electrocardiagram machines - and pass the
data directly into each patient\'s EHR. This task is made more difficult because different devices
and/or vendors often use different standards for communicating over the network. As a result,
specialized software is required to receive the data and translate it into a form suitable for
updating the EHR. Until communications standards implemented across the healthcare industry,
each new piece of monitoring equipment that outputs a nonstandard signal requires a new
interface with the EHR. So if a promising new vital sign monitoring device is developed, some
hospitals looking to use the device may be required to create a new software middleware layer to
connect the new device to the EHR. Connecting monitoring devices and EHRs is expected to
become a major business growth area over the next decade.
Many software vendors and device manufacturers are moving quickly to capitalize on the
opportunities involved with automating the many clinical-support activities that involve
minotoring devices. THe center for Medical Interoperability has enlisted many of the nation\'s
largest healthcare systems as part of its effort to strongly encourage device vendors to adopt
communications standards that will ease the problems with interoperablity. The FDA is working
to encourage the development of interoperable devices by defining some 25 device standards.
Solving the interoperability problem will require an agreement on standards through the
cooperation of multiple shareholders.
1. What benefits can be achieved through the successful implementation of EHRs? What
additional benefits will be gained by feeding data directly from patient monitoring devices
directly into EHRs?
2. Can you identify any legal, ethical, or social concerns with the use of EHRs? What additional
concerns arise from connecting patient monitoring devices to the IoT?
3. What actions need to be taken by EHR software vendors, patient monitoring device vendors,
government agencies, and hospital administrators to enable patient monitoring devices to be
safely and reliably connected to EHRs?
Solution
Question 1
What benefits can be achieved through the successful implementation of EHRs? Wha.
Electronic Health Records: purpose of electronic health records, popular electronic health record system, advantages of electronic records, challenges of electronic health records, the key players involved.
Technology is constantly transforming healthcare for the better, but getting technology right is an understated challenge for the industry. This webinar addresses three of healthcare's top challenges in tapping technology's full potential: cost, privacy and adoption. Experts and providers share tips, strategies and stories to help overcome these challenges to truly harness the power of transformative healthcare technology.
One can expect a smart, mobile-powered solutions for improved patient care, efficient record maintenance, high level of data security, enhanced interpersonal communication and a resourceful healthcare training and innovation.
How Mobile Technology dominate the world of Healthcare industryPeerbits
One can expect a smart, mobile-powered solutions for improved patient care, efficient record maintenance, high level of data security, enhanced interpersonal communication and a resourceful healthcare training and innovation.
2015 Healthcare IT Vision: Top 5 eHealth Trendsaccenture
Read about the five key Health IT trends and innovations shaping the business landscape in 2015 and beyond according to Accenture’s Healthcare Technology Vision 2015.
POST EACH DISCUSSION SEPARATELYThe way patient data is harvested.docxLacieKlineeb
POST EACH DISCUSSION SEPARATELY
The way patient data is harvested and used is rapidly changing. Patient data itself has become quite complex.
In the future
, patient data will be combined with financial data, product or drug data, socioeconomic factors, social patterns, and social determinants of health. Cognitive behavior and artificial intelligence will be applied to the data to help prevent and depict rather than cure disease.
Evaluate the future of Healthcare information technology.
Include the following aspects in the discussion:
Find two articles related to the future of information systems (IS) in healthcare
Include telehealth, wearable technology, patient portals, and data utilization
Analyze potential benefits from advances
Discuss, from your own perspective, the advantages and disadvantages of having a system where the patient manages their own data
REPLY TO MY CLASSMATE’S DISCUSSION TO THE ABOVE QUESTIONS AND EXPLAIN WHY YOU AGREE. MINIMUM OF 150 WORDS EACH
Classmate’s Discussion 1
The technological advancements that have occurred in the field of healthcare have greatly changed the way people view and interact with the healthcare system. They have also led to the reduction of costs and the increasing efficiency of the system. We expect that the future of healthcare will continue to be influenced by information technology.
Due to the technological advancements that have occurred in the field of healthcare, physicians are now able to spend less time with their patients. This has allowed them to provide more effective and efficient care to their patients. In the future, we can expect that the increasing number of specialists who can delegate their work to other doctors will have a significant impact on the healthcare system. The increasing efficiency of doctors is expected to have a significant impact on the shortage of specialist physicians in the future. This issue could be solved using technology. Hopefully, the use of information technology can help boost the number of specialist physicians (Patric, 2022).
Electronic health records have revolutionized the way healthcare is done. Despite the progress that has been made in terms of keeping and tracking these records, they are still not widely used yet. This means that the kind of growth that was expected from the adoption of these records has not materialized. Although the adoption of electronic health records has been made in various parts of the world, it’s still not widely used in all areas. This means that the ability to keep track of one’s medical history is still very important (Patric, 2022).
The increasing importance of information technology in healthcare has led to the prediction that the cost of healthcare will eventually come down. Various factors such as better accessibility and efficiency will help make healthcare more affordable and more effective.
It’s widely believed that keeping one's health is much cheaper and easier than treating a.
Pg2 Beginning in 1991, the IOM (which stands for the Institute o.docxrandymartin91030
Pg2 Beginning in 1991, the IOM (which stands for the Institute of Medicine of the National Academies) sponsored studies and created reports that led the way toward the concepts we have in place today for electronic health records. Originally, the IOM called them computer-based patient records.1 During their evolution, the EHR have had many other names, including electronic medical records, computerized medical records, longitudinal patient records, and electronic charts. All of these names referred to essentially the same thing, which in 2003, the IOM renamed as the electronic health records, or EHR.
Note: EHR
The acronym EHR is commonly used as shorthand for Electronic Health Records, and will be used in the remainder of this book.
Institute of Medicine (IOM)
The IOM report2 put forth a set of eight core functions that an EHR should be capable of performing:
Health information and data
This function provides a defined data set that includes such items as medical and nursing diagnoses, a medication list, allergies, demographics, clinical narratives, and laboratory test results. Further, it provides improved access to information needed by care providers when they need it.
Result management
Computerized results can be accessed more easily (than paper reports) by the provider at the time and place they are needed.
· Reduced lag time allows for quicker recognition and treatment of medical problems.
· The automated display of previous test results makes it possible to reduce redundant and additional testing.
· Having electronic results can allow for better interpretation and for easier detection of abnormalities, thereby ensuring appropriate follow-up.
· Access to electronic consults and patient consents can establish critical links and improve care coordination among multiple providers, as well as between provider and patient
Order management
Computerized provider order entry (CPOE) systems can improve workflow processes by eliminating lost orders and ambiguities caused by illegible handwriting, generating related orders automatically, monitoring for duplicate orders, and reducing the time required to fill orders.
· CPOE systems for medications reduce the number of errors in medication dose and frequency, drug allergies, and drug–drug interactions.
· The use of CPOE, in conjunction with an EHR, also improves clinician productivity.
Decision Support
Computerized decision support systems include prevention, prescribing of drugs, diagnosis and management, and detection of adverse events and disease outbreaks.
· Computer reminders and prompts improve preventive practices in areas such as vaccinations, breast cancer screening, colorectal screening, and cardiovascular risk reduction.
Electronic communication and connectivity
Electronic communication among care partners can enhance patient safety and quality of care, especially for patients who have multiple providers in multiple settings that must coordinate care plans.
· Electronic co.
Leveraging emerging standards for patient engagement pchamHealth2015
Patients are playing an increasingly important role in creating relevant healthcare data about themselves using mobile devices and applications. It is important this data can move with them securely throughout a healthcare ecosystem. The increased use of medical devices and mobile applications opens the dialogue around open source and non-proprietary standards with complementing policies.
Empowering Wellness_ The Ultimate Guide to Healthcare Software Development!.pdfKathy Miller
In the rapidly evolving landscape of healthcare, technology has emerged as a powerful force in enhancing patient care, streamlining operational efficiency, and revolutionizing the way healthcare is delivered and experienced. Central to this transformation is the world of Healthcare Software Development, a realm where cutting-edge technology meets the noble mission of improving patient care, simplifying processes, and reshaping the healthcare industry.
Advancing Healthcare Through Software Development
Healthcare Software Development is the driving force behind a multitude of innovations and advancements that have the potential to transform the healthcare sector for the better. These software solutions are designed to facilitate the efficient management of patient data, streamline hospital operations, improve communication between healthcare professionals, and empower patients to take a more active role in their own well-being.
Benefits of Healthcare Software Development
The advantages of Healthcare Software Development are manifold. Firstly, these solutions offer healthcare providers the tools they need to enhance the quality of patient care. The ability to access and manage patient information with ease leads to more informed medical decisions, ultimately resulting in better patient outcomes.
Secondly, the operational benefits are significant. Healthcare facilities can optimize their workflows, improve resource allocation, and reduce administrative burdens, leading to cost savings and a more efficient healthcare system.
Thirdly, communication is a cornerstone of effective healthcare, and Healthcare Software Development enhances this aspect dramatically. Real-time communication and data sharing between healthcare professionals ensure that critical information is always at their fingertips, allowing for swift and well-informed decisions.
Customization is Key
One of the standout features of Healthcare Software Development is its customization capabilities. Every healthcare organization is unique, with distinct needs and objectives. To address this diversity, Healthcare Software Development offers tailor-made solutions that align perfectly with each organization's specific requirements.
From small clinics to large hospital networks, these customized applications are designed to meet the unique challenges of each setting. They can be adapted to manage electronic health records.
Data Security and Compliance
In the realm of healthcare, data security and compliance with healthcare regulations are of paramount importance. Healthcare Software Development ensures that all patient data is handled with the utmost care and is protected from breaches.
These solutions adhere to strict healthcare regulations, including the Health Insurance Portability and Accountability Act (HIPAA) in the United States. Robust encryption, secure data storage, and stringent access controls are implemented to safeguard sensitive patient information.
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfJim Jacob Roy
Cardiac conduction defects can occur due to various causes.
Atrioventricular conduction blocks ( AV blocks ) are classified into 3 types.
This document describes the acute management of AV block.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
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Hot Selling Organic intermediates
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.