The document discusses the future of data and the need to move from simply collecting data to utilizing high-value data. It notes that the COVID-19 pandemic highlighted issues with timely access to the right data. Key learnings include: improving data acquisition, breaking down data silos, and improving user trust in data. The vision is outlined as moving from static to fast-acquiring data, siloed to integrated data, and untrusted to a single source of truth. Important assumptions driving product directions are also discussed, focusing on healthcare data being a critical asset and analytics converting data into insights.
Why a Build-Your-Own Healthcare Data Platform Will Fall Short and What to Do ...Health Catalyst
Health system may have some compelling reasons for choosing to build a data platform versus partner with a healthcare analytics vendor on a commercial solution. However, while organizations may think they’re saving money, gaining control and security, and more by opting for a homegrown approach, they’ll more than likely encounter challenges, hidden costs, and limitations. In comparison to a commercial-grade, healthcare-specific platform from a vendor, build-your-own solutions fall short when it comes to domain-specific content, technical expertise, total cost of ownership, and more. Organizations that partner on a vended platform vastly improve their chances of optimizing and scaling their analytic investment over time and achieving measurable improvement.
How to Drive ROI from Your Healthcare Projects: Practical Tools, Templates, a...Health Catalyst
At a time when average hospital’s margins are stagnating, executives should be asking tough questions about the ROI of “indispensable” technologies. Will new technologies prove their worth or drive them further into the red? How do you measure and track ROI?
Clinicians need more education on financial metrics and finance people need to learn more about the clinical processes and outcomes. One of the historical problems with calculating ROI has been the fundamental culture divide between clinicians and finance.
This slide set gives some practical tools, templates (Excel), and how tos based on years of experience to quickly and effectively develop the ability to measure and communicate ROI on healthcare IT and improvement projects.
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...Health Catalyst
The enterprise data warehouse (EDW) at Intermountain Healthcare went live in 1998. The EDW at Northwestern Medicine went live in 2006. Dale Sanders was the chief architect and strategist for both. The business inspiration behind Health Catalyst was, in essence, to create the commercial availability of the technology, analytics, and data utilization skills associated with these systems at Intermountain and Northwestern. Lee Pierce assumed leadership of the Intermountain EDW in 2008. Andrew Winter assumed leadership of the Northwestern EDW in 2009, and transitioned leadership of the EDW to Shakeeb Akhter in 2016. This webinar is a fireside chat among friends and colleagues as they look back across their healthcare IT decisions to answer these questions:
What did we do right and what did we do wrong?
What advice do we have for others in this emerging era of Big Data?
What does the future of analytics and Big Data look like in healthcare?
Does it feel like you’re falling behind on the latest CMS regulatory updates? You’re not alone. The CareOptimize COVID-19 Insights webinar is designed to keep you informed of everything going on with CMS as healthcare practices continue to adjust. Along with CMS updates, this webinar goes over SBA loans and Fee-for-service Advance/Accelerated Medicare payments.
The Power and Promise of Unstructured Patient Data Healthline
Unstructured search capabilities, superior natural language processing, and healthcare ontology capabilities will help distinguish the leading products in the category (information and data-driven decision making).
As the Age of Analytics emerges in healthcare, health system executives are increasingly challenged to define a data governance strategy that maximizes the value of data to the mission of their organizations.
Adding to that challenge, the competitive nature of the data warehouse and analytics market place has resulted in significant noise from vendors and consultants alike who promise to help health systems develop their data governance strategy. Having gone on his own turbulent data governance ride as a CIO in the US Air Force and healthcare, Dale Sanders, Senior Vice President at Health Catalyst will cut through the market noise to cover the following topics:
General concepts of data governance, regardless of industry
Unique aspects of data governance in healthcare
Data governance in a “Late Binding” data warehouse
The layers and roles in data governance
The four “Closed Loops” of healthcare analytics and data governance
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...Health Catalyst
Lessons learned over 20 years. This time we focus on technology lessons learned from experience at Intermountain Healthcare, Northwestern Medicine and Cayman Islands Health Authority
Why a Build-Your-Own Healthcare Data Platform Will Fall Short and What to Do ...Health Catalyst
Health system may have some compelling reasons for choosing to build a data platform versus partner with a healthcare analytics vendor on a commercial solution. However, while organizations may think they’re saving money, gaining control and security, and more by opting for a homegrown approach, they’ll more than likely encounter challenges, hidden costs, and limitations. In comparison to a commercial-grade, healthcare-specific platform from a vendor, build-your-own solutions fall short when it comes to domain-specific content, technical expertise, total cost of ownership, and more. Organizations that partner on a vended platform vastly improve their chances of optimizing and scaling their analytic investment over time and achieving measurable improvement.
How to Drive ROI from Your Healthcare Projects: Practical Tools, Templates, a...Health Catalyst
At a time when average hospital’s margins are stagnating, executives should be asking tough questions about the ROI of “indispensable” technologies. Will new technologies prove their worth or drive them further into the red? How do you measure and track ROI?
Clinicians need more education on financial metrics and finance people need to learn more about the clinical processes and outcomes. One of the historical problems with calculating ROI has been the fundamental culture divide between clinicians and finance.
This slide set gives some practical tools, templates (Excel), and how tos based on years of experience to quickly and effectively develop the ability to measure and communicate ROI on healthcare IT and improvement projects.
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...Health Catalyst
The enterprise data warehouse (EDW) at Intermountain Healthcare went live in 1998. The EDW at Northwestern Medicine went live in 2006. Dale Sanders was the chief architect and strategist for both. The business inspiration behind Health Catalyst was, in essence, to create the commercial availability of the technology, analytics, and data utilization skills associated with these systems at Intermountain and Northwestern. Lee Pierce assumed leadership of the Intermountain EDW in 2008. Andrew Winter assumed leadership of the Northwestern EDW in 2009, and transitioned leadership of the EDW to Shakeeb Akhter in 2016. This webinar is a fireside chat among friends and colleagues as they look back across their healthcare IT decisions to answer these questions:
What did we do right and what did we do wrong?
What advice do we have for others in this emerging era of Big Data?
What does the future of analytics and Big Data look like in healthcare?
Does it feel like you’re falling behind on the latest CMS regulatory updates? You’re not alone. The CareOptimize COVID-19 Insights webinar is designed to keep you informed of everything going on with CMS as healthcare practices continue to adjust. Along with CMS updates, this webinar goes over SBA loans and Fee-for-service Advance/Accelerated Medicare payments.
The Power and Promise of Unstructured Patient Data Healthline
Unstructured search capabilities, superior natural language processing, and healthcare ontology capabilities will help distinguish the leading products in the category (information and data-driven decision making).
As the Age of Analytics emerges in healthcare, health system executives are increasingly challenged to define a data governance strategy that maximizes the value of data to the mission of their organizations.
Adding to that challenge, the competitive nature of the data warehouse and analytics market place has resulted in significant noise from vendors and consultants alike who promise to help health systems develop their data governance strategy. Having gone on his own turbulent data governance ride as a CIO in the US Air Force and healthcare, Dale Sanders, Senior Vice President at Health Catalyst will cut through the market noise to cover the following topics:
General concepts of data governance, regardless of industry
Unique aspects of data governance in healthcare
Data governance in a “Late Binding” data warehouse
The layers and roles in data governance
The four “Closed Loops” of healthcare analytics and data governance
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...Health Catalyst
Lessons learned over 20 years. This time we focus on technology lessons learned from experience at Intermountain Healthcare, Northwestern Medicine and Cayman Islands Health Authority
A Health Catalyst Overview: Learn How a Data First Strategy Can Drive Increas...Health Catalyst
Without the pressure of a one-on-one demo, you can join a crowd of peers to ‘kick the tires’ if you will, as you listen to Jared Crapo—a sought after healthcare strategist—talk about what a data-first strategy is, and the strategic components to a data-first strategy employing a data operating system, a breakthrough engineering approach that combines the features of data warehousing, clinical data repositories, and health information exchanges in a single, common-sense technology platform that turns data into actionable assets used for all types of outcomes improvements.
Lest you worry about too much ‘pie in the sky’ strategy talk with few results to show, Sam Turman, Senior Solution Architect, will provide tangible solution demonstrations that are driving material results. Even if you aren’t in the market for Health Catalyst solutions and services, you will be able to:
Think with more clarity through your approach to overcoming the current market challenges.
Reconsider the strategy you are employing to build cross-organizational awareness and support to put a data-first plan at the center of your plan.
Define action you can take today to assess your gaps, understand your options, and accelerate your progress to drive outcomes improvements.
Join us and you won’t be disappointed. Jared is one of those types of thinkers that many pay big money to listen to and it is our fortune to have 60 minutes with him to think deeply about moving healthcare forward, one patient at a time. We hope you can join us.
Client is a California based healthcare company, they uniquely combine technology, services and analytics to produce scalable, high touch care models that enrich the patient-provider experience and reduce the cost of care.
The digital care management platform empowers people with personalized actionable data and consultations to help them achieve better health.
In this webinar, Dale Sanders will provide a pragmatic, step-by-step, and measurable roadmap for the adoption of analytics in healthcare-- a roadmap that organizations can use to plot their strategy and evaluate vendors; and that vendors can use to develop their products. Attendees will have a chance to learn about:
1) The details of his eight-level model, 2) A brief introduction to the HIMSS/IIA DELTA Model, 3) The importance of permanent organizational teams to sustain improvements from analytic investments, 4) The process of curating and maturing data governance, and 5) The coordination of a data acquisition strategy with payment and reimbursement strategies
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.
A hybrid approach to data management is emerging in healthcare as organizations recognize the value of an enterprise data warehouse in combination with a data lake.
In this SlideShare, we discuss data lakes in healthcare and we:
Provide an overview of a Hadoop-based data lake architecture and integration platform, and its application in machine learning, predictive modeling, and data discovery
Discuss several key use cases driving the adoption of data lakes for both providers and health plans
Discuss available data storage forms and the required tools for a data lake environment
Detail best practices for conducting data lake assessments and review key implementation considerations for healthcare
Deliver Data to Decision Makers: Two Important Strategies for SuccessHealth Catalyst
Surviving on thin operating margins underscores the need for all end users at a health system to make decisions based on comprehensive data sets. This data-centered approach to decision making allows team members to take the right course of action the first time and avoid making decisions based on fragmented data that exclude key pieces of information.
To promote data-driven decision making and a data-centric culture, healthcare organizations should increase data access and availability across the institution. With easy access to complete data, end users rely on the same data to make decisions, no matter where they work within the health system.
Two strategies can help organizations integrate and deliver data to end users when they need it:
Select infrastructure that fits most people’s needs.
Ask the right questions.
Link to the recorded webinar - https://youtu.be/RE6j3tF1MHA
Topics for this webinar include:
• How to integrate existing HIE data in the Health Catalyst analytics platform, DOS™ (Data Operating System)
• Gaining insights from HIE data that can drive outcome improvements
• Existing applications and tools available that can leverage HIE data
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
Introducing Healthfinch by Health Catalyst: Charlie for Refill Management: Im...Health Catalyst
Healthcare providers are overwhelmed with administrative EHR tasks that take precious time away from patient care and can lead to an unhealthy work-life balance. As a result, providers face burnout and declining productivity, impacting quality and delaying patient care.
That’s why Health Catalyst is excited to introduce its new partnership with Healthfinch. Healthfinch’s solution, Charlie for Refill Management, is the healthcare industry’s most trusted and used prescription renewal solution. Charlie for Refill Management safely and efficiently delegates renewal requests to non-provider staff, reducing the EHR administrative burden so that providers can focus on top-of-license work.
In this webinar, you’ll learn how Charlie for Refill Management provides EHR-embedded insights fueled by evidence-based protocols, allowing staff to quickly approve prescription renewal requests on behalf of providers and proactively close gaps in patient care. Specifically, learn how Charlie for Refill Management helps achieve the following:
- Saves time by eliminating time-consuming, manual chart review.
- Improves quality by implementing standardized, evidence-based protocols across an organization.
- Transforms workflows with a fully integrated solution that provides insights directly in EHR workflows.
- Identifies care gaps to provide a better, safer patient experience while also driving additional or missed revenue.
Clinical Data Repository vs. A Data Warehouse - Which Do You Need?Health Catalyst
It can be confusing to know whether or not your health system needs to add a data warehouse unless you understand how it’s different from a clinical data repository. A clinical data repository consolidates data from various clinical sources, such as an EMR, to provide a clinical view of patients. A data warehouse, in comparison, provides a single source of truth for all types of data pulled in from the many source systems across the enterprise. The data warehouse also has these benefits: a faster time to value, flexible architecture to make easy adjustments, reduction in waste and inefficiencies, reduced errors, standardized reports, decreased wait times for reports, data governance and security.
The Health Catalyst Data Operating System (DOS™): Lessons Learned and Plans ...Health Catalyst
Just over three years ago, Health Catalyst publicly announced the development of the Data Operating System (DOSTM). Conceptually, DOS goes back more than 20 years as a single platform that could support what Dale Sanders calls the “Three Missions of Data”—analytics, data-first application development, and interoperability.
“Data platforms are the next evolution of the technology stack,” Sanders says. While the Cloud made infrastructure an easy and scalable platform, modern operating systems and programming languages made software platforms scalable and easy to build. He cautions, however, “Data wrangling, especially in healthcare, is still a giant challenge.” Sanders explains that DOS is therefore an essential strategy for Health Catalyst, as well as an important new concept in the world of platforms.
“DOS and its concept is a data platform that makes analytics, app development, and interoperability easy and scalable,” Sanders says.
In this webinar, Sanders and Bryan Hinton will review the concept of a data operating system and the vision behind it. Hinton, who leads the DOS team for Health Catalyst, will reflect on lessons learned over the past three years and what he has planned for the future.
Data Science for Healthcare: What Today’s Leaders Must KnowHealth Catalyst
Healthcare leaders who understand data science can embrace the significant improvement potential of the industry’s vast data stores, including an estimated $300 billion in annual costs savings. Executives must know the value of data science to understand the urgency in investing and supporting the technology and data scientists to fully leverage data’s capabilities. Today’s data science-savvy executives will lead the healthcare transformation by enabling faster, more accurate diagnoses and more effective, lower-risk treatments.
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
The Philosophy, Psychology, and Technology of Data in HealthcareDale Sanders
Over-application of data and analytics in healthcare is alienating clinicians and, for the most part, not bending the cost-quality curves. This lecture spends 60% of the time on the softer issues, 40% on the technology.
Big Data in Healthcare Made Simple: Where It Stands Today and Where It’s GoingHealth Catalyst
Health system leaders have questions about big data: When will I need it? How should I prepare? What’s the best way to use it? It’s important to separate the hype of big data from the reality. Where big data stands in healthcare today is a far cry from where it will be in the future. Right now, the best use cases are in academic- or research-focused healthcare institutions. Most healthcare organizations are still tackling issues with their transactional databases and learning how to use those databases effectively. But soon—once the issues of expertise and security have been addressed—big data will play a huge role in care management, predictive analytics, prescriptive analytics, and genomics for everyday patients. The transition to big data will be easier if health systems adopt a late-binding approach to the data now.
Network, Technology, and Data: Missing Pieces of the Puzzle for Clinical Tria...Health Catalyst
There is a massive shortfall in the enrollment and accrual of patients for clinical trials. Identifying the “right patients for the right trials at the right time” is a growing concern for providers, pharmaceutical companies, and clinical research organizations. In this webinar, we will discuss the evolution of clinical trials, including how to break barriers to enable successful clinical research as a care option, how clinical research impacts patient satisfaction and revenue, and more.
Finding the perfect data governance environment is an elusive target. It’s important to govern to the least extent necessary in order to achieve the greatest common good. With the three data governance cultures, authoritarian, tribal, and democratic, the latter is best for a balanced, productive governance strategy.
The Triple Aim of data governance is: 1) ensuring data quality, 2) building data literacy, and 3) maximizing data exploitation for the organization’s benefit. The overall strategy should be guided by these three principles under the guidance of the data governance committee.
Data governance committees need to be sponsored at the executive board and leadership level, with supporting roles defined for data stewards, data architects, database and systems administrators, and data analysts. Data governance committees need to avoid the most common failure modes: wandering, technical overkill, political infighting, and bureaucratic red tape.
Healthcare organizations that are undergoing analytics adoption will also go through six phases of data governance including: 1) establishing the tone for becoming a data-driven organization, 2) providing access to data, 3) establishing data stewards, 4) establishing a data quality program, 5) exploiting data for the benefit of the organization, 6) the strategic acquisition of data to benefit the organization.
As U.S. healthcare moves into its next stage of evolution, the organizations that will survive and thrive will be those who most effectively acquire, analyze, and utilize their data to its fullest extent. Such is the mission of data governance.
Revenue opportunities in the management of healthcare data delugeShahid Shah
Healthcare data is hard to deal with and getting even harder and more expensive. In this presentation, Shahid Shah covers why:
* Healthcare data is going from hard to nearly impossible to manage.
* Applications come and go, data lives forever.
* Data integration is notoriously difficult, even in the best of circumstances, and requires sophisticated tools and attention to detail.
And, then talks about how new techniques are needed to store and manage healthcare data.
A Health Catalyst Overview: Learn How a Data First Strategy Can Drive Increas...Health Catalyst
Without the pressure of a one-on-one demo, you can join a crowd of peers to ‘kick the tires’ if you will, as you listen to Jared Crapo—a sought after healthcare strategist—talk about what a data-first strategy is, and the strategic components to a data-first strategy employing a data operating system, a breakthrough engineering approach that combines the features of data warehousing, clinical data repositories, and health information exchanges in a single, common-sense technology platform that turns data into actionable assets used for all types of outcomes improvements.
Lest you worry about too much ‘pie in the sky’ strategy talk with few results to show, Sam Turman, Senior Solution Architect, will provide tangible solution demonstrations that are driving material results. Even if you aren’t in the market for Health Catalyst solutions and services, you will be able to:
Think with more clarity through your approach to overcoming the current market challenges.
Reconsider the strategy you are employing to build cross-organizational awareness and support to put a data-first plan at the center of your plan.
Define action you can take today to assess your gaps, understand your options, and accelerate your progress to drive outcomes improvements.
Join us and you won’t be disappointed. Jared is one of those types of thinkers that many pay big money to listen to and it is our fortune to have 60 minutes with him to think deeply about moving healthcare forward, one patient at a time. We hope you can join us.
Client is a California based healthcare company, they uniquely combine technology, services and analytics to produce scalable, high touch care models that enrich the patient-provider experience and reduce the cost of care.
The digital care management platform empowers people with personalized actionable data and consultations to help them achieve better health.
In this webinar, Dale Sanders will provide a pragmatic, step-by-step, and measurable roadmap for the adoption of analytics in healthcare-- a roadmap that organizations can use to plot their strategy and evaluate vendors; and that vendors can use to develop their products. Attendees will have a chance to learn about:
1) The details of his eight-level model, 2) A brief introduction to the HIMSS/IIA DELTA Model, 3) The importance of permanent organizational teams to sustain improvements from analytic investments, 4) The process of curating and maturing data governance, and 5) The coordination of a data acquisition strategy with payment and reimbursement strategies
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.
A hybrid approach to data management is emerging in healthcare as organizations recognize the value of an enterprise data warehouse in combination with a data lake.
In this SlideShare, we discuss data lakes in healthcare and we:
Provide an overview of a Hadoop-based data lake architecture and integration platform, and its application in machine learning, predictive modeling, and data discovery
Discuss several key use cases driving the adoption of data lakes for both providers and health plans
Discuss available data storage forms and the required tools for a data lake environment
Detail best practices for conducting data lake assessments and review key implementation considerations for healthcare
Deliver Data to Decision Makers: Two Important Strategies for SuccessHealth Catalyst
Surviving on thin operating margins underscores the need for all end users at a health system to make decisions based on comprehensive data sets. This data-centered approach to decision making allows team members to take the right course of action the first time and avoid making decisions based on fragmented data that exclude key pieces of information.
To promote data-driven decision making and a data-centric culture, healthcare organizations should increase data access and availability across the institution. With easy access to complete data, end users rely on the same data to make decisions, no matter where they work within the health system.
Two strategies can help organizations integrate and deliver data to end users when they need it:
Select infrastructure that fits most people’s needs.
Ask the right questions.
Link to the recorded webinar - https://youtu.be/RE6j3tF1MHA
Topics for this webinar include:
• How to integrate existing HIE data in the Health Catalyst analytics platform, DOS™ (Data Operating System)
• Gaining insights from HIE data that can drive outcome improvements
• Existing applications and tools available that can leverage HIE data
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
Introducing Healthfinch by Health Catalyst: Charlie for Refill Management: Im...Health Catalyst
Healthcare providers are overwhelmed with administrative EHR tasks that take precious time away from patient care and can lead to an unhealthy work-life balance. As a result, providers face burnout and declining productivity, impacting quality and delaying patient care.
That’s why Health Catalyst is excited to introduce its new partnership with Healthfinch. Healthfinch’s solution, Charlie for Refill Management, is the healthcare industry’s most trusted and used prescription renewal solution. Charlie for Refill Management safely and efficiently delegates renewal requests to non-provider staff, reducing the EHR administrative burden so that providers can focus on top-of-license work.
In this webinar, you’ll learn how Charlie for Refill Management provides EHR-embedded insights fueled by evidence-based protocols, allowing staff to quickly approve prescription renewal requests on behalf of providers and proactively close gaps in patient care. Specifically, learn how Charlie for Refill Management helps achieve the following:
- Saves time by eliminating time-consuming, manual chart review.
- Improves quality by implementing standardized, evidence-based protocols across an organization.
- Transforms workflows with a fully integrated solution that provides insights directly in EHR workflows.
- Identifies care gaps to provide a better, safer patient experience while also driving additional or missed revenue.
Clinical Data Repository vs. A Data Warehouse - Which Do You Need?Health Catalyst
It can be confusing to know whether or not your health system needs to add a data warehouse unless you understand how it’s different from a clinical data repository. A clinical data repository consolidates data from various clinical sources, such as an EMR, to provide a clinical view of patients. A data warehouse, in comparison, provides a single source of truth for all types of data pulled in from the many source systems across the enterprise. The data warehouse also has these benefits: a faster time to value, flexible architecture to make easy adjustments, reduction in waste and inefficiencies, reduced errors, standardized reports, decreased wait times for reports, data governance and security.
The Health Catalyst Data Operating System (DOS™): Lessons Learned and Plans ...Health Catalyst
Just over three years ago, Health Catalyst publicly announced the development of the Data Operating System (DOSTM). Conceptually, DOS goes back more than 20 years as a single platform that could support what Dale Sanders calls the “Three Missions of Data”—analytics, data-first application development, and interoperability.
“Data platforms are the next evolution of the technology stack,” Sanders says. While the Cloud made infrastructure an easy and scalable platform, modern operating systems and programming languages made software platforms scalable and easy to build. He cautions, however, “Data wrangling, especially in healthcare, is still a giant challenge.” Sanders explains that DOS is therefore an essential strategy for Health Catalyst, as well as an important new concept in the world of platforms.
“DOS and its concept is a data platform that makes analytics, app development, and interoperability easy and scalable,” Sanders says.
In this webinar, Sanders and Bryan Hinton will review the concept of a data operating system and the vision behind it. Hinton, who leads the DOS team for Health Catalyst, will reflect on lessons learned over the past three years and what he has planned for the future.
Data Science for Healthcare: What Today’s Leaders Must KnowHealth Catalyst
Healthcare leaders who understand data science can embrace the significant improvement potential of the industry’s vast data stores, including an estimated $300 billion in annual costs savings. Executives must know the value of data science to understand the urgency in investing and supporting the technology and data scientists to fully leverage data’s capabilities. Today’s data science-savvy executives will lead the healthcare transformation by enabling faster, more accurate diagnoses and more effective, lower-risk treatments.
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
The Philosophy, Psychology, and Technology of Data in HealthcareDale Sanders
Over-application of data and analytics in healthcare is alienating clinicians and, for the most part, not bending the cost-quality curves. This lecture spends 60% of the time on the softer issues, 40% on the technology.
Big Data in Healthcare Made Simple: Where It Stands Today and Where It’s GoingHealth Catalyst
Health system leaders have questions about big data: When will I need it? How should I prepare? What’s the best way to use it? It’s important to separate the hype of big data from the reality. Where big data stands in healthcare today is a far cry from where it will be in the future. Right now, the best use cases are in academic- or research-focused healthcare institutions. Most healthcare organizations are still tackling issues with their transactional databases and learning how to use those databases effectively. But soon—once the issues of expertise and security have been addressed—big data will play a huge role in care management, predictive analytics, prescriptive analytics, and genomics for everyday patients. The transition to big data will be easier if health systems adopt a late-binding approach to the data now.
Network, Technology, and Data: Missing Pieces of the Puzzle for Clinical Tria...Health Catalyst
There is a massive shortfall in the enrollment and accrual of patients for clinical trials. Identifying the “right patients for the right trials at the right time” is a growing concern for providers, pharmaceutical companies, and clinical research organizations. In this webinar, we will discuss the evolution of clinical trials, including how to break barriers to enable successful clinical research as a care option, how clinical research impacts patient satisfaction and revenue, and more.
Finding the perfect data governance environment is an elusive target. It’s important to govern to the least extent necessary in order to achieve the greatest common good. With the three data governance cultures, authoritarian, tribal, and democratic, the latter is best for a balanced, productive governance strategy.
The Triple Aim of data governance is: 1) ensuring data quality, 2) building data literacy, and 3) maximizing data exploitation for the organization’s benefit. The overall strategy should be guided by these three principles under the guidance of the data governance committee.
Data governance committees need to be sponsored at the executive board and leadership level, with supporting roles defined for data stewards, data architects, database and systems administrators, and data analysts. Data governance committees need to avoid the most common failure modes: wandering, technical overkill, political infighting, and bureaucratic red tape.
Healthcare organizations that are undergoing analytics adoption will also go through six phases of data governance including: 1) establishing the tone for becoming a data-driven organization, 2) providing access to data, 3) establishing data stewards, 4) establishing a data quality program, 5) exploiting data for the benefit of the organization, 6) the strategic acquisition of data to benefit the organization.
As U.S. healthcare moves into its next stage of evolution, the organizations that will survive and thrive will be those who most effectively acquire, analyze, and utilize their data to its fullest extent. Such is the mission of data governance.
Revenue opportunities in the management of healthcare data delugeShahid Shah
Healthcare data is hard to deal with and getting even harder and more expensive. In this presentation, Shahid Shah covers why:
* Healthcare data is going from hard to nearly impossible to manage.
* Applications come and go, data lives forever.
* Data integration is notoriously difficult, even in the best of circumstances, and requires sophisticated tools and attention to detail.
And, then talks about how new techniques are needed to store and manage healthcare data.
Big Data - it's the big buzz. But is it dead on arrival?
In this presentation Daragh O Brien looks at the history of information management, the challenges of data quality and governance, and the implications for big data...
Charities and other not-for-profit businesses tackle everyday business issues differently, which impacts on how big a difference they can make with the funds they have. We identified eight common issues our NFP customers faced, and examples of how they overcome it by using operational intelligence.
Webinar #2 - Transforming Challenges into Opportunities for Credit UnionsDenodo
Watch full webinar here: https://buff.ly/3vhzqL5
Join our exclusive webinar series designed to empower credit unions with transformative insights into the untapped potential of data. Explore how data can be a strategic asset, enabling credit unions to overcome challenges and foster substantial growth.
This webinar will delve into how data can serve as a catalyst for addressing key challenges faced by credit unions, propelling them towards a future of enhanced efficiency and growth.
Big Data Tools PowerPoint Presentation SlidesSlideTeam
Enhance your audiences knowledge with this well researched complete deck. Showcase all the important features of the deck with perfect visuals. This deck comprises of total of twenty slides with each slide explained in detail. Each template comprises of professional diagrams and layouts. Our professional PowerPoint experts have also included icons, graphs and charts for your convenience. All you have to do is DOWNLOAD the deck. Make changes as per the requirement. Yes, these PPT slides are completely customizable. Edit the colour, text and font size. Add or delete the content from the slide. And leave your audience awestruck with the professionally designed Big Data Tools PowerPoint Presentation Slides complete deck. http://bit.ly/39AwSro
Keeping the Pulse of Your Data: Why You Need Data Observability to Improve D...Precisely
With the explosive growth of DataOps to drive faster and more confident business decisions, proactively understanding the quality and health of your data is more important than ever. Data observability is an emerging discipline within data quality used to expose anomalies in data by continuously monitoring and testing data using artificial intelligence and machine learning to trigger alerts when issues are discovered.
Join Julie Skeen and Shalaish Koul from Precisely, to learn how data observability can be used as part of a DataOps strategy to improve data quality and reliability and to prevent data issues from wreaking havoc on your analytics and ensure that your organization can confidently rely on the data used for advanced analytics and business intelligence.
Topics you will hear addressed in this webinar:
• Data observability – what is it and how it can complement your data quality strategy
• Why now is the time to incorporate data observability into your DataOps strategy
• How data observability helps prevent data issues from impacting downstream analytics
• How integrated data catalog capabilities allow you to understand the context of alerts.
• Examples of how data observability can be used to prevent real-world issues
Telecommunications Challenges and Opportunities in a Changing WorldPrecisely
Our world has changed - the way we work, shop, travel and spend our leisure time has dramatically changed in 2020. More people are working from home, less people are travelling, people are shopping online more and using streaming services more than ever. Consumers are looking for better deals. This has a big impact on the telecommunications network.
Hear from a panel of experts from across the Asia Pacific region on the impacts of COVID-19 on the telecommunications industry and how using location intelligence and data can help address the challenges and opportunities arising from the global pandemic.
Unprecedented Patient-Visit Care Continuity: Introducing Health Catalyst Embe...Health Catalyst
Gaps in patient care contribute to declining health for preventable conditions and cost health systems millions of precious healthcare dollars. Furthermore, COVID-19-induced delays to standard preventive care and routine screenings have exacerbated gaps in patient care. Now, as organizations play catch up to understand patients’ current health status, they can’t afford to waste limited resources on inefficient care processes and guesswork.
Health Catalyst Embedded Care GapsTM is a fully EMR-embedded patient-visit solution combined with a world-class rules engine. Care Gaps increases revenue by performing more needed procedures, decreases costs by streamlining visits, and improves quality by improving adherence capacity. With Embedded Care Gaps, healthcare organizations can easily integrate into a system’s EHR, close gaps in patient care, and maximize every patient’s visit.
Join Chris Tyne, Senior Vice President of Product Development, and TJ Nicolaides, Director of Product Management, to learn how Care Gaps can deliver actionable insights directly into your EHR workflow, empower your clinicians to close patient care gaps in real time, and ultimately deliver better, more cost-effective care.
What You’ll Learn About Embedded Care Gaps:
• Seamless and actionable care gap information. Care gap information is embedded directly into the EMR with regulatory measures (MIPS, HEDIS, and eCQMs).
• The right insight, for the right person, at the right time. A proactive and automated way to notify clinicians to give the best care at the right time.
• Easier and less costly. Better user experience than EMR-based tools and less costly than staffing EMR tool development.
• Reduced time demands and physician administrative workload. Empowers physicians to provide better care before, during, and after the patient visit.
• Improved patient confidence in the provider team. The patient gets higher quality of care and appreciates a more efficient and well-planned visit.
"Disruptive" Technology in Healthcare Implications for the Workforce & HR Pro...Cornerstone OnDemand
Electronic Medical Records, Meaningful Use, remote patient monitoring, and healthcare apps galore, just to name a few. The industry has recently seen a tremendous rise in new technologies that are changing the way healthcare is delivered today. These advancements have led to new standards of care but have also had a significant impact to the knowledge and skill-sets needed for healthcare staff to remain successful and deliver quality care.
However, rolling out new technology initiatives across organizations often come with their own set of challenges – possibly leading to a totally different type of “disruption”. Learn strategies for how your organization can minimize “growing pains” and realize the benefits of these new healthcare technologies sooner.
Join Elizabeth Robledo, Talent Management System Program Manager at Legacy Health and Rehan Mirza, Product & Verticals Marketing Manager at Cornerstone OnDemand as they discuss:
-Big health tech trends of 2016
-Impacts of new technology on the modern healthcare workforce
-Strategies for implementing new technology at your organization
Defining and Applying Data Governance in Today’s Business EnvironmentCaserta
Caserta Concepts President Joe Caserta featured at Data Governance Winter 2014 Conference with a session on the basic and necessary steps needed for data quality and data governance success
For more information on the event and presentation: http://ow.ly/G3N9N
For more information on the services and solutions offered by Caserta Concepts, visit http://casertaconcepts.com/.
How to Run Analytics for More Actionable, Timely Insights: A Healthcare Data ...Health Catalyst
Healthcare organizations increasingly understand the value of data quality, but many lack a systematic process for establishing and maintaining that quality. However, as COVID-19 response and recovery further underscores the need for timely, actionable data, organizations must take a more proactive approach to data quality.
A structured process engages technical and subject matter expertise to define, evaluate, and monitor data quality throughout the pipeline. Health systems can follow a simple, four-level framework to measure and monitor data quality, ensuring that data is fit to drive quality data-informed decisions:
Think of data as a product.
Address structural data quality first.
Define content level data quality with subject matter experts.
Create a coalition for multidisciplinary support.
2022 and Beyond: Navigating the Road Ahead in Healthcare: Don’t Worry, It Won...Health Catalyst
With 2021 coming to a close, it’s time to get ready for 2022. Join Stephen Grossbart, PhD, and Bobbi Brown, MBA, as they tackle the challenges of what’s next for healthcare in the new year and why data and analytics are foundational to your success. Dr. Grossbart and Bobbi will review the trends and policies most impactful to the industry and offer actionable, long-range insights to help organizations navigate successfully from 2022 to 2030.
Major topics include the following:
• Health equity.
• Care delivery.
• Patient safety.
• Ongoing impact of COVID-19.
• Staffing challenges.
• Payment and payers.
Moving Data Science from an Event to A Program: Considerations in Creating Su...Domino Data Lab
The exponential growth of Big Data and Analytics has outpaced the ability of organizations to govern their data appropriately. The ability to reuse the work done by data scientists work is becoming an economic necessity. The mix of data sources is changing from tradition transactional and ERP systems to include a mix of structured, semi-structured and unstructured data. Data Governance needs to adapt to these changes. This session discusses these data changes and proposed how to adapt current data governance processes. These include, how the concept of a stakeholder has changed and the need for expansion of communications and content management. We look at need to consolidate data from disparate systems and how it governed. Lastly we will investigate how context is emerging as an important factor in governance and how it can be leveraged to provide for accurate, reliable data reuse.
Internal auditors regularly access organization information for audit purposes. Many organizations now maintain computerized data warehouses containing useful management and financial information. Audit professionals therefore need to understand both the concepts of data warehousing as well as data mining techniques.
Data warehousing is a process for assembling and managing data from various sources for the purpose of gaining a single, detailed view of part or all of a business.
Data mining is the use of automated tools to explore and analyze large amounts of data stored in those data warehouses.
Print reports represent a valuable source of unstructured data which can be useful for internal auditors. Using print reports for data mining will be the main area covered in this Webinar.
Objectives
1. Identify the difference between data analysis and data mining Understand the importance between structured and unstructured data
2. Learn tips and best practices for data mining print reports
3. Understand how excel and IDEA handle importing different PDF formats
4. How to use templates to make future imports a one button task
Similar to The Future of Data: High-Value Data is the Next Big Thing (20)
Empowering ACOs: Leveraging Quality Management Tools for MIPS and BeyondHealth Catalyst
Join us as we delve into the crucial realm of quality reporting for MSSP (Medicare Shared Savings Program) Accountable Care Organizations (ACOs).
In this session, we will explore how a robust quality management solution can empower your organization to meet regulatory requirements and improve processes for MIPS reporting and internal quality programs. Learn how our MeasureAble application enables compliance and fosters continuous improvement.
Unlock the Secrets to Optimizing Ambulatory Operations Efficiency and Change ...Health Catalyst
Today’s healthcare leaders are seeking technology solutions to optimize efficiencies and improve patient care. However, without effective change management and strategies in place, healthcare leaders struggle to strategically improve patient flow, space, to strategically improve patient flow, space, and schedule management, and implement daily huddles. The role of technology in supporting operational efficiency and change management initiatives is inevitable.
During this webinar, attendees will learn how to optimize Ambulatory Operational Efficiencies and Change Management. Attendees will also learn about the importance of visual management boards in enhancing clinic performance and insights into effective change management approaches.
Patient expectations are rising, and organizations are continuously being asked to do more with less.
Additionally, the convergence of several significant emerging market and policy trends, economic uncertainty, labor force shortages, and the end of the COVID-19 public health emergency has created a unique set of challenges for healthcare organizations.
Attend this timely webinar to learn about new trends and their impact on key healthcare issues, such as patient engagement, migration to value-based care, analytics adoption, the use of alternative care sites, and data governance and management challenges.
During this webinar, we will discuss the complexities of AI, trends, and platforms in the industry. Dive deep into understanding the true essence of AI, exploring its potential, real-world use cases, and common misconceptions. Gain valuable insights into the latest technology trends impacting healthcare and discover strategies for maximizing ROI in your technology investments.
Explore the profound impact of data literacy on healthcare organizations and how it shapes the utilization of data and technology for transformative outcomes. Understand the top technology priorities for healthcare organizations and learn how to navigate the digital landscape effectively. Furthermore, simplify industry jargon by defining common data elements, fostering clearer communication and collaboration across stakeholders.
Finally, uncover the transformative potentials of platforms in healthcare and how they can revolutionize scalability, interoperability, and innovation within your organization. Don't miss this opportunity to gain invaluable insights from industry experts and stay ahead in the ever-evolving healthcare landscape. Reserve your spot now for an enlightening journey into the future of healthcare technology!
Three Keys to a Successful Margin: Charges, Costs, and LaborHealth Catalyst
How can cost management and complete charge capture protect and enhance the margin?
In this webinar, we will look at 2024 margin pressures likely to impact your organization’s financial resiliency. This presentation will also share how organizations can move from Fee-for-Service to Value; bringing Cost to the forefront.
2024 CPT® Updates (Professional Services Focused) - Part 3Health Catalyst
Each year the CPT code set undergoes significant changes. Physicians and their office staff need to be aware of the changes in order to ensure a smooth transition into 2024. Join us for a discussion of the new, deleted and revised CPT codes and associated guidelines for 2024. This presentation will focus on the changes to the CPT dataset and the associated work RVU value changes that impact professional service reporting.
During this complimentary webinar, we will empower you to correctly apply the new and revised codes and discuss the rationale behind this year’s changes. You will leave with an understanding of the financial implications of the changes on your practice.
2024 CPT® Code Updates (HIM Focused) - Part 2Health Catalyst
Each year the CPT code set and the HCPCS code set undergo significant changes, and your coding staff needs to be aware of the changes in order to ensure a smooth transition into 2024. Join us for a discussion of the new, deleted and revised CPT codes and associated guidelines for 2024. This is part two in a three-part series.
During these complimentary webinars, we will empower you to correctly apply the new and revised codes and discuss the rationale behind this year’s changes. This presentation will be geared towards hospital staff with a focus on the surgical section of the CPT book in addition to surgical Category III codes.
2024 CPT® Code Updates (CDM Focused) - Part 1Health Catalyst
Each year the CPT and the HCPCS code sets undergo significant changes, and your staff needs to be aware of the changes in order to ensure a smooth transition into 2024. Join us for a discussion of the new, deleted, and revised CPT codes and associated guidelines for 2024. This is part one in a three-part series, with a CDM focus.
During these complimentary webinars, we will empower you to correctly apply the new and revised codes and discuss the rationale behind this year’s changes. This presentation will be geared towards hospital staff with a focus on the non-surgical sections of the CPT book.
What’s Next for Hospital Price Transparency in 2024 and BeyondHealth Catalyst
The Centers for Medicare & Medicaid Services (CMS) published updates to the hospital price transparency requirements in the CY 2024 Outpatient Prospective Payment System (OPPS) Final Rule. The updates will be phased in over the next 14 months and include several significant changes including the use of a CMS-mandated template, a requirement for an affirmation statement from the hospital, and several new data elements. Join us to discover what changes are scheduled for implementation in 2024 and 2025 and how they’ll impact your facility.
During this complimentary 60-minute webinar, we’ll analyze the key provisions of the Price Transparency regulations and provide insights to help you prepare for the upcoming changes.
Automated Patient Reported Outcomes (PROs) for Hip & Knee ReplacementHealth Catalyst
What was once voluntary reporting will soon be made mandatory with penalties.
On July 1, 2024, all health systems will be required to collect Patient Reported Outcome Measures (PROM) as part of the Centers for Medicare & Medicaid Services (CMS) regulation for the following measures:
Hospital-Level, Risk Standardized Patient-Reported Outcomes Performance Measure (PRO-PM) Following Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA)
Hospital-Level Risk-Standardized Complication Rate (RSCR) Following Elective Primary THA/TKA
Are you equipped to handle these new requirements?
Mandatory data collection begins April 1, 2024, and failure to submit timely data can result in a 25 percent reduction in payments by Medicare.
Attend this webinar to learn how mobile engagement can empower your organization to meet this requirement.
2024 Medicare Physician Fee Schedule (MPFS) Final Rule UpdatesHealth Catalyst
According to the Centers for Medicare & Medicaid Services (CMS), the calendar year (CY) 2024 MPFS final rule was created to advance health equity and improve access to affordable healthcare. This webinar will cover the major policy updates of the MPFS final rule including updates to the telehealth services policy and remote monitoring services and enrollment of MFTs and MHCs as Medicare providers. The conversation will also cover policy changes on split (or shared) evaluation and management (E/M) visits, and the Appropriate Use Criteria (AUC) for Advanced Diagnostic Imaging.
What's Next for OPPS: A Look at the 2024 Final RuleHealth Catalyst
During this webinar, we’ll analyze the key provisions of the OPPS final rule and identify the significant changes for the coming year to help prepare your staff for compliance with the 2024 Medicare outpatient billing guidelines.
Insight into the 2024 ICD-10 PCS Updates - Part 2Health Catalyst
Prepare for mandatory ICD-10 PCS diagnosis code updates, which take effect on October 1, 2023. By attending this 60-minute educational session, medical coders and healthcare professionals will gain a comprehensive understanding of the changes to the 2024 ICD-10 procedure codes and their guidelines, enabling accurate and compliant coding for optimal billing and reimbursement.
Vitalware Insight Into the 2024 ICD10 CM Updates.pdfHealth Catalyst
Prepare for mandatory ICD-10 CM diagnosis code updates, which take effect on October 1, 2023. By attending this 60-minute educational session, medical coders and healthcare professionals will gain a comprehensive understanding of the changes to the 2024 ICD-10 diagnosis codes and their guidelines, along with major complication or comorbidity (MCC), complication or comorbidity (CC), and Medicare Severity Diagnosis Related Groups (MS-DRGs) classification changes. With this information, professionals can ensure accurate and compliant diagnosis coding for optimal billing and reimbursement.
Driving Value: Boosting Clinical Registry Value Using ARMUS SolutionsHealth Catalyst
Many hospitals today face a perfect storm of operational and financial challenges. With increasing competition from outpatient facilities and rising care costs negatively impacting budgets, now is the time to boost your clinical registry’s value. However, collecting and analyzing data can be time-consuming and costly without the right tools. During this webinar, we will share insights and best practices for increasing the value of registry participation and how it’s possible to reduce costs while improving outcomes using the ARMUS Product Suite.
Tech-Enabled Managed Services: Not Your Average OutsourcingHealth Catalyst
During this webinar you'll learn the following:
The importance of optimizing performance, reducing labor costs and sourcing talent given current market challenges.
Highlighting the need for a balanced approach to cost reduction.
How to reap the benefits of outsourcing (cost cutting, expertise, etc) while protecting yourself from the collateral damage that often comes with them.
This webinar will provide an in-depth review of the CPT/HCPCS code set changes that will be effective on July 1, 2023. The review will include additions and deletions to the CPT/HCPCS code set, revisions of code descriptors, payment changes, and rationale behind the changes.
How Managing Chronic Conditions Is Streamlined with Digital TechnologyHealth Catalyst
Chronic conditions across the United States are prevalent and continue to rise. Managing one or more chronic diseases can be very challenging for patients who may be overwhelmed or confused about their care plan and may not have access to the resources they need. At the same time, care teams are overburdened, making it difficult to provide the support these patients require to stay as healthy as possible. A new approach to chronic condition management leverages technology to enable organizations to scale high-quality care, identify gaps in care, provide personalized support, and monitor patients on an ongoing basis. Such streamlined management will result in better outcomes, reduced costs, and more satisfied patients.
COVID-19: After the Public Health Emergency EndsHealth Catalyst
In this fast-paced webinar, we will discuss the impact of the end of the public health emergency (PHE), including upcoming changes to the different flexibilities allowed during the PHE and the timeline for when these flexibilities will end. We’ll also cover coding changes and reimbursement updates.
Automated Medication Compliance Tools for the Provider and PatientHealth Catalyst
When it comes to sustaining patient health outcomes, compliance and adherence to medication regimens are critically important, especially as providers manage patients with complex care needs and multiple medications. But, with provider burnout and staffing shortages at an all-time high, an efficient solution is critical. The use of automated medication management workflows to decrease provider burnout, while improving both medication compliance and patient engagement, is the way forward.
Trauma Outpatient Center is a comprehensive facility dedicated to addressing mental health challenges and providing medication-assisted treatment. We offer a diverse range of services aimed at assisting individuals in overcoming addiction, mental health disorders, and related obstacles. Our team consists of seasoned professionals who are both experienced and compassionate, committed to delivering the highest standard of care to our clients. By utilizing evidence-based treatment methods, we strive to help our clients achieve their goals and lead healthier, more fulfilling lives.
Our mission is to provide a safe and supportive environment where our clients can receive the highest quality of care. We are dedicated to assisting our clients in reaching their objectives and improving their overall well-being. We prioritize our clients' needs and individualize treatment plans to ensure they receive tailored care. Our approach is rooted in evidence-based practices proven effective in treating addiction and mental health disorders.
TEST BANK For Accounting Information Systems, 3rd Edition by Vernon Richardso...rightmanforbloodline
TEST BANK For Accounting Information Systems, 3rd Edition by Vernon Richardson, Verified Chapters 1 - 18, Complete Newest Version
TEST BANK For Accounting Information Systems, 3rd Edition by Vernon Richardson, Verified Chapters 1 - 18, Complete Newest Version
TEST BANK For Accounting Information Systems, 3rd Edition by Vernon Richardson, Verified Chapters 1 - 18, Complete Newest Version
DECODING THE RISKS - ALCOHOL, TOBACCO & DRUGS.pdfDr Rachana Gujar
Introduction: Substance use education is crucial due to its prevalence and societal impact.
Alcohol Use: Immediate and long-term risks include impaired judgment, health issues, and social consequences.
Tobacco Use: Immediate effects include increased heart rate, while long-term risks encompass cancer and heart disease.
Drug Use: Risks vary depending on the drug type, including health and psychological implications.
Prevention Strategies: Education, healthy coping mechanisms, community support, and policies are vital in preventing substance use.
Harm Reduction Strategies: Safe use practices, medication-assisted treatment, and naloxone availability aim to reduce harm.
Seeking Help for Addiction: Recognizing signs, available treatments, support systems, and resources are essential for recovery.
Personal Stories: Real stories of recovery emphasize hope and resilience.
Interactive Q&A: Engage the audience and encourage discussion.
Conclusion: Recap key points and emphasize the importance of awareness, prevention, and seeking help.
Resources: Provide contact information and links for further support.
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This document is designed as an introductory to medical students,nursing students,midwives or other healthcare trainees to improve their understanding about how health system in Sri Lanka cares children health.
Veterinary Diagnostics Market PPT 2024: Size, Growth, Demand and Forecast til...IMARC Group
The global veterinary diagnostics market size reached US$ 6.6 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 12.6 Billion by 2032, exhibiting a growth rate (CAGR) of 7.3% during 2024-2032.
More Info:- https://www.imarcgroup.com/veterinary-diagnostics-market
5. Just In Time Is No Longer Good Enough
Access to the right data at the right time is an issue for healthcare. Over the last eighteen months
Covid-19 has increased visibility to the issue of high-value data for decision making.
• Data acquisition takes too long
• A lack of common definitions makes sharing insights a challenge
• Integrating data is a challenge outside of a common data model
• Poor data quality impacts the readiness of data
The data challenges are not limited to the response to Covid-19, and are surfaced in several other
use cases
• Population health and the shift from fee-for-service to value-based care
• Moving from inpatient focused analytics to the inclusion of outpatient insights
• Increasing merger and acquisition activity in the industry
6. Improve Data Acquisition
Static data provides some reporting value, but to unlock high-value data it needs to be
readily available .
• Changing care models necessitating a variety of data sources
• Growing security concerns from granting access across systems
• Complex reporting needs bogging down a system
• Integrating data through report creation creating redundant work
6
Static data to fast acquisition
7. Breaking Down Data Silos
Siloed data that has been collocated in a single system provides some insight, but to unlock
high-value data it needs to be integrated
• Limited view of the patient or member through a single system
• A single patient may come across as multiple patients when viewing siloed systems
• Layering in labor, revenue cycle, supply chain data, etc. can provide additional value
• A lack of a common data model can make report creation a challenge across similar
source systems
7
Siloed data to integrated data
8. Improve User Trust In Data
Data that has been collocated into a single system and integrated can provide a great
starting point, but to unlock high-value data you need to ensure the overall quality
• Data that is not fit for purpose provides little value
• Generated reports, insights, and metrics will get little traction without trust in the
underlying data
• Transparency into the transformation and quality process is a must to promote trust
8
Untrusted data to a single source of truth
14. Our Product Strategy
14
Market-leading innovation in healthcare data and analytics
In Our Data & Analytics Platform
• A modern, enterprise-wide platform is foundational to enable data and analytics success
• The market is recognizing this with multiple platform models
• We believe we have the winning model
• Open – supports the broad variety of standard and custom use cases (data, analytics, applications)
• Modern, performant, scalable – supports high-growth, high-value data, and analytics needs
• Healthcare-specific – supports the complexities of healthcare
• Trusted – confidence demonstrated in over 270 case studies
In Our Applications
• Our applications will address the most important revenue, cost, quality use cases
• Our applications will lead by integrating the best data and analytics
• Application success will be correlated to the strength of the underlying data and analytics
healthcare data and analytics
15. • The average hospital has affiliated
provides using 16 different EHR vendors
• The average health system has affiliated
provides using 18 different EHR vendors
15
Sullivan, Tom. “Why EHR data interoperability is such a mess in 3 charts.” healthcareitnews.com, HIMSS, 05/16/2018,
https://www.healthcareitnews.com/news/why-ehr-data-interoperability-such-mess-3-charts
Data Acquisition
19. FHIR and Interoperability Standards
Expanded DOS Marts provide the foundation for true analytic and transactional interoperability
of data via an expanded data model and deep commitment to scalable terminology normalization
• First phase supports CPCDS regulations that go into place July 1
• The next phase of DOS FHIR enhancements will add support for USCDI elements
− Allergies and Intolerances
− Assessment and Plan of
Treatment
− Care Team Members
− Clinical Notes
− Goals
− Health Concerns
− Immunizations
− Laboratory
− Medications
− Patient Demographics
− Problems
− Procedures
− Provenance
− Smoking Status
− Unique Device Identifiers
− Vital Signs
U.S. Core Data for Interoperability (USCDI) Common Payer Consumer Data Set (CPCDS)
− Patient
− Organization
− Practitioner
− Coverage
− Pharmacy
− EOB Inpatient
− EOB Outpatient
− EOB Professional/Non-clinical
23. Standard Process: Acquisition
• Data acquisition starts at the source and ends when Health Catalyst delivers integrated,
reusable, scalable data asset
• Health Catalyst has a growing library of 350 data source connectors and data quality
checks for its healthcare data model
• Health Catalyst stood up a data specific business unit in early 2021
• Consolidated all functions of the data pipeline into a single team
• Data acquisition includes a variety of different strategies
• Direct database connections
• Flat file ingestion
• Streaming data ingestion
• HIE data ingestion
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24. Standard Process: Standardization
• Terminology standardization uses a common code set to
create standard reference content
• Applies standard sets and attributes (ICD, CPT, MS-
DRG, etc.)
• Allows for the grouping of codes (Health Catalyst
Clinical Improvement Hierarchy, Value Sets)
• Makes interoperability, standardization, and
governance easier to achieve
• Leverages publicly available and standard content
classification
• Develops data standards that create consistency in the
data set
• Health Catalyst has developed additional Terminology
tooling to aid in value set creation
• Automated terminology mapping/Map Manager
• Value Set Builder
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25. Standard Process: Integration
• The integration of data allows the blending of data from multiple sources of a similar
grain and type
• Empowers identity resolution (Master Data Management)
– Use deterministic matching to merge, cleanse, and standardize data to create a
more comprehensive view of a patient or provider
• Increases the breadth and depth of insight that can be generated
• Allows for more automated measure creation across numerous programs
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26. Standard Process: Data Quality Framework
• Data quality is key to fostering a sense of trust in your organization’s data and analytic
insights
• Missing or incorrect data can:
• Remain hidden until your team has headed in the wrong direction
• Take weeks or months to track down the source and fix
• Consume resources and delay progress
• Destroy trust in your organization’s analytic insights
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27. Standard Process: Data Quality Framework
HEALTH CATALYST leverages an adaptive library of assessments to validate and monitor data
quality; provides expert services
Data Knowledge Adaptive Assessment Library: Data quality checks that codify data knowledge, surface
hidden issues or quality changes, and avoid repeat issues.
Data Quality Deployment Pipeline: Remotely deploy the Adaptive Assessment Library
to position checks throughout each client’s data pipeline.
Monitoring Active Monitoring: Data quality monitoring results are centralized and enable Health
Catalyst teams to validate and monitor data quality and provide robust support.
Expert Services Data Quality Services: Our Data Quality team provides consulting and training on
best practices; helps define, build, and govern data quality checks; and provides custom
services.
CLIENTS can build their own data quality program in DOS
Review Data Profiles Atlas: Review standard data profiles in the Atlas Data Catalog.
Define and Organize
Data Quality Checks
SAM Designer: Define and organize custom data quality checks that output to a standard
data model, allowing results to be surfaced in Atlas and Operations Console.
Review Reporting
.
Atlas and Operations Console: Assess and monitor results of custom and standard data
quality checks over time in the Data Quality Assessment worklist.
30. Value Driven Expert Data Collections
• Expert Data Collections
• Combination of our expert healthcare data model with a suite of curated
data content, such as value sets, populations, and metrics.
• Tuned to a variety of healthcare solutions to help you build a sustainable
data management system for the future needs of healthcare.
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31. Value Driven Expert Data Collections
• Expert Data Collections
• Data management strategies to support a rapidly shifting future
• Compounded value from integrated data
• Solution to challenges of acquiring, integrating, or sharing high quality, timely data
• Need to spend less time managing data complexity and get more time to
manage data insights
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32. Health Catalyst Expert Data Collections™ Naming
Healthcare Foundations
Collection Population Health Collections
1. Source Mart ingestion
o Clinical
o Billing
o NPI registry
2. Health Catalyst EMPI
3. Terminology Mapping
o Person attributes
o Provider attributes
o Encounter attributes
4. DOS Marts Model
o Person (episode of care elements)
o Provider
o Person/Provider relationships
o Organizations and locations
o Encounter
o Diagnosis (admit & discharge)
o Procedure
o Lab results
o Medications
o Immunizations
o Allergies
o Charges
5. Core KPI data
o Length of stay
o Inpatient days
o Readmissions
o Total charges
o Total payment
o Volume metrics
6. Data Quality and Performance Optimization
• 100+ Data Quality Checks
7. Data and Model Maintenance & Updates
Stratify Collection Financials Collection Care Management Collection
1. Value Sets
o CMS Chronic Condition Warehouse
2. DOS Marts Model
o DOS Risk
o Contract Enrollment
3. Claims and Clinical Integration
4. Chronic Condition Populations
• Asthma
• Alzheimer’s Disease and Related Dementia
• Arthritis (Osteoarthritis and Rheumatoid)
• Atrial Fibrillation
• Autism Spectrum Disorders
• Cancer (Breast, Colorectal, Lung, and Prostate)
• Chronic Kidney Disease
• Chronic Obstructive Pulmonary Disease
• Coronary Artery Disease (CAD)
• Dementia; Cognitive Decline
• Depression
• Diabetes
• Hepatitis (Chronic Viral B & C)
• Heart Failure (CHF)
• HIV/AIDS
• Hyperlipidemia (High cholesterol)
• Hypertension (High blood pressure)
• Ischemic Heart Disease
• Osteoporosis
• Schizophrenia and Other Psychotic Disorders
• Stroke
• Comorbidity Population: anyone with two or
more of the chronic conditions
5. Risk Models
o LACE
o Charlson-Deyo
o Elixhauser
6. Pre-built templates
7. Data and Model Maintenance & Updates
1. Source Mart ingestion
o Payer claims
2. DOS Marts Model
o Payer claims
§ Claim header
§ Claim line
§ Claim diagnosis
§ Claim procedure
§ Member
3. Core KPI data
• Member months
• PMPM
• Readmissions
• Inpatient utilization
• ED utilization
• E/M utilization
• High-cost services/imaging
• Radiology utilization
• Lab/pathology utilization
• Post-acute care utilization
4. Benchmark data
• Touchstone data
• Third-party data
5. Data Quality and Performance Optimization
6. Data and Model Maintenance & updates
1. Source Mart Ingestion
• Care Mgt data source(s)
2. DOS Marts Model
• Care Managers
• Care Team relationships
• Care Mgt problems
• Care Mgt assessments
• Care Mgt goals
• Care Mgt programs
• Care Mgt interventions
3. Care Mgt KPI data
• Patients per care mgr
• Duration
• Enrollment days
• Number of patients enrolled
• Attrition rate
• Enrollment rate
• Dropout rate
• Graduation rate
4. Data and Model Maintenance & updates
Regulatory Quality
Collection
Ambulatory Quality Collection
1. ECQMs
• 22 certified (subset)
2. HEDIS Measures
• 40 certified (subset)
3. MIPS Measures
• 100+ (subset)
4. Data Marts Models
• DOS Measures
• Contract Enrollment
5. Data and Model Maintenance & Update
6. Tailored data services
• TBD
8. Tailored data services (applies to all)
o Core data model extensions
o Additional data models
o Additional sources
o Custom metrics
o 3rd party data integration
o 3rd
party application integration (i.e.
ACG grouper)
o Real-time data
o External updates
33. Value Driven Expert Data Collections
• Expert Data Collections Benefits
• Reusable content foundation across a diverse set of data
• Improve the ability to acquire, integrate, and share high-value data
• Provides an optimized data model
• Manage data as a strategic asset
• Significantly improve time to deliver insights
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34. Value Driven Expert Data Collections
• What is new with the DOS Mart healthcare data model
• Improve time to value
– Data products that focus on expert data collections
– Data quality framework integrated into the acquisition process
• Support for regulatory quality reporting
– Expanded ambulatory content
– Augmented intelligence for terminology mapping
• Increased data integration and scale
– Parallel loading, expanded content
– DOS Marts on the Snowflake data cloud
• Interoperability Standards
– FHIR (Cures Act)
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35. High-Value Data
• High-value data requires timely acquisition, standard applied definitions, a flexible model
to integrate, and wrapped in a robust data quality program
• To bring high-value data to Health Catalyst clients, we are bringing innovation into our
approach, organization, and data model
• New tooling, an updated engagement strategy, and targeted data acquisition strategies
will move our clients from data to high-value data
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