Payer Analytics In A Shifting Healthcare Landscape - June Presentation To Chi...Dan Wellisch
This is the June 2018 presentation to the Chicago Technology For Value-Based Healthcare https://www.meetup.com/Chicago-Technology-For-Value-Based-Healthcare-Meetup/
In today’s healthcare market, financial challenges rank as the number one issue hospitals face. To maintain a margin to support their mission, hospital CEOs must always be on the lookout for opportunities to boost revenue through improved reimbursement. In this webinar, Thibodaux Regional Medical Center’s Greg Stock, president and chief executive officer, and Mikki Fazzio, director, HIM and clinical documentation improvement, as they share how Thibodaux Regional leveraged analytics to provide actionable feedback to continuously improve the process, and how you can too.
Managing ‘discharged not final billed’ (DNFB) cases is one important way hospitals can improve financial performance by increasing collection on bills with incomplete payment due to coding or documentation gaps. Historically, Thibodaux Regional’s DNFB caseload had reached 500 cases per month, with about a third of patients discharged without a completed bill due either to missing documentation or incomplete coding. Thibodaux Regional tackled this process problem by expanding the use of analytics to measure and track every aspect of their billing services. The results were impressive and sustainable. Three years after launching its initial DNFB redesign effort, Thibodaux Regional has realized $2.4M in additional annual reimbursement and a 61% relative reduction in DNFB dollars, as well as a 6.2 reduction in AR days, resulting in significantly improved cash flow.
View this webinar to learn how to:
- Increase reimbursement levels by optimizing workflow analytics
- Ease the documentation burden on overloaded physicians with time-efficient communication
- Provide critical analytics visibility to key stakeholders
This document discusses trends in digitizing healthcare, including adopting electronic medical records and mobile health technologies. It describes investment in healthcare IT in various countries and regions, focusing on China. The opportunities of transforming healthcare through more integrated systems with better quality of care and outcomes are outlined. The document promotes using multifunction printers and analytics platforms to capture paper documents, simplify workflows, and unlock insights from structured and unstructured clinical data through searching, automated outputs, and personalized patient engagement.
Leveraging Healthcare Analytics to Reduce Heart Failure Readmission Rates Health Catalyst
Heart failure patients are adding an enormous strain to the US healthcare system. In addition, readmission rates for these diseases are adding to the burden. Healthcare analytics can play a key role. By following these 4 steps, all of which include data analytics, health systems can begin to reduce readmission rates: 1) Understand your true admission rates. 2) Establish reliable baseline measures. 3) Be aware of balance measures. 4) Establish an EDW.
POV Healthcare Payer Medical Informatics and AnalyticsFrank Wang
1) Healthcare payers are facing increasing pressures to reduce costs while improving quality of care and consumer engagement. This is driving needs for modernized claims processing, population health management, and business intelligence solutions.
2) The document discusses various healthcare informatics and analytics solutions that can help payers address these challenges, including solutions for claims processing, care management, utilization management, disease management, wellness programs, and compliance and regulatory reporting.
3) It provides examples of how analytics can be used for cost containment, care coordination, and enabling accountable care through risk stratification, predictive modeling, and outcomes measurement.
Partners’ Care Management Strategy: A 10-Year JourneyHealth Catalyst
Chronic diseases are responsible for seven out of 10 deaths each year, killing more than 1.7 million Americans annually. Additionally, 133 million Americans—approximately 45 percent of the population—have at least one chronic disease. Partners HealthCare believes that chronically ill patients with multiple medical conditions often need the most help coordinating their care, which is why this well-respected health system has spent the last 10 years perfecting an integrated care management program (iCMP).
Key elements of the iCMP at Partners include access to specialized resources (e.g., mental health, palliative care), involvement through the continuum of care, patient self-management, IT-enabled systems to improve care coordination, data-driven analytics to support strategic decision making, a payer-blind approach, and ongoing support and training for its teams and staff.
Attendees will learn how to:
Identify the essential elements of an effective care management program for chronically ill patients
Recognize how care management plays a key role in an effective population health management strategy
Determine how to use information to identify and effectively manage complex, chronically ill patients
Despite massive investment in both people and technology, health systems are still struggling to maximize the value of their greatest asset: their data. Delivering high-quality, valuable insight from data and pushing those insights to the frontline healthcare professionals remains challenging and expensive. According to a recent survey conducted by HealthLeaders Media, health systems are hiring more analytics staff than almost any other role in health care. We know there’s an alternative to the massive hiring of analytics staff, a better way to dramatically increase the efficiency of your existing resources and provide an ROI that grows over time. The better way is the Rapid Response Analytics Solution.
Rapid Response Analytics Solution (RRA Solution) consists of two elements: curated, modular data called DOS™ Marts and Population Builder, a powerful self-service tool that lets any type of user, from physician executive to frontline nurses and population health teams explore their data and quickly build and share populations without needing to know how to write SQL and data science code. RRA Solution increases an analytics team’s productivity by up to 10x and reduces its time to develop analytics by as much as 90 percent. Analysts can spend more time focusing on key strategic analysis and less time on repetitive tasks that can lead to inconsistent results and a backlog of requests.
Learning Objectives:
- Discover how RRA Solution allows you to take components and customize them to quickly tailor and deliver meaningful insights.
- Learn about DOS™ Marts and Population Builder and how they drive consistency and efficiency, without needing to know SQL and data science coding.
- Understand how to use RRA Solution to increase the value of your analytics team and get them operating at the top of their function.
View this webinar and learn how RRA Solution can help you achieve a 10x increase in productivity and reduce your time to develop new analytics reports by more than 90 percent.
Explains about Evolution of IT in Healthcare, how analytics can make a difference and evolution of IT in healtcare. For more information visit: http://www.transformhealth-it.org/
Payer Analytics In A Shifting Healthcare Landscape - June Presentation To Chi...Dan Wellisch
This is the June 2018 presentation to the Chicago Technology For Value-Based Healthcare https://www.meetup.com/Chicago-Technology-For-Value-Based-Healthcare-Meetup/
In today’s healthcare market, financial challenges rank as the number one issue hospitals face. To maintain a margin to support their mission, hospital CEOs must always be on the lookout for opportunities to boost revenue through improved reimbursement. In this webinar, Thibodaux Regional Medical Center’s Greg Stock, president and chief executive officer, and Mikki Fazzio, director, HIM and clinical documentation improvement, as they share how Thibodaux Regional leveraged analytics to provide actionable feedback to continuously improve the process, and how you can too.
Managing ‘discharged not final billed’ (DNFB) cases is one important way hospitals can improve financial performance by increasing collection on bills with incomplete payment due to coding or documentation gaps. Historically, Thibodaux Regional’s DNFB caseload had reached 500 cases per month, with about a third of patients discharged without a completed bill due either to missing documentation or incomplete coding. Thibodaux Regional tackled this process problem by expanding the use of analytics to measure and track every aspect of their billing services. The results were impressive and sustainable. Three years after launching its initial DNFB redesign effort, Thibodaux Regional has realized $2.4M in additional annual reimbursement and a 61% relative reduction in DNFB dollars, as well as a 6.2 reduction in AR days, resulting in significantly improved cash flow.
View this webinar to learn how to:
- Increase reimbursement levels by optimizing workflow analytics
- Ease the documentation burden on overloaded physicians with time-efficient communication
- Provide critical analytics visibility to key stakeholders
This document discusses trends in digitizing healthcare, including adopting electronic medical records and mobile health technologies. It describes investment in healthcare IT in various countries and regions, focusing on China. The opportunities of transforming healthcare through more integrated systems with better quality of care and outcomes are outlined. The document promotes using multifunction printers and analytics platforms to capture paper documents, simplify workflows, and unlock insights from structured and unstructured clinical data through searching, automated outputs, and personalized patient engagement.
Leveraging Healthcare Analytics to Reduce Heart Failure Readmission Rates Health Catalyst
Heart failure patients are adding an enormous strain to the US healthcare system. In addition, readmission rates for these diseases are adding to the burden. Healthcare analytics can play a key role. By following these 4 steps, all of which include data analytics, health systems can begin to reduce readmission rates: 1) Understand your true admission rates. 2) Establish reliable baseline measures. 3) Be aware of balance measures. 4) Establish an EDW.
POV Healthcare Payer Medical Informatics and AnalyticsFrank Wang
1) Healthcare payers are facing increasing pressures to reduce costs while improving quality of care and consumer engagement. This is driving needs for modernized claims processing, population health management, and business intelligence solutions.
2) The document discusses various healthcare informatics and analytics solutions that can help payers address these challenges, including solutions for claims processing, care management, utilization management, disease management, wellness programs, and compliance and regulatory reporting.
3) It provides examples of how analytics can be used for cost containment, care coordination, and enabling accountable care through risk stratification, predictive modeling, and outcomes measurement.
Partners’ Care Management Strategy: A 10-Year JourneyHealth Catalyst
Chronic diseases are responsible for seven out of 10 deaths each year, killing more than 1.7 million Americans annually. Additionally, 133 million Americans—approximately 45 percent of the population—have at least one chronic disease. Partners HealthCare believes that chronically ill patients with multiple medical conditions often need the most help coordinating their care, which is why this well-respected health system has spent the last 10 years perfecting an integrated care management program (iCMP).
Key elements of the iCMP at Partners include access to specialized resources (e.g., mental health, palliative care), involvement through the continuum of care, patient self-management, IT-enabled systems to improve care coordination, data-driven analytics to support strategic decision making, a payer-blind approach, and ongoing support and training for its teams and staff.
Attendees will learn how to:
Identify the essential elements of an effective care management program for chronically ill patients
Recognize how care management plays a key role in an effective population health management strategy
Determine how to use information to identify and effectively manage complex, chronically ill patients
Despite massive investment in both people and technology, health systems are still struggling to maximize the value of their greatest asset: their data. Delivering high-quality, valuable insight from data and pushing those insights to the frontline healthcare professionals remains challenging and expensive. According to a recent survey conducted by HealthLeaders Media, health systems are hiring more analytics staff than almost any other role in health care. We know there’s an alternative to the massive hiring of analytics staff, a better way to dramatically increase the efficiency of your existing resources and provide an ROI that grows over time. The better way is the Rapid Response Analytics Solution.
Rapid Response Analytics Solution (RRA Solution) consists of two elements: curated, modular data called DOS™ Marts and Population Builder, a powerful self-service tool that lets any type of user, from physician executive to frontline nurses and population health teams explore their data and quickly build and share populations without needing to know how to write SQL and data science code. RRA Solution increases an analytics team’s productivity by up to 10x and reduces its time to develop analytics by as much as 90 percent. Analysts can spend more time focusing on key strategic analysis and less time on repetitive tasks that can lead to inconsistent results and a backlog of requests.
Learning Objectives:
- Discover how RRA Solution allows you to take components and customize them to quickly tailor and deliver meaningful insights.
- Learn about DOS™ Marts and Population Builder and how they drive consistency and efficiency, without needing to know SQL and data science coding.
- Understand how to use RRA Solution to increase the value of your analytics team and get them operating at the top of their function.
View this webinar and learn how RRA Solution can help you achieve a 10x increase in productivity and reduce your time to develop new analytics reports by more than 90 percent.
Explains about Evolution of IT in Healthcare, how analytics can make a difference and evolution of IT in healtcare. For more information visit: http://www.transformhealth-it.org/
Healthcare payer medical informatics and analyticsFrank Wang
The document discusses healthcare payer needs and solutions for addressing rising costs, consumer engagement, data management, and other drivers of change. It outlines the business value of improved information management, and describes key building blocks for accountable care like EHR integration, data sharing, analytics, and outcomes reporting. Use cases are provided on stratifying members for different care interventions and reducing costs through case management of high-risk, high-cost individuals.
Care Management Part 2 - A Critical Component of Effective Population HealthHealth Catalyst
Care management plays a central role in the world of value-based reimbursements, at-risk contracts, and population health management. Such programs require high-touch and resource-intensive care as teams work to deliver on the substantial promise of delivering patient care improvements while reducing costs.
This report collects data, surveys and commentary on U.S. physicians. It includes data on supply & demand, regulatory impacts, compensation & reimbursement, outlook & satisfaction, practice environment and employment.
This document discusses applications of big data and data analytics in healthcare. It provides two case studies: 1) a rural clinically integrated network in Kansas that uses data analytics to identify at-risk patients and reduce costs, and 2) an analysis of billing data for a Department of Justice investigation. The document also outlines other healthcare data analytics projects and discusses growing demand for data analytics expertise and the potential for analytics to improve healthcare outcomes and reduce costs.
While Healthcare 1.0 was broadly defined by a focus on defensive medicine, billing, and fee-for-service, culminating in the mass adoption of EMRs, Healthcare 2.0 is a new wave focused on improving clinical efficiency, quality of care, affordability, and fee-for-value; culminating in a new age of healthcare analytics. This new age of analytics will require a new set of organizational skills and a foundational set of analytic information systems that many executives have not anticipated.
Join Dale Sanders, a 20-year healthcare CIO veteran and the industry's leading analytics expert, as he discusses his lessons learned, best practices in analytics, and what the C-level suite needs to know about this topic, now. Listen to Dale discuss 1) A step-by-step curriculum for analytic adoption and maturity in healthcare organizations, 2) the basic approach to a late-binding data warehouse, 3) pros and cons of early versus late binding, 4) the volatility in vocabulary and business rules in healthcare, 5) how to engineer your data to accommodate volatility in the future
Physicians are increasingly selling their private practices to hospitals due to rising costs and reimbursement cuts under healthcare reform. The top reasons for physicians to sell are to reduce costs and gain financial stability and security. Hospitals acquire physician practices mainly to expand services and meet community needs. While physicians sacrifice autonomy through employment, they gain benefits like reduced administrative burdens and stress. A survey found that most physicians who sold their practices to hospitals have had their expectations met under the new employment arrangements.
How to Use Text Analytics in Healthcare to Improve Outcomes: Why You Need Mor...Health Catalyst
Given the fact that up to 80 percent of clinical data is stored in unstructured text, healthcare organizations need to harness the power of text analytics. But, surprisingly, less than five percent of health systems use it due to resource limitations and the complexity of text analytics.
But given the industry’s necessity to use text analytics to create precise patient registries, enhance their understanding of high-risk patient populations, and improve outcomes, this executive report explains why systems must start using it—and explains how to get started.
Health systems can start using text analytics to improve outcomes by focusing on four key components:
Optimize text search (display, medical terminologies, and context).
Enhance context and extract values with an NLP pipeline.
Always validate the algorithm.
Focus on interoperability and integration using a Late-Binding approach.
This broad approach with position health systems for clinical and financial success.
Healthcare Analytics: Right-Brain Advice in a Left-Brain WorldHealth Catalyst
U.S. healthcare is badly missing the soft, human side of healthcare analytics, especially as it impacts clinicians. How do we fix that? This webinar explores those ideas.
You won’t hear Dale talk about SQL, inner joins, outer joins, R, Python, logistic regression, random forest, or convolutional neural networks but instead, in this webinar he talks about the principles and philosophy of analytics.
For the most part, we’ve figured out the technology of analytics. That is all left-brain thinking—analytical, logical and methodical in nature—and it is literally getting easier every day with new data technology. But, in healthcare, we’re missing the right-brain thinking—creative and artistic in nature—that has almost nothing to do with technology but has everything to do with the human side of pursuing “data driven healthcare.”
Right-brain thinking is required for the oddities and shortcomings of healthcare data, and how to manage those shortcomings in the context of delivering data to the humans who we hope will consume it. The right-brain relates to the personality characteristics of the people who are leading your analytics strategy. It relates to the leadership culture of the organization and where that culture resides on a scale of transparency, internally and externally. The right-brain relates to behavioral economics, evolutionary psychology, human decision making theories, and the fundamental factors that motivate or demotivate human behavior. The right-brain relates to concepts like experimental design and PICO—patients, interventions, comparisons, and outcomes—that, if followed, can make your analytics more truthful and believable. It has to do with the way we negotiate and structure performance-based contracts that are loaded with quality metrics that either measure things that can’t be measured accurately or may measure the wrong thing, altogether.
You see, right-brained thinking in this left-brain world of analytics relates to a bunch of things, but mostly it relates to the Golden Rule of Data. Do unto others with data as you would have them do unto you.
The Path to Shared Savings With Population Health Management ApplicationsHealth Catalyst
Eric Just, Vice President of Technology and Kathleen Merkley, Clinical Engagement Executive and Vice President at Health Catalyst, will demonstrate live several advanced applications built on a Late-Binding Catalyst data warehouse. Attendees will better understand how to:
Identify variability in care
Define accurate populations
Report on key health indicators across the continuum of care
Apply flexible models for risk stratification
Measure detailed process metrics spanning transitions of care for HF patients
Next generation health systems and Accountable Care Organizations will be paid based on an evolving model that rewards healthcare providers through ‘shared savings.’ Those savings must be achieved through systematic cost reductions while still improving quality of care. For most, this dual focus will prove to be the most critical and difficult part of realizing success.
Best Practices in Implementing Population Health Health Catalyst
To manage population health, one needs to intimately understand the anatomy of healthcare and model how healthcare is delivered, in order to systematically improve healthcare outcomes. In this webinar, Dr. Burton draws on his 26-year executive career at Intermountain, Select Health, and Health Catalyst. He emphasizes the importance of linking administrative data (e.g., billing codes) to processes of clinical care to use the 80/20 principle to prioritize care processes within each venue to focus improvement initiatives on the things that matter most. He will also discuss a Clinical Integration framework to use in driving out waste by reducing variation in the ordering of care, the efficiency with which the care that is ordered is delivered and reducing defects in care delivery to make it safer.
Measuring, Mismeasuring, and Remeasuring - Creating Meaningful Key Performanc...Dan Wellisch
Here is our September 2019 meeting presentation to the Chicago Technology For Value-Based Healthcare Group (https://www.meetup.com/Chicago-Technology-For-Value-Based-Healthcare-Meetup/) on meaningful KPIs in the hospital setting.
Catasys provides integrated treatment solutions to health plans to improve member health and lower costs. It focuses on members with behavioral health conditions who rarely seek treatment. Catasys utilizes predictive analytics, telehealth, and human engagement to deliver virtual, scalable programs. It has signed contracts with major health insurers and expects $20 million in billings in 2018 based on its existing pool of eligible members. Catasys addresses challenges around access to care, reimbursement, lack of evidence-based practices, and low treatment rates for behavioral health conditions.
The Healthcare Analytic Adoption Model outlines 8 levels of analytic maturity for healthcare organizations. Level 5 maturity involves using data-driven improvement to optimize clinical processes and outcomes. Reaching Level 5 requires a robust data governance function to achieve conditions like standardized controlled vocabularies, patient registries, and an enterprise data warehouse.
Clinical Decision Support: Driving the Last MileHealth Catalyst
Self-driving cars have become the most visible form of computer-aided decision support in society. What can we learn from these innovations—both good and bad, technically and culturally—about computer-aided decision support for clinicians? The adoption of EHRs provided a foundation; what and how do we build on that foundation to help clinicians, and patients, benefit from meaningful, precise decision support?
Scott Weingarten, MD, MPH, and Dale Sanders explore clinical decision support in a joint webinar. Dr. Weingarten is recognized throughout the U.S. and international healthcare space as a physician and for his contributions to decision support, including his role in founding Zynx and Stanson Health. Dale brings a technologist’s viewpoint to the conversation, informed by his background in computer-aided decision support in the healthcare, military, and national intelligence sectors.
During this webinar, learn more about the following topics:
-How clinical decision support can improve the quality, safety, and value of care.
-How developments in the field of artificial intelligence will impact clinical decision support.
-The conceptual framework for digitizing an industry.Tradeoffs in artificial intelligence models between data volume and algorithm complexity.
-The approach to digitization in the automobile and aerospace industries.
-Shortcomings in current healthcare data.Future aspirations and plans for further digitization of healthcare.
Getting The Most Out of Your Data Analyst - HAS Session 9Health Catalyst
Many analysts spend 90% of their time managing rather than analyzing data. How do we enable analysts to do what they were hired to do? In this session, you will learn best practices on helping your analyst focus more on analytics and less on data capture and provisioning, as well as how to create sustainable and meaningful analytics. We will show best practices and common pitfalls to avoid. This will be a fun and interactive session with many hands-on examples and exercises.
Why the Data Steward’s Role is Critical to Sustained Outcomes Improvement in ...Health Catalyst
The data steward is critical to sustained outcomes improvement, yet they tend to be underappreciated members of the healthcare analytics family. Combining the invaluable technical expertise of a data analyst with the vital clinical knowledge of an experienced caregiver, the data steward’s skills and proficiency at both positions brings value beyond measure to any outcomes improvement project. Unfortunately, all too often, their role is non-existent even though potential candidates for the job are located in multiple data sources throughout the organization. Among other responsibilities, the data steward:
Reinforces the global data governance principles.
Helps develop and refine details of local data governance practices.
Is the eyes and ears of the organization with respect to data governance and the governance committee.
Provides direction to peers regarding appropriate data definitions, usage, and access.
Anticipates local consequences of global changes
For innovative health system leaders who have specifically recognized this emerging role, the ROI of data stewards who help achieve improved outcomes is very worthwhile.
Levi Thatcher, Health Catalyst Director of Data Science and his team provide a live demonstration using healthcare.ai to implement a healthcare-specific machine learning model from data source to patient impact. Levi goes through a hands-on coding example while sharing his insights on the value of predictive analytics, the best path towards implementation, and avoiding common pitfalls. Frequently asked questions are answered during the session.
During the webinar, we will:
Describe and install healthcare.ai
Build and evaluate a machine learning model
Deploy interpretable predictions to SQL Server
Discuss the process of deploying into a live analytics environment.
If you’d like to follow along, you should download and install R and RStudio prior to the event. We look forward to you joining us!
Demystifying Text Analytics and NLP in HealthcareHealth Catalyst
Leading the discussion, we have two exceptional thinkers in this space, Mike Dow, a former CIO and current Health Catalyst product manager and software developer, and Dr. Carolyn Simpkins, Health Catalyst’s Chief Medical Informatics Officer.
They will share thoughts on the challenges of text in clinical analytics as well as demonstrate:
Why text is an important part of clinical analytics
Why a text search is not enough
How clinical text search can be refined with NLP techniques
1) The role of health care data analysts is evolving as the volume of available data grows exponentially. With zettabytes of data being generated, analysts must make sense of both structured and unstructured information.
2) Data analytics can provide insights to improve patient outcomes, lower costs, and enhance the health care experience. Examples show how visualizing data helps health systems better understand utilization and identify at-risk patients.
3) As incentives shift from fee-for-service to value-based models, health systems must transform to focus on population health. Advanced analytics and predictive modeling will be crucial to achieving the goals of better care, lower costs, and improved health.
Truven Health Analytics is a healthcare data and analytics company with over 2,300 employees and 9,000 customers worldwide. It has a large collection of healthcare data from over 1,000 data suppliers and affects healthcare benefit decisions for 1 in 3 Americans. Truven Health works with hospitals, physicians, government agencies, payers, employers, and life sciences companies to help improve healthcare through data-driven analytics and services.
Healthcare payer medical informatics and analyticsFrank Wang
The document discusses healthcare payer needs and solutions for addressing rising costs, consumer engagement, data management, and other drivers of change. It outlines the business value of improved information management, and describes key building blocks for accountable care like EHR integration, data sharing, analytics, and outcomes reporting. Use cases are provided on stratifying members for different care interventions and reducing costs through case management of high-risk, high-cost individuals.
Care Management Part 2 - A Critical Component of Effective Population HealthHealth Catalyst
Care management plays a central role in the world of value-based reimbursements, at-risk contracts, and population health management. Such programs require high-touch and resource-intensive care as teams work to deliver on the substantial promise of delivering patient care improvements while reducing costs.
This report collects data, surveys and commentary on U.S. physicians. It includes data on supply & demand, regulatory impacts, compensation & reimbursement, outlook & satisfaction, practice environment and employment.
This document discusses applications of big data and data analytics in healthcare. It provides two case studies: 1) a rural clinically integrated network in Kansas that uses data analytics to identify at-risk patients and reduce costs, and 2) an analysis of billing data for a Department of Justice investigation. The document also outlines other healthcare data analytics projects and discusses growing demand for data analytics expertise and the potential for analytics to improve healthcare outcomes and reduce costs.
While Healthcare 1.0 was broadly defined by a focus on defensive medicine, billing, and fee-for-service, culminating in the mass adoption of EMRs, Healthcare 2.0 is a new wave focused on improving clinical efficiency, quality of care, affordability, and fee-for-value; culminating in a new age of healthcare analytics. This new age of analytics will require a new set of organizational skills and a foundational set of analytic information systems that many executives have not anticipated.
Join Dale Sanders, a 20-year healthcare CIO veteran and the industry's leading analytics expert, as he discusses his lessons learned, best practices in analytics, and what the C-level suite needs to know about this topic, now. Listen to Dale discuss 1) A step-by-step curriculum for analytic adoption and maturity in healthcare organizations, 2) the basic approach to a late-binding data warehouse, 3) pros and cons of early versus late binding, 4) the volatility in vocabulary and business rules in healthcare, 5) how to engineer your data to accommodate volatility in the future
Physicians are increasingly selling their private practices to hospitals due to rising costs and reimbursement cuts under healthcare reform. The top reasons for physicians to sell are to reduce costs and gain financial stability and security. Hospitals acquire physician practices mainly to expand services and meet community needs. While physicians sacrifice autonomy through employment, they gain benefits like reduced administrative burdens and stress. A survey found that most physicians who sold their practices to hospitals have had their expectations met under the new employment arrangements.
How to Use Text Analytics in Healthcare to Improve Outcomes: Why You Need Mor...Health Catalyst
Given the fact that up to 80 percent of clinical data is stored in unstructured text, healthcare organizations need to harness the power of text analytics. But, surprisingly, less than five percent of health systems use it due to resource limitations and the complexity of text analytics.
But given the industry’s necessity to use text analytics to create precise patient registries, enhance their understanding of high-risk patient populations, and improve outcomes, this executive report explains why systems must start using it—and explains how to get started.
Health systems can start using text analytics to improve outcomes by focusing on four key components:
Optimize text search (display, medical terminologies, and context).
Enhance context and extract values with an NLP pipeline.
Always validate the algorithm.
Focus on interoperability and integration using a Late-Binding approach.
This broad approach with position health systems for clinical and financial success.
Healthcare Analytics: Right-Brain Advice in a Left-Brain WorldHealth Catalyst
U.S. healthcare is badly missing the soft, human side of healthcare analytics, especially as it impacts clinicians. How do we fix that? This webinar explores those ideas.
You won’t hear Dale talk about SQL, inner joins, outer joins, R, Python, logistic regression, random forest, or convolutional neural networks but instead, in this webinar he talks about the principles and philosophy of analytics.
For the most part, we’ve figured out the technology of analytics. That is all left-brain thinking—analytical, logical and methodical in nature—and it is literally getting easier every day with new data technology. But, in healthcare, we’re missing the right-brain thinking—creative and artistic in nature—that has almost nothing to do with technology but has everything to do with the human side of pursuing “data driven healthcare.”
Right-brain thinking is required for the oddities and shortcomings of healthcare data, and how to manage those shortcomings in the context of delivering data to the humans who we hope will consume it. The right-brain relates to the personality characteristics of the people who are leading your analytics strategy. It relates to the leadership culture of the organization and where that culture resides on a scale of transparency, internally and externally. The right-brain relates to behavioral economics, evolutionary psychology, human decision making theories, and the fundamental factors that motivate or demotivate human behavior. The right-brain relates to concepts like experimental design and PICO—patients, interventions, comparisons, and outcomes—that, if followed, can make your analytics more truthful and believable. It has to do with the way we negotiate and structure performance-based contracts that are loaded with quality metrics that either measure things that can’t be measured accurately or may measure the wrong thing, altogether.
You see, right-brained thinking in this left-brain world of analytics relates to a bunch of things, but mostly it relates to the Golden Rule of Data. Do unto others with data as you would have them do unto you.
The Path to Shared Savings With Population Health Management ApplicationsHealth Catalyst
Eric Just, Vice President of Technology and Kathleen Merkley, Clinical Engagement Executive and Vice President at Health Catalyst, will demonstrate live several advanced applications built on a Late-Binding Catalyst data warehouse. Attendees will better understand how to:
Identify variability in care
Define accurate populations
Report on key health indicators across the continuum of care
Apply flexible models for risk stratification
Measure detailed process metrics spanning transitions of care for HF patients
Next generation health systems and Accountable Care Organizations will be paid based on an evolving model that rewards healthcare providers through ‘shared savings.’ Those savings must be achieved through systematic cost reductions while still improving quality of care. For most, this dual focus will prove to be the most critical and difficult part of realizing success.
Best Practices in Implementing Population Health Health Catalyst
To manage population health, one needs to intimately understand the anatomy of healthcare and model how healthcare is delivered, in order to systematically improve healthcare outcomes. In this webinar, Dr. Burton draws on his 26-year executive career at Intermountain, Select Health, and Health Catalyst. He emphasizes the importance of linking administrative data (e.g., billing codes) to processes of clinical care to use the 80/20 principle to prioritize care processes within each venue to focus improvement initiatives on the things that matter most. He will also discuss a Clinical Integration framework to use in driving out waste by reducing variation in the ordering of care, the efficiency with which the care that is ordered is delivered and reducing defects in care delivery to make it safer.
Measuring, Mismeasuring, and Remeasuring - Creating Meaningful Key Performanc...Dan Wellisch
Here is our September 2019 meeting presentation to the Chicago Technology For Value-Based Healthcare Group (https://www.meetup.com/Chicago-Technology-For-Value-Based-Healthcare-Meetup/) on meaningful KPIs in the hospital setting.
Catasys provides integrated treatment solutions to health plans to improve member health and lower costs. It focuses on members with behavioral health conditions who rarely seek treatment. Catasys utilizes predictive analytics, telehealth, and human engagement to deliver virtual, scalable programs. It has signed contracts with major health insurers and expects $20 million in billings in 2018 based on its existing pool of eligible members. Catasys addresses challenges around access to care, reimbursement, lack of evidence-based practices, and low treatment rates for behavioral health conditions.
The Healthcare Analytic Adoption Model outlines 8 levels of analytic maturity for healthcare organizations. Level 5 maturity involves using data-driven improvement to optimize clinical processes and outcomes. Reaching Level 5 requires a robust data governance function to achieve conditions like standardized controlled vocabularies, patient registries, and an enterprise data warehouse.
Clinical Decision Support: Driving the Last MileHealth Catalyst
Self-driving cars have become the most visible form of computer-aided decision support in society. What can we learn from these innovations—both good and bad, technically and culturally—about computer-aided decision support for clinicians? The adoption of EHRs provided a foundation; what and how do we build on that foundation to help clinicians, and patients, benefit from meaningful, precise decision support?
Scott Weingarten, MD, MPH, and Dale Sanders explore clinical decision support in a joint webinar. Dr. Weingarten is recognized throughout the U.S. and international healthcare space as a physician and for his contributions to decision support, including his role in founding Zynx and Stanson Health. Dale brings a technologist’s viewpoint to the conversation, informed by his background in computer-aided decision support in the healthcare, military, and national intelligence sectors.
During this webinar, learn more about the following topics:
-How clinical decision support can improve the quality, safety, and value of care.
-How developments in the field of artificial intelligence will impact clinical decision support.
-The conceptual framework for digitizing an industry.Tradeoffs in artificial intelligence models between data volume and algorithm complexity.
-The approach to digitization in the automobile and aerospace industries.
-Shortcomings in current healthcare data.Future aspirations and plans for further digitization of healthcare.
Getting The Most Out of Your Data Analyst - HAS Session 9Health Catalyst
Many analysts spend 90% of their time managing rather than analyzing data. How do we enable analysts to do what they were hired to do? In this session, you will learn best practices on helping your analyst focus more on analytics and less on data capture and provisioning, as well as how to create sustainable and meaningful analytics. We will show best practices and common pitfalls to avoid. This will be a fun and interactive session with many hands-on examples and exercises.
Why the Data Steward’s Role is Critical to Sustained Outcomes Improvement in ...Health Catalyst
The data steward is critical to sustained outcomes improvement, yet they tend to be underappreciated members of the healthcare analytics family. Combining the invaluable technical expertise of a data analyst with the vital clinical knowledge of an experienced caregiver, the data steward’s skills and proficiency at both positions brings value beyond measure to any outcomes improvement project. Unfortunately, all too often, their role is non-existent even though potential candidates for the job are located in multiple data sources throughout the organization. Among other responsibilities, the data steward:
Reinforces the global data governance principles.
Helps develop and refine details of local data governance practices.
Is the eyes and ears of the organization with respect to data governance and the governance committee.
Provides direction to peers regarding appropriate data definitions, usage, and access.
Anticipates local consequences of global changes
For innovative health system leaders who have specifically recognized this emerging role, the ROI of data stewards who help achieve improved outcomes is very worthwhile.
Levi Thatcher, Health Catalyst Director of Data Science and his team provide a live demonstration using healthcare.ai to implement a healthcare-specific machine learning model from data source to patient impact. Levi goes through a hands-on coding example while sharing his insights on the value of predictive analytics, the best path towards implementation, and avoiding common pitfalls. Frequently asked questions are answered during the session.
During the webinar, we will:
Describe and install healthcare.ai
Build and evaluate a machine learning model
Deploy interpretable predictions to SQL Server
Discuss the process of deploying into a live analytics environment.
If you’d like to follow along, you should download and install R and RStudio prior to the event. We look forward to you joining us!
Demystifying Text Analytics and NLP in HealthcareHealth Catalyst
Leading the discussion, we have two exceptional thinkers in this space, Mike Dow, a former CIO and current Health Catalyst product manager and software developer, and Dr. Carolyn Simpkins, Health Catalyst’s Chief Medical Informatics Officer.
They will share thoughts on the challenges of text in clinical analytics as well as demonstrate:
Why text is an important part of clinical analytics
Why a text search is not enough
How clinical text search can be refined with NLP techniques
1) The role of health care data analysts is evolving as the volume of available data grows exponentially. With zettabytes of data being generated, analysts must make sense of both structured and unstructured information.
2) Data analytics can provide insights to improve patient outcomes, lower costs, and enhance the health care experience. Examples show how visualizing data helps health systems better understand utilization and identify at-risk patients.
3) As incentives shift from fee-for-service to value-based models, health systems must transform to focus on population health. Advanced analytics and predictive modeling will be crucial to achieving the goals of better care, lower costs, and improved health.
Truven Health Analytics is a healthcare data and analytics company with over 2,300 employees and 9,000 customers worldwide. It has a large collection of healthcare data from over 1,000 data suppliers and affects healthcare benefit decisions for 1 in 3 Americans. Truven Health works with hospitals, physicians, government agencies, payers, employers, and life sciences companies to help improve healthcare through data-driven analytics and services.
- The document is a corporate presentation that provides an overview of Catasys, Inc., which combines predictive analytics and evidence-based treatment programs to improve outcomes and lower costs for health plans.
- Catasys' proprietary OnTrak program identifies high-cost patients with behavioral health and medical conditions, engages them in treatment, and provides a virtual 52-week care program, achieving a 50% reduction in costs on average.
- Catasys has national agreements with several leading health plans covering over 7.5 million lives initially, with plans to expand to more states and conditions. Clinical results show reductions in ER visits and hospitalizations along with 46% lower healthcare costs for enrolled members.
Dignity Health is one of the largest health systems in the US, founded in 1986. It operates 39 hospitals and has over 56,000 employees. The presentation discusses Dignity Health's population health management strategy and supporting data and technologies. It outlines their clinical integrated networks and the key pillars of their population health approach. It also describes the challenges of accessing and integrating data from multiple sources to support population health management goals.
Medical Practices’ Survival Depends on Four Analytics StrategiesHealth Catalyst
With limited resources compared to large healthcare organizations and fewer personnel to shoulder burdens like COVID-19, medical practices must find ways to deliver better care with less. Delivering quality care, especially in a pandemic, is challenging, but analytics insight can guide effective care delivery methods, especially for smaller practices.
Comprehensive data combined with team members who can turn numbers into real-world information are essential for medical practices to ensure a strong financial, clinical, and operational future. Independent medical practices can rely on four analytics strategies to survive the uncertain healthcare market and plan for a sustainable future:
Prioritize access to up-to-date, comprehensive data sources.
Form a multidisciplinary approach to data governance.
Translate data into analytics insight.
Invest in analytics infrastructure to support rapid response.
- Catasys provides an integrated virtual healthcare program called OnTrak that uses predictive analytics and outreach to identify and enroll high-cost members with behavioral health issues.
- OnTrak provides a 52-week treatment program that combines medical, pharmacological and psychosocial treatments to reduce costs by an average of 50% for enrolled members.
- Catasys has national agreements with several leading health plans covering over 7.5 million lives and is currently enrolling participants in 18 states.
How to Accelerate Clinical Improvement Using Four Domains of Clinical AnalyticsHealth Catalyst
As health systems increase their focus on improving clinical performance, they rely on clinical analytics from different sources to identify opportunities for improvement. Although the process of aggregating, organizing, and deriving analytic insight from data is complex, Holly Rimmasch, Chief Clinical Officer, SVP, and General Manager of Clinical Quality Analytics at Health Catalyst, explains why it’s critical for health systems’ survival. She also takes a deep dive into the following four domains of clinical analytics, showing how healthcare organizations can take their data farther and scale long-lasting clinical improvements:
1. Data acquisition.
2. Clinical analytics usage.
3. Unrealized opportunities of clinical analytics.
4. Patient engagement.
The Changing Role of Healthcare Data AnalystsHealth Catalyst
The healthcare industry is undergoing a sea change, and healthcare data analysts will play a central role in this transformation. This report explores how the evolution to value-based care is changing the role of healthcare data analysts, how data analysts’ skills can best be applied to achieve value-based objectives and, finally, how Health Catalyst’s most successful health system clients are making this cultural transformation happen in the real world.
Preparing for the Future: How one ACO is Using Analytics to Drive Clinical & ...Health Catalyst
Crystal Run Healthcare — a physician-led Accountable Care Organization (ACO) and one of the first ACOs to participate in the Medicare Shared Savings Program — is experiencing the long-anticipated shift toward more value-based reimbursement.
To ensure financial stability as they assume more risk, Crystal Run is implementing a strategy focused on rapid growth and aligning physician reimbursement with favorable patient outcomes. To effectively execute on this strategy they knew they needed to become more data-driven. Webinar attendees will learn how this ACO is using advanced analytics to execute on their population management and growth strategies with a focus on continuous improvement in the following areas:
Ensuring patient care aligns with evidence based practices
Reducing inappropriate clinical variation
Enhancing operational efficiency
Analyzing data from a “single source of truth” integrated from their EMR, billing, costing, patient satisfaction and other operational systems
Making “self-service analytics” available to decision-makers to decrease time to decision
Please join Greg Spencer, MD, Chief Medical & Chief Medical Information Officer and Scott Hines, MD, Chief Quality Officer and Medical Specialties Medical Director, Crystal Run, as they discuss how advanced analytics is helping position the ACO for continued success in an increasingly value-based reimbursement environment.
The document discusses trends in healthcare data and analytics. It covers four main topics: 1) industry dynamics and business priorities in healthcare are driving a focus on value-based care and lower costs while engaging patients, 2) healthcare is experiencing a big data explosion from sources like EMRs and devices, 3) key trends include predictive analytics, cognitive computing, and value-based care, and 4) opportunities exist in population health and clinical decision support while challenges include lack of integration and security concerns.
A data integrator like IMS could help reduce costs and improve care coordination for the US correctional health system. IMS enables communication across different internal and external health systems on a single platform. It would allow Corizon Health, the largest private correctional healthcare provider, to establish performance indicators, integrate electronic health records, facilitate telemedicine, and improve reporting and billing. IMS could address challenges like reducing costs while maintaining service quality, ensuring continuity of care when inmates transition between facilities or back to the community, and complying with regulations. This would help Corizon Health shift to a more patient-centered vision and meet the growing needs of the aging inmate population.
The document provides an overview of trends in the healthcare sector and a roadmap for investing in healthcare in 2016. Some of the key points summarized are:
1. The healthcare sector is experiencing several secular trends that are positive, including durable demand driven by aging demographics, growing affluence globally, and a shift from acute to chronic diseases.
2. Innovation is also fueling growth in the sector, including advances in genomics, immuno-oncology, and new therapies for various diseases.
3. Both regulatory and public policy trends have also become more positive recently for healthcare companies and products. The regulatory environment has sped up approval times while expanding pathways for approval.
Aami hitech mu impact on the future on HC ITAmy Stowers
Relate the components of The HITECH Act and Meaningful Use to health management technology
Identify whether existing systems meet requirements
Communicate technology needs and request feedback from end users for a smooth transition
Implement best practices to move people and systems forward under these new requirements
Unleashing Data: The Key To Driving Massive ImprovementsHealth Catalyst
The document discusses unleashing the power of data to drive massive improvements in healthcare outcomes. It advocates adopting a balanced approach to improvement across both the spectrum of effort (from light to high effort projects) and value (clinical, financial, patient experience). Following this balanced approach will lead to the greatest results by focusing on data infrastructure, training, and creating a data-driven culture. Examples of improvements across the spectrum are provided.
Findings on health information technology and electronic health recordsDeloitte United States
The Deloitte Center for Health Solutions 2016 Survey of US Physicians set out to understand physician adoption and perception of key market trends around health information technology and electronic health record data. Explore key survey findings to discover where physicians find the most value, barriers to adoption, and what they want next. http://deloi.tt/2d3b4w6
Oncology Big Data: A Mirage or Oasis of Clinical Value? Michael Peters
The title of the presentation, Oncology Big Data: A Mirage or Oasis of Clinical Value, reflects what I believe the field of Oncology is challenged with on a growing basis, from a clinical and business side perspective.
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.
Similar to Health IT Summit Miami 2015 - Keynote Presentation "Creating Competitive Advantage Through Analytics" (20)
1) Hackensack University Medical Center is part of a large healthcare network in New Jersey serving over 6 million people. It has received numerous awards and recognition for clinical excellence.
2) The presentation discusses HackensackUMC's strategies for managing risk-based care and consumerism, which includes a focus on patient engagement, care coordination across settings, and using technology like EHRs and analytics to improve outcomes and reduce costs.
3) HackensackUMC is managing care for over 100,000 beneficiaries through its Medicare ACO, a Blue Cross ACO, and an Aetna Medicare Advantage plan. It aims to shift care toward prevention and meet the growing demands of consumerism through increased access,
The U.S. healthcare system is the most expensive yet least effective compared to other industrialized nations. While some areas of the U.S. have high quality care, it is not universal. The document discusses leveraging design thinking and positive deviance to spread best practices more widely. It emphasizes starting with a compelling vision, building trust through networks rather than strict workflows, using data to measure important outcomes, and developing skills and resources to build capacity for change. Spreading ideas requires a social as well as scientific approach.
The document discusses Cleveland Clinic's strategy for managing patient populations beyond meaningful use requirements. It provides an overview of Cleveland Clinic including its size and services. It then summarizes the history of Cleveland Clinic's patient portal called MyChart, highlighting growth in usage and new features added over time. Finally, it outlines Cleveland Clinic's growth strategy, which includes increasing transparency by providing access to medical records and surveys, improving access to care through online services, and engaging patients through collection of patient entered data.
Development and implementation of a system to support prediction of suicide risk in the Department of Veterans Affairs - DR. Robert Bossarte and Paul Bradley
The document discusses participatory health care and the need to shift from the current health care system to one focused on health. It notes that the health care problem stems from issues with care delivery design rather than a lack of medical innovation. The Center for Innovation at Mayo Clinic is working to transform health care delivery and the patient experience through human-centered design, collaboration, and rapid experimentation. Some of their projects include connected care apps and redesigning prenatal care to reduce visits and increase patient connectivity. The document advocates for engaging patients in their own health and activating them as partners in health care through tools that provide autonomy, mastery and purpose.
The document discusses Illumina's role in advancing precision medicine through next-generation sequencing and data analytics. It notes that while sequencing costs have decreased dramatically, challenges remain in interpreting, integrating, and analyzing the large volumes of genomic and other healthcare data. Illumina aims to develop comprehensive, patient-centric analytics platforms and knowledgebases to help address these challenges and enable more effective prevention, diagnosis, and treatment based on a patient's genetics, environment, and lifestyle. The success of these efforts will be measured by improvements in patient outcomes, healthcare costs and efficiencies, and changes in clinical practice guided by integrated genomic and clinical data analysis.
This document discusses partnering for success in healthcare IT leadership. It provides strategies for building trusted relationships, embracing change, and shifting the focus from technology management to strategic business partnerships. Approaches include being open, a problem solver, agile, and willing to empower teams and make difficult decisions. The changing role of the healthcare IT leader is also addressed, such as anticipating change, having strong change management skills, and developing a broad industry network to address challenges from resistors. The overall message is that partnership, communication, and adaptability are key for healthcare IT leaders to successfully guide their organizations through a rapidly changing environment.
This document summarizes a presentation about setting vision and strategy for health IT leaders in dynamic times. It discusses exploring new leadership skills required for effective collaboration. It also addresses aligning technology strategies with organizational services and objectives. Additionally, it covers representing the organization to external partners to achieve business goals while leveraging technology. The presentation provides approaches for health IT leaders to develop an organizational vision and strategy that can adapt to changing conditions.
The document discusses developing talent and effective teams in healthcare leadership. It provides tips for leaders such as acting as a role model who embraces learning, celebrating outcomes and learning from assignments, building sustainable processes for development where managers coach their people, and leveraging problems as opportunities for learning. Developing talent requires focusing on culture through employee engagement, rewards and recognition, and building a positive organizational reputation. The presentation was given by Liz Johnson and Geoff Brown at a CHIME leadership forum on developing healthcare talent and teams.
The document discusses top cybersecurity risk mitigation strategies presented at a CHIME Leadership Education and Development Forum. It provides an overview of resources from the Department of Homeland Security and FBI that can help with gathering threat intelligence and establishing situational awareness. It emphasizes that proper user training, monitoring, and access management are important for risk mitigation. It also stresses the importance of the "people factor" and how human awareness and behavior are key to creating an effective human firewall against cybersecurity threats.
This document summarizes a presentation on cybersecurity threats facing healthcare organizations. It discusses how threat actors have evolved tactics like spear phishing and malware to target individuals. The presentation outlines the typical stages of an attack from initial reconnaissance to exfiltration of data. It provides recommendations for technical defenses like multifactor authentication and network segmentation as well as cultural changes like leadership support and security awareness training. Case studies from Emory Healthcare show the types of attacks blocked each month and techniques used to manage risk through frameworks and continuous improvement.
The Internet of Things (IoT) allows physical objects to be connected to the internet and to collect and exchange data. This enables remote monitoring and control of those objects over existing network infrastructure. It creates opportunities to more closely integrate the physical world with information systems, resulting in improved efficiency, accuracy, and economic benefits.
This document summarizes a presentation given by Doug Fridsma on meaningful use and precision medicine. Some key points from the presentation include:
- Meaningful use focused on EHR adoption over interoperability. Standards development received little funding.
- Health IT should be viewed as an ultra-large scale system like a city, not just software, with decentralized control, data sharing standards, and emphasis on the patient experience.
- Moving forward will require structured data standards, full export of patient records, and testing exchanges between systems to improve interoperability for precision medicine and new payment models.
- EHRs will not be the most important health IT - areas like consumer devices, precision medicine, and
Sajid Ahmed presented on the implementation of an EHR system at Martin Luther King Jr Community Hospital on a limited budget and tight timeline. The hospital was established through a public-private partnership between LA County and UCLA. Key strategies for successful implementation included aligning the culture, processes and people; allowing the processes to drive the EHR design rather than the other way around; and focusing on the hospital's mission when facing challenges. Through extensive planning and vendor management, the EHR went live on time and on budget to support the hospital's opening.
This document provides an overview of Dignity Health's strategies for achieving Meaningful Use objectives across their large health system. It discusses their centralized governance structure and tools for tracking progress. Significant attention is given to challenging objectives like patient electronic access, summary of care exchange, and public health reporting. The document outlines communication plans, education provided to sites, and techniques for monitoring metrics and preparing strong audit defenses.
The document discusses healthcare leadership and the implementation of electronic medical records (EMRs). It notes that in 1999, the Institute of Medicine reported that medical errors resulted in 44,000 preventable deaths annually in the US. As of 2009, only 1.5% of hospitals and 4% of physician practices had fully implemented EMR systems. The document emphasizes that successful EMR implementation requires focusing on people first by engaging user leaders, getting everyone onboard, and setting clear ground rules. It also stresses the importance of moving quickly with an aggressive schedule, capitalizing on moments of crisis to drive change, and clear communication throughout the process.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
BÀI TẬP DẠY THÊM TIẾNG ANH LỚP 7 CẢ NĂM FRIENDS PLUS SÁCH CHÂN TRỜI SÁNG TẠO ...
Health IT Summit Miami 2015 - Keynote Presentation "Creating Competitive Advantage Through Analytics"
1. Creating Competitive Advantage Using Analytics
Jon Scholl, Chief Strategy Officer at Texas Health Resources
February 11, 2015
2. Texas Health Resources – Who we are
• Our Mission: “To improve the health of the people in the communities we serve”
• THR is one of the largest faith-based, nonprofit health systems in the US
− 21K employees
− 25 acute care, transitional, rehab and short-stay hospitals that are owned,
joint-ventured or affiliated
• 17 acute-care hospitals
• 6 short-stay hospitals
− 3,800 licensed hospital beds
− 59 outpatient facilities, surgery centers,
fitness centers, and imaging centers
− More 250 other community access points
− $3.7 billion in operating revenue (FY 2012)
2/17/2015 2
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
** Physicians on the medical staff practice independently and are not employees or agents of the hospital or Texas Health Resources.
• Texas Health Physicians Group with
560 physicians and more than 240
advanced practitioners
4. Guest ID predictive analytics
− Useful patterns in buying
behavior emerge
− Pregnancy prediction score
− Target sends timed
coupons relevant to each
stage of pregnancy
• Target determines
customer’s potential to
spend, markets to identified
customers
Are you pregnant? If so, Target knows!
4
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources2/11/2015
Source: Andrew Pole, Target Analytics
5. Caesars Entertainment “Total Gold” loyalty program
5
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources2/11/2015
“We know if you like golf ... chardonnay, down pillows, if
you like your room close to the elevator, which properties
you visit, what games you play and which offers you
redeemed….We not only use these things on the front end
of marketing but for the service experience”
24% increase in spending from loyal customers,
82% of revenue base
6. Marriott International : micro-segmenting the
demand curve
“One Yield” revenue management
system
− Frequent pricing adjustments to
account for changing conditions
− Predictive models to maximize yield
− Extended to catering, restaurants and
meeting space
• Marriott Rewards micro-segments
most profitable customers and targets
offers
2/11/2015 6
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
Source: Competing on Analytics,
HBR, 2006
$86M in increased profits
7. Basis for Competitive Advantage
• Since the 1950s, volatility in operating margins (historically stable), has more
than doubled
• More than 40% of GDP comes from companies where the industry market share
is considered volatile and highly unpredictable
• 1960s Portfolio Theory (growth/share) is evaporating as share position and
market power are becoming less linked
− BCG calculated that the probability that market share leader = profit leader is
less than 7 percent, down from 34 percent in the 1950s
• The historical frameworks for strategic advantage are under fire
− Scale and position can be fleeting
− Industry borders are becoming less defined, more fluid
− Forecasting is unreliable
− Data rich, information starved
− Rapid change = planning tools are less accurate and less important
2/11/2015 7
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
8. Analytics competitors (i)
8
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources2/11/2015
Supply Chain
Customer selection,
loyalty, and service
Source: Competing on Analytics,
HBR, 2006
9. Analytics competitors (ii)
9
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources2/11/20152/11/2015 Source: Competing on Analytics,
HBR, 2006
Human capitalPricing
Research and
development
10. Data analytics as a competitive advantage
• Data analytics has become increasingly important to organizations
looking for a competitive edge
• Rapid advances the use of real-time data has been enabled by
technology
− Additional access points created through online interactions
− Increasing adoption of large customer-centric data warehouses
− Healthcare: transition to Electronic Health Records has enabled
searchable real-time clinical data
2/11/2015 10
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
Source: Accenture survey of 600 Executive Leaders 2013
Aggressively using
analytics
33%
Senior management
engaged with analytics
68%
Have senior figure such
as a “Chief Data Officer”
2/3
11. Industry interest in data analytics was
jumpstarted in 2007
2/11/2015 11
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
"Make analytics part of your
overarching competitive
strategy, and push it down to
decision makers at every
level. You'll arm your
employees...for making the
best decisions - big and small,
every day“
- Thomas Davenport, 2007
12. Health Care: Investments in predictive funding
increased 5X in 3 years
2/11/2015 12
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
$902M
$520M
$300M
$201M
2011 2012 2013
5X
2014
Predicting Funding
Venture funding for companies using predictive analytics (2011-Q3 2014)
Source: RockHealth
13. Go Big…..or Go Little?
DATA DATA
13
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources2/11/2015
Collecting unique data
about the customer, the
vendor, the location, and
interactions
Collecting giant stream of
digital metadata to mine
common behavior
patterns
BIG Little
14. Electronic Health Predictive (e-HPA) Analysis can
be used to predict future clinical events
Through analysis we can…
2/11/2015
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources 14
Stratify patients according to risk level
Allocate scarce clinical resources
Prevent adverse or harmful events
1
2
3
15. From admission to 90 days post discharge; six
activities reduce readmissions
2/11/2015 15
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
Post 90 Days
Identify HF
Patients
Risk Stratify
& Rank
Notify Team
Discharge
Plan
Monitoring
& IP/OP
interventions
Ongoing
Analysis
Admission
1 3 5
2 4 6
Discharge
16. How the patient is identified as a risk:
Natural Language Processing
“68 yo WF presents with acute on chronic non
ischemic systolic and diastolic chf, severely
depressed ef and grade ii diastolic dysfunction.”
2/11/2015
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources 16
Notes from EMR:
17. Natural Language Processing Interpretation
2/11/2015 17
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
Disease/ Symptom Time Attribute
Acute Heart Failure current and
primary
• Systolic, significant depression in
ejection fraction;
• Diastolic dysfunction, grade 2
• Non-ischemic
Chronic Heart
Failure
historic
Software
Interpretation:
19. Pieces™ gives THR a measureable benefit
Feedback from clinicians and case management
• “Pieces real-time risk scoring allows us to be notified of cases
earlier.”
• “Task management is simplified with integration in Epic system
list and order sets.”
• “Appreciate ability to enroll medium risk patients.”
• “No need for separate manual process.”
• “Pieces identification of heart failure patients was accurate.”
2/11/2015 19
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
20. “Know your number” as a marketing campaign
2/11/2015 Confidential And Proprietary – All Rights Reserved – For Internal Use Only Texas Health Resources 20
21. Cost goes down when well-being goes up
2/11/201521
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
1%Well-Being
2.2%
likelihood of
hospital
admission
1.7%
likelihood of
ER visit
1.0%
likelihood of
incurring
healthcare costs
Source: “Evaluation of the Relationship Between Individual Well-Being and Future Health Care Utilization and Cost”
Population Health Management, Volume 15, Number 00 2012. Patricia L. Harrison, MPH, James E. Pope, MD, Carter R.
Coberley, PhD, and Elizabeth Y. Rula, PhD
22. Fortune 50 case study: Results
3/26/201322
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
Individual Well-Being Score
%ofEmployees
2011: Average 71.0
2012: Average 73.9
(std dev = 13.4)
(std dev = 13.6)
Δ= 2.9*
Well-Being Improved Significantly
in Matched Respondents
T1-T2 Matched Cohort, N = 780
*Paired sample t-test, p < 0.05
23. Translating odds to probability of business
impact
3/26/201323
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
ER Visit Next 12 Months
Turnover Intention
1+ Absence / Month
Being Rated a
“High Performer”
Based on the odds,
the chance of…
Well-being Segment
Fortune 50 Case Study
Probability of occurrence
24. The dark green shows where WB5 scores are
high; light green represents low scores
2/11/2015 24
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
We will target assets and
physicians to populations
and geographies
Incorporate data into
predictive risk analysis Incorporate data in employer
wellness offerings
25. Analytics has proved to be a powerful tool in the
commercial industry; now applies to healthcare
2/11/2015 25
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources
Advances in technology have made
it possible for us to utilize analytics
in Healthcare
Well-Being
Inpatient
events
26. What’s next for healthcare….
26
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources2/11/2015
We have invested in EMR systems …so we have
data…what should we do with it?
IT
Infrastructure
& Integration
Interpreters of
data
Organizational
Commitment
1 2 3
EMR Systems
1
Investment NeededDone
27. Healthcare is ripe for analytics competitors;
current organizations will have to invest
• Strategic guidance (“what do
we want to know?”)
− pmpm population health
reports
− Network quality and
utilization
• Walk, then run
27
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources2/11/2015
Organize for success… …and keep an eye on the future
28. Summary
• The pace and change of Healthcare is unprecedented
• What will be the new source of competitive advantage in this industry?
− Power and influence or deep understanding of the analytics of the industry?
• Of all industries, Healthcare is ripe for analytic-competitors
• Requires key elements to succeed
− Organizing for success
− Strategic guidance (“what do we want to know?”)
• pmpm population health reports
• Network quality and utilization
• Etc
− Walk, then run
2/11/2015 28
Confidential And Proprietary – All Rights Reserved – For Internal Use Only
Texas Health Resources