By leveraging Big Data, the healthcare industry has an incredible potential to improve lives. This session will give examples of how data volume, velocity and variety is transforming the “art” of a doctor to the science of care. It will describe how the use of machine learning and massive amount of data will drive the new Consumer Drive healthcare movement.
By leveraging Big Data, the healthcare industry has an incredible potential to improve lives. This session will give examples of how data volume, velocity and variety is transforming the “art” of a doctor to the science of care. It will describe how the use of machine learning and massive amount of data will drive the new Consumer Drive healthcare movement.
Where Technology Meets Medicine: SickKids High Performance Computing Data CentreScalar Decisions
Case study look at the work Scalar conducted on the High-Performance Computing Data Centre at the Hospital for Sick Children (SickKids). The system is able to do 107 trillion calculations per second - one of the largest systems dedicated to health research.
This white paper offers a detailed perspective on how big data is impacting the healthcare industry and its underlying implication on the industry as a whole. It outlines the role of big data in healthcare, its benefits, core components and challenges faced by the healthcare sector towards full-fledged adoption & implementation.
Data science and the use of big data in healthcare delivery could revolutionize the field by decreasing costs and vastly improving efficiency and outcomes. There is an abundance of healthcare data in Canada, but it is mostly siloed and difficult to access due to privacy and security challenges. This session will offer insights into best practices for healthcare analytics programs, as well as use cases that demonstrate the potential benefits that can be realized through this work.
This presentation is about basics of Big data Analytics along with Characteristics,Challenges,Structures,Differences between Traditional and Big data,How Big data is getting benefited in Healthcare Industry,Big data in Real time
Healthcare Best Practices in Data Warehousing & AnalyticsDale Sanders
This is from a class lecture that I gave in 2005. Rather dated, but 95% of content is still very relevant today, which is a bit unfortunate. That's an indication of how little we've progressed in the healthcare domain.
Break All The Rules: What the Leading Health Systems Do Differently with Anal...Dale Sanders
This was my attempt to capture the intangible differences between leaders and followers in data driven healthcare. It should be noted that the organizations listed are not necessarily Health Catalyst clients. This slide deck is not intended to market or advertise Health Catalyst, but rather highlight leadership in analytics, wherever it exists.
Big Data Applications | Big Data Application Examples | Big Data Use Cases | ...Simplilearn
In this Big Data presentation, we will be discussing the Big data growth over the last few years followed by the various big data applications. We will look into the various sectors where big data is used such as weather forecast, healthcare, media and entertainment, logistics, travel & tourism and finally in the government & law enforcement sector.
We will be discussing how below industries are using Big Data presentation:
1. Weather forecast
2. Media and entertainment
3. Healthcare
4. Logistics
5. Travel n tourism
6. Government and law enforcement
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
The application of big data in health care is a fast-growing field, with many discoveries and methodologies published in the last five years. Big data refers to datasets that are not only big but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Moreover, medical data is one of the most growing data, as it is obtained from Electronic Health Records (EHRs) or patients themselves. Due to the rapid growth of such medical data, we need to provide suitable tools and techniques in order to handle and extract value and knowledge from these datasets to improve the quality of patient care and reduces healthcare costs. Furthermore, such value can be provided using big data analytics, which is the application of advanced analytics techniques on big data. This paper presents an overview of big data content, sources, technologies, tools, and challenges in health care. It also intends to identify the strategies to overcome the challenges.
Data Governance Talking Points: Simple Lessons From the TrenchesHealth Catalyst
About 7 months ago, one of Health Catalyst's clients asked for a 90-minute cram course on data governance, including time for questions and answers. They were struggling, like so many other healthcare organizations, caught in the swing of extremes from too much to too little, while equilibrium eluded them. With a last-minute rush, Dale Sanders (President of Technology, Health Catalyst) fell back on his time in the Air Force and threw together a talking points paper to facilitate the conversation. At the end of the meeting, the client was effusive with their appreciation, using words like “incredibly insightful,” “brilliant,” and “hugely valuable.” Dale didn’t think it was that good, but their data governance function was “dramatically better,” and they were happy, so something worked.
Since then, Dale has used the same talking points in two other similar meetings, with similar feedback and results. It still doesn’t feel that great or insightful to him, but he's glad to flow with the feedback and share the same style in this webinar in the hope that it’s useful.
After viewing this webinar, Dale hopes that you will have some tactical ideas to assess your organization’s data governance strategy. Are you leveraging the data you have? What could improve?
The Advisory Board Company Drives Healthcare Transformation with APIs and Mob...CA Technologies
As a global research, technology and performance improvement partner for over 180,000 leaders in healthcare and higher education, The Advisory Board Company is at the forefront of helping providers leverage investments in electronic medical records and identity management to deliver secure, consistent access across every digital channel from web to mobile and beyond. In this session, Ivan Sager, Director of Product Engineering, The Advisory Board Company, will discuss how API integration, mobile SDKs and centralized security are critical capabilities for driving innovation in healthcare.
For more information, please visit http://cainc.to/Nv2VOe
Where Technology Meets Medicine: SickKids High Performance Computing Data CentreScalar Decisions
Case study look at the work Scalar conducted on the High-Performance Computing Data Centre at the Hospital for Sick Children (SickKids). The system is able to do 107 trillion calculations per second - one of the largest systems dedicated to health research.
This white paper offers a detailed perspective on how big data is impacting the healthcare industry and its underlying implication on the industry as a whole. It outlines the role of big data in healthcare, its benefits, core components and challenges faced by the healthcare sector towards full-fledged adoption & implementation.
Data science and the use of big data in healthcare delivery could revolutionize the field by decreasing costs and vastly improving efficiency and outcomes. There is an abundance of healthcare data in Canada, but it is mostly siloed and difficult to access due to privacy and security challenges. This session will offer insights into best practices for healthcare analytics programs, as well as use cases that demonstrate the potential benefits that can be realized through this work.
This presentation is about basics of Big data Analytics along with Characteristics,Challenges,Structures,Differences between Traditional and Big data,How Big data is getting benefited in Healthcare Industry,Big data in Real time
Healthcare Best Practices in Data Warehousing & AnalyticsDale Sanders
This is from a class lecture that I gave in 2005. Rather dated, but 95% of content is still very relevant today, which is a bit unfortunate. That's an indication of how little we've progressed in the healthcare domain.
Break All The Rules: What the Leading Health Systems Do Differently with Anal...Dale Sanders
This was my attempt to capture the intangible differences between leaders and followers in data driven healthcare. It should be noted that the organizations listed are not necessarily Health Catalyst clients. This slide deck is not intended to market or advertise Health Catalyst, but rather highlight leadership in analytics, wherever it exists.
Big Data Applications | Big Data Application Examples | Big Data Use Cases | ...Simplilearn
In this Big Data presentation, we will be discussing the Big data growth over the last few years followed by the various big data applications. We will look into the various sectors where big data is used such as weather forecast, healthcare, media and entertainment, logistics, travel & tourism and finally in the government & law enforcement sector.
We will be discussing how below industries are using Big Data presentation:
1. Weather forecast
2. Media and entertainment
3. Healthcare
4. Logistics
5. Travel n tourism
6. Government and law enforcement
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
The application of big data in health care is a fast-growing field, with many discoveries and methodologies published in the last five years. Big data refers to datasets that are not only big but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Moreover, medical data is one of the most growing data, as it is obtained from Electronic Health Records (EHRs) or patients themselves. Due to the rapid growth of such medical data, we need to provide suitable tools and techniques in order to handle and extract value and knowledge from these datasets to improve the quality of patient care and reduces healthcare costs. Furthermore, such value can be provided using big data analytics, which is the application of advanced analytics techniques on big data. This paper presents an overview of big data content, sources, technologies, tools, and challenges in health care. It also intends to identify the strategies to overcome the challenges.
Data Governance Talking Points: Simple Lessons From the TrenchesHealth Catalyst
About 7 months ago, one of Health Catalyst's clients asked for a 90-minute cram course on data governance, including time for questions and answers. They were struggling, like so many other healthcare organizations, caught in the swing of extremes from too much to too little, while equilibrium eluded them. With a last-minute rush, Dale Sanders (President of Technology, Health Catalyst) fell back on his time in the Air Force and threw together a talking points paper to facilitate the conversation. At the end of the meeting, the client was effusive with their appreciation, using words like “incredibly insightful,” “brilliant,” and “hugely valuable.” Dale didn’t think it was that good, but their data governance function was “dramatically better,” and they were happy, so something worked.
Since then, Dale has used the same talking points in two other similar meetings, with similar feedback and results. It still doesn’t feel that great or insightful to him, but he's glad to flow with the feedback and share the same style in this webinar in the hope that it’s useful.
After viewing this webinar, Dale hopes that you will have some tactical ideas to assess your organization’s data governance strategy. Are you leveraging the data you have? What could improve?
The Advisory Board Company Drives Healthcare Transformation with APIs and Mob...CA Technologies
As a global research, technology and performance improvement partner for over 180,000 leaders in healthcare and higher education, The Advisory Board Company is at the forefront of helping providers leverage investments in electronic medical records and identity management to deliver secure, consistent access across every digital channel from web to mobile and beyond. In this session, Ivan Sager, Director of Product Engineering, The Advisory Board Company, will discuss how API integration, mobile SDKs and centralized security are critical capabilities for driving innovation in healthcare.
For more information, please visit http://cainc.to/Nv2VOe
Performance Testing of Big Data Applications - Impetus WebcastImpetus Technologies
Impetus webcast "Performance Testing of Big Data Applications" available at http://lf1.me/cqb/
This Impetus webcast talks about:
• A solution approach to measure performance and throughput of Big Data applications
• Insights into areas to focus for increasing the effectiveness of Big Data performance testing
• Tools available to address Big Data specific performance related challenges
Lokukaluge Prasad Perera
SINTEF Ocean, Trondheim, Norway.
The Smart Ship Technology conference
The Royal Institution of Naval Architects,
January 2017, London, UK.
The presentation on Appium was done during #ATAGTR2017, one of the largest global testing conference. All copyright belongs to the author.
Author and presenter : Sunket Ingale
How to Test Big Data Systems | QualiTest GroupQualitest
Big Data is perceived as a huge amount of data and information but it is a lot more than this. Big Data may be said to be a whole set of approach, tools and methods of processing large volumes of unstructured as well as structured data. The three parameters on which Big Data is defined i.e. Volume, Variety and Velocity describes how you have to process an enormous amount of data in different formats at different rates.
QualiTest is the world’s second largest pure play software testing and QA company. Testing and QA is all that we do! visit us at: www.QualiTestGroup.com
Big Data: Architecture and Performance Considerations in Logical Data LakesDenodo
This presentation explains in detail what a Data Lake Architecture looks like, how data virtualization fits into the Logical Data Lake, and goes over some performance tips. Also it includes an example demonstrating this model's performance.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/9Jwfu6.
Big Data Testing Approach - Rohit KharabeROHIT KHARABE
This presentation speaks about -
1) How to perform big data testing
2) Tools that can be used for testing
3) Different validation stages involved
4) Performance testing
The presentation on Performance Testing of Big Data Application was done during #ATAGTR2017, one of the largest global testing conference. All copyright belongs to the author.
Author and presenter : Harpreet Kaur Kahai
Big data architectures and the data lakeJames Serra
With so many new technologies it can get confusing on the best approach to building a big data architecture. The data lake is a great new concept, usually built in Hadoop, but what exactly is it and how does it fit in? In this presentation I'll discuss the four most common patterns in big data production implementations, the top-down vs bottoms-up approach to analytics, and how you can use a data lake and a RDBMS data warehouse together. We will go into detail on the characteristics of a data lake and its benefits, and how you still need to perform the same data governance tasks in a data lake as you do in a data warehouse. Come to this presentation to make sure your data lake does not turn into a data swamp!
TEDx Manchester: AI & The Future of WorkVolker Hirsch
TEDx Manchester talk on artificial intelligence (AI) and how the ascent of AI and robotics impacts our future work environments.
The video of the talk is now also available here: https://youtu.be/dRw4d2Si8LA
Data-Ed Webinar: Demystifying Big Data DATAVERSITY
We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype.
Takeaways:
- The means by which Big Data techniques can complement existing data management practices
- The prototyping nature of practicing Big Data techniques
- The distinct ways in which utilizing Big Data can generate business value
- Bigger Data isn’t always Better Data
We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype.
Check out more of our Data-Ed webinars here: www.datablueprint.com/webinar-schedule
The Pros and Cons of Big Data in an ePatient WorldPYA, P.C.
PYA Principal Dr. Kent Bottles, who is also PYA Analytics’ Chief Medical Officer, presented “The Pros and Cons of Big Data in an ePatient World” at the ePatient Connections 2013 conference.
Big Data Analytics and Open Data : The presentation aim is to enhance the awareness about big data analytics by process and importance of open data. Two case studies overview with accuracy and introduction is presented by Sharjeel Imtiaz.
PhD from University of East London
MedChemica BigData What Is That All About?Al Dossetter
A light look at the world of BigData for the lay person - a look at a couple of examples and what we do in MedChemica to speed up drug discovery. First presented at Macclesfield SciBar, and then Knutsford SciBar.
Sdal air health and social development (jan. 27, 2014) finalkimlyman
The American Institutes for Research (AIR) and Virginia Tech are collaborating to explore and develop new approaches to combining, manipulating and understanding big data. The two are also looking at how big data analytics can help answer questions critical to solving issues in education, workforce, health, and human and social development. They held two workshops on January 7 and 27, 2014- the first on Education and Workforce Analytics and the second on Health and Social Development Analytics.
We are living in the world of “Big Data”. “Big Data” is mainly expressed with three Vs – Volume, Velocity and Variety. The presentation will discuss how Big Data impacts Pharmaceutical Industry and how drug companies can lead this new Big Data environment.
BIMCV, Banco de Imagen Medica de la Comunidad Valenciana. María de la IglesiaMaria de la Iglesia
Según Hal Varian (experto en microeconomía y economía de la información y, desde el año 2002, Chief Economist de Google) “En los próximos años, el trabajo más atractivo será el de los estadísticos: La capacidad de recoger datos, comprenderlos, procesarlos, extraer su valor, visualizarlos, comunicarlos serán todas habilidades importantes en las próximas décadas. Ahora disponemos de datos gratuitos y omnipresentes. Lo que aún falta es la capacidad de comprender estos datos“.
Microsoft: A Waking Giant In Healthcare Analytics and Big DataHealth Catalyst
In 2005, Northwestern Memorial Healthcare embarked upon a strategic Enterprise Data Warehousing (EDW) initiative with the Microsoft technology platform as the foundation. Dale Sanders was CIO at Northwestern and led the development of Northwestern’s Microsoft-based EDW. At that time, Microsoft as an EDW platform was not en vogue and there were many who doubted the success of the Northwestern project. While other organizations were spending millions of dollars and years developing EDW’s and analytics on other platforms, Northwestern achieved great and rapid value at a fraction of the cost of the more typical technology platforms. Now, there are more healthcare data warehouses built around Microsoft products than any other vendor. The risky bet on Microsoft in 2005 paid off.
Ten years ago, critics didn’t believe that Microsoft could scale in the second generation of relational data warehouses, but they did. More recently, many of these same pundits have criticized Microsoft for missing the technology wave du jour in cloud offerings, mobile technology, and big data. But, once again, Microsoft has been quietly reengineering its culture and products, and as a result, they now offer the best value and most visionary platform for cloud services, big data, and analytics in healthcare.
In this context, Dale will talk about:
His up and down journey with Microsoft as an Air Force and healthcare CIO, and why he is now more bullish on Microsoft like never before
A quick review of the Healthcare Analytics Adoption Model and Closed Loop Analytics in healthcare, and how Microsoft products relate to both
The rise of highly specialized, cloud-based analytic services and their value to healthcare organizations’ analytics strategies
Microsoft’s transformation from a closed-system, desktop PC company to an open-system consumer and business infrastructure company
The current transition period of enterprise data warehouses between the decline of relational databases and the rise of non-relational databases, and the new Microsoft products, notably Azure and the Analytic Platform System (APS), that bridge the transition of skills and technology while still integrating with core products like Office, Active Directory, and System Center
Microsoft’s strategy with its PowerX product line, and geospatial analysis and machine learning visualization tools
Meet 1 - Introduction Data Mining - Dedi Darwis.pdf09372002dedi
What is data mining
Why do we need data mining
The data is also very complex
Behavioral data
Types of Attributes
Why data mining
Models vs. Analytic Processing
From Biology to Industry. A Blogger’s Journey to Data Science.Shirin Elsinghorst
What does blogging mean for Data Sciences?
What is Big Data today?
How to become a Data Scientist and what type of work results from this transformation?
Do you know everything you need to know about Medicaid's Meaningful Use program? Watch this video to learn more about Meaningful Use's eligibility, registration and timeline.
Accountable Care Organizations: 4 Physician BenefitsGreenway Health
Why would physicians join an Accountable Care Oragnization (ACO)? This informative slide presentation gives a brief overview of ACOs, their benefits, and four reasons physicians may have for joining one.
The Marketplace - Insurance Exchanges and ProvidersGreenway Health
Exploring coverage options through the Marketplace a/k/a Health Insurance Exchange (HIX) is among a growing lexicon of terms for governmental and insurance stakeholders. Intended to provide the consumer with an intuitive way to shop coverage with built-in protections, HIX open enrollment launches Oct. 1, 2013 and offers assistance with coverage choices and comparisons, calculation of costs, and education on public program options. Some HIXs will be run by state governments while others will be administered wholly or in partnership with the federal government. Explore the four exchange tiers, what constitutes "essential benefits" and "essential community providers," the role consumer assistants such as navigators in facilitating coverage for each American, and what providers and practices should be doing today to prepare. Review the basic functions of the HIX and the available subsidies for individuals and families. Regulations on Medicaid eligibility expansion will also be covered, as well as the impact on adult coverage and the future HIX milestones.
Source: Webinar presented August 28, 2013 by Adele Allison, National Director of Government Affairs for SuccessEHS
6 Tips to Leverage EHR Patient Data EffectivelyGreenway Health
If you have an EHR and practice management system, you have a very valuable asset at your fingertips: patient level health data. This presentation covers six practical ways your organization can use the data you already have to improve financial and clinical practice performance and position for coming value-based reimbursement.
How much money have the Meaningful Use Incentive Programs paid so far? Which states are the biggest adopters of new health care technology and which ones are behind? Discover the total amount providers, hospitals and eligible professionals are getting paid in Medicare and Medicaid incentives.
How many moustaches are present in the newly minted 113th Congress? What percentage of women comprise the Senate? Discover the answers and many interesting facts in this slideshow about our U.S. representatives.
Recently, a study published in the Journal of the American Dental Association shows a growing trend among U.S. dentists to incorporate EDR technology into their practice. Learn about how technology adoption has changed over the last decade among dentists, as well as how they are using the technology in their practices.
The Top 10 Tech Trends that affect health care organizations and providers. Includes organization considerations and optimum implementation timeline. (Source: Health Data Management)
Patient Engagement & the Matrix: How plugged in are we?Greenway Health
Americans are plugged in to "the Matrix" more than ever. Read about the digital and mobile habits of the American patient and how this has crossed over into health care.
What's the difference between fraud, waste and abuse when it comes to health care? What is the government doing to prevent fraud, waste and abuse from happening? Learn the definitions and differences in these legal terms and how CMS has worked to prevent these from happening since its inception in 1965.
Meaningful Use measures can be categorized into four distinct "buckets." Adele Allison, National Director of Government Affairs at SuccessEHS, defines the four different marks of Meaningful Use and the health IT goals that go along with each one. She also presents which categories are going to be significant moving forward into Stage 2, as well as how the categories will impact providers and reimbursement reform.
Medicaid Incentive Payouts and Stage 2 Meaningful UseGreenway Health
Adele Allison, National Director of Government Affairs at SuccessEHS, explains the details and deadlines providers need to know for Medicaid Meaningful Use. She highlights the incentive payouts for meeting Stage One, as well as the changes Stage 2 brings for both Medicare and Medicaid.
For a copy of the Medicaid Timeline, visit our blog: info.successehs.com/blog
How will Medicare pay providers who successfully attest to Meaningful Use? This slideshow highlights the timeline and details of Medicare incentive payouts. To view, print or download a copy of the timeline, visit our blog at http://info.successehs.com/blog/
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
263778731218 Abortion Clinic /Pills In Harare ,sisternakatoto
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Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
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Big Data - Outcomes Performance Measured
1. Big Data Outcomes / Performance
Adele Allison, National Director of Gov’t Affairs
SuccessEHS, Inc.
2. Big Data and Health Care
•
•
•
•
•
•
Perspective on Data
Federal Policy and Data
Health IT Today
Data and Performance
Data Capture for Success
Questions
www.SuccessEHS.com • 888.879.7302
3. Bits, Nibbles and Bytes
• Bit = 1 or 0 (on / off) → Binary Digit
• Nibble = 4 Bits of Data
• Byte = 8 Bits of Data
www.SuccessEHS.com • 888.879.7302
Source: doi:10.1093/bioinformatics/btn582
4. Bits, Nibbles and Bytes
Bit = 1 or 0 (on / off) → Binary Digit
Nibble = 4 Bits of Data
Byte = 8 Bits of Data
Kilobyte (KB) = 1,024 Bytes
Megabyte (MB) = 1,048,576 Bytes
or 1,024 KB
• 1 MB = 873 Pages of Plain Text (1,200
•
•
•
•
•
characters)
• 800 MB = Human Genome
www.SuccessEHS.com • 888.879.7302
Source: doi:10.1093/bioinformatics/btn582
5. Gigabyte (GB)
• 1 GB = 1,024 Megabytes
• 1 GB =7 Minutes HD-TV
Video
• 2 GB = 20 Yards of Books
on a Shelf
• 4.7 GB = Standard DVD-R
www.SuccessEHS.com • 888.879.7302
Source: www.mozy.com
6. Terabyte (TB)
1 TB = 1,024 GBs
1 TB = All X-rays in large hospital
2 TB = Academic Research Library
7 TB = Amount of Tweets/Day
10 TB = All Printed Materials of U.S.
Library of Congress
• 45 TB = Data Amassed by Hubble
Telescope first 20 years
•
•
•
•
•
www.SuccessEHS.com • 888.879.7302
Source: www.mozy.com
7. Petabyte (PB)
1 PB = 1,024 TB
1 PB = 20 Million, 4-drawer filing cabinets of text
1 PB = 13.3 Years of HD-TV Video
1.5 PB = Size of Facebook photos → 10 Billion
20 PB = Data processed by Google EVERY DAY!
50 PB = ALL Mankind’s written works from
Beginning of Recorded History (All Languages)
• 100 PB = Facebook data storage before IPO (2.1.2012)
• 300 PB = Facebook data today!
•
•
•
•
•
•
www.SuccessEHS.com • 888.879.7302
Source: www.mozy.com
8. Zettabyte (ZB)
• 1 ZB = 1 Million Petabytes!
• 1 ZB = 1,000,000,000,000,000,000,000
Bytes
o That is 21 Zeros, or
o 1 Sextillion Bytes
• If 1 GB = 60 Watt Bulb, then …
• 1 ZB = 15.7 years of energy from the
Hoover Dam to power a 1 ZB Light Bulb
for 1 hour
www.SuccessEHS.com • 888.879.7302
Source: www.mozy.com
9. Who’s Using Big Data?
• Snowden → NSA receives data from
Google, Facebook, Yahoo, YouTube, Skype,
AOL and Apple
• Average Am. Stats
o Avg. 150 Facebook friends/users (teens avg. 300)
o Avg. 150 add’l email/phone contacts/person
o Total Avg. Electronic “Contacts” = 300
• PRISM → NSA’s surveillance program
300 Contacts x Their 300 Contacts
x Their 300 Contacts
= 27 Million People
www.SuccessEHS.com • 888.879.7302
10. Who’s Using Big Data?
• Facebook → Presto
• 1,000 Employees
o Run 30,000 interactive Queries
per Day
o Over 1 PB of processing
• Open Source
• Types of Queries → Trends,
Marketing, Business Intelligence
www.SuccessEHS.com • 888.879.7302
11. Perspective
• 1-40 MB = Average Size of a
Patient’s EHR record
o Excluding Images
o 80 MB at Large Hospitals
o Top Average Size, including
imaging, 3-5 GB
• 3,281 = Average Number of
Active Patients for FP*
Estimate: 12 MB x 3,200 =
38,400 MB / FP or 37.5 GB / FP
www.SuccessEHS.com • 888.879.7302
*Source: AAFP
12. Real Ambulatory Metrics
• 653 DBs totaling 59.2 TB
• Wide variance in DB size → Average 90 GB
• Smallest 3.5 GB – Largest 1.7 TB
o Average is > 50 users is 226 GB
o Pictures, Word, Scanning, etc. ↑ Size Directly
o Transactional data creates marginal increases
• Examples:
o NJ CHC 44 Providers → 2.6 TB
o CA Ped. Practice 3 Providers → 10 GB
o LA School Based 1 Provider → 3.6 GB
www.SuccessEHS.com • 888.879.7302
13. Health Care “Score”
• Financial Data creates Individual
Credit Score
o Payment History Data
o Amounts Owed
o Length of Credit History
o New Credit
o Types of Credit
www.SuccessEHS.com • 888.879.7302
14. Health Care “Score”
• Will Health Care data create
Individual Health Score?
o
o
o
o
o
o
Lifestyle Choices (E.g., Smoking, BMI)
Worksite Wellness (E.g., Environment)
Activity Levels (E.g., Sedentary, Exercise)
Nutrition (E.g., Chips v. Broccoli)
Adherence / Compliance (E.g., Meds)
Behavioral Health (E.g., Quality of Life
Questionnaire, Sleep)
o Genomics (E.g., Genetic marker for Breast
Cancer)
www.SuccessEHS.com • 888.879.7302
16. Big Data and Health Care
• Perspective on Data
• Federal Policy and Data
•
•
•
•
Health IT Today
Data and Performance
Data Capture for Success
Questions
www.SuccessEHS.com • 888.879.7302
17. Affordable Care Act – By the Numbers
•
•
•
•
•
•
•
24 percent of federal budget goes to health care
36 times ACA mentions Patient Centeredness
15 times ACA references the Medical Home
73 times ACA mentions Accountable Care Organizations
93 times ACA references Quality Measures
29 times ACA links Quality to reporting Clinical Data
100 times ACA discusses Value-Based and Payment Modifiers
as relates to Hospital/MD Reimbursement and Measures
•
12 SCOTUS Opinion mentions Broccoli
www.SuccessEHS.com • 888.879.7302
18. Patient Centeredness and Policy
•
•
•
•
•
Behavioral Economics sought → About an Engaged Patient
Federal Gov’t → Leadership role in Health Care Reform
Transition → Episodic Care to Long-Term Healing and Wellness
Patient Centered Care → Measured Quality Performance
Federal Policymaking and Patient Centered Care
o
o
o
o
Regs CMS Meaningful Use Stage 2 – 7 Measures
Regs CMS Accountable Care Organizations (ACOs) – 7 Measures
Regs CMS Value-based Purchasing – Differential Payment
Regs CMS Public Measure Transparency – Physician Compare
www.SuccessEHS.com • 888.879.7302
19. Public Transparency
• IOM → $105 Billion Annually in Waste due to
o Lack of Competition
o Excessive Price Variation
• Obama Executive Order → CMS hospital pricing by
Top 100 DRGs (May 8, 2013)
o Charge vs. Medicare Allowable http://go.cms.gov/124pbRh
o E.g., Joint Replacement → $5,300 (Ada, OK) v. $233,000
(Monterey Park, CA)
• Medicare Data Access for Transparency and
Accountability Act (H.R. 2843, S. 1180)
www.SuccessEHS.com • 888.879.7302
20. CMS Proposed Rule – CY2014
•
Physician Compare Website – CY2014
o
o
o
o
Provider Transparency
PQRS GPRO 2012 and 2013 Performance Data
ACO Performance Data
CG-CAHPS Patient Experience Survey Data (All groups by CY2015)
www.SuccessEHS.com • 888.879.7302
22. Big Data and Health Care
• Perspective on Data
• Federal Policy and Data
• Health IT Today
• Data and Performance
• Data Capture for Success
• Questions
www.SuccessEHS.com • 888.879.7302
23. Value and Difficulty Continuum
Data Analytics
• Prescriptive
o How can we make it happen?
• Predictive
o What will happen?
• Diagnostic
o Why did it happen?
• Descriptive
www.SuccessEHS.com • 888.879.7302
o What happened?
24. Decision-Making and Health IT
• 4 Habits of High Performing Health Care Systems (NEJM,
Dec. 2011)
1.
2.
Specification and Planning → Use data to trigger an “advanced plan”
Infrastructure Design → Workflows that:
Simplify the process
3.
4.
Deliver timely information at the right decision point
Match the proper skills, resources to process
Measurement & Oversight → Realtime, Data-driven Operations
Self-Study → Apply measurements for ongoing learning and
improvement
www.SuccessEHS.com • 888.879.7302
25. Data Impact Potential
• 5 Potential Areas of Impact → Quality, Patient Engagement,
Efficiency / Revenue, Clinical Research, Risk / Liability
• Today, Market Remains …
o Fragmented
o Transaction-based
o Acute Care / Reactive Care Delivery
• Reform Goal: Morph into agile, responsive system that is …
o Proactive with a focus on prevention
o Engaging the patient for wellness lifestyles
o Managing complex patient populations
• Industry is Young → Health IT Hype Cycle
www.SuccessEHS.com • 888.879.7302
28. EHR Adoption Rates
•
MU launched in 2011 → Physician Adoption around 20%
www.SuccessEHS.com • 888.879.7302
Source: Healthcare Technology Online, May, 2013
30. Big Data and Health Care
• Perspective on Data
• Federal Policy and Data
• Health IT Today
• Data and Performance
• Data Capture for Success
• Questions
www.SuccessEHS.com • 888.879.7302
31. MU Cultural Shift
• 4 V’s of Health Care Data
o Volume – Large data stores for research
o Variety – Multiple approaches
o Velocity
Info to Provider when with the Patient
Info to Patient when they can still make a
behavior change
o Value – Data that drives a cultural shift
and ongoing process improvement
www.SuccessEHS.com • 888.879.7302
32. Incremental Approach
• Incremental approach today positions for
Incredible Future
• Call to Action …
o What do market and regulatory changes mean?
o Evaluate the Must Do vs. the Must Do
o Collaborate with stakeholders
Align goals with public health, hospitals, payers,
patients, clinicians, vendors
Identify potential barriers and formulate solutions
o Primary Care Health IT Application
New approaches to managing patient populations for
prevention
Use of data for purpose-driven performance
improvement
www.SuccessEHS.com • 888.879.7302
33. CDS Workflow
• Great place to start!
• MU1 → Implement 1 CDS Intervention
and Track Adherence
• MU2 → Implement 5 CDS
Interventions, align with 4+ CQMs
• MU3 → Implement 15 CDS
Interventions
www.SuccessEHS.com • 888.879.7302
34. Text to Code Translation
• Guidelines are Narrative → Human Readable
• AHRQ eRecommendation for Technical Specification →
Machine Readable
• Consistency in coded logic statements aligns:
o Development Costs
o Implementation Timelines
o Uniformity of data for comparative effectiveness
• AHRQ 5-Rights of CDS
o
o
o
o
o
Get the Right Information
To the Right Person
In the Right CDS Format
In the Right Technology Channel
At the Right time in the Patient Workflow
www.SuccessEHS.com • 888.879.7302
35. CDS Workflow
eMeasure NQF 0059; CMS CQM 122 → Hemoglobin A1c screenings
of Poorly Controlled Diabetic Patients
Report the percentage of patients age 18-75 with diabetes who had
hemoglobin A1c > 9.0% during the measurement period
The “Right”
The Answer
Redesign
1.Rule-logic pre-built?
2.Available in EHR?
• Initial assessment of
DM; target A1c value
of ≤ 7%
Get the Right
Information
www.SuccessEHS.com • 888.879.7302
3.If pt. presents for
unrelated issue, will
system alert?
• A1c at least 2x/year
for stable patients.
• More frequently for
poorly controlled.
4.Can EHR generate list
of non-compliant pts.
for outreach based on
pt. communication
preference?
36. CDS Workflow
The “Right”
The Answer
• Monitor and treat
hyperglycemia with a
target A1c of 7%
Redesign
1.Who needs this
information during
clinic workflows?
2.Who needs this
information for noncompliance tracking
and outreach?
To the Right
Person
www.SuccessEHS.com • 888.879.7302
37. CDS Workflow
The “Right”
The Answer
Redesign
1.What is the proper
CDS Format(s) to
manage DM A1c?
• Alerts / Reminders
• Reference Guidelines
In the Right
CDS Format
• Condition-focused
Order Sets
• Pt. Reports
• Flowsheets
• Documentation
Templates
• Other
www.SuccessEHS.com • 888.879.7302
2.What can my EHR
provide?
3.Can alerts, order sets
and documentation
templates be
customized?
38. CDS Workflow
The “Right”
In the Right
Technology
Channel
The Answer
• Mobile Device
• Internet Patient Portal
• EHR
• PHR
• Other
Alert!
www.SuccessEHS.com • 888.879.7302
Redesign
1.Will the alert be a popup note or will the user
have to prompt?
2.Can communication
for outreach be done
via secure email?
3.Should an alert be
sent to the Patient
Portal?
39. CDS Workflow
The “Right”
The Answer
Redesign
1.Can and should CDS
information be
provided at more than
one time of the patient
workflow?
At the Right
Time in the
Patient
Workflow
• Pt. Registration
• Assessment / Triage
• Exam Room / PE
• Treatment / Plan Dev.
• Performing Orders
• Check-out
• Remote / After Hours
www.SuccessEHS.com • 888.879.7302
2.Can alerting be
configured (E.g.,
based upon severity)?
3.Can patient education
/ information be
customized?
40. Let Technology Work for You!
CDS Type
Patient Alerts
Patient
Reminders
EvidenceBased Clinical
Guidelines
Point-ofCare
Workflow
X
X
X
www.SuccessEHS.com • 888.879.7302
Pop.
Mgmt.
Workflow
X
X
X
EHR
Adoption
Maturity
Level
BeginnerModerate
Beginner
BeginnerModerate
Types of CDS
Technology
Solutions
Rx Interactions,
Formulary,
Delinquent
Orders and
Deferred Orders
Patient Portal,
Secured Patient
emails, Text
Messages, Form
Letters/Postcard
s, Phone Call List,
Auto-Phoning
Pre-designed
CDS rulesengine, Point-ofCare alerts,
Intelligence
Prompting,
Patient
Education
Improves Improves
Quality
Patient
Safety
of Care
X
X
X
Cautionary Notes
X
Alert Fatigue can result
in clinicians ignoring
alerts.
X
System should
automatically identify
the patient’s preferred
method of
communication under
HIPAA.
X
System needs to allow
for customizable
guidelines; variance in
recognized standards of
care
41. Let Technology Work for You!
CDS Type
Order Sets
Flow-Sheets
Dashboards
EHR
Adoption
Point-ofPop.
Maturity
Care
Mgmt.
Level
Workflow Workflow
X
X
X
www.SuccessEHS.com • 888.879.7302
X
Types of CDS
Technology
Solutions
Wellness age
65+ and
Moderate pediatric,
Chronic Disease
Management
Vitals, Lab
Moderate
results, Antepartum, growth
Advanced charts
Timely followup, Results
signed-off,
Delinquent
orders and
Advanced
deferred orders,
appt.
compliance,
protocol
compliance
Improve
Quality
of Care
Improve
Patient
Safety
X
X
System needs to allow
for customization.
X
System needs to allow
for customization and
graphing.
X
System should have
metric drill-through for
details; requires
consist workflows for
data capture.
X
X
Cautionary Notes
42. EHR
Adoption
Point-ofPop.
Maturity
Care
Mgmt.
Level
Workflow Workflow
Let Technology Work for You!
CDS Type
Structured
Knowledgebase
Documentati
on Templates
Diagnostic
Support
Workflow
Tools
X
X
X
www.SuccessEHS.com • 888.879.7302
X
X
X
Types of CDS
Technology
Solutions
Intelligent
prompting for
differential
diagnoses,
Advanced clinical element
prompting for
symptoms, PE
considerations
Intelligence
prompting for
differential
diagnoses, autoAdvanced monitoring
based upon
results (e.g. lab),
recommended
therapies
Point-of-care
alerting, waitModerate time analysis,
mobile devices,
Advanced Internet,
compliance
tracking
Improve
Quality
of Care
X
X
X
Improve
Patient
Safety
Cautionary Notes
X
While significant time
savers, pre-filled
forms/lists and autonegatives/positives
can result in “cookiecutter”
documentation.
X
Requires providers to
break out of intuitive
decision-making and
adopt analytically
decision-making.
X
Critical to CDS
adoption, successful
workflow integration
requires the clinician’s
time and involvement.
43. Do’s and Don’ts
Don’t
Practice “Cookie-Cutter” Medicine → Same Tests
to all Patients with Similar Symptoms
Efficient, but not necessarily Effective
Seek all answers from a Data Warehouse
• Big, powerful but …
• Expensive and not suitable for many day-today needs
Approach Data as a Hunter, Gatherer
• Time consuming, expensive
• Data is often not compatible
www.SuccessEHS.com • 888.879.7302
Do
Practice Evidence-Based Medicine
• Use HIE to look beyond 4-walls
• Use Standardized Vocabularies
E.g., Sys. 1→ High BP; Sys. 2 → Elev. BP; Sys. 3 →
HTN; Instead use SNOMED CT
Leverage MU2 CCDA/CCD to support patientspecific tasks
• Use coded data to standardize terminology
• Supports HIE
• Helps with predictive modeling
• Can fill-in record gaps
Domesticate Data by “Normalizing,” if possible
• Map/Document using structured vocabularies
(E.g., SNOMED, LOINC)
• Meets MU and other regs
• Strive for consistent Data Capture
44. Do’s and Don’ts
Don’t
Do
Wait to consider new ways to use your data
• Don’t wait for Big Data to knock on your
door
• You have a wealth of enterprise data
today
Aggregate data wherever you can afford to
do so
• Does your vendor have a ServiceOriented Architecture (SOA) strategy?
• Where can data come from?
E.g., Financial, Operational and Clinical
E.g., Medical devices, Labs, Questionnaires
Limit your vision to your Health Care
Organization; you will only be able to react
to the market for competitiveness
Use free Public Health Data for Strategic
Planning
www.SuccessEHS.com • 888.879.7302
E.g., Univ. of FL merged health data with
Google Maps to create “heat” sensitivity for
chronic dz. Found 3 counties underserved
for breast screening and sent mobile units.
46. Big Data and Health Care
•
•
•
•
Perspective on Data
Federal Policy and Data
Health IT Today
Data and Performance
• Data Capture for Success
• Questions
www.SuccessEHS.com • 888.879.7302
47. Here’s Your Patient
• Miss West
• Belligerent
• Some kind of Liver
Function Problem
• Paranoia
• Non-Compliant ALL the
time
www.SuccessEHS.com • 888.879.7302
48. Patient Scenario
• Patient presents for wart removal
• Key → Must Consistently Capture Your Data
• 4 CQM / PQRS Measures:
o Influenza & Pneumonia Immunizations
o Breast & Colorectal Cancer Screenings
• What do you accomplish?
• 4
www.SuccessEHS.com • 888.879.7302
→ 1
49. Consistent Data Capture
• Consistent Data Capture = Strong Reporting
• Data Reporting Drives Performance for VBP
• Data Reporting Provides Credit for treat the
“Miss West” Patient
• Three Ways to Capture Data
o Performed (Here or Elsewhere)
o Not Performed (Medical Reason)
o Not Performed (Patient Refusal)
www.SuccessEHS.com • 888.879.7302
50. Patient Complexity Data
Health plans
use claims data
to build patient
complexity
profiles
www.SuccessEHS.com • 888.879.7302
The patient
complexity profile
must be
repopulated
annually using
calendar-year
claims data
(i.e., patient
complexity starts
at baseline
every year).
Diagnosis Codes
(ICD-9 and
ICD-10) are
used to
calculate
patient
complexity.
51. The Impact of Documentation & Coding
www.SuccessEHS.com • 888.879.7302
Source: BCBSAL, Complete Picture of Health Documentation and Coding
Improvement Initiative, Aug., 2013
52. CEUs or Copies
webinars@successehs.com
White Papers
www.SuccessEHS.com
Follow me on Twitter:
www.twitter.com/Adele_Allison
Added to The BRIEF or Questions:
adelea@successehs.com
www.SuccessEHS.com • 888.879.7302
Editor's Notes
ACA By the Numbers
23% of the Federal Budget currently goes to health care. The only line item that is higher than health care is the military – and together they represent nearly 50% of the total federal budget. 16% of the federal budget went to pay for Medicare last year; and, on average 57 cents of every Medicaid dollar is paid by the Federal gov’t.
36 times ACA talks about Patient-Centeredness. The full continuum is called to patient-centeredness. Americans are unengaged as patients. We want to smoke our cigarettes, drink our beer, sit on the couch in a sedentary lifestyle and watch football – no where more so than in the SEC! Then when things start to go wrong and break, we want to go to someone and get a quick fix. This is about a cultural shift within your practice and with the relationship you have with the American patient.
15 times ACA discusses a return to wellness, prevention and chronic disease management through the Medical Home – a model in patient centeredness for primary care.
73 times ACOs are referenced. We are seeing uptick trends in the development and establishment of ACOs. A model of value-based purchasing through the creation of a care “community” and the use of health IT.
93 times ACA talks about measuring quality – PQRS will be the vehicle for Medicare patient quality measures. Boomers are enrolling at a rate of 2.8 million/year – and will continue to do so for the next 18 years, essentially doubling the number of Medicare beneficiaries (what’s % of your payer mix does Medicare represent?). The health care industry is being called to action – this is your health care system. Data will be the barometer of your reimbursement, public comparison and comparative effectiveness. This requires the consistent capture and reporting of accurate clinical data on the patient, which is why …
29 times ACA links quality to the reporting of Clinical Data
100 times ACA talks about value-based and payment modifiers when it comes to reforming hospital and physician reimbursement.
And, as a side note, the Supreme Court of the U.S. (SCOTUS) final opinion upholding ACA references “Broccoli” 12 times. During oral argument in March of last year, counsel argued that it was a slippery slope to allow the federal gov’t the ability to require an American to purchase something under threat of penalty. If they can require an American to purchase health insurance, then can they also require them to buy a certain type of care – or broccoli, because it promotes health.