The document describes preparing Medicaid claims data for directed data mining in SAS. It discusses extracting transactional data from multiple tables, summarizing the data to the recipient level to create total cost targets, and using SAS procedures to transform diagnosis codes, procedures, drugs, and providers into binary input variables for modeling and analysis. The goal is to explain or predict total costs using common directed data mining techniques like decision trees.
Is "healthcare intelligence" an oxymoron? What can we expect to accomplish with the data we have in healthcare? How do we transform data in electronic health records into superior clinical and financial outcomes? What are the information building blocks for a continuously learning health system? How important is technology in healthcare intelligence? What is the role of Big Data in healthcare and how do we prepare for it?
Case Study "Big Data, Little Data: Value and Transformation stemming from KP's HIT"
Learning Objectives:
∙ Learn about KP's investment in the EHR and its transformative value
∙ Learn how data and access to information has impacted clinical operations, the patient experience and how we approach research
∙ Learn how this data is more patient centric and patient empowering
Macquarie University Workshop on Text Mining and HealthDiego Molla-Aliod
Slides of the opening presentation at the Macquarie University workshop on Text Mining and Health, http://comp.mq.edu.au/research/collaboration-workshops/2014-mq-clinical-nlp/
4 Essential Lessons for Adopting Predictive Analytics in HealthcareHealth Catalyst
Predictive analytics is quite a popular current topic. Unfortunately, there are many potential side tracks or pit falls for those that do not approach this carefully. Fortunately for healthcare, there are numerous existing models from other industries that are very efficient at risk stratification in the realm of population management. David Crocket, PhD shares 4 key pitfalls to avoid for those beginning predictive analytics. These include
1) confusing data with insight
2) confusing insight with value
3) overestimating the ability to interpret the data
4) underestimating the challenge of implementation.
Data Mining in Healthcare: How Health Systems Can Improve Quality and Reduce...Health Catalyst
This is the complete 4-part series demonstrating real-world examples of the power of data mining in healthcare. Effective data mining requires a three-system approach: the analytics system (including an EDW), the content system (and systematically applying evidence-based best practices to care delivery), and the deployment system (driving change management throughout the organization and implementing a dedicated team structure). Here, we also show organizations with successful data-mining-application in critical areas such as: tracking fee-for-service and value-based payer contracts, population health management initiatives involving primary care reporting, and reducing hospital readmissions. Having the data and tools to use data mining and predict trends is giving these health systems a big advantage.
Is "healthcare intelligence" an oxymoron? What can we expect to accomplish with the data we have in healthcare? How do we transform data in electronic health records into superior clinical and financial outcomes? What are the information building blocks for a continuously learning health system? How important is technology in healthcare intelligence? What is the role of Big Data in healthcare and how do we prepare for it?
Case Study "Big Data, Little Data: Value and Transformation stemming from KP's HIT"
Learning Objectives:
∙ Learn about KP's investment in the EHR and its transformative value
∙ Learn how data and access to information has impacted clinical operations, the patient experience and how we approach research
∙ Learn how this data is more patient centric and patient empowering
Macquarie University Workshop on Text Mining and HealthDiego Molla-Aliod
Slides of the opening presentation at the Macquarie University workshop on Text Mining and Health, http://comp.mq.edu.au/research/collaboration-workshops/2014-mq-clinical-nlp/
4 Essential Lessons for Adopting Predictive Analytics in HealthcareHealth Catalyst
Predictive analytics is quite a popular current topic. Unfortunately, there are many potential side tracks or pit falls for those that do not approach this carefully. Fortunately for healthcare, there are numerous existing models from other industries that are very efficient at risk stratification in the realm of population management. David Crocket, PhD shares 4 key pitfalls to avoid for those beginning predictive analytics. These include
1) confusing data with insight
2) confusing insight with value
3) overestimating the ability to interpret the data
4) underestimating the challenge of implementation.
Data Mining in Healthcare: How Health Systems Can Improve Quality and Reduce...Health Catalyst
This is the complete 4-part series demonstrating real-world examples of the power of data mining in healthcare. Effective data mining requires a three-system approach: the analytics system (including an EDW), the content system (and systematically applying evidence-based best practices to care delivery), and the deployment system (driving change management throughout the organization and implementing a dedicated team structure). Here, we also show organizations with successful data-mining-application in critical areas such as: tracking fee-for-service and value-based payer contracts, population health management initiatives involving primary care reporting, and reducing hospital readmissions. Having the data and tools to use data mining and predict trends is giving these health systems a big advantage.
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
TUW- 184.742 Analyzing and Specifying Concerns for DaaSHong-Linh Truong
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
SAS Clinical training program in Hyderabadmadhupriya3zen
Excel in healthcare analytics with our top SAS Clinical training in Hyderabad. Gain hands-on expertise from clinical data analysis to SAS certification prep. Tailored for all, from fresh grads to pros. Enroll now!
Outlines Watson accomplishments in 2012 and new products announced in early 2013. THIS DOCUMENT IS PROVIDED FOR REFERENCE PURPOSES ONLY. IBM RESERVES THE RIGHTS TO MAKE CHANGES TO THIS EVOLVING PORTFOLIO.
National Patient Safety Foundation 2012 Dashboard DemoEdgewater
Edgwater attended the NPSF 2012 Patient Safety Congress in order to showcase our proven expertise in developing Patient Safety & Quality systems and processes. This presentation highlights some Edgewater client success stories as well as a demonstration of dashboards developed as part of our projects.
Panel presentation providing an introduction to open source VistA (history, community, and technology) as well as an implementor’s perspective, given at the 2010 Open Source Conference.
Recording of presentation: http://www.youtube.com/watch?v=ExoF_Tq14WY
SAS Big Data Forum - Transforming Big Data into Corporate GoldLouis Fernandes
Synopsis: How SAS believes organisations can turn Big Data in to competitive advantage through the use of High Performance Analytics.
In this presentations, we look at how SAS is seeing organisations take the outputs from big data analysis and turn them into tangible business outcomes through real-time decision-making.
In it, we explore:
- Why we believe organisations need to exploit their data assets to create the insights that build competitive advantage
- How to develop infrastructures required to support multi-dimentsional insight
- What SAS is doing to make this a reality
Key topics include:
- Data governance
- Big data infrastructure
- High performance analytics
- Data visualisation
About SAS:
- World’s largest, privately held software company,
- 35 years old
- Focus on advanced and predictive analytics right from the word go
- Big data has been in our DNA before it became mainstream
Big Data Expo 2015 - Trillium software Big Data and the Data QualityBigDataExpo
Successful Big Data initiatives rely on accurate, complete data, but the information they draw on is often not validated when it enters an organization. In this session we will look at the challenges big data brings to an organization, and how data quality principles are adapting to ensure business goals and return on investments in big data are realised. We will cover:
- Challenges of big data
- Turning data lakes into reservoirs
- How data quality tools are adapting
- Why data governance disciplines remain crucial
How Big Data is Reducing Costs and Improving Outcomes in Health CareCarol McDonald
There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics.
Join this talk to hear how MapR customers are using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer.
We will cover big data healthcare trends and production use cases that demonstrate how to deliver data-driven healthcare applications
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
TUW- 184.742 Analyzing and Specifying Concerns for DaaSHong-Linh Truong
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
SAS Clinical training program in Hyderabadmadhupriya3zen
Excel in healthcare analytics with our top SAS Clinical training in Hyderabad. Gain hands-on expertise from clinical data analysis to SAS certification prep. Tailored for all, from fresh grads to pros. Enroll now!
Outlines Watson accomplishments in 2012 and new products announced in early 2013. THIS DOCUMENT IS PROVIDED FOR REFERENCE PURPOSES ONLY. IBM RESERVES THE RIGHTS TO MAKE CHANGES TO THIS EVOLVING PORTFOLIO.
National Patient Safety Foundation 2012 Dashboard DemoEdgewater
Edgwater attended the NPSF 2012 Patient Safety Congress in order to showcase our proven expertise in developing Patient Safety & Quality systems and processes. This presentation highlights some Edgewater client success stories as well as a demonstration of dashboards developed as part of our projects.
Panel presentation providing an introduction to open source VistA (history, community, and technology) as well as an implementor’s perspective, given at the 2010 Open Source Conference.
Recording of presentation: http://www.youtube.com/watch?v=ExoF_Tq14WY
SAS Big Data Forum - Transforming Big Data into Corporate GoldLouis Fernandes
Synopsis: How SAS believes organisations can turn Big Data in to competitive advantage through the use of High Performance Analytics.
In this presentations, we look at how SAS is seeing organisations take the outputs from big data analysis and turn them into tangible business outcomes through real-time decision-making.
In it, we explore:
- Why we believe organisations need to exploit their data assets to create the insights that build competitive advantage
- How to develop infrastructures required to support multi-dimentsional insight
- What SAS is doing to make this a reality
Key topics include:
- Data governance
- Big data infrastructure
- High performance analytics
- Data visualisation
About SAS:
- World’s largest, privately held software company,
- 35 years old
- Focus on advanced and predictive analytics right from the word go
- Big data has been in our DNA before it became mainstream
Big Data Expo 2015 - Trillium software Big Data and the Data QualityBigDataExpo
Successful Big Data initiatives rely on accurate, complete data, but the information they draw on is often not validated when it enters an organization. In this session we will look at the challenges big data brings to an organization, and how data quality principles are adapting to ensure business goals and return on investments in big data are realised. We will cover:
- Challenges of big data
- Turning data lakes into reservoirs
- How data quality tools are adapting
- Why data governance disciplines remain crucial
How Big Data is Reducing Costs and Improving Outcomes in Health CareCarol McDonald
There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics.
Join this talk to hear how MapR customers are using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer.
We will cover big data healthcare trends and production use cases that demonstrate how to deliver data-driven healthcare applications