Mine or theirs, where do users go? A comparison of collection usage at a loca...Juleah Swanson
This presentation shares research on recent trends in usage of electronic content by platform, comparing patron usage at a publisher platform, Elsevier’s Science Direct, to patron usage of the same content at a locally hosted platform, OhioLINK’s Electronic Journal Center. From the data, this presentation will open up a discussion on whether there is a continued place for locally hosted digital collections in our libraries; as well as what the long term implications are for relying on publisher platforms for our collections.
Universities that don’t enjoy high demand have to worry about their admissions yield policy. While some universities have the prowess to admit as few as 5 percent of applicants, even these universities must consider admissions yield before they can set such low admissions standards. Even elite universities have to balance the books and enrollment is usually the largest portion of what pays the bills. For the thousands of universities without demand high enough to decline 90+% of applicants yearly, knowing the predictors of admissions yield are especially important.
Mine or theirs, where do users go? A comparison of collection usage at a loca...Juleah Swanson
This presentation shares research on recent trends in usage of electronic content by platform, comparing patron usage at a publisher platform, Elsevier’s Science Direct, to patron usage of the same content at a locally hosted platform, OhioLINK’s Electronic Journal Center. From the data, this presentation will open up a discussion on whether there is a continued place for locally hosted digital collections in our libraries; as well as what the long term implications are for relying on publisher platforms for our collections.
Universities that don’t enjoy high demand have to worry about their admissions yield policy. While some universities have the prowess to admit as few as 5 percent of applicants, even these universities must consider admissions yield before they can set such low admissions standards. Even elite universities have to balance the books and enrollment is usually the largest portion of what pays the bills. For the thousands of universities without demand high enough to decline 90+% of applicants yearly, knowing the predictors of admissions yield are especially important.
The goal of this project is to find the best tool for predicting the life expectancy of people with Hepatitis B. Different Machine Learning methods have been completely studied and various Machine Learning methods have been carried out by different experimenters. Hepatitis B is a worldwide disease with a high mortality rate. Different methods have been used by different researchers to predict the life expectancy of Hepatitis B patients. The Machine Learning models and algorithms such as the Classification model, Logistic Regression model, Recursive Feature Elimination Algorithm, Cirrhosis Mortality model, Extreme Gradient Boosting, Random Forest, Decision Tree have been utilized by different researchers to predict the life expectancy of Hepatitis B patients. Some algorithms and models showed very interesting and proving results whereas some were not that good. Area Under Curve analysis was used to assess the estimation of various models. The AUROC value of the PSO model was minimal, while the ADT model had the highest accuracy. XGBoost showed appropriate predictive performance. All other models showed good calibration.
Comorbidity and the cost implications for long term conditions webinar hosted by Dr Umesh Kadam, Senior Lecturer, Clinical Epidemiologist & GP.
Learning outcomes:
• Understand the importance of transition for people with multi morbidity
• Know how to use local data for targeted improvement interventions for people with multiple long term conditions
• Consider how to use pairing of complex diseases to drive pathway development and potential contracting arrangements.
More at http://www.nhsiq.nhs.uk/improvement-programmes/long-term-conditions-and-integrated-care.aspx
Cheryl Davenport, Director of Health and Care Integration at Leicestershire County Council, talks about how simulation is helping to evaluate how emergency hospital admissions can be reduced.
NYU Langone Medical Center’s TJA BPCI Experience: Lessons in How to Maximize ...Wellbe
The Bundled Payments for Care Improvement (BPCI) Initiative began generating data in January of 2013. Dr. Iorio will outline the challenges and benefits of implementing BPCI for Total Joint Arthroplasty at an urban, tertiary, academic medical center with a hybrid compensation model. Early results from the implementation of a Medicare BPCI Model 2 primary TJA program demonstrate cost-savings with an improvement in quality of care metrics and continued cost savings through year 3 of our experience. Changes in patient optimization, care coordination, clinical care pathways, and evidence-based protocols are the key to improving the quality metrics and cost effectiveness within the implementation of the Bundled Payment for Care Initiative, thus bringing increased value to our TJA patients.
Maximizing Value in a Bundled Environment – Keys to Success:
• Evidence based, cost effectiveness analysis
• Standardized protocol adoption
• Transparent data
• Perioperative Patient Optimization
• Care management
• Physician-hospital alignment with Gain sharing
• Enhanced pain relief and rehabilitation protocols
• Blood management and rational VTED prophylaxis
About the Speaker:
Richard Iorio, MD, is the William and Susan Jaffe Professor of Orthopaedic Surgery at New York University Langone Medical Center Hospital for Joint Diseases and Chief of Adult Reconstruction at NYU Langone HJD. He co-founded Labrador Healthcare Consulting Services, Responsive Risk Solutions, and the Value Based Healthcare Consortium in 2015. He is a member of the Board of Directors for LIMA, the Lifetime Initiative for the Management of Arthritis. Dr. Iorio is a national expert in physician and hospital quality and safety and a leader in the implementation of alternate payment paradigms in orthopaedic surgery.
Industry Perspectives and Future Trends in Population HealthRohan DSouza
Presentation on industry perspectives on the future of population health management. This is a talk I gave at the eClinicalWorks National Users Conference in Nashville, TN (2015). With a lot of buzz surrounding pop health programs, I wanted to provide a roadmap on making the switch and succeeding.
How to establish and evaluate clinical prediction models - StatsworkStats Statswork
A clinical prediction model can be used in various clinical contexts, including screening for asymptomatic illness, forecasting future events such as disease, and assisting doctors in their decision-making and health education. Despite the positive effects of clinical prediction models on practice, prediction modelling is a difficult process that necessitates meticulous statistical analysis and sound clinical judgments. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following always on Time, outstanding customer support, and High-quality Subject Matter Experts.
Read More With Us: https://bit.ly/3dxn32c
Why Statswork?
Plagiarism Free | Unlimited Support | Prompt Turnaround Times | Subject Matter Expertise | Experienced Bio-statisticians & Statisticians | Statistics across Methodologies | Wide Range of Tools & Technologies Supports | Tutoring Services | 24/7 Email Support | Recommended by Universities
Contact Us:
Website: www.statswork.com
Email: info@statswork.com
United Kingdom: 44-1143520021
India: 91-4448137070
WhatsApp: 91-8754446690
The Center for Medicare & Medicaid Innovation (CMS Innovation Center) hosted the first of two webinars on November 19 to describe the final rule and respond to questions about the Comprehensive Care for Joint Replacement Model.
- - -
CMS Innovation Center
http://innovation.cms.gov
We accept comments in the spirit of our comment policy:
http://newmedia.hhs.gov/standards/comment_policy.html
CMS Privacy Policy
http://cms.gov/About-CMS/Agency-Information/Aboutwebsite/Privacy-Policy.html
A Data Mining Framework for the Analysis of Patient Arrivals into Healthcare ...Gurdal Ertek
We present a data mining framework that can be applied for analyzing patient arrivals into healthcare centers. The sequentially applied methods are association mining, text cloud analysis, Pareto analysis, cross-tabular analysis, and regression analysis. We applied our framework using real-world data from a one of the largest public hospitals in the U.A.E., demonstrating its applicability and possible benefits. The dataset used was eventually 110,608 rows in total for the regression models, covering the most utilized 14 hospital units. The dataset is at least 10-fold larger than datasets used in closely-related research. The developed data mining framework can provide the input for a subsequent optimization model, which can be used to optimally assign appointments for patients, based on their arrival patterns.
http://ertekprojects.com/gurdal-ertek-publications/
https://dl.acm.org/citation.cfm?id=3176740
Population Level Commissioning for the Future
Wednesday 3 December 2014, 1pm – 1.45pm
Dr Abraham George
Assistant Director/Consultant in Public Health
Kent County Council
&
Beverley Matthews
LTC Programme Lead, NHS Improving Quality
Abraham George: Kent Year of Care Programme Nuffield Trust
Dr Abraham George, Consultant in Public Health
Kent County Council, presents on using whole population linked datasets to develop higher value models of care in Kent's Year of Care Programme on long term conditions.
The CMS Innovation Center hosted a special webinar featuring Dr. Patrick Conway, CMS Deputy Administrator for Innovation and Quality and CMS Chief Medical Officer, on Monday, November 10, 2014 from 10:30am – 11:30 am ET. Dr. Conway will provided an update about the work of the CMS Innovation Center and the models being tested to improve better care for patients, better health for our communities, and lower costs through improvement for our health care system. Opportunities for questions were provided.
- - -
CMS Innovation Center
http://innovation.cms.gov
We accept comments in the spirit of our comment policy:
http://newmedia.hhs.gov/standards/comment_policy.html
CMS Privacy Policy
http://cms.gov/About-CMS/Agency-Information/Aboutwebsite/Privacy-Policy.html
In this presentation, Shaheen Gauher talks about two things: (1) How data science and machine learning can be used to manage and control escalating healthcare costs, and (2) How to create a Population Health Management Solution using state of the art Azure Data Lake Analytics and Population Health Report with real time visualization capability using Power BI. The solution presented can be deployed on Azure through a one-click deployment option in https://gallery.cortanaintelligence.com/
The goal of this project is to find the best tool for predicting the life expectancy of people with Hepatitis B. Different Machine Learning methods have been completely studied and various Machine Learning methods have been carried out by different experimenters. Hepatitis B is a worldwide disease with a high mortality rate. Different methods have been used by different researchers to predict the life expectancy of Hepatitis B patients. The Machine Learning models and algorithms such as the Classification model, Logistic Regression model, Recursive Feature Elimination Algorithm, Cirrhosis Mortality model, Extreme Gradient Boosting, Random Forest, Decision Tree have been utilized by different researchers to predict the life expectancy of Hepatitis B patients. Some algorithms and models showed very interesting and proving results whereas some were not that good. Area Under Curve analysis was used to assess the estimation of various models. The AUROC value of the PSO model was minimal, while the ADT model had the highest accuracy. XGBoost showed appropriate predictive performance. All other models showed good calibration.
Comorbidity and the cost implications for long term conditions webinar hosted by Dr Umesh Kadam, Senior Lecturer, Clinical Epidemiologist & GP.
Learning outcomes:
• Understand the importance of transition for people with multi morbidity
• Know how to use local data for targeted improvement interventions for people with multiple long term conditions
• Consider how to use pairing of complex diseases to drive pathway development and potential contracting arrangements.
More at http://www.nhsiq.nhs.uk/improvement-programmes/long-term-conditions-and-integrated-care.aspx
Cheryl Davenport, Director of Health and Care Integration at Leicestershire County Council, talks about how simulation is helping to evaluate how emergency hospital admissions can be reduced.
NYU Langone Medical Center’s TJA BPCI Experience: Lessons in How to Maximize ...Wellbe
The Bundled Payments for Care Improvement (BPCI) Initiative began generating data in January of 2013. Dr. Iorio will outline the challenges and benefits of implementing BPCI for Total Joint Arthroplasty at an urban, tertiary, academic medical center with a hybrid compensation model. Early results from the implementation of a Medicare BPCI Model 2 primary TJA program demonstrate cost-savings with an improvement in quality of care metrics and continued cost savings through year 3 of our experience. Changes in patient optimization, care coordination, clinical care pathways, and evidence-based protocols are the key to improving the quality metrics and cost effectiveness within the implementation of the Bundled Payment for Care Initiative, thus bringing increased value to our TJA patients.
Maximizing Value in a Bundled Environment – Keys to Success:
• Evidence based, cost effectiveness analysis
• Standardized protocol adoption
• Transparent data
• Perioperative Patient Optimization
• Care management
• Physician-hospital alignment with Gain sharing
• Enhanced pain relief and rehabilitation protocols
• Blood management and rational VTED prophylaxis
About the Speaker:
Richard Iorio, MD, is the William and Susan Jaffe Professor of Orthopaedic Surgery at New York University Langone Medical Center Hospital for Joint Diseases and Chief of Adult Reconstruction at NYU Langone HJD. He co-founded Labrador Healthcare Consulting Services, Responsive Risk Solutions, and the Value Based Healthcare Consortium in 2015. He is a member of the Board of Directors for LIMA, the Lifetime Initiative for the Management of Arthritis. Dr. Iorio is a national expert in physician and hospital quality and safety and a leader in the implementation of alternate payment paradigms in orthopaedic surgery.
Industry Perspectives and Future Trends in Population HealthRohan DSouza
Presentation on industry perspectives on the future of population health management. This is a talk I gave at the eClinicalWorks National Users Conference in Nashville, TN (2015). With a lot of buzz surrounding pop health programs, I wanted to provide a roadmap on making the switch and succeeding.
How to establish and evaluate clinical prediction models - StatsworkStats Statswork
A clinical prediction model can be used in various clinical contexts, including screening for asymptomatic illness, forecasting future events such as disease, and assisting doctors in their decision-making and health education. Despite the positive effects of clinical prediction models on practice, prediction modelling is a difficult process that necessitates meticulous statistical analysis and sound clinical judgments. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following always on Time, outstanding customer support, and High-quality Subject Matter Experts.
Read More With Us: https://bit.ly/3dxn32c
Why Statswork?
Plagiarism Free | Unlimited Support | Prompt Turnaround Times | Subject Matter Expertise | Experienced Bio-statisticians & Statisticians | Statistics across Methodologies | Wide Range of Tools & Technologies Supports | Tutoring Services | 24/7 Email Support | Recommended by Universities
Contact Us:
Website: www.statswork.com
Email: info@statswork.com
United Kingdom: 44-1143520021
India: 91-4448137070
WhatsApp: 91-8754446690
The Center for Medicare & Medicaid Innovation (CMS Innovation Center) hosted the first of two webinars on November 19 to describe the final rule and respond to questions about the Comprehensive Care for Joint Replacement Model.
- - -
CMS Innovation Center
http://innovation.cms.gov
We accept comments in the spirit of our comment policy:
http://newmedia.hhs.gov/standards/comment_policy.html
CMS Privacy Policy
http://cms.gov/About-CMS/Agency-Information/Aboutwebsite/Privacy-Policy.html
A Data Mining Framework for the Analysis of Patient Arrivals into Healthcare ...Gurdal Ertek
We present a data mining framework that can be applied for analyzing patient arrivals into healthcare centers. The sequentially applied methods are association mining, text cloud analysis, Pareto analysis, cross-tabular analysis, and regression analysis. We applied our framework using real-world data from a one of the largest public hospitals in the U.A.E., demonstrating its applicability and possible benefits. The dataset used was eventually 110,608 rows in total for the regression models, covering the most utilized 14 hospital units. The dataset is at least 10-fold larger than datasets used in closely-related research. The developed data mining framework can provide the input for a subsequent optimization model, which can be used to optimally assign appointments for patients, based on their arrival patterns.
http://ertekprojects.com/gurdal-ertek-publications/
https://dl.acm.org/citation.cfm?id=3176740
Population Level Commissioning for the Future
Wednesday 3 December 2014, 1pm – 1.45pm
Dr Abraham George
Assistant Director/Consultant in Public Health
Kent County Council
&
Beverley Matthews
LTC Programme Lead, NHS Improving Quality
Abraham George: Kent Year of Care Programme Nuffield Trust
Dr Abraham George, Consultant in Public Health
Kent County Council, presents on using whole population linked datasets to develop higher value models of care in Kent's Year of Care Programme on long term conditions.
The CMS Innovation Center hosted a special webinar featuring Dr. Patrick Conway, CMS Deputy Administrator for Innovation and Quality and CMS Chief Medical Officer, on Monday, November 10, 2014 from 10:30am – 11:30 am ET. Dr. Conway will provided an update about the work of the CMS Innovation Center and the models being tested to improve better care for patients, better health for our communities, and lower costs through improvement for our health care system. Opportunities for questions were provided.
- - -
CMS Innovation Center
http://innovation.cms.gov
We accept comments in the spirit of our comment policy:
http://newmedia.hhs.gov/standards/comment_policy.html
CMS Privacy Policy
http://cms.gov/About-CMS/Agency-Information/Aboutwebsite/Privacy-Policy.html
In this presentation, Shaheen Gauher talks about two things: (1) How data science and machine learning can be used to manage and control escalating healthcare costs, and (2) How to create a Population Health Management Solution using state of the art Azure Data Lake Analytics and Population Health Report with real time visualization capability using Power BI. The solution presented can be deployed on Azure through a one-click deployment option in https://gallery.cortanaintelligence.com/
1. 21/02/2015
1
Patient Cost Analysis
Shiquan REN, PhD
http://lnkd.in/bSEMhzb
ctusren@outlook.com
Contents
• IHPA Classification and Pricing
• Distribution of Cost
• Cost drivers
• Nonlinear regression of Cost
• The other models of Cost
• Future modelling of Cost
• Conclusion
2. 21/02/2015
2
My understanding of IHPA Classifications
There are six patient service categories in Australia
currently which have classifications being used
nationally or in development stage.
• Admitted acute care
• Subacute and non-acute care
• Non-admitted care
• Mental health care
• Emergency care
• Teaching, training and research
My understanding of IHPA Pricing
• Annual National Efficient Price (NEP) and National
Efficient Cost (NEC)
• Cost and Pricing models
• To determine the NEP, IHPA first develops a cost model
based on cost and activity data from three years prior
• Price weights and adjustments are combined to define
the National Weighted Activity Unit (NWAU)
• The price of a hospital service can then be determined
by multiplying the NEP, which is a reference cost, by the
number of NWAU.
3. 21/02/2015
3
My Experience of Cost Analysis
• Data source - simulated data
• Analysis objectives - set up price
• Analysis methods – based on nonlinear
regression
• Expected outcomes - set up a reasonable price
Understand Data Distribution
4. 21/02/2015
4
Cost drivers
• Remoteness
• Age
• Length of stay
• Disease complexity (DRG used as
classification)
• …
Outlier Detection: Box Plot of Cost by
Remoteness
9. 21/02/2015
9
The Other Models of Cost
(Ren et al, 2006)
• Two-part Models - Parametric
• Mixed Models - Parametric
• Generalized Additive Models (GAM) -
Semiparametric
• Markov Chain Monte Carlo (MCMC) -
Bayesian
Extending Regression Models
Generalized Linear Model Linear Model
Additive ModelGeneralized Additive Model
Mixed Model Generalized Additive Mixed Model
10. 21/02/2015
10
New possible modelling of Cost for hospitals
• Generalized Additive Mixed Models (GAMM) - Semiparametric
• My own temporal (daily, weekly, monthly) modelling - Nonparametric
Outliers?
Interpolating Missing Data
Forecast
Conclusion
• Data clearance – Outliers
• Cost – Log-normal Distribution
• Cost drivers – Remoteness, Age, Length of Stay
and Disease complexity (DRG used as
classification)
• Cost models – MCMC, GAM, Two-part models
and Mixed models
• New cost models – GAMM, Monthly modelling,
…