Medicaid Health Care Claims Institute for Health Policy
Bill Given, PhD
Kathleen Oberst, RN, PhD Director of Research
Michigan State University
April 7, 2016
MPH candidate of Boston University School of Public Health concentrating in biostatistics searching for data analysis position. Experience with using SAS, R and Epidata to perform data management and analysis; experience with using UCINET to perform network analysis; 2-year epidemiological survey background in the field of congenital disease, cardiovascular disease and maternal &children health; collaborative approach working with health providers.
MPH candidate of Boston University School of Public Health concentrating in biostatistics searching for data analysis position. Experience with using SAS, R and Epidata to perform data management and analysis; experience with using UCINET to perform network analysis; 2-year epidemiological survey background in the field of congenital disease, cardiovascular disease and maternal &children health; collaborative approach working with health providers.
Care coordination synchronizes the delivery of a patient’s health care from multiple providers and specialists. The goals of coordinated care are to improve health outcomes by ensuring that care from disparate providers is not delivered in silos, and to help reduce health care costs by eliminating redundant tests and procedures.
Comparative effectiveness randomized trial to improve stroke care delivery c...Marilyn Mann
A Vanderbilt University Medical Center study comparing the current way stroke care is delivered with a redesigned model that better integrates rehabilitation and skilled nursing facilities as well as lay health educators who make home visits. A pilot project suggests this new model can decrease hospital length of stay and readmissions, recurrence rates, and lower cost.
Validity and bias in epidemiological studyAbhijit Das
Validity and bias are essential aspects of any research—a brief description of internal and external validity and different types of bias related to the epidemiological study.
Peter Embi: Leveraging Informatics to Create a Learning Health SystemPAÍS DIGITAL
Presentación del Dr. Peter Embi, Presidente y CEO del Regenstrief Institute, en el marco del Primer Simposio Salud: Nuevas Tecnologías, Avances y Desafíos, realizado en Santiago de Chile los días 18 y 19 de julio, 2017
ODF III - 3.15.16 - Day Two Morning SessionsMichael Kerr
Slide presentations delivered during morning sessions of Day Two of the California Statewide Health and Human Services Open DataFest - March 14 - 15, 2016, Sacramento, CA
Care coordination synchronizes the delivery of a patient’s health care from multiple providers and specialists. The goals of coordinated care are to improve health outcomes by ensuring that care from disparate providers is not delivered in silos, and to help reduce health care costs by eliminating redundant tests and procedures.
Comparative effectiveness randomized trial to improve stroke care delivery c...Marilyn Mann
A Vanderbilt University Medical Center study comparing the current way stroke care is delivered with a redesigned model that better integrates rehabilitation and skilled nursing facilities as well as lay health educators who make home visits. A pilot project suggests this new model can decrease hospital length of stay and readmissions, recurrence rates, and lower cost.
Validity and bias in epidemiological studyAbhijit Das
Validity and bias are essential aspects of any research—a brief description of internal and external validity and different types of bias related to the epidemiological study.
Peter Embi: Leveraging Informatics to Create a Learning Health SystemPAÍS DIGITAL
Presentación del Dr. Peter Embi, Presidente y CEO del Regenstrief Institute, en el marco del Primer Simposio Salud: Nuevas Tecnologías, Avances y Desafíos, realizado en Santiago de Chile los días 18 y 19 de julio, 2017
ODF III - 3.15.16 - Day Two Morning SessionsMichael Kerr
Slide presentations delivered during morning sessions of Day Two of the California Statewide Health and Human Services Open DataFest - March 14 - 15, 2016, Sacramento, CA
Using Data, Transforming Practice: Evaluating Mental Health Transformation in...MHTP Webmastere
Using Data, Transforming Practice: Evaluating Mental Health Transformation in Washington State</strong><br />
This presentation, made in February 2008 to the 18th Annual Conference on State Mental Health Agency Services
Research, details the approach of the Mental Health Transformation Project in using data to evaluate transformation
BUILDing Multi-Sector Collaborations to Advance Community HealthPractical Playbook
The Practical Playbook
National Meeting 2016
www.practicalplaybook.org
Bringing Public Health and Primary Care Together: The Practical Playbook National Meeting was at the Hyatt Regency in Bethesda, MD, May 22 - 24, 2016. The meeting was a milestone event towards advancing robust collaborations that improve population health. Key stakeholders from across sectors – representing professional associations, community organizations, government agencies and academic institutions – and across the country came together at the National Meeting to help catalyze a national movement, accelerate collaborations by fostering skill development, and connect with like-minded individuals and organizations to facilitate the exchange of ideas to drive population health improvement.
The National Meeting was also a significant source of tools and resources to advance collaboration. These tools and resources are available below and include:
Session presentations and materials
Poster session content
Photos from the National Meeting
The conversation started at the National Meeting is continuing in a LinkedIn Group "Working Together for Population Health" and Twitter. Use #PPBMeeting to provide feedback on the National Meeting.
The Practical Playbook was developed by the de Beaumont Foundation, the Duke University School of Medicine Department of Community and Family Medicine, the Centers for Disease Control and Prevention (CDC), and the Health Resources & Services Administration (HRSA).
Wendy Davis: Leveraging Public Health Capacity to Improve Health System Effic...NASHP HealthPolicy
Many provisions of the ACA hold promise for public health agencies. The reorganization of the healthcare system in the wake of health reform also poses challenges for the public health system. This session will address how public health agency roles may change, opportunities to use public health agencies to lower health costs and improve health outcomes, and the integration of categorical funding streams to build a comprehensive public health system in a post-health reform world.
Wake up Pharma and look into your Big data Yigal Aviv
The vast volumes of medical data collected offers pharma the opportunity to harness the information in big data sets
Unlocking the potential in these data sources can ultimately lead to improved patients outcomes
This presentation describes consideration how to maximize the impact of Big Data.
its methodology, practical challenges and implications.
Big Data Technologies in Support of a Medical School Data Science InstituteDataWorks Summit
Join the presenters from Meharry Medical College as they present an overview of the technologies that support the Data Science Institute for the advancement of medical training, Data Science and medical research. In 2016 the president of Meharry Medical College initiated a program to establish the Data Science Institute that would concentrate on programs to support the underserved population of Nashville, Tennessee.
As a rule, Medical Colleges that serve this population are usually the last on the list to avail themselves of advanced technology. Meharry Medical College through an innovative approach was able to leapfrog their better funded peers by utilizing and applying the same opensource technologies used by Google, Facebook, Twitter, LinkedIn and Yahoo. The technical infrastructure, academic programs, research and the applied data science use cases will be discussed.
Bruno Basso, of the department of Environmental Science at MSU, illustrates the important work pertaining to crop and corn data being used throughout a digital landscape.
Advanced Genome Engineering Services and Transgenic Model Generation
at MSU’s Transgenic and Genome Editing Facility
Huirong Xie, Elena Demireva, Nate Kauffman, Richard Neubig
Back to the Future: Plastics from Plants and Cars that Run on Electricity, presented by Thomas Gregory, owner/consultant for Borealis Technology Solutions at the Michigan State University Bioeconomy Institute on 10-12-16.
Arend Hintze, Department of Integrative Biology, Department of Computer Science and Engineering, and BEACON Center for the Study of Evolution in Action at Michigan State University, presents his computational analysis of evolutionary processes at the Michigan State University Bioeconomy Institute on 10-12-16.
Presentation by Michaela TerAvest, assistant professor of Biochemistry and Molecular Biology at Michigan State University, at the MSU Bioeconomy Institute in Holland, Mich., on Mar. 16, 2016.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
1. Big Data Use: Medicaid Health
Care Claims
Institute for Health Policy
Bill Given, PhD
Kathleen Oberst, RN, PhD Director of Research
2. College of Human
Medicine
Aron Sousa, MD
Division of Public
Health
Dean Sienko, MD, MS
Institute for
Health Policy
Dean Sienko, MD, MS
Bruce Bragg, MPH
Health Policy
Dennis Paradis, MPH
Quality
Improvement
Debra Darling, BSN, RN, CCM
Health Services
Research
Kathleen Oberst, RN, PhD
3. Institute for Health Policy (IHP)
Mission – improve healthcare for all MI residents
Outreach and policy analyses
Quality improvement initiatives
Research projects
Collaborative role with:
Policy makers, State agencies (e.g. MDHHS)
Variety of healthcare organizations and non-profits
across Michigan
MSU and other Universities
4. Data Supporting Work
Predominantly claims/encounter based
Ex: Medicaid eligibility, enrollment, utilization
PROS
• Relatively confident that procedures performed
• Relatively confident that relevant diagnoses documented
• FFS claims have some cost information available
CONS
• Time lag before data available – 3-6 months, upwards of a
year
• Clinical information missing (i.e. lab values)
• Encounters lack cost data
• Health care coverage affects completeness of data
5. Data Supporting Work
Clinical/assessment data
Ex: MDS on LTC residents or Inter-RAI on MI Choice
participants, EMRs
PROS:
• Clinical information available
• Independent of health care coverage processing
• Social, cognitive and functional information
• Medications
CONS:
• Less standardized
• Available on small groups
• Variation by practice setting