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Schedule: Value-Based Care sessions

The growing trend toward evidence-based care and value-based reimbursement, from point-of-care decision support tools for providers to ACO case studies to the prediction of adverse events.

Salon F
Workshop Please note: to attend, your registration must include Workshops on Wednesday.
Nancy Braun (Thavron Solutions)
Improving the business of healthcare requires merging data and business analytics to surface opportunities that make it easier for the right people to get the right healthcare at the right costs. Understanding and improving the complexities of system costs and interactions underlying Health Services is blue water in the HealthCare big data domain. Read more.
Salon F
Workshop Please note: to attend, your registration must include Workshops on Wednesday.
Eugene Kolker (Seattle Children's)
Average rating: **...
(2.50, 2 ratings)
This workshop is designed for managers and leaders working in healthcare (HC) interested in demystifying the big data and analytics hype to discover how data can drive real and meaningful organizational changes. Participants will learn how to prioritize objectives and use a project-based approach to achieve real success in manageable increments. Read more.
Salon G
Bill Tan (Transcendent Endeavors), Maurice Collins (Vocatta, Inc.)
Average rating: ****.
(4.00, 1 rating)
The Communication Genome Project is a large-scale data analysis project that breaks communication down into incremental, machine-readable “genes”. This nuanced knowledge of communication can be used to optimize patient-provider interactions and meaningfully influence patient adherence patterns. Read more.
Salon H-K
Jeffrey Miller (Children's Hospital of Philadelphia)
The Care Assistant is a framework for developing clinical decision support interventions within commercial electronic health records using familiar technologies like JavaScript, Python and JBoss Drools. This talk will focus on the framework's architecture and how it is being used to support the complex care of premature infants at the Children's Hospital of Philadelphia. Read more.
Salon H-K
Miriam Paramore (Emdeon), David Talby (John Snow Labs)
Average rating: ****.
(4.50, 2 ratings)
Learn how Emdeon and Atigeo collaborated to create a patient health record composed of historical medical, pharmacy and e-prescription information across healthcare providers (using tens-of-terabytes of claims data). See how they developed and trained a data driven statistical model for assessing and lowering the risk of hospital readmission at the point of check-in and each day after discharge. Read more.
Salon H-K
Tuan Dinh (Archimedes)
Average rating: *****
(5.00, 1 rating)
Model-Based Medicine (MBM), the next generation of Evidence-Based Medicine, is the use of advanced mathematical modeling to synthesize evidence and medical knowledge into a unified framework to support clinical decision making at individual patient level. Based on Archimedes's experience, we will outline the challenges and opportunities in developing and implementing MBM. Read more.
Salon H-K
Jennifer Vogel (Capital BlueCross), John Rollins (IBM), Greg Rodd (IBM Corporation)
Average rating: **...
(2.00, 2 ratings)
Hospital readmission rates have become an increasingly urgent concern in the face of competition and federally mandated requirements. A recent pilot project undertaken jointly by Capital Blue Cross and IBM demonstrates the business value of in-database analytics for reducing costs and improving outcomes for CHF patients. Read more.
Salon G
Tim Darling (Objective Health, McKinsey & Company), Arijit Sengupta (BeyondCore)
Average rating: *****
(5.00, 2 ratings)
McKinsey and BeyondCore analyzed 30M+ claims lives to predict the patients most likely to experience increases in healthcare costs. Best predictors of increases involve multiple variables such as: 50 year old patients with depression who have been discharged from a heart procedure. We used Big Data analytics to automatically evaluate a million variable combinations to reveal actionable patterns. Read more.
Salon G
John Mattison (Kaiser Permanente, SCAL), Hulya Emir-Farinas (Pivotal)
Average rating: ****.
(4.50, 2 ratings)
Public datasets can be used to enrich proprietary data and obtain more robust predictive models. However, public data, especially user-generated content, is notoriously messy. In this talk, using the FDA’s Adverse Event Reporting System (AERS), we will explain how to cleanse data and mash it up with other data sources for insight. Read more.
Salon H-K
Our NIH-funded study hypothesizes that a new method of EHR data capture using Natural Language Processing (“NLP”) would improve EHR usability and documentation quality. With test subjects from various specialties, we compared the NLP-Based method against the standard EHR data capture method. Learn the surprising results of our study. Read more.
Salon G
Pioneers and leaders in comparative effectiveness and pharma health economics and outcomes research and real world data will debate the various challenges posed by the evolving need to extract evidence from clinical trial and real world data. Read more.
Salon G
Andrew Cardon (Health Catalyst), John Shepard (Stanford University)
Average rating: *****
(5.00, 2 ratings)
Hospital reporting requirements are increasing, resulting in the need for more surveillance. The issue is how to streamline surveillance in order to shift resources from surveillance toward clinical interventions that result in improved outcomes. Read more.

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