* Keynote Speaker 1

Andrew L. Masica, MD, MSCI

Vice President, Chief Clinical Effectiveness Officer, Baylor Scott & White Health

“Applied Health Informatics Through the Lens of an Integrated Care Delivery System.”

Abstract

• Provide context on the importance applied health informatics for care delivery organizations in operational innovation and research efforts
• Demonstrate the role of integrated delivery systems in accelerating the impact of health informatics on daily patient care
• Present brief case studies of applied informatics at Baylor Scott & White Health (including lessons learned)
• Discuss key opportunities for the health informatics community to support and collaborate with integrated care delivery systems

Biography

Andrew Masica, MD, MSCI serves as Vice-President and Chief Clinical Effectiveness Officer for Baylor Scott & White Health (BSWH). Following graduation from Harvard University, Dr. Masica received his MD from the Indiana University School of Medicine, underwent residency training at University of Texas-Southwestern Medical Center, and completed a clinical pharmacology research fellowship and a Master of Clinical Investigation program at the Vanderbilt University School of Medicine.

Since his arrival at BSWH in 2006, Dr. Masica has maintained system-level roles in quality, patient safety, and health services research, while continuing to practice clinically as a board certified hospital-based internist. His main research interests are in the areas of rational use of therapeutic drugs, clinical effectiveness, and delivery science. He has received funding as a principal or co-investigator on several studies funded by the Agency for Healthcare Research and Quality, the National Institutes of Health, and the Center for Medicare and Medicaid Innovation, as well as pharma. He has translated this work into numerous publications in peer-reviewed journals. Dr. Masica’s operational responsibilities are focused on population health and the deployment of evidence-based practices into daily patient care, particularly the design of accelerated adoption strategies and assessing impacts of those implementations.

Dr. Masica has been designated as a Senior Fellow by the Society of Hospital Medicine, and has an appointment as an Assistant Clinical Professor of Medicine at the Texas A&M Health Sciences Center (Dallas Campus). He was recognized by the Dallas-Fort Worth Hospital Council as their 2012 Young Healthcare Executive of the Year, and leads Baylor Scott & White’s involvement in the High Value Healthcare Collaborative.

* Keynote Speaker 2

Joydeep Ghosh

Schlumberger Centennial Chaired Professor, Dept of Electrical and Computer Engineering, University of Texas at Austin

Towards Personalized Medicine: Building Predictive Models for “Segments of One”

Abstract

Strong, diverse forces arising from technological, regulatory and attitudinal changes as well as economic compulsions are leading to a revolution in how healthcare is practiced in the USA. Central to these developments is the rise of Digital Health: the collection or conversion of a variety of health-related information into electronic form and the analysis of the resulting data for more reliable and proactive healthcare.
This movement ultimately promises to deliver precision diagnoses and prognoses that are accurate at the level of an individual person, in other words, creating accurate predictive and prescriptive models for “segments of one”.

In this talk, I will describe diverse factors that are fostering the digital health movement and highlight some promising developments in this area. Key challenges facing this movement will also be outlined, including the integration of such approaches with existing domain knowledge to produce even more readily acceptable and actionable results. Some thoughts on the future of data-driven healthcare analytics will also be shared.

Biography

Joydeep Ghosh is currently the Schlumberger Centennial Chair Professor of Electrical and Computer Engineering at the University of Texas, Austin. He joined the UT­Austin faculty in 1988 after being educated at, (B. Tech ’83) and The University of Southern California (Ph.D’88). He is the founder­director of IDEAL (Intelligent Data Exploration and Analysis Lab) and a Fellow of the IEEE. His research interests lie primarily in data mining and web mining, predictive modeling / predictive analytics, machine learning approaches such as adaptive multi­learner systems, and their applications to a wide variety of complex real­world problems such as healthcare. He has published more than 400 refereed papers and 50 book chapters, and co­edited over 20 books. He has received 14 Best Paper Awards over the years, including the 2005 Best Research Paper Award across UT and the 1992 Darlington Award. He also received the 2015 Technical Achievement Award from IEEE CS for development of multi-learner systems.

Dr. Ghosh has been a plenary/keynote speaker on several occasions such as ICDM’13 and (Health Informatics oriented workshops at) KDD’15, KDD14, ICML13 and ICHI13., and has widely lectured on intelligent analysis of large­scale data. He served as the Conference Co-Chair or Program Co­Chair for several top data mining oriented conferences, including SDM’13, SDM’12, KDD 2011, CIDM’07, ICPR’08 (Pattern Recognition Track) and SDM’06. He was the Conf. Co­Chair for Artificial Neural Networks in Engineering (ANNIE)’93 to ’96 and ’99 to ’03. He has also co­organized workshops on health informatics, high dimensional clustering, Web Analytics, Web Mining and Parallel/ Distributed Knowledge Discovery. Dr. Ghosh has served as a co­founder, consultant or advisor to several successful startups in addition to consulting for large corporations. Currently he is on the advisory board of Cognitive Scale (Healthcare thrust) and Accordion Health.

* Keynote Speaker 3

Veerasamy “Ravi” Ravichandran

Program Director Biomedical Technology, Bioinformatics and Computational Biology Division, National Institute of General Medical Sciences, National Institutes of Health

Current trends in NIGMS/NIH funding opportunities

Abstract

Veerasamy “Ravi” Ravichandran is with the Biomedical Technology, Bioinformatics, and Computational Biology (BBCB) division of NIGMS, NIH. The BBCB division supports the development, use and dissemination of computational tools, sophisticated quantitative approaches and unique experimental technologies to enable studies of biological, behavioral and social systems that underlie health and disease; the creation of innovative methods to store, organize, share, visualize, integrate and analyze vast quantities of biological data; and training opportunities in the quantitative and data sciences to prepare the next generation of biomedical researchers. In his presentation, Ravi will be talking about the current trends in NIH, particularly the NIGMS funding opportunities. This presentation is intended to be informal and preferred to have an interactive discussion with the audience.

Biography

Veerasamy “Ravi” Ravichandran, Ph.D., is a program director in the Division of Biomedical Technology, Bioinformatics, and Computational Biology. He manages research, resource and training grants in the areas of biomedical technology, bioinformatics and computational biology. Ravichandran is also involved in facilitating and coordinating trans-NIH activities related to big data. Earlier in his career, he was a staff scientist at the National Institute of Neurological Disorders and Stroke, a research scientist at the National Institute of Standards and Technology, and an associate research scientist at Yale University School of Medicine and the University of Pennsylvania. Ravichandran conducted postdoctoral research as an IRTA fellow in the NCI Laboratory of Pathology and Experimental Immunology Branch. He earned a bachelor’s degree in chemistry, master’s degrees in biochemistry and philosophy/clinical biochemistry, and a Ph.D. in biochemistry from the University of Madras in India. Ravichandran also earned a master’s degree in computer science and bioinformatics from John Hopkins University and a certificate degree in database development from George Washington University.

There are many patient/caregiver support forums where patients/caregivers can post their questions regarding their health conditions. Some examples include cancer compass, ehealthforums , patientslikeme, etc. In many of these forums, there is a significant degree of repetitive questions. It is quite common in patient support forums to find questions that are very similar in meaning (i.e., have high similarity in terms of their semantics) but are worded differently. One possible reason of this repetition could be that as the forums grow longer, patients/caregivers do not have the time or patience to read through previous questions before posing their own question.

In this context, a system that can point a patient/caregiver posting a question on a support forum to semantically similar questions that were previously posted on the forum will be immensely helpful to patients and caregivers. This challenge aims to design foundational techniques towards building such a system.

Challenge Specification

Consider a corpus of questions Q= {q₁, q₂, q₃, …. , q_n} from a patient support forum, where each q_i represents a question from a patient forum on Type II Diabetes. For simplicity, all the questions in the corpus are assumed to pertain to the same disease/chronic health condition (e.g., diabetes). Furthermore, each question is assumed to have a unique ID. The order of questions in the corpus is assumed to be arbitrary. Suppose IQ = {iq₁, iq₂, …., iq_m} be the set of incoming questions (iq₁ being the first incoming question and so on).

The challenge is to design and implement a system that for each incoming query iq_j identifies a maximum of three most similar questions from the corpus Q. In other words, for each iq_j, your system has to retrieve three or less queries from Q that are semantically most similar to iq_j. For each iq_j, the output from your system should be a set of three or less question IDs from Q. It is not necessary to rank the retrieved results (i.e., the systems will only be evaluated for containment and not for ranking of the results).

You can use any external data in your approach (ontologies etc.) provided you reveal all the data sources used in your approach.

Test Data Sets and System Evaluation

Systems submitted for this challenges will be evaluated and compared with respect to their effectiveness in retrieving most similar queries from the corpus. Although the systems will not be evaluated for speed, they are expected to complete execution in a reasonable time frame (~5 minutes for a data set with |Q|≈ 100 and |IQ| ≈ 10).

The evaluation will be done by using domain expert-curated datasets. The query corpuses Q and the incoming query set IQ will be derived from real patient support forums on Type II Diabetes. For each query in IQ, domain experts will identify up to three most similar queries from Q. Systems will be evaluated based on the percentage of expert-identified results that are included in the system-identified results set. For instance, let us suppose the domain expert identified q₆ and q₃₇ as the most similar queries to the incoming query iq₁ and suppose a system identified q₃₇, q₅₂ and q₇₄ as the most relevant queries. This system will receive 50 points. The system with maximum number of total points (over all queries in IQ) will win.

Rules

1. Each participating group can have at most 5 people.
2. Each person can be part of no more than 2 groups
3. System can be developed in one of the standard programming language (C, C++, Java, Python). If you intend to use any other language, you will need to obtain prior permission from the ICHI 2015 challenge chair.
4. You can use databases, ontologies, dictionaries, etc. in your system provided you all reveal all such knowledgebases that you have used.
5. We will make one dataset available on our website by June 10, 2015. You can use this data set for development, tuning and testing of your system. This dataset will be used in determining the finalists of the grand challenge (see below).
6. You will need to submit the following as a part of the package: (1) A paper (two pages IEEE conference proceedings format) outlining your approach; (2) Source code of your system; (3) Any databases, Ontologies etc. that are required for your system to function; (4) A readme file containing the names of the group members and clear instructions on how to compile, deploy and run your system; (5) The results of your system on the dataset that is made available on the website;
7. Based on the results on the dataset that is made available, we will select up to six finalists. The finalists are expected to demo their system during a dedicated session in the conference and give a 5-minute presentation outlining their approach. The papers from the finalist groups will be included in the conference proceedings. At least one member of each group is required to register for the conference and be present at the conference.
8. During the conference, the finalist systems will be evaluated on a data set that has not been shared with the participants before. Results from this data set will decide the final winners of the challenge.

Important Dates:

Grand Challenge Solution Submission Deadline: July 10, 2015. July 17, 2015

Finalist Decision Notification: August 10, 2015.

Camera Ready Papers Due from Finalists: August 15, 2015. August 21, 2015

Please submit electronically via the EasyChair system at https://easychair.org/conferences/?conf=ichi2015 (Please select the track for Data Analytics Challenge.)

Please contact the Healthcare Data Analytics Challenge Chair – Dr. Lakshmish Ramaswamy (laks@cs.uga.edu) if you have any questions or need additional information about the challenge.

]]> https://cs.utdallas.edu/ichi2015/contributors/healthcare-data-analytics-challenge/feed/ 0 https://cs.utdallas.edu/ichi2015/contributors/call-for-industry-track/ https://cs.utdallas.edu/ichi2015/contributors/call-for-industry-track/#comments Tue, 07 Apr 2015 23:37:11 +0000 http://cs.utdallas.edu/ichi2015/?page_id=655 SCOPE OF THE INDUSTRY TRACK

We cordially invite submissions of papers describing research, innovation and implementations that are applicable and show demonstrate high practical value to the industry in areas including but not limited to:

• Information technologies and tools for healthcare delivery and management
• Health data acquisition and visualization, privacy preservation
• Data analytics, data mining, and machine learning
• Healthcare data & knowledge management and decision support
• Healthcare actuarial analytics
• Provider network analytics
• Community benefit systems
• Social behavior and network systems
• Health information systems
• Healthcare communication networks and environments
• Smart health technologies

The application domains of interest include, but are not limited to providers, payors, public health organizations, other healthcare industry, government, or non-profit settings. The primary emphasis is on papers that advance the understanding of, and show how to deal with, practical issues related ranging from privacy, data exchange and sharing to deploying analytics technologies. This track is distinct from the Research Track in that submissions solve real-world problems and focus on systems that have large utility in real word healthcare industry.

SUBMISSION AND PUBLICATION

The industry track will accept both short papers and demonstrations that have clear applications in the industry or government.

Short papers (2-4 pages) should describe innovative ideas or implementations of practical significance with validated results. They may also provide insight into issues and factors that affect the successful use and deployment of information and analytic systems or new interesting discoveries made from data that are useful to the community.

Papers submitted for demonstration should be 4 pages in limit including all parts of a proposal: title, abstract, body, and bibliography. The demo paper should provide a description of the objective of the system, the novel intellectual content of the underlying system and of the system architecture. In addition an overview of what would be demonstrated to the audience should be clearly elicited. The system should solve a non-trivial real-world problem.

The camera-ready of accepted papers must observe the same page limits. Industry track content will be submitted for inclusion into IEEE Xplore as well as other Abstracting and Indexing (A&I) databases.

REVIEWING

The review process will include multiple experts from relevant industries for the applications.

ICHI uses blind reviewing, and therefore ICHI submissions should NOT have the names and affiliations of authors listed on the paper.

IMPORTANT DATES

• Full & Short papersubmission deadline: June 20, 2015 July 6, 2015
• Notification of acceptance: August 1,2015
• Camera-ready copy due: August 15,2015 August 21, 2015

Long Papers – 20 minutes; Short Papers – 15 minutes.

Posters – Up to 4’ x 6’

Best Paper Candidates Session:

• Session Chair: Sanda Harabagiu, University of Texas at Dallas; Wai-Tat Fu, University of Illinois, Urbana-Champaign; Fei Wang, University of Connecticut

1. Analyzing the Moving Parts of a Large-Scale Multi-Label Text Classification Pipeline: Experiences in Indexing Biomedical Articles
2. An RCT Simulation Study on Performance and Accuracy of Inexact Matching Algorithms for Patient Identity in Ambulatory Care Settings
3. Patient Centered Identification, Attribution and Ranking of Adverse Drug Events

Session 1: Processing Medical Information from Text

• Session Chair: Sanda Harabagiu, University of Texas at Dallas

1. Text Classification-based Automatic Recruitment of Patients for Clinical Trials A Silver Standards-based Case Study
2. Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource
3. Context-Aware Experience Extraction from Online Health Forums

Session 2: Social Media & Home-based systems

• Session Chair: Wai-Tat Fu, University of Illinois, Urbana-Champaign

1. The Evolution and Diffusion of User Roles in Online Health Communities – A Social Support Perspective
2. Dietary Habits of an Expat Nation: Case of Qatar
3. Object-centred recognition of human activity
4. Introducing Telerehabilitation in Patients with Multiple Sclerosis with Significant Mobility Disability Pilot Feasibility Study

Session 3: Drug Adverse Reactions, Risk Prediction and Clinical Events

• Session Chair: Robert Moskovitch, Columbia University

1. A Systematic Prediction of Adverse Drug Reactions Using Pre-clinical Drug Characteristics and Spontaneous Reports
2. Predicting Adverse Reactions to Blood Transfusion
3. Automagically Encoding Adverse Drug Reactions in MedDRA
4. A Clinical Decision Support System for Preventing Adverse Reactions to Blood Transfusion

Session 4: Forecasting and Detection

• Session Chair: Gregor Stiglic, University of Maribor

1. FluCaster: A Pervasive Web Application For High Resolution Situation Assessment and Forecasting of Flu Outbreaks
2. Fractals for Malignancy Detection in Dermoscopy Images
3. Calculating Patient Similarity Based On Respiration Induced Tumor Motion

Session 5: Prediction & Practice

• Session Chair: Fei Wang, University of Connecticut

1. Predicting Sequences of Clinical Events by using a Personalized Temporal Latent Embedding Model
2. Improving risk prediction of Clostridium Difficile Infection using temporal event-pairs
3. Design and evaluation of an interactive proof-of-concept dashboard for general practitioners
4. The Role of Explanations on Trust and Reliance in Clinical Decision Support Systems

Session 6: Visualization and Applications

• Session Chair: Jennifer Kim, University of Illinois at Urbana-Champaign

1. Visual Analysis of Relationships between Behavioral and Physiological Sensor Data
2. Flow-SNE: A New Approach for Flow Cytometry Clustering and Visualization

Session 7: Platforms, Devices, and Mobile Apps

• Session Chair: Wai-Tat Fu, University of Illinois, Urbana-Champaign

1. A Mobile Health System to Identify the Onset of Paroxysmal Atrial Fibrillation
2. Ecosphere Principles for Medical Application Platforms
3. Supporting Preliminary Decisions on Patient Requests for Access to Health Records An Integrated Ethical and Legal Framework
4. A Wearable NFC Wristband to locate Dementia Patients through a Participatory Sensing System

Session 8: Modeling and Learning

• Session Chair: Carlo Combi, University of Verona, Italy

1. A Data-Driven Behavior Modeling and Analysis Framework for Diabetic Patients on Insulin Pumps
2. The Role of Semantic and Discourse Information in Learning the Structure of Surgical Procedures
3. Feedback-Driven Radiology Exam Report Retrieval with Semantics

Session 9: Processing Clinical Notes

• Session Chair: Christopher Yang, Drexel University

1. Simultaneous Prognosis and Exploratory Analysis of Multiple Chronic Conditions Using Clinical Notes
2. A Predictive Chronological Model of Multiple Clinical Observations
3. Clinico-genomic Data Analytics for Precision Diagnosis and Disease Management

Posters from the 3 tracks:

Human Factors:

1. Untangling the Complexity of Connected Health Evaluations POSTER
2. Comparison of patient empowerment frameworks POSTER
3. An Easily Adopted Markup Discipline For Annotating Electronic Medical Records with Ontological and Epistemological Qualification: Toward Disciplined Asterisks, Parentheticals, Marginalia, Footnotes, and Hashtags

Systems:

1. A Framework for Mining Evolution Rules and its Application to the Clinical Domain
2. An HL7 Data Pseudonymization Pipeline
3. A prototype of mobile app/EHR communication through standards for home treatment of transcranial Direct Current Stimulation
4. Anatomical District Recognition in CT Bio-Images
5. Ontology-based visualization of healthcare data mined from Online Healthcare Forums
6. Identifying Documentation of Delirium in Clinical Notes through Topic Modeling (short)
7. Detection of episodes of Major Depression in older adults through physiological markers and movement patterns Case Study
8. BPMN-based Representation and Comparison of Clinical Pathways for Catheter-related Bloodstream Infections
9. A Smartwatch Software Architecture for Health Hazard Handling for Elderly People
10. LiSE: a personal booklet for Health care annotation
11. Familiar Video Stories as A Means for Children with Autism: An Analytics Approach

Data Analytics:

1. New Accurate Automated Melanoma Diagnosing Systems
2. Evaluation of Pose Tracking Accuracy in the First and Second Generations of Microsoft Kinect POSTER
3. Discovering and Validating Breast Cancer Treatment Correlations using an Associative Memory Model and Statistical Methods POSTER
4. Energy Saving using Scenario based Sensor Selection on Medical Shoes POSTER
5. An adaptive rule-based approach to classifying activities of daily living POSTER
6. Temporal Pattern and Assoication Discovery of Diagnosis Codes using DeepTemporal Pattern and Association Discovery of Diagnosis Codes using Deep Learning POSTER
7. Smartphone Inference of Alcohol Consumption Levels from Gait POSTER
8. Elderly Mobility and Daily Routine Analysis Based on Behavior-Aware Flow Graph Modeling POSTER
9. Process Mining applied to Laboratory Workflow: a comparison between two sites

Tutorials:

1. Tutorial 1: Data Analytics in Healthcare Informatics – Fei Wang and Gregor Stiglic
2. Tutorial 2: Robust Medical Monitor Design – James Weimer, Oleg Sokolsky, and Insup Lee
3. Tutorial 3: Ontology and Knowledge Sharing in E-Health – Morcous Massoud and Reham Ikram

Non-Refereed Abstracts:

1. Personalized health plan ranking –One application of cloud computing to health care data
2. Finding difficult-to-disambiguate wordsTowards an efficient workflow to implement word sense disambiguation
3. Location-Dependent Vocabularies and Speaker Style Personalization for Accurate Mobile Diet Recognition
4. Feasibility Study of A Machine Learning Approach to Predict Dementia Progression
5. Healthcare Collaborative Network Based on Common KADS Methodology
6. Older Adults Technology Assessment, Use and Needs for Health Applications
7. Exploring Statistical GLCM Texture Features for Classifying Food Images
8. Virtual Sleep Laboratory for Population Health

Technical Demo Session:

1. Knowledge Management of Controlled Vocabularies for Semantic Interoperability of Healthcare Applications.
2. Summit: A Method and Software Application for Analyzing Healthcare Technology Investments.
3. Providing Full Semantic Interoperability for the Fast Healthcare Interoperability Resources Schemas with Resource Description Framework

Doctoral Consortium Papers:

1. How do persons with Mild Acquired Cognitive Impairment use eservices and social media? Results from a Swedish national survey.
2. Prediction and Tracking Changes in Bio-medical Sensor Data
3. Robot-assisted Rehabilitation for Smart Assessment and Training.
4. Human Motion Analysis and Vision-Based Articulated Pose Estimation.
5. Augmenting drug discussions in general practice.
6. Information System Hazard Analysis and Mitigation.
7. Applying lessons learned from the Birmingham Free Clinic dispensary to inform pharmaceutical supply chain management in low-resource settings
8. Predicting User Participation and Detecting User Role Diffusion in Online Health Communities
9. Discovering the Temporal Interactions between Clinical Observations
10. Toward a complete database of drug repurposing candidates extracted from Social Media, Biomedical Literature, and Genetic data.
11. Biomedical Named Entity Recognition with Less Supervision.
12. Learning the Structure of Surgical Procedures From Operative Notes.
13. Simultaneous prognosis of multiple chronic conditions from heterogeneous EHR data
14. Implicit Information Extraction from Clinical Notes.
15. Strategies for Handling Missing Data in Detecting Postoperative Surgical Site Infections
16. Articulating a framework for patient empowerment to support greater e-health integration.

Industry Track Papers:

1. A Web-based Application for Visualizing the CMS Referral Network
2. Design and implementation of a privacy aware framework for sharing electronic health records
3. A Middleware to Support HL7 Standards for the Integration between Healthcare Applications

Data Analytics Challenge Finalists:

1. “Did You Know?” A Rule-based Approach to Finding Similar Questions on Online Health Forums
2. Healthcare Data Analytics Challenge.
3. Retrieval of Semantically Similar Healthcare Questions in Healthcare Forums
4. Golden Retriever: Question Retrieval System
5. Similarity in Patient Support Forums Using TF-IDF and Cosine Similarity Metrics
6. IEEE ICHI Healthcare Data Analytics Challenge

Smart and Connected Health Workshop Papers:

1. 360^­o Quantified Self
2. In-situ Measurement and Prediction of Hearing Aid Outcomes Using Mobile Phones
3. Extraction of Clinical Phenotypic Information from Online Heterogeneous Healthcare Networks
4. Design, Development, Deployment of a Telemedicine System in a Developing Country: Dealing with Organizational and Social Issues
5. SpareMe How: Towards an Empathetic Tool for Helping Adolescents & Teenagers Cope with Sickle Cell
6. Automated Detection of Sleep Disorder-Related Events from Polysomnographic Data
7. mHealth Platform for Breast Cancer Risk Assessment
8. Modeling Disease Spread at Global Mass Gatherings: Hajj as a case study.
9. Information Technology Challenges for Mobile Integrated Healthcare

Health Information Quality Workshop Papers:

1. What’s to Learn from Unvalidated Sources of Health Information?
2. The Impact of Senior-Friendliness Guidelines on Seniors’ Use of Personal Health Records

 We cordially invite you to submit your contribution to the non-refereed extended abstract track of the IEEE International Conference on Healthcare Informatics (ICHI 2015).

Vipin Gopal

Enterprise Vice President, Clinical Analytics, Humana

Biography

Dr. Vipin Gopal is the Enterprise Vice President of Clinical Analytics at Humana, a Fortune 100 company.  In this role, Dr. Gopal is responsible for the organization that develops and applies advanced analytics that shapes Humana’s clinical strategy, operations, programs and quality.  He is an expert in developing differentiating analytic competencies, and has previously led analytic organizations in diverse companies ranging from industrial conglomerates to healthcare.  Dr. Gopal obtained his Ph.D. from Carnegie Mellon University and B.Tech. from Indian Institute of Technology, Bombay, both in Engineering, and has an MBA from New York University Stern School of Business.  He has served on the organizing/advisory committees of many international analytic conferences and was previously Associate Editor of IEEE Transactions on Control Systems Technology.  Most recently, Dr. Gopal was the Chairperson of the World Congress Leadership Summits on Predictive Analytics held in October 2010 and August 2011, and the Data Analytics Summit in April 2012, and delivered the Opening Plenary at the Seventh National Predictive Modeling Summit in December 2013.

Adam Wilcox

Medical Informatics Director, Homer Warner Center for Informatics Research, Intermountain.

Leveraging Information Technology for Personalized Medicine: Near Future and Next Steps

Biography

Adam Wilcox, PhD, is the Director of Medical Informatics at Intermountain Healthcare.  He has spent over 15 years in clinical informatics and clinical research informatics, much of that in supporting comparative effectiveness and patient-centered outcomes research.  At Intermountain, he leads efforts in applying health information technology to quality improvement processes, supports health IT applications to primary care, and leads Intermountain’s clinical decision support efforts.  He also directs Intermountain’s analytic health repository, where he leads the development of a more research-accessible database extracted from electronic health records.  Prior to his return to Intermountain, he was an associate professor in the Department of Biomedical Informatics at Columbia University, where he was the initial principal investigator for the Washington Heights/Inwood Informatics Infrastructure for Comparative Effectiveness Research (WICER) project. He also directed the clinical data warehouse, the clinical data repository and legacy electronic health record, a local health information exchange, and the informatics support for the Herbert Irving Comprehensive Cancer Center.  He has broad experience in both applied and research informatics, and was the creator and director of the Research Methods in Informatics course at Columbia University.  In 2015, Dr. Wilcox was appointed a member of the PCORI Methodology Committee. He is an elected fellow of the American College of Medical Informatics, is a senior editor for eGEMs, and serves on the Clinical Informatics Subcommittee for the American Board of Preventive Medicine, which administers the board examination for the clinical informatics subspecialty. He has authored over 100 book chapters, peer-reviewed articles and abstracts, and has presented at conferences and institutions across the country.

Ninad Mishra

Health Scientist at CDC working in National Center for Public Health Informatics (NCPHI)

Biography

Dr. Ninad Mishra, MD is a lead health scientist with National Center for STD, HIV, Hepatitis and TB Prevention (NCHHSTP) at Centers for the Disease Control (CDC). Dr. Mishra’s primary focus lies in the intersection of clinical informatics, clinical analytics, and quality-of-care. The common theme across Dr. Mishra’s work relates to helping clinicians make better decisions, provide quality care, and improve care delivery processes through the use of health information technology.

Dr. Mishra is currently leading a number of CDC funded projects including one that uses cloud based services to provide contextual knowledge at the point-of-care through electronic health systems. The system has been undergoing testing and evaluation with partners namely Alliance of Chicago community health centers, National Association of Community Health Centers (NACHC) and GE Health. Dr. Mishra is also leading projects on quality related e-measures from (Electronic Medical Record) EMR Data. The latest e-quality project was showcased in partnership with Commonwealth Informatics based in Boston, MA under a small business innovation research grant. The goal of the project was to build and demonstrate a prototype for eMeasure calculation that conformed to the national specifications for both the numerator and denominator and that worked with clinical data from the Epic EMR at the Metro Health System of Northeast Ohio. A long-term goal is to develop an eMeasure application that will be easy to install, configure, and use with a broad variety of different EMR systems.

Ninad had been consulted by the Institute of Medicine(IOM) to formulate strategies for digital health technologies in the past. He has previously served as Vice Chair of the Surveillance Science Advisory Group (SurvSAG) evaluation subcommittee and has served on the AMIA (American Medical Informatics Association) publication committee. He also assisted National Biosurveillance Advisory committee, established by a presidential directive, while being on a short term detail to Biosurveillance Coordination Unit (BCU).

Chris Lunt

VP Engineering, GetInsured

“Bringing the Model to the Mountain”

You have found actionable signal in your data, now you want people to do something with it. A practical guide to innovation and adoption, including managing organizational resistance, structuring implementation, and overseeing the lifecycle of your change.

Biography

Chris Lunt is a VP Engineering at GetInsured, a company that builds health insurance exchanges for states, companies and the consumer market.  Previously he was an “HHS entrepreneur” with the US Department of Health and Human Services, where he created the “MAGI eligibility-in-the-Cloud” effort.  He has been a technology executive for 10+ years, with 1 IPO, and 10 social networking patents now owned by Facebook.  If you will sing, he’ll play his ukulele for you.

Celette Skinner

Endowed Title Parkland Community Medicine Professorship
Department of Clinical Science, Simmons Comprehensive Cancer Center

TITLE
Development of the Parkland-UT Southwestern Colonoscopy Reporting System (CoRS) for evidence-based colon cancer surveillance recommendations

ABSTRACT
OBJECTIVE: Through colonoscopy, polyps can be identified and removed to reduce colorectal cancer incidence and mortality . Appropriate use of surveillance colonoscopy, post polypectomy, is a focus of healthcare reform.
MATERIALS AND METHODS: We developed and implemented the first EMR-based Colonoscopy Reporting System (CoRS) that matches endoscopic findings with guideline-consistent surveillance recommendations and generates tailored results and recommendation letters for patients and providers.
RESULTS: In its first year, CoRS was used in 98.6% of indicated cases. Via a survey, colonoscopists agreed/strongly agreed it is easy to use (83%), provides guideline-based recommendations (89%), improves quality of Spanish letters (94%), they would recommend it for other institutions (78%), made their work easier (61%), and led to improved practice (56%).
DISCUSSION: CoRS’ widespread adoption and acceptance likely resulted from stakeholder engagement throughout the development and implementation process.
CONCLUSION: CoRS is well-accepted by clinicians and provides guideline-based recommendations and results communications to patients and providers.

Biography

Dr. Skinner was named Chief of the Division of Behavioral & Communication Sciences in the Department of Clinical Sciences, and Associate Director of Population Research & Cancer Control for the Simmons Cancer Center in the spring of 2007. This appointment followed her tenure as Associate Director for Population Research and Interim Director of Duke Comprehensive Cancer Center’s Research Program in Cancer Prevention, Detection & Control. Dr. Skinner received her MA in Communications Research from the Wheaton Graduate School and PhD in Health Behavior from the University of North Carolina School of Public Health.

Prior to her move to UT Southwestern, Dr. Skinner was a member of the Siteman Cancer Center of Washington University in St. Louis (1993-1998) and the Indiana University Simons Cancer Center (1991-1993).

Dr. Skinner’s research interest focuses on communications interventions to promote health behavior change, especially using computer-tailored interventions (CTIs). She was a member of the National Cancer Institute’s first Working Group on CTIs in 1994 and is Co-chair of the NCI’s newly established Research Group for Disseminating CTIs for integration into public health and clinical practice. Her extramural service has included membership on the National Comprehensive Cancer Network Breast Cancer Screening Panel, the North Carolina Advisory Committee on Cancer Control, and charter membership on the NIH’s Community-Level Health Promotion Study Section. She is an author of the upcoming second edition of the textbook, Tailoring Health Messages: Customizing Communication with Computer Technology.