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Speakers Predictive Analytics World Healthcare 2014
 Daniel Bailey

Daniel Bailey

Director of Commercial Analytics

Elder Research

Daniel has been helping organizations navigate the complexities of creating actionable insights from their data for more than 10 years. At Elder Research, Daniel is responsible for leading the Commercial Analytics group. He leads highly specialized teams in the building and assessment of analytical models, having worked across a wide-range of industries including insurance, oil and gas, and manufacturing. Examples of Daniel's successes include creating custom scoring algorithms to identify outliers and rare business events, providing model validation audits, and developing ensemble models that help reduce operational downtime and associated losses.

Daniel earned a BS degree in Applied Mathematics and Master's Degree in Advanced Analytics from North Carolina State University. Prior to joining ERI, he owned a project and logistics management consulting firm and served as a Captain in the US Army in numerous leadership and intelligence roles. He is an expert data scientist, comfortable with diverse data sources in diverse industries.

Session: Improving Provider Performance and Patient Outcomes with Evidence-Based Scoring

 Katrina  Belt

Katrina Belt


Baptist Health

Katrina received her bachelor of arts in business administration from Huntingdon College and a master's of public administration at New York University.

Since joining the UAB Health System, Katrina has played a key role in public finance, affiliation and acquisition transactions for the health system.

Prior to her arrival at UAB, Katrina acted as liaison with IBM for the New York City Department of Finance to facilitate a citywide e-government initiative, and as a project consultant to the New York City Partnership and Chamber of Commerce in the aftermath of Sept. 11, 2001.

Katrina continues to serve as a resource to the UAB Health System. She has also held former posts including treasurer of the UAB Health System, associate director of the Alabama-West Florida Conference of UMC, assistant director of Admission for Huntingdon College and ombudsman for the Robert F. Wagner Graduate School of Public Service.

Session: Predicting the Invisible Patient: Using Predictive Analytics to Reduce Suffering, Save Lives, and Optimize Cost of Care

 Charles  Boicey

Charles Boicey

Enterprise Analytics Architect

Stony Brook Medicine

Charles Boicey, MS, RN-BC, CPHIMS is the Enterprise Analytics Architect at Stony Brook Medicine. Prior to joining Stony Brook Medicine in April 2014 he led the team at the University of California, Irvine that developed "Saritor" an open source Healthcare Data Platform comprised of "Big Data" technologies. The Saritor platform is capable of ingesting any healthcare data in it's native state and in it's entirety. Structured, unstructured, device, wearable and social are a few of the types ingested. Machine Learning, Pattern Recognition, Anomaly Detection, Graph Analysis and Predictive Analytics are components of the system.

Charles clinical practice includes Trauma/Surgical Intensive Care Unit nursing. After making a transition from clinical practice to clinical informatics he obtained his MS in Technology Management from Stevens Institute of Technology. He is the Vice President of the American Nursing Informatics Association and a member of the HIMSS Innovation Committee.

Session: Healthcare 2020: How Emerging Technologies Will Advance Clinical Practice and Research

 Aran  Canes

Aran Canes

Sr. Healthcare Economist

Open Minds

Aran Canes has been leveraging his expertise in data analytics since graduating from the University of Virginia in 1998 with a BA in Physics. He worked for several years at an economics consulting firm and the Antitrust Division of the Justice Department, during which he calculated damages from intellectual property lawsuits, determined potential fines for collusion, and analyzed the competitive effects of mergers.

Since graduating from the University of Maryland in 2010 with a MA in Economics, Aran has been working in health care-in program integrity, quality improvement and pharmaceuticals. He has built models to detect pain killer over-utilization, created metrics to compare hospice performance, analyzed regional variation in care for Pennsylvania Medicaid recipients and assessed the effects of different pharmaceutical policies.

While employed by Open Minds, he worked closely with the Medical Director of Pennsylvania Medicaid to utilize data science to improve the state's Medicaid program. He is currently a Senior Analytic Consultant at Cigna, where he is using his background and experience to investigate ways to improve health care in the private sector.

Session: Superutilizers Made Simple. Identifying High-Cost Recipients Using a Model Any Medicaid Agency Could Implement

 John  Cromwell, MD

John Cromwell, MD

Associate Professor

University of Iowa Hospitals & Clinics

John W. Cromwell MD is Clinical Associate Professor of Surgery at the University of Iowa where he serves as the Director of the Division of Gastrointestinal, Minimally-Invasive and Bariatric Surgery, Surgical Director at the James A. Clifton Center for Digestive Diseases, Quality Officer for Surgical Services, and faculty in the Interdisciplinary Program in Health Informatics. Dr. Cromwell is also the Chief Medical Officer for Entac Medical, LLC, a medical device startup company developing wearable technology for predicting postoperative complications.

He received his BS in Chemistry from Nebraska Wesleyan University and his MD from the University of Minnesota Medical School. He was the recipient of the University of Tennessee Innovation Award in 2011 and recipient of the University of Iowa Research Foundation Inventor Award in 2012.

Dr. Cromwell has published widely on the topic of predictive modeling and automated decisioning systems for improving patient outcomes, is a frequent speaker at predictive modeling venues as well as medical conferences, and most recently served as Co-Chair of the First International Workshop on Hospital Readmission Prediction and Clinical Risk Management at the 2013 IEEE International Conference on Healthcare Informatics.

Keynote: Real-Time Modeling of Surgical Site Infections
Expert Panel : Healthcare Analytics: Potential vs. Reality

 Devore  Culver

Devore Culver

Executive Director and CEO


Dev is HealthInfoNet's Chief Executive Officer. He joined HealthInfoNet in this capacity in June of 2006 and has worked to build the organization from a working concept to an organization that is nationally recognized as operating one of the most successful statewide health information exchanges in the U.S. Prior to coming to HealthInfoNet, Dev held Health IT leadership positions in both the for profit and not for profit sectors including time with EHR vendors Eclipsys and Cerner as well as sixteen years as the Chief Information Officer for Eastern Maine Healthcare System. He earned his Master of Management degree from Northwestern University and his Bachelor of Arts degree from Brown University.

Session: Deploying Predictive Patient Risk Models through a Heialth Information Exchange (HIE)

 Jeff Deal

Jeff Deal

Chief Operating Officer

Elder Research

Jeff Deal is the Chief Operating Officer for Elder Research, the nation's leading data science, machine learning, and artificial intelligence consultancy. He has also been the Chair of the Predictive Analytics World for Healthcare conference since its inception in 2014.  In his role at Elder Research, Jeff oversees the operations of the business including contracting, finances, regulatory/legal issues and human resources. Jeff has worked with dozens of clients to understand their business needs and organizational goals and, in the process, has gained insight into organizational obstacles to successful data analytics engagements. His talk on the Top 10 Data Mining Business Mistakes has been well received at prior Predictive Analytics World conferences. In 2016, Jeff and the Elder Research President & CEO, Gerhard Pilcher, published, Mining Your Own Business: A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics.

Jeff has more than 30 years of experience in business operations, planning, and government relations, primarily in the health care industry. Prior to ERI, he was the president of a health planning consulting business that assisted hospitals and physicians with operational analysis, forecasting, and navigating through complex regulatory processes. Before that, Jeff spent 16 years in hospital administration with responsibility for clinical, support, and planning functions. Jeff has a Master of Health Administration degree from Virginia Commonwealth University and an undergraduate degree from the College of William and Mary.

Conference Chair Welcome

Dr. John Elder, Ph.D.

Dr. John Elder, Ph.D.

Founder & Chair

Elder Research


John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

Special Plenary Session: The Peril of Vast Search (and How Target Shuffling Can Save Science)

 Nish Hartman

Nish Hartman

Global Director of Healthcare

Predixion Software

Nish Hartman, Global Director of Healthcare at Predixion Software, is an experienced leader at building and executing strategies for innovative healthcare solutions. Nish gained much of her hands on leadership experience early in her career when she was responsible for developing, deploying and managing a global account organization for Fortune 500 clients. Prior to joining Predixion, she held leadership positions at Microsoft, Sun Microsystems and Oracle.

Nish has been an active participant in professional and community focused organizations including The American College of Healthcare Executives, a former Board Member of North Carolina HiMMS and Fellow for the Batten Leadership Institute. As a student of the complete healthcare system Nish understands the challenges of Healthcare information management and is focused on applying the latest information technology treatments to promote wellness.

Sponsor Presentation: Preventable Hospital Readmissions are a Significant - yet Avoidable - Cost

 Thomas Hill, Ph.D.

Thomas Hill, Ph.D.

Executive Director Analytics

Dell Software Group

Dr. Thomas Hill is Executive Director for Analytics at Dell Software Group. He joined Dell through the acquisition of StatSoft Inc. in April 2014, where he had been Senior Vice President for Analytic Solutions for over 20 years and was responsible for building out Statistica into a leading analytics platform. Dr. Hill received his Vordiplom in psychology from Kiel University in Germany and earned an M.S. in industrial psychology and a Ph.D. in psychology and quantitative methods from the University of Kansas. He was on the faculty of the University of Tulsa from 1984 to 2009, where he conducted research in cognitive science and taught data analysis and data mining courses. He has received numerous academic grants and awards from the US National Science Foundation, the National Institute of Health, the Center for Innovation Management, and other institutions. Over the past 20 years, his team has completed diverse consulting projects with companies from practically all industries and has worked with leading financial services, insurance, retailing, manufacturing, pharmaceutical, healthcare, and other companies in the United States and internationally on identifying and refining effective predictive modeling solutions for a broad scope of applications. Dr. Hill has published widely on innovative applications for data mining and predictive analytics and is also the author (with Paul Lewicki, 2005) of "Statistics: Methods and Applications," the "Electronic Statistics Textbook" (a popular on-line resource on statistics and data mining), and a co-author of "Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications" (2012) and "Practical Predictive Analytics and Decisioning Systems for Medicine" (Elsevier/Academic Press, 2014). Hill is also a contributing author to the popular "Handbook of Statistical Analysis and Data Mining Applications (2009)."

Gold Sponsor Presentation : Applying Predictive Analytics to Improve Healthcare Delivery and Outcomes - Lessons Learned

Dr. Martin Kohn

Dr. Martin Kohn

Chief Medical Scientist

Sentrian (formerly with IBM Watson)

Dr. Martin Kohn is Chief Medical Scientist at Sentrian. His research work includes healthcare population analytics and the role of expert systems in the clinical decision process. Dr. Kohn is a board-certified emergency physician with over 30 years of hospital-based practice and management experience. He is an alumnus of MIT, Harvard Medical School and NYU, and is a Fellow of the American College of Emergency Physicians and the American College of Physician Executives. He is board certified in Clinical Informatics through the American Board of Preventive Medicine. Dr. Kohn is on the editorial board of the Journal of Emergency Medicine and has published multiple articles and book chapters on clinical, technical and management subjects.

Prior to joining Jointly Health, Dr. Kohn was the Chief Medical Scientist for Care Delivery Systems in IBM Research where he led IBM's support for the transformation of healthcare, including the use of the Watson supercomputer in healthcare. He speaks frequently on the issues of healthcare transformation, the role of information technology, the Patient Centered Medical Home and clinical decision support. Dr. Kohn is a co-author of IBM's white paper "Patient-Centered Medical Home - What, Why and How." Dr. Kohn was previously in IBM Healthcare Strategy and Change, which helped healthcare systems and clinicians optimize process and make best use of health information technology.

His extended training and experience in health care management, policy and operations, as well as his background as a systems engineer, enable him to communicate with all stakeholder groups. He has had major roles in addressing the interaction between clinical process and information technology in projects involving information sharing, clinical process re-design, patient access and policy.

Keynote: Big Data and Clinical Decision Support

 Linda  Miner, Ph.D

Linda Miner, Ph.D


Southern Nazarene University

Linda A. Winters-Miner, PhD, has been an educator for over 30 years, in teacher education and statistics & research design. She spent nearly two years as a site coordinator for a major (Coxnex) drug trial.

For 23 years Miner directed academic programs, with an adjunct faculty comprising over 50 instructors, for Southern Nazarene University- Tulsa. During the past 12 years she has designed and been author of many of the tutorials in two predictive analytic books published in 2009 and 2012.

At present, she teaches undergraduate statistics & research, teaches online for University of California-Irvine and is lead author on a book on predictive analytics for medicine and healthcare delivery that will be released in 2014. She has written some of the major predictive & prescriptive analytic and decisioning models as tutorials for this latest book in the series.

Session: Developing a Mortality Prediction Model for Disseminated Intravascular Coagulation (DIC)

 William  Moschella

William Moschella

CEO & Co-Founder


Bio is forthcoming.

Gold Sponsor Presentation : Real-Time Analytics: What is possible and how do you optimize performance

 Robert  Palmer

Robert Palmer

President and CEO


Robert is an experienced technology developer, entrepreneur and executive with over 20 years of industrial experience in developing analytic models for healthcare (payers, providers, life sciences), financial services, private equity, professional sports, and manufacturing. Robert developed the firm's healthcare analytics products including comparative effectiveness analysis and predictive analytics for clinical and economic outcomes. Robert has also held executive leadership across various privately held companies and startups.

Robert holds an MBA with a focus on finance from Washington University, Olin School of Business, and a BS in Business Administration Regis University. He is an adjunct with the Hatchery Program, Skandalaris Center for Entrepreneurial Studies at the Olin School of Business and a lecturer on business valuation, planning, financial modeling and analytics. He is also a member of the William Greenleaf Eliot Society and the YPO (Young Presidents Organization).

Session: Using Predictive Analytics to Empower Cancer Patients through "MyCancerJourney"

 Jay  Piccirillo

Jay Piccirillo

Professor, Vice-Chair Research, and Director of the Clinical Outcomes Research Office

Washington University in St. Louis School of Medicine

Dr. Piccirillo is a Professor of Otolaryngology, Medicine, and Biostatistics and leads the Clinical Outcomes Research Office at Washington University School of Medicine in St. Louis. His National Institutes of Health-supported research interests include the importance of comorbidity in the care of cancer patients and evaluation of cancer statistics, the use of functional connectivity MRI to study chemotherapy-induced cognitive impairment, and the development of MyCancerJourney's MyNavigator (Prognostigram) (web-based programs to empower cancer patients with tailored health information).

Session: Using Predictive Analytics to Empower Cancer Patients through "MyCancerJourney"

 Shaju  Puthussery

Shaju Puthussery

Chief Analytics Officer


Shaju Puthussery is an experienced executive currently serving as the Chief Analytics Officer and Vice President for DentaQuest, one of the largest dental insurance providers in the US.

Shaju has been providing the vision and roadmap for infusing analytics across all areas of the dental insurance industry and has served as a panel speaker at numerous health conferences.

Session: Improving Provider Performance and Patient Outcomes with Evidence-Based Scoring

 George Savage

George Savage

Co-Founder & Chief Medical Officer

Proteus Digital Health

George Savage is chief medical officer and co-founder of Proteus Digital Health, and formerly the company's vice president of research and development. He sees Digital Medicine as an invaluable collaboration platform for patient and physician, integrating information about a patient's response to therapy directly into everyday healthcare.

George is focused on developing the clinical and economic evidence needed to secure global regulatory approvals and spur widespread adoption of Proteus's ingestible sensor platform. He serves on the board of the California Life Sciences Association, the Boston University College of Engineering advisory council, and in 2016 was elected a Fellow of the American Institute for Medical and Biological Engineering.

George holds a B.S. in biomedical engineering from Boston University, an M.D. from Tufts University School of Medicine, and an M.B.A. from Stanford University Graduate School of Business. He completed postgraduate training in surgery at the University of Massachusetts and is licensed to practice medicine in California. George has a successful 27-year track record of starting and developing technology-based healthcare companies in Silicon Valley.

Keynote: Predictive Analytics: Advancing Precision and Population Medicine
Expert Panel : Healthcare Analytics: Potential vs. Reality

 Nephi  Walton

Nephi Walton

MD, MS Biomedical Informatics

Washington University / University of Utah

Nephi Walton received an MD as well as a masters in Biomedical Informatics from the University of Utah, where his work was focused on using data mining and predictive analytics in the fields of genetics, bio-surveillance and hospital management.

He was the winner of the 2008 American Medical Informatics Association National Data Mining Competition. He has more than 7 years of experience using neural networks, Bayesian networks, decision trees, and other data mining methods for predictive analytics. He has 18 years of experience in industry programming and managing databases, including the development of award winning complex 3D and mobile applications.

In addition to his work in industry he is a physician at Washington University where he is completing a dual residency in both pediatrics and genetics. He has contributed to several books and papers on predictive analytics and data mining.

Session: Using Predictive Analytics to Forecast Hospital Patient Volume for Hospital Resource Allocation and Staffing

 Ken Yale, JD, DDS

Ken Yale, JD, DDS


University of California - Irvine

Ken is trained in population statistics, medicine/dentistry, and law. He worked in clinical practice, data science, care management, and health regulations. Ken was a government official in the US Senate and White House. After that he was Founder/CEO of Advanced Health Solutions and held executive positions at CorSolutions, Matria Healthcare, UnitedHealth Group, and Aetna. Ken held leadership roles in the Maryland State Task Force on Electronic Medical Records, the University of Maryland Center for Health Information and Decision Systems, and Utilization Review Accreditation Commission (URAC). He is a frequent author and speaker, including Handbook of Statistical Analysis and Data Mining Applications; Clinical Integration: Population Health and Accountable Care; Divining Healthcare Charges for Optimal Health Benefits Under the Affordable Care Act. With a team of data science industry experts he leads a certificate program in Healthcare Predictive Analytics at University of California, to train the next generation of health data scientists.

Session: Significant Improvements in Population Health Management
Expert Panel : Healthcare Analytics: Potential vs. Reality

 Scott  Zasadil, Ph.D

Scott Zasadil, Ph.D

Chief Scientist

UPMC Health Plan

Dr. Zasadil holds a Ph.D. in Mathematical Physics from Indiana University with a specialization in Partial Differential Equations, Numerical Analysis, and Statistical Mechanics. He is the Chief Scientist for the Health Economics department at UPMC Health Plan where he utilizes machine learning and data mining techniques in the development of predictive models. His prior job titles have included positions as: mathematician, physicist, software engineer and scientist. He has been involved in the programming, modeling, simulation and data analysis of projects in the fields of atmospheric physics, radiation oncology, supply chain logistics, and medical informatics.

Session: Using Association Rule Mining to Identify Risks for Readmissions

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