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Predictive Modeling in health care is an analytics process involving assessment and adjustment of risk and behavior, applied to a given population based upon available data for purposes of stratifying that population according to their future probabilities of incurring a given outcome or behavior. The purpose of Predictive Modeling is to risk stratify a population to identify individual opportunities for intervention or action before the projected outcome has occurred.

As pressures on health plans and providers magnify to improve clinical, quality, operational, and financial performance; the demand for and role of predictive analytics within healthcare organizations continue to expand.

Prediction of risk for hospital readmissions, involved with initiatives to identify and intervene with applicable individuals at-risk, is emerging as a significant activity, despite various implementation challenges. Risk adjustment initiatives involved with emerging provider payment structures (such as value based purchasing, bundled payments, accountable care arrangements and more) that have been advanced by health reform and marketplace pressures require increased application of predictive analytics. Predictive Modeling has also emerged as a leading tool in the growing fight to defeat health care fraud in the Medicare, Medicaid and Commercial arenas.

The demand for advancing and managing Big Data, along with enhanced data mining to drive these and other initiatives also requires increased investment of resources. Furthermore, as Predictive Modeling in health care matures as a field, exciting developments continuously emerge with respect to available tools and technologies; applications in new and expanded functions and settings; refinements of techniques and data repositories; and external forces.

The National Predictive Modeling Summit provides the leading forum on predictive analytics applied to key health care functions, populations and settings, and will fully address the impact of these developments to best position attending professionals and their organizations for the future.

The Sixth National Predictive Modeling Summit provides nationally renowned keynote speakers covering a wide range of expertise applicable to the field of predictive modeling, in an innovative hybrid conference format, offering attendees the choice of in-person or Internet attendance.

Presentations during the Summit will provide the most current insights, information, experiences and solutions available regarding the role of and use of Predictive Modeling in the above key topics and much more. The Summit also provides the ideal networking opportunity for professionals throughout all industry sectors to interact, develop future relationships, discuss shared experiences and meet key contacts.

Learning Objectives:
  • Explore the current environment regarding predictive modeling concepts, trends, initiatives, and results
  • Examine predictive analytics initiatives to address identification and intervention of patients at-risk for hospital readmissions
  • Ascertain risk adjustment techniques and strategies for emerging provider payment structures including value based purchasing, bundled payments and accountable care arrangements
  • Grasp the role and detailed considerations for predictive analytics in reducing fraud and improper payments
  • Address Big Data and data mining challenges and solutions to drive predictive modeling initiatives
  • Analyze the challenges, issues and strategies to address Medicaid, Dual Eligible and Medicare populations
  • Offer insights into new innovations in predictive modeling techniques and applications
  • Delve into the current role and impact of predictive analytics in various aspects of health care reform,
  • Consider clinical, actuarial, care management, payment and business perspectives of predictive modeling as applied to specific functions
  • Examine predictive modeling applied to a variety of populations and settings
  • Gain a working knowledge of specific challenges being addressed by health plans, provider networks, health care organizations and purchasers of health care services
  • Understand the information technology, data and infrastructure requirements to undertake various predictive modeling applications
  • Share case experiences of predictive modeling initiatives already applied in the industry
  • Examine various solutions available to implement various types of predictive modeling programs
  • Provide a basic understanding of predictive modeling concepts, techniques and issues for those previously not intimately familiar with the subject
Who Should Attend:

Specifically, the Summit will benefit leadership teams and key staff from health plans, self-insured employers, hospital systems, provider networks, accountable care organizations, TPAs, insurance companies, government agencies, consulting firms, pharmaceutical companies, PBMs, solution developers and others, including the following individuals:

  • Chief Executive Officers
  • Chief Actuarial Officers
  • Chief Clinical Officers
  • Chief Information Officers
  • Chief Marketing Officers
  • Chief Medical Officers
  • Chief Operating Officers
  • Chief Science Officers
  • Chief Strategy Officers
  • Medical Directors
  • Actuarial and Underwriting Staff
  • Predictive Modeling and Analytics Staff
  • Healthcare Informatics Staff
  • Statisticians and Data Analyts
  • Business Intelligence Staff
  • Business Transformation Staff
  • Care and Case Management Staff
  • Clinical Research and Intelligence Staff
  • Decision Support Staff
  • Disease Management Staff
  • Employer Benefit Management Staff
  • Information Technology Staff
  • Planning and Strategy Staff
  • Provider Relations and Contracting Staff
  • Quality Management Staff
  • Research Analysts
  • System Vendors and Integrators
  • Fraud & Abuse Prevention and Recovery Executives and Staff
  • Claims Unit Executives and Staff
  • Health Care Economists

Overview | Agenda | Promotional Opportunities | Sponsors & Exhibitors
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