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.
Health Reform, through implementation of the Affordable Care Act and related legislation and regulations, presents a new array of issues, opportunities and challenges to address through application of predictive analytics. Marketplace changes fueled by reform, notably involving new provider delivery and payment models, add to the demand for applicable 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. 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 Fifth 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 such key topics as health care reform; evolving health plan-provider contractual arrangements; employer programs to identify and treat members with chronic diseases; reducing fraud and improper payments; agent based modeling: application to cost effectiveness analysis of preventive strategies; Medicare predictive analytics; predictive modeling case studies; predictive modeling basics and beyond; 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.
Who Should Attend:
- Explore the current environment regarding predictive modeling concepts, trends, initiatives, and results
- Delve into the role and impact of predictive analytics in various aspects of health care reform, including newer health plan - provider contractual arrangements, delivery models, and expanded population coverage
- Grasp the role and detailed considerations for predictive analytics in reducing fraud and improper payments
- Offer insights into new innovations in predictive modeling techniques and applications
- 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
Specifically, the Summit will benefit leadership teams and key staff from health plans, self-insured employers, hospital systems, provider networks, 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
- 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
- Healthcare Informatics Staff
- Information Technology Staff
- Planning and Strategy Staff
- Predictive Modeling and Analytics Staff
- Provider Relations and Contracting Staff
- Quality Management Staff
- Research Analysts
- System Vendors and Integrators