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, hospitals, physicians and other stakeholders magnify to improve clinical, quality, operational, and financial performance, the importance, demand for and role of predictive analytics within healthcare organizations continue to intensify and expand.
The issues facing stakeholders in this arena continue to become more complex in this post-ACA environment, as well as while clinical integration and outcomes initiatives advance, and technological developments present opportunities and challenges that require organizations to keep pace.
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 Ninth National Predictive Modeling Summit provides nationally renowned ple-nary 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.
This year's Summit plenary sessions will tackle topics including: Making Predictive Analytics a Routine Part of Patient Care; The Role of Analytics in the Development of a Successful Readmissions Program; Documenting for defensibility in predicting healthcare fraud overpayments; Predictive Analytics at the Point Of Care; Predicting Consumer Choice in Medical Plan Elections; Using Actuarial Methods to Minimize Chronic Disease, Considerations for Population Segmentation in Population Health Management Programs; The value of authorization data to inform financial forecast-ing by self-insured companies; Utilizing Predictive Models to Target for Clinical and Diagnosis Gaps; and Putting the Building Blocks in Place for Effective Predictive Analytics at a Healthcare Organization. Preconference and Postconference sessions will address predictive modeling basics and beyond; and predictive modeling and clinical innovation.
Presentations during the Summit will provide the most current insights, informa-tion, 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.
Who Should Attend:
- Explore the current environment regarding predictive modeling concepts, trends, initiatives, and results
- Address challenges, issues, opportunities; strategies and innovations in the application of predictive analytics to key topics including leveraging EHR data; chronic disease management; clinical innovation; healthcare fraud overpayments; population health management; readmissions management; targeting gaps in care; and more
- Offer insights into new innovations in predictive modeling techniques and applications
- Consider clinical, actuarial, care management, payment and business perspectives of predictive modeling and risk assessment 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 includ-ing hospitals, health plans, provider networks and other stakeholders
- Understand the information technology, data and infrastructure require-ments 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, accountable care organizations, TPAs, insurance companies, government agencies, consulting firms, pharmaceutical companies, PBMs, solution developers and others, includ-ing 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 Analysts
- 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