Description: This article describes methodologies for detection and deterrence of Medicare fraud. It also describes the validation of PRIDIT for fraud detection in Medicare.

Description: Renal disease is a very heterogenous medical condition whose end state is dialysis, a recurring cost intensive medical condition. Dialysis cost is one of the major medical cost drivers in USA. Insufficient and improper care management in the early stages of CKD (chronic kidney disease) leads to early incidence of end stage renal disease (ESRD) among CKD patients which not only leads to high medical costs, but also reflects poor health quality.

Description: Many life and health insurers are beginning to use Predictive Analytics (PA) for a variety of purposes. This article addresses the unique challenges and potential disruption PA brings to the risk manager, as well as the opportunities.

Description: This dissertation by Tia Sawhney will help you understand this issue and start measuring it, or start promoting equitable public policy.

Description: Explore wellness programs and their effectiveness within the LTC industry by attending the Considerations for LTC Wellness Programs webcast. You will experience discussions about design tactics and evaluation processes for programs, as well as discovering ways to assist policyholders achieve a sustainable and equitable life. There will also be a conversation about the current regulatory environment as it relates to LTC wellness programs. This webinar will focus on subsets of insured populations that are high risk of claim in order to properly manage care decisions and ensure unfair bias is avoided. Learn how to test for unfair bias and determine best possibilities on how to guard against this when testing is unavailable.

Description: Many life and health insurers are beginning to use Predictive Analytics (PA) for a variety of purposes. This article addresses the unique challenges and potential disruption PA brings to the risk manager, as well as the opportunities.

Description: This is a list of links to research papers on predictive modeling.

Description: Feature article discussing futurism and a study that contains in-depth descriptions of the Delphi and TIA methods; listings of the rationales and thought processes, the plausible future developments that could influence the values of these four economic variables and the resulting “fan of possibilities” for the values of these variables

Description: The article focuses on the use of predictive analytics in the development of experience studies, pros and cons of using predictive analytics versus traditional techniques, and the implications for setting assumptions and improving profitability.

Description: "Risk adjustment is an important aspect of establishing appropriate capitation rates. When a set of services is carved out for specific management under a sub-capitation, establishing appropriate adjustments for varying levels of underlying risk is more complicated. Dive into analytical and operational challenges and resolutions as presenters share more about developing a risk adjustment model specific to the carve-out of behavioral health services through a real-life case study. You will further explore a definition of the use case, availability of historical data sets, selection of the modeling approach, learnings from the iterative modeling process, and the potential application of the results. After attending this session, you will be able to: Understand why a behavioral health specific-risk adjustment model has business value Understand the unique challenges related to developing risk adjustment on member and cost subsegments Understand the impact of trade-offs between model complexity and interpretability in the context of implementation Increase awareness of data nuances and requirements unique to this type of project Describe analytic techniques that can be investigated for use in projects of similar business objectives"