Description: Review of a research project, co-sponsored by the SOA, which examined 83 organizations and over 150 programs that measure the quality and efficiency of hospitals and physicians.

Description: A study of disability experience examines cost burden and degree of disability, and how these measures vary across different subpopulations. This article summarizes a presentation given at the Society of Actuaries’ Living to 100: Survival to Advanced Ages International Symposium held on Jan. 7–9, 2008 in Orlando, Florida. An abstract of the author's paper was presented in the September 2008 issue of Long-Term Care News.

Description: An economic analysis of bariatric surgery and health care costs supports the case for health plans to cover these procedures.

Description: Discussion of the separate and joint effects of obesity and diabetes on disability and mortality, and ways these effects can be used to improved insurance pricing and reserving, reverse the increasing rates of obesity and diabetes, and improve current projections of disability and mortality risks.

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.

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: Comparison of healthcare costs for early retirees versus active workers in the same age band. When adjusted for age, there is not a significant difference in costs between each group.

Description: This article describes a method that can be useful when re-fitting a risk score model to a population of only moderate size. Learn how to use concepts like ridge regression to train a model with partial credibility.

Description: A general introduction about predictive modeling in insurance applications. Some basic models are discussed, such as Generalized Linear Model(GLM), Calssification and Regression Tree Model. Other models are also briefly introduced, including data clustering, neural networks and support vector machine.