Description: In Medicaid rate development, actuaries have not historically shared models that developed the margin (i.e., underwriting gain) assumption. This is unfortunate, given the margin assumption is one of the most critical components of the rate development in ensuring financial solvency of the Medicaid managed care organizations (MCOs). In this session, we will discuss the primary components of the this assumption and will share working models that help actuaries quantify these components—including the cost of capital and risk (or contingency) margin. We expect a lively discussion as we “open the black box” and discuss these actuarial assumptions in the public for the first time.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: The Johns Hopkins ACG Team's comments regarding their participation in the Comparative Analysis of Claims-Based Tools for Health Risk Assessment.

Description: This session 99PD of the New Orleans Annual Meeting summary: Insurers today are looking for new ways to use currently available experience data to better predict future costs. Both the federal and state governments are looking at the possibility of using prescription drug data because it is more available and often of higher quality than other experience data. From the Record of the Society of Actuaries, Volume 27, No. 3, Session 99PD.

Description: This paper provides an outline of the pricing methodology used by Blue Cross and Blue Shield of Virginia which incorporates trend analysis by trend component. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This session will explore the various methods of determining the credibility levels that are given to various size employer groups and Medicare plans. The background and theory of the methods that have commonly been used will be explained and then some new data-driven research in the area and possible alternatives will be 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: This article compares three potential approaches to determining new coefficients for health-based risk scoring models: full recalibration, p-value credibility weighting, and penalized ridge regression.

Description: In this paper the authors analyze data from group medical expense insurance claims and show that many insurance loss distributions have very 'heavy tails' because large losses represent a disproportionate fraction of the total cost. They also present a simple model to reproduce and explain the large loss behavior. From Actuarial Research Clearing House 1990, VOL. 2

Description: Discussion that developing credibility factors for group health insurance can be accomplished empirically through the use of stochastic models with appropriate parameters and fairly readily obtainable data, without the need for unrealistic assumptions.