Description: Health claims are not normally distributed. Claims Forecasting can be improved by understanding the entire distribution of plausible values of future claims, for example knowing there is an 80% chance future claims are between $340 and $375 PMPM. Confidence intervals around our estimates allow us to understand for each range around the best estimate (for example +/- 1%) what is the probability that future claims will fall in that range. Quantile Regression is a mathematical technique where you can estimate any percentile of the claims distribution you are looking for as a function of demographics, diagnosis indicators, prior cost variables, or other significant predictors. You can see which coefficients are important at different parts of the distribution. Individual and group distributions can be constructed. There are numerous applications in pricing and underwriting, stop loss, provider profiling, ACO target setting, allocation of group risk charges based on volatility, discounting strategy, and experience analysis.

Description: This article is an update on the No Surprises Act, which is a U.S. Act aimed to reduce the risk that a person unexpectedly receives out of network charges for their health care visits. This is Part 2; Part 1 was featured in Health Watch's Sept 2024 issue.

Description: This article is an update on the No Surprises Act, which is a U.S. Act aimed to reduce the risk that a person unexpectedly receives out of network charges for their health care visits.

Description: In preparing claims reserves in the annual statement, health insurers and their opining actuaries will generally include a provision for adverse deviation (PAD) in their reserved amount in order to satisfy language in both in the National Association of Insurance Commissioners (NAIC) Health Annual Statement Instructions and in Actuarial Standards of Practice. This article explores the total level of PAD (both implicit and explicit margin combined) included in the reported claims reserves by examining NAIC filing data from 2016 through 2022.