Description: The US healthcare system is among the world's most advanced, but is the highest-cost by far. At Swiss Re we studied the highest-cost US Medicare beneficiaries during 2016. The Medicare government program primarily covers seniors and individuals with disabilities. Total Medicare spending during 2016 was nearly USD 700,000,000,000. In our study, the 1% of beneficiaries with costs of USD 125,000 or higher generated 15% of total claim costs. Better understanding of these beneficiaries and their treatment could lead to improved quality and efficiency of care. Analysis of their claims can aid projections of the expected level and variance of costs. We calculated claim costs and rates, and identified higher-cost segments (including inpatient claims, individuals with disabilities or end-stage renal disease, Pacific states including California, and men). We look forward to expanding the analysis in future updates.

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.

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.