健康保险索赔审计的代表性抽样计划

医疗保险定价的神经网络模型

Neural Network Model of Pricing Health Care Insurance

在健康保险计划的定价中，统计学家使用数学模型来预测客户未来的健康状况。一般成瘾模型（GAM）是一种被广泛接受的解决这一问题的方法。然而，它有几个局限性。为了解决这一问题，提出了一种新的方法--神经网络模型。与GAM模型相比，神经网络的预测结果更准确。

Long-Term Implications of the Revenue Transfer Methodology in the Affordable Care Act

The Affordable Care Act introduced a revenue transfer formula that requires insurance plans with generally healthier enrollees to pay funds into a revenue transfer pool for to reimburse plans with generally less healthy enrollees. For a given plan, the issue arises of whether the plan will be a payer into or a receiver from the pool in a chosen future year. To examine that issue, we analyze data from The Actuary Magazine on transfer payments for 2014-2015, and we infer strong evidence of a statistical relationship between year-to-year transfer payments. We also apply to the data a Markov trans…

Importance of diagnostic accuracy in big data: False-positive diagnoses of type 2 diabetes in health insurance claims data of 70 million Germans

Large data sets comprising diagnoses about chronic conditions are becoming increasingly available for research purposes. In Germany, it is planned that aggregated claims data including medical diagnoses from the statutory health insurance with roughly 70 million insurants will be published on a regular basis. Validity of the diagnoses in such big data sets can hardly be assessed. In case the data set comprises prevalence, incidence and mortality, it is possible to estimate the proportion of false positive diagnoses using mathematical relations from the illness-death model. We apply the method …

Statistical Implications of the Revenue Transfer Methodology in the Affordable Care Act

The Affordable Care Act (ACA) includes a permanent revenue transfer methodology which provides financial incentives to health insurance plans that have higher than average actuarial risk. In this paper, we derive some statistical implications of the revenue transfer methodology in the ACA. We treat as random variables the revenue transfers between individual insurance plans in a given marketplace, where each plan's revenue transfer amount is measured as a percentage of the plan's total premium. We analyze the means and variances of those random variables, and deduce from the zero sum nature of…

Modelling Joint Lifetimes of Couples by Using Bivariate Phase-type Distributions

Many insurance products and pension plans provide benefits which are related to couples, and thus under influence of the survival status of two lives. Some studies show the future lifetime of couples is correlated. Three reasons are available to confirm this fact: (1) catastrophe events that affect both lives, (2) the impact of spousal death and (3) the long-term association due to common life style. Dependence between lifetimes of couples could have a financial impact on insurance companies and pension plans providers. In this paper, we use a health index called physiological age in a Markov …

Boosting insights in insurance tariff plans with tree-based machine learning methods

Pricing actuaries typically operate within the framework of generalized linear models (GLMs). With the upswing of data analytics, our study puts focus on machine learning methods to develop full tariff plans built from both the frequency and severity of claims. We adapt the loss functions used in the algorithms such that the specific characteristics of insurance data are carefully incorporated: highly unbalanced count data with excess zeros and varying exposure on the frequency side combined with scarce, but potentially long-tailed data on the severity side. A key requirement is the need for t…