Mortality in rheumatoid disease

This paper provides an overview of rheumatoid disease from the perspective of its impact on mortality. The term, rheumatoid arthritis, may promote the misconception that this disease is relatively trivial and easily managed; therefore, "rheumatoid disease" is preferred. Numerous long-term studies in many settings have established that significant excess mortality is associated with rheumatoid disease, and that this excess mortality is related to cardiovascular disease deaths. Inflammation in rheumatoid and cardiovascular diseases shares the same biologic mechanisms. Severity of extraarticular disease, decline in functional level, and level of inflammatory activity are associated with increased risk of mortality. Detection and measurement of novel inflammatory biomarkers may provide tools to assess prognosis and to monitor therapy. Close attention to the management of traditional cardiovascular risk factors is essential in these patients. Whether disease modifying antirheumatic drug (DMARD) therapy will reduce all-cause and cardiovascular disease mortality in rheumatoid disease is the subject of ongoing studies.     

Konventionelle und moderne Einschätzungsmethoden in der Lebensversicherungsmedizin

The concepts of tariffs in the life insurance are built up with several layers of models. The foundation of the risk assessment of an applicant is the mortality rate in the actuarial model, based on the selection factors of gender and age. In the conventional medical risk assessment the anomalies of the applicant will be transformed into extra mortality rates. With modern methods of evaluation, the risk factors of the applicant will be assessed with statistical practices, in relation to the average values of the insurance portfolio. The deviations built up the insurance medical adjustment factor of the actuarial mortality rate and the basis of the insurance economical classification of the applicant to a risk class or a tariff portfolio.     

Anorexia nervosa: a 63-year population-based survival study

As eating disorders attract increasing publicity, more affected individuals will seek medical attention. Many will have needs for life insurance. Due to selection bias, most of the literature on anorexia nervosa (AN) presents an unfavorable prognosis. Therefore, the impairment is considered an adverse life insurance risk. This review is from an unselected, community population. The demographics of the study population and its expected mortality are similar to a population purchasing life insurance products. Comparative experience over 63 years of follow-up reveals mortality ratios and excess death rates similar to those expected for the population. High-risk comorbid diagnoses of depression and alcoholism are discussed.     

Pricing Term Insurance in the Presence of a Family History of Breast or Ovarian Cancer

Abstract

We estimate the increased mortality and term life insurance costs for women who have a family history of breast or ovarian cancer. Using data from the medical literature on age-specific and family history-specific incidence rates, we develop double-decrement models to evaluate the actuarial impact of breast cancer and ovarian cancer in the family. We also calculate the increased mortality and term insurance costs for women who test positive for the BRCA1 or BRCA2 gene mutation. We find that the type of affected relative and her age at onset of the disease are key underwriting factors. We find substantial mortality increases (up to 100%) for women with two relatives with cancer and women with a first-degree relative who developed cancer at an early age. Mortality increases for women with the BRCA gene mutation reach 150%. While some females with a family history of cancer can be accepted at standard rates, others may need to be quoted substandard rates, depending on the underwriting policy of the company. Females with the gene mutation can possibly be accepted at a rate that incorporates a severe mortality surcharge.     

Comparison of body mass index and waist circumference as predictors of all-cause mortality in a male insured lives population

Obesity assessed by body mass index (BMI) is associated with increased mortality risk, but there is uncertainty about whether BMI is the best way to measure obesity. Waist circumference (WC) has been proposed as a better measure. The Swiss Re BMI/WC Study was conducted to determine whether BMI or WC is a better predictor of future all-cause mortality in a large male insurance population. Using Cox proportional hazard models, risk ratios for increasing BMI and WC were 1.033 (P < .001) and 1.027 (P < .001), respectively. Risk ratios for obesity defined by BMI > or = 30 kg/m2 and WC > or = 40 inches were 1.33 (P < .001) and 1.20 (P = .002), respectively. In this study, BMI and WC are essentially equivalent in their ability to predict mortality risk in a male insurance population. Obesity, measured by either BMI or WC, has important underwriting and pricing implications.     

Increased QRS voltage in the limb leads

Increased QRS voltage accompanied by repolarization abnormalities in a life insurance applicant's electrocardiogram should alert the medical director to the possibility of left ventricular hypertrophy. If confirmed, left ventricular hypertrophy or increased left ventricular mass is a strong independent risk factor for future cardiac events and all cause mortality. The use of the electrocardiogram to diagnose left ventricular hypertrophy can be helpful, but there are limitations that need to be considered. This ECG case study illustrates some of the pitfalls in the electrocardiographic diagnosis of left ventricular hypertrophy.     

The Metabolic Syndrome and All-Cause Mortality in an Insured Lives Population

Abstract

Metabolic syndrome and its association with mortality have not been studied in insured lives populations. The Swiss Re Study evaluated metabolic syndrome prevalence and associated mortality from all causes and circulatory disease in a cohort of 35,470 predominantly healthy individuals, aged 18–83 years, who were issued life insurance policies between 1986 and 1997. Metabolic syndrome was defined using the National Cholesterol Education Program (NCEP) Expert Panel Adult Treatment Panel (ATP) III guidelines. The NCEP obesity criteria were modified with a prediction equation using body mass index, gender, and age substituted for waist circumference. Adjustments also were made for nonfasting triglyceride and blood glucose values. Risk ratios for policyholders identified with metabolic syndrome were 1.16 (P = .156) for mortality from all causes and 1.45 (P = .080) for mortality from circulatory disease compared with individuals without the syndrome. Risk was proportional to the number of components, or score, of the metabolic syndrome present. Risk ratios for metabolic syndrome score were 1.14 (P < .001) for mortality from all causes and 1.38 (P < .001) for mortality from circulatory disease compared with individuals without metabolic syndrome factors. In both all-cause and circulatory death models, relative risk was highest for the blood pressure risk factor. Based on a modified NCEP definition, increased mortality risk is associated with metabolic syndrome in an insured lives cohort and has life insurance mortality pricing implications.     

Peripartum cardiomyopathy: mortality outcomes

Mortality estimates of peripartum cardiomyopathy have been reported to be between 18 and 56% without reference to time frames. Although this is an unusual impairment, medical directors need accurate information to meet the gold standard of underwriting: decisions must be based on sound underwriting and actuarial principles reasonably related to actual or anticipated loss experience. In an insurance purchasing population, the excess mortality in peripartum cardiomyopathy can be nearly eliminated by not insuring those with the impairment within the first 6 months postpartum or until all abnormal physiologic parameters have resolved. Thereafter, the risk is probably negligible. This abstract illustrates the challenge to determine expected mortality when the study population exhibits strong racial diversity and when available expected life tables contain raw data of only alive and dead at each yearly interval.     

Diabetes mellitus--long time survival

The medical literature of the last decade enables us to estimate survival of diabetics. Insulin dependent diabetic (IDDM) present a 3 to 6-fold mortality and die after age 30, the most frequent causes being end stage renal and vascular diseases. Non insulin-dependent diabetic (NIDDM) mortality is 1.4 to 3.7 times that of non-diabetics. Cardiovascular events and strokes are the major causes of death. Pancreatic carcinoma occurs twice as frequently in NIDDM compared to non-diabetics. Early markers of late severe complications are hypertension and proteinuria. Retinopathy has little influence on morality if other risk factors are considered. Yet, glaucoma and lens changes are associated with three- and twofold mortalities. One of five IDDM with microalbuminuria progresses to overt nephropathy in 5 years. In NIDDM micro-albuminuria predicts cardiovascular disease with a mortality of up to 2 times. Careful treatment of cardiovascular risk factors and of microalbuminuria combined with optimal metabolic control substantially reduces mortality of diabetics.     

台湾地区"全民健康保险"制度对癌症患者医疗保障的启示

癌症多年来占据疾病死因顺位榜首,不仅严重威胁居民的健康和生命,更让患者面临较大的医疗费用支付压力。本文介绍了我国台湾地区“全民健康保险”制度在癌症患者医疗保障方面的特点,包括通过免除个人部分负担等措施为癌症患者提供经济协助、为癌症终末期患者提供安宁疗护、实行卫生技术评估、开展“全民健康保险”信息化建设。台湾地区的经验为改善癌症患者医疗保障带来以下启示:提高现行社会医疗保险对癌症相关医疗费用支付的待遇;推动社区开展癌症的慢性病管理;利用卫生技术评估匹配癌症治疗新药及新技术的医保准入与定价;以信息化建设助力肿瘤诊疗。     

Ankle/arm blood pressure index: an insurance perspective

Recent studies conclude that the ankle/arm blood pressure index (AAI) is a useful clinical tool for refining cardiovascular risk classification in the elderly. A reduction in the AAI to 0.9 or less is associated with increased risk for both coronary heart disease and total cardiovascular disease morbidity and mortality, as well as all-cause mortality. This relationship persists after adjusting for traditional risk factors and known cardiovascular disease. AAI will appear more common in attending physician's statements, prompting a need to educate underwriters about this technology. AAI may be of particular interest to insurers dealing in the elderly market, to those with strong physician examiner systems, and in markets where blood or urine tests are not commonly used in underwriting.     

A partial internal model for longevity risk

This paper proposes a simple partial internal model for longevity risk within the Solvency 2 framework. The model is closely linked to the mechanisms associated with the so-called Danish longevity benchmark, where the underlying mortality intensity and the trend is estimated yearly based on mortality experience from the Danish life and pension insurance sector, and on current data from the entire Danish population. Within this model, we derive an estimate for the 99.5% percentile for longevity risk, which differs from the longevity stress of 20% from the standard model. The new stress explicitly reflects the risk associated with unexpected changes in the underlying population mortality intensity on a one-year horizon and with a 99.5% confidence level. In addition, the model contains a component, which quantifies the unsystematic longevity risk associated with a given insurance portfolio. This last component depends on the size of the specific portfolio.     

From insurance risk to credit portfolio management: a new approach to pricing CDOs

We present a new approach for pricing collateralized debt obligations (CDOs) which takes into account the issue of the market incompleteness. In particular, we develop a suitable extension of the actuarial framework proposed by Bayraktar et al. [Valuation of mortality risk via the instantaneous Sharpe ratio: Applications to life annuities. J. Econ. Dyn. Control, 2009, 33, 676–691], Milevsky et al. [Financial valuation of mortality risk via the instantaneous Sharpe-ratio: Applications to pricing pure endowments. Working Paper, 2007. Available at: http://arxiv.org/abs/0705.1302], Young [Pricing life insurance under stochastic mortality via the instantaneous Sharpe ratio: Theorems and proofs. Technical Report, 2007. Available at: http://arxiv.org/abs/0705.1297] and Young [Pricing life insurance under stochastic mortality via the instantaneous Sharpe ratio. Insurance: Math. Econ., 2008, 42, 691–703], which is based on the so-called instantaneous Sharpe ratio. Such a procedure allows us to incorporate the attitude of investors towards risk in a direct and rational way and, in addition, is also suitable for dealing with the often illiquid CDO market. Numerical experiments are presented which reveal that the market incompleteness can have a strong effect on the pricing of CDOs, and allows us to explain the high bid-ask spreads that are frequently observed in the markets.     

Individual Annuity Demand Under Aggregate Mortality Risk

Aggregate mortality risk—the risk that the mortality trend in a population changes in a nondeterministic way—and its implications for corporate decisions has recently been the subject of lively scientific discussion. We show that aggregate mortality risk is also a key determinant for individual annuitization decisions. Aggregate mortality risk appears to be a risk very difficult to transfer for individuals. Whether its existence leads to a higher or lower annuity demand depends on objective factors (e.g., insurers’ vulnerability to aggregate mortality changes). Subjective factors (i.e., individuals’ preferences) determine only the intensity of the annuity demand reaction to aggregate mortality risk. Our results are of significant importance not only for financial planning approaches of individual annuity buyers but also for strategic decisions in insurance companies and for solvency regulators. Furthermore, consideration of aggregate mortality risk may alleviate, but also intensify, the annuity puzzle.     

Converting Clinical Literature to an Insured Population: A Comparison of Models Using Nhanes

Abstract

The use of clinical literature to set risk classification standards for life insurance underwriting stems from the need to set the most accurate standards using the best available information. A necessary hurdle in this process is converting any excess mortality observed in a clinical study to the appropriate rating for use in underwriting. A widely accepted model in the insurance industry, the Excess Death Rate model, treats the excess as additive to the conditional probability of death for an insurance company’s unimpaired class.

In this paper we test the validity of that model versus other common predictive models of excess mortality in an insured population. Applying these models to National Health and Nutrition Examination Survey (NHANES) data, we derive estimates for excess mortality from three commonly seen underwriting impairments in what could be considered a clinical population. These estimates are added to an estimate of an insurance company’s unimpaired mortality class and then used to predict deaths in an “insurable” subset of that clinical population.

The Excess Death Rate model performed the best of all models, having the smallest cumulative difference of actual to predicted deaths. The use of publicly available data, such as that in NHANES, could help bridge the gap between clinical literature and its application in insurance underwriting if insurable cohorts can be reliably identified from these generally healthy, ambulatory groups.     

Biometric Solvency Risk for Portfolios of General Life Contracts. I. The Single-Life Multiple Decrement Case

Abstract

Solvency II splits life insurance risk into seven risk classes consisting of three biometric risks (mortality risk, longevity risk, and disability/morbidity risk) and four nonbiometric risks (lapse risk, expense risk, revision risk, and catastrophe risk). The best estimate liabilities for the biometric risks are valued with biometric life tables (mortality and disability tables), while those of the nonbiometric risks require alternative valuation methods. The present study is restricted to biometric risks encountered in traditional single-life insurance contracts with multiple causes of decrement. Based on the results of quantitative impact studies, process risk was deemed to be not significant enough to warrant an explicit calculation. It was therefore assumed to be implicitly included in the systematic/parameter risk, resulting in a less complex standard formula. For the purpose of internal models and improved risk management, it appears important to capture separately or simultaneously all risk components of biometric risks. Besides its being of interest for its own sake, this leads to a better understanding of the standard approach and its application extent. Based on a total balance sheet approach we express the liability risk solvency capital of an insurance portfolio as value-at-risk and conditional value-at-risk of the prospective liability risk understood as random present value of future cash flows at a given time. The proposed approach is then applied to determine the biometric solvency capital for a portfolio of general life contracts. Using the conditional mean and variance of a portfolio’s prospective liability risk and a gamma distribution approximation we obtain simple solvency capital formulas as well as corresponding solvency capital ratios. To account for the possibility of systematic/parameter risk, we propose either to shift the biometric life tables or to apply a stochastic biometric model, which allows for random biometric rates. A numerical illustration for a cohort of immediate life annuities in arrears reveals the importance of process risk in the assessment of longevity risk solvency capital.     

Use of a Markov Model to Estimate Long-Term Insured Lives’ Mortality Risk Associated With BRCA1 and BRCA2 Gene Mutations

Abstract

There is uncertainty regarding the degree of insurance risk associated with BRCA1/2, the gene mutations associated with breast cancer. Most reports to date have been based on high-risk populations selected from families with multiple and/or early-onset cancers; more favorable data have been reported in studies without this selection bias.

This paper discusses use of a Markov model to estimate mortality risk associated with BRCA1/2 gene mutations in female life insurance applicants. The goal is to derive a range of risk estimates based on different assumptions of breast and ovarian cancer incidence. A particular strength of the model is that transition probabilities after cancer diagnosis vary with age and cancer stage, as do excess hazard rates.

Data calculated by the model indicate that no single mortality curve characterizes risk for all life insurance applicants with a BRCA1/2 mutation. Rather, mortality risk depends on breast and ovarian cancer incidence rates and subsequent mortality rates, and on the method used to deal with competing breast and ovarian cancer incidence and mortality rates. Further refinement of risk estimates will depend on better incidence data and on resolution of complex statistical problems, such as informative censoring.

Widespread use of genetic information by insurance consumers could have important economic implications. For companies that sell individually underwritten products, profitability might decrease. Consumers might find higher prices and reduced availability, with a corresponding decrease in quantity of insurance purchased. Insurance and consumer ramifications would vary by cover, with living-benefit products, such as critical-illness insurance, most adversely affected. Societal choices are limited. Given assumptions in the cited scenario, it is likely premiums would rise and quantity of insurance purchased would decrease even with no change in existing social policy; attempted legal or regulatory remedies would further accentuate price increases and reductions in quantity purchased.     

医疗保险风险调剂机制在全民医保制度构建中的应用

自荷兰、德国等国发端的医疗保险风险调剂机制在世界“全民医保”浪潮中越来越受到重视,并逐渐成为各国政府整合分散医保基金的重要手段。我国以“全民医保”为目标的新一轮医改是建立在财政分权、县域统筹等制度背景下的,医疗保险基金“碎片化”问题十分突出。科学引入医疗保险风险调剂机制,改变现有粗放的“调剂金”管理模式,有助于我们既兼...     

Estimation of future mortality rates and life expectancy in chronic medical conditions

Estimates of old-age mortality are necessary for the construction of life tables and computation of life expectancy, and are essential in the growing area of life insurance for the elderly. Two common assumptions are that either the excess death rate (EDR) or the relative risk (RR) stays constant with increasing age. It is known, however, that for most medical conditions the former underestimates the risk and the latter overestimates it. A third popular method is that of rating up: a subject is said to be "rated up k years" if his future mortality rates are assumed to be those of a person in the general population who is k years older. It is shown here that this method generally leads to gross overestimates of old-age mortality. We consider two less-commonly used models, log-linear declining relative risk (LDR) and constant proportional life expectancy (PLE), and compare them to the methods of constant EDR, constant RR and rating up. Although slightly more complicated to employ than the other methods, both LDR and PLE generally give better estimates of mortality and life expectancy. When mortality rates for chronic conditions are known within a certain age range, and estimates outside of the range are required, the LDR and PLE methods may be preferable to the more familiar methods of constant EDR, constant RR, or rating up.