A 30-year-old woman with tetralogy of Fallot (TOF) repaired at age 5 years was seen in the adult congenital heart disease (ACHD) clinic. Her physician gave encouraging advice: there was no arrhythmia, the pulmonary regurgitation was only moderate, and right ventricular function was close to normal. With this favorable report, the woman asked why an insurer had recently more than doubled her premium for life insurance and declined her individual health and disability insurance applications. Her physician commented that the insurer’s actions were possibly unfair and the result of inadequate information.
Insurers have only limited statistics on clients with congenital heart disease (CHD). They rely mostly on the medical literature, combined with “armchair” reasoning and, for some medical directors, clinical experience. At present, clinical follow-up studies contain few patients older than age 50 years and estimation of mortality beyond this is at best an educated guess.
Today, a 30-year-old normal female insurance applicant is expected to survive past age 85, and with a premium increase of 150% is still expected to reach age 77. If medical consensus is that this patient will reach age 85 and not manifest an adverse claims record, why recommend yearly clinic visits to a cardiologist, a yearly electrocardiogram with treadmill testing, and echocardiography or Holter monitoring either yearly or every few years? These recommendations clearly eliminate the possibility of individual health insurance.
The primary focus of this discussion is the insurability of life insurance applicants with congenital heart lesions. Individual health insurance may not be available for patients requiring regular cardiac follow-up and will not be addressed. Availability of income replacement insurance, also called disability insurance, for CHD patients may be limited. Subjects with structural heart defects could theoretically use their cardiac problem to support a claim, whereas disability claims are often related to nonmedical factors such as job dissatisfaction, motivation, and mental health status. Subjects with CHD may have access to coverage through group programs that do not require individual assessment for their health, disability, or life insurance needs.
Individual life insurance is voluntary individual financial planning, with some applicants requesting coverage for over $10 million. Through the risk selection process, individual risks are evaluated and grouped with broadly similar risks to establish basic premium rates. Individuals with higher than expected mortality are assigned to substandard risk classes, while healthy individuals with expected mortality comprise the standard risk class. Although it may seem discriminatory to penalize an applicant for health problems not of his or her own making, reliance on objective, relevant, and reliable data enables insurers to fairly differentiate risks and to categorize subjects according to risk. Without this provision, higher insurance prices with lower availability and fewer choices would likely result.
To understand life insurance decisions, it is essential to understand normal and substandard mortality.
Expression of Mortality
Population mortality rates are usually expressed as the number of deaths per 1000 or per 100,000 subjects per year at each age. It is easier for underwriters and medical directors to think in terms of the mortality ratio—the observed number of deaths in a population of patients similar to the applicant, divided by the expected number of deaths in a normal reference population expressed as a percent. If a patient’s group expected mortality is the same as the reference group, the mortality ratio would be 100%; if a group has 3 times the expected number of deaths, the ratio would be 300%. In subjects younger than 20 years, insurers will often use the excess death rate as a means of calculating premium rather than mortality ratios.
Longevity (years of life remaining) is strongly related to age, gender, and smoking status, independent of any medical problems. In many jurisdictions, life insurers may classify the population of applicants into smoker, nonsmoker, male, or female and have four separate tables for expected survival for each age. Table 28.1 shows a partial mortality table for 30-year-olds. Using this table, a 30-year-old male nonsmoker with a medical problem who is predicted to survive 41 instead of 52 years will be assigned a mortality ratio of 300%. In addition to mortality costs, insurance premiums cover fixed costs including agents’ commissions and head office administration. For each 100% increase in mortality, the premium is increased about 90%, so a male projected to reach age 71 would be charged about 280% of the standard premium.
| Mortality Ratio (%) | Life Expectancy (yr) | |||
|---|---|---|---|---|
| Female Aged 30 | Male Aged 30 | |||
| Nonsmoker | Smoker a | Nonsmoker | Smoker a | |
| 100 b | 55 c | 49 | 52 | 44 |
| 150 | 52 | 45 | 48 | 40 |
| 200 | 49 | 42 | 45 | 37 |
| 250 | 47 | 39 | 43 | 35 |
| 300 | 45 | 37 | 41 | 34 |
| 400 | 43 | 34 | 39 | 31 |
| 500 | 40 | 32 | 36 | 29 |
| 700 | 37 | 29 | 34 | 27 |
| 1000 | 34 | 26 | 31 | 24 |
a Some insurers classify a smoker as a client who admits to smoking a cigarette within the past year. Other insurers may categorize any tobacco users as smoker or tobacco rates. Applicants who test positive for cotinine (nicotine metabolite) are classified as smokers.
b Subjects accepted as standard mortality after the underwriting process.
c Many insurers further divide their standard risk pool of applicants into select (preferred) and super-select categories based on ideal coronary risk factors, body build, family history, and other positive wellness attributes projecting 1 to 2 years of additional life expectancy.
Gender Difference in Mortality
Gender differences in mortality are well recognized in both the insurance and general populations. Table 28.1 demonstrates differences in life expectancy between males and females aged 30 for both standard and substandard risk classes. The difference in mortality between insured subjects and the general population is smaller in females compared with males. Since December 2012, insurance companies in the European Union (EU) are required to charge the same price to men and women for the same insurance products based on the EU gender equality legislation.
Smoker Versus Nonsmoker Differences in Mortality
Insurers frequently have separate rates for smokers and nonsmokers, or alternately, have aggregate (combined smoker/nonsmoker) rates. Some companies classify according to tobacco status with potential nontobacco rates for limited occasional cigars, smokeless tobacco, and with sustained smoking cessation for 1 year. Insurance data ( Table 28.2 ) show that at ages 30 and 40, smoking reduces life expectancy by 7 to 8 years. At age 70 and 80, the difference is 2 years. At age 30, smoking is the equivalent of assigning a mortality ratio of 225% to a nonsmoker. Smoking would lead to a greater increase in premium than many CHD conditions.
| Current Age (yr) | Life Expectancy (yr) | Smoker Mortality Ratio vs. Nonsmoker (%) | ||
|---|---|---|---|---|
| Nonsmoker | Smoker | Difference | ||
| 30 | 52 | 44 | 8 | 225 |
| 40 | 42 | 35 | 7 | 212 |
| 50 | 33 | 27 | 6 | 200 |
| 60 | 25 | 20 | 5 | 185 |
| 70 | 18 | 16 | 2 | 150 |
| 80 | 12 | 10 | 2 | 130 |
Mortality and the Underwriting Process
Insurers have long been aware that mortality in their policyholders is lowest in the first year after clearing the underwriting process, with gradual increases for the next 15 years. The insurance examination that clears the subject may simply be a medical history or may include a full examination and laboratory tests.
Table 28.3 shows the annual mortality rates for five populations of 32-year-old males: population A with a recent insurance examination, population B having had their examination 5 years previously, population C 10 years previously, and population D 15 years previously; population E is a current unexamined general population. The annual mortality in deaths per 1000 is significantly lower in population A than in population D. Fifteen years after policy issue, insurers use the term ultimate mortality , and this rate is often used as the reference level for underwriting. From age 20 to 50, this mortality is about two-thirds of the mortality of the general population. When mortality ratios are calculated in the medical literature, the patient group is compared with a demographically similar general population; insurers would adjust these ratios upward, taking into consideration the lower mortality in insured subjects classified as being at normal risk.
| Population | Age at Examination | Current Age | Deaths per 1000 | Description |
|---|---|---|---|---|
| A | 32 | 32 | 0.63 | Newly issued policies |
| B | 27 | 32 | 0.80 | Policies underwritten 5 years ago |
| C | 22 | 32 | 0.90 | Policies underwritten 10 years ago |
| D | 17 | 32 | 1.12 | Policies underwritten 15 years ago |
| E | General population | 32 | 1.70 | Unexamined general population |
Age and Relative Mortality Risk
Age has a profound effect on the relative mortality risk associated with a medical impairment. Medical follow-up studies often report percent survival or mortality at specific follow-up intervals. Given the marked increase in mortality rates in the general population with increasing age, any excess mortality risk associated with a congenital heart lesion will result in a much higher mortality ratio at the age of 30 compared with the ratio at age 50. Each insurance company determines their own approach to classes of risks that are accepted or declined. In general, many insurers decline risks with mortality ratios of over 500%. Thus, subjects with impairments associated with excess mortality risk may be uninsurable at age 30 and then find themselves insurable at age 50.
Life Expectancy in the Insured Population
Table 28.4 provides sample current life expectancy data from one large insurer for nonsmokers at ages 30 to 70 years. Clients accepted as standard risks have mortality ratios of 100%. A 50-year-old woman is expected to reach age 87, a male, age 83. If a 30-year-old female applicant with a medical problem is assessed at 300% mortality ratio, she is still expected to reach age 75 years. This type of table is a useful guideline for the underwriter and the public for understanding what a given rating means. The 30-year-old subject rated at 300% may be misled into thinking death is near, whereas expected survival is to 75 years.
| Age | Mortality Ratios (%) | |||||
|---|---|---|---|---|---|---|
| Female | 100 a | 150 | 200 | 300 | 400 | 500 |
| 30 | 55 | 52 | 49 | 45 | 43 | 40 |
| 40 | 46 | 42 | 40 | 36 | 33 | 31 |
| 50 | 37 | 34 | 31 | 28 | 26 | 24 |
| 60 | 28 | 25 | 23 | 20 | 19 | 17 |
| 70 | 21 | 19 | 17 | 15 | 14 | 13 |
| Male | 100 a | 150 | 200 | 300 | 400 | 500 |
| 30 | 52 | 48 | 45 | 41 | 39 | 37 |
| 40 | 42 | 38 | 36 | 33 | 30 | 29 |
| 50 | 33 | 30 | 27 | 25 | 22 | 21 |
| 60 | 25 | 22 | 20 | 18 | 16 | 15 |
| 70 | 18 | 16 | 14 | 12 | 11 | 10 |
a 100% = Standard or normal life expectancy, insurance population.
Limitations to Existing Long-Term Mortality Data
Published survival information for CHD has several limitations ( Table 28.5 ), but for predicting mortality, the main drawbacks are that follow-up information after age 40 is very limited and late survival of subjects having surgery after 1995 may be very different from those who had surgery from 1954 to 1970.
