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1 |
Informationalize the structure of risk management; move
medical science to risk management professional and
business applications. |
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2 |
Optimize
the predictive & protective value of evidence-based
medical risk appraisal and life expectancy analysis for: |
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Fact-based classification & pricing of insurable
risk products.
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Revision and adaptation of medical underwriting
manuals for electronic commerce.
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Leverage high value clinical information for
economic and social gain.
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Simplify and streamline the predictive & protective
value of medical-actuarial measurement of high
volume – high risk impairments from info-sphere
databases.
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Simplify understanding of “best case and what if”
scenarios.
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Simultaneously calculate impairment specific life
expectancy and develop age and sex-specific life
expectancy tables to age 109 years based on the
1989-91 U.S. Decennial Life Tables.
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3 |
Life
expectancy determinations are necessary for Longevity
Risk Products including: |
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Annuities
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Disabilities
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Structured settlements
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Viaticals
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Overview &
general methodologic steps for determining mortality &
life expectancy |
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1 |
Subjects
studied: Breast cancer survival data by age, sex, stage
and grade were obtained from a 1988-1999 cohort of the
National Cancer Institute SEER (Surveillance,
Epidemiology, End-Results) database (SEER*Stat 4.2.3)
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2 |
Sex-specific annual survival must first be ascertained
and translated to annual mortality. |
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3 |
With an
original software program we have automated the
conversion of survival to mortality using standard
actuarial methods in two simultaneous electronic steps:
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conversion of the 12-year survival table to a
12-year mortality table
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conversion of 1-year annual mortality to a condensed
mortality table with five durational intervals in
order to derive the total excess death rate (EDR) (see
slides 4-9 in the MS PowerPoint Illustration)
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EDRs are useful for Suggested Underwriting Pricing
Projections for Mortality Risk Products such as life
insurance in cancer patients (see
slide 10)
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4 |
Life
expectancy is also calculated simultaneously by the
software program. |
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5 |
Decimal
values of the excess mortality values are added to
annual mortality rates for females in the U.S.
population to obtain projected mortality rates for a
group with a set of risk factors similar to those in the
hypothetical vignette illustration of Ms. Jane Doe. |
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6 |
These
values are converted into a figure for reduced life
expectancy, displayed in a life expectancy table from
attained age 70 years to 109 years, and compared with
the life expectancy of persons matched by age and sex in
the latest Decennial U.S. Life Tables (see
slides 11-13) |
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7 |
In the case
of Ms. Jane Doe, annual calculations for life expectancy
(e˚ ) are needed from age 70 (age at the time of her
diagnosis and treatment of breast cancer) to age 109 to
derive the most accurate possible calculation of
remaining life expectancy. |
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8 |
Conclusions
are easily prepared concerning |
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remaining years of life expectancy
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percent reduction from normal expected life
expectancy
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Download the PowerPoint
Presentation |
