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Related Concept Videos

Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Applications of Life Tables01:22

Applications of Life Tables

Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
Life Tables01:22

Life Tables

A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
Relative Risk01:12

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
Methods Of Healthcare Delivery System01:26

Methods Of Healthcare Delivery System

At the different levels of the healthcare system, we see varying methods of healthcare used. These methods include managed care systems, case management, and primary healthcare.
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is limited...

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Related Experiment Video

Updated: May 24, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Infant mortality: an insured population perspective.

Daniel D Zimmerman1, Brad Roudebush

  • 1Northwestern Mutual Life Insurance Company, 720 E. Wisconsin Avenue, Milwaukee, WI 53202-4797, USA. danielzimmerman@northwesternmutual.com

Journal of Insurance Medicine (New York, N.Y.)
|March 9, 2012
PubMed
Summary
This summary is machine-generated.

Infant life insurance mortality rates are lower than the general population. Leading causes of death also differ significantly in this insured cohort.

Related Experiment Videos

Last Updated: May 24, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Area of Science:

  • Actuarial science
  • Public health
  • Pediatric mortality

Background:

  • Life insurance is commonly offered to infants, often with features like premium waivers.
  • Infant mortality rates are notably higher compared to older age groups.
  • Understanding infant mortality is crucial for public health and insurance risk assessment.

Purpose of the Study:

  • To analyze the mortality experience of infants insured under life policies.
  • To compare infant mortality rates and causes of death between an insured cohort and the general population.
  • To identify specific risk factors and patterns within infant life insurance.

Main Methods:

  • Retrospective cohort study of insured individuals who died under one year of age.
  • Analysis of mortality data from life insurance policies.
  • Comparison of cause-specific mortality rates with general population data for the same age group.

Main Results:

  • The insured infant cohort exhibited a significantly lower mortality rate compared to the general infant population.
  • Leading causes of death in the insured cohort differed from those in the general population.
  • Specific policy features (e.g., premium waivers) may influence risk profiles.

Conclusions:

  • Infant life insurance populations demonstrate distinct mortality patterns.
  • Further research into the factors influencing infant mortality within insured groups is warranted.
  • Findings have implications for underwriting practices and public health interventions for infants.