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Related Experiment Video

Updated: Jun 18, 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

Creating Evidence-Based Ratings and Life Expectancies Medical Impairments.

John R Iacovino

    Journal of Insurance Medicine (New York, N.Y.)
    |June 17, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study shows how to use survival and mortality curves from medical literature to calculate Medical Impairment Manual (MIM) ratings and life expectancy estimations for accurate risk selection.

    Keywords:
    Life ExpectancyMortality RatiosSurvival of Essential Thrombocytosis

    Related Experiment Videos

    Last Updated: Jun 18, 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:

    • Medical statistics
    • Actuarial science
    • Risk assessment

    Background:

    • Accurate risk selection is crucial for profitability in insurance and financial sectors.
    • Evidence-based survival data is essential for underwriting and actuarial assessments.
    • Existing medical literature contains valuable survival and mortality information.

    Purpose of the Study:

    • To demonstrate a practical method for deriving Medical Impairment Manual (MIM) ratings.
    • To illustrate how to estimate life expectancies using medical literature data.
    • To provide a framework for evidence-based survival information utilization in risk assessment.

    Main Methods:

    • Identifying and extracting relevant survival and/or mortality curves from medical literature.
    • Applying graphical analysis techniques to interpret these curves.
    • Calculating Medical Impairment Manual (MIM) ratings based on curve data.
    • Estimating remaining life expectancies from the derived data.

    Main Results:

    • A systematic approach to quantify survival data from graphical representations.
    • The ability to generate specific MIM ratings for various medical impairments.
    • Quantifiable life expectancy estimations derived directly from illustrated medical data.
    • Demonstrated feasibility of using published curves for actuarial calculations.

    Conclusions:

    • Medical literature curves are a viable source for calculating MIM ratings and life expectancies.
    • This method enhances the accuracy and evidence-based nature of risk selection.
    • The approach offers a practical tool for actuaries and underwriters to improve profitability.