Journal of insurance medicine (New York, N.Y.)最新文献

Fetal alcohol spectrum disorder (FASD) and its associated physical and mental conditions is the most prevalent congenital impairment causing developmental and intellectual disability worldwide. Like alcohol abuse, FASD is typically undiagnosed by primary care providers. And like alcohol abuse, life underwriters and medical directors need to be aware of the signs, symptoms, and behaviors associated with FASD to accurately detect, identify, evaluate and assess the mortality risk. Three cases of suspected undiagnosed FASD that were underwritten for life expectancies in legal matters are discussed in this report. Not only were these patients' risks for excess mortality elevated due to their initial neurologic injury due to prenatal exposure to alcohol, but these cases demonstrate the importance of the stability and care needed to make them insurable. The following paper discusses the clinical and social settings at birth that may give underwriters and medical directors some clue to a potential case of the child having FASD and then to assess their statistical and lifestyle mortality risks.

This commentary article highlights the need for an insurance product for hospital-employed physicians that provides coverage against sham peer review and a complete defense against wrongful hospital allegations of incompetent, whistleblowing, or disruptive behavior.

As life insurance companies evaluate prospective health and wellness programs, one frequently used tool is the number needed to treat (NNT) calculation. It is helpful to identify what the NNT might be for individual components of the program as well as for the whole program when all components are combined.

Introduction: -Due to early detection and improved therapies, the prevalence of long-term breast cancer survivors is increasing. This has increased the need for more inclusive underwriting in individuals with a history of breast cancer. Herein, we developed a method using algorithm aiming facilitating the underwriting of multiple parameters in breast cancer survivors.

Methods: -Variables and data were extracted from the SEER database and analyzed using 4 different machine learning based algorithms (Logistic Regression, GA2M, Random Forest, and XGBoost) that were compared with Kaplan Meier survival estimates. The performances of these algorithms have been compared with multiple metrics (Log Loss, AUC, and SMR). In situ (non-invasive) and metastatic breast cancer were excluded from this analysis.

Results: -Parameters included the pathological subtype, pTNM staging (T: tumor size, N; number of nodes; M presence or absence of metastases), Scarff-Bloom-Richardson grading, the expression of estrogen and progesterone hormone receptors were selected to predict the individual outcome at any time point from diagnosis. While all models had identical performance in terms of statistical metrics (AUC, Log Loss, and SMR), the logistic regression was the one and only model that respects all business constraints and was intelligible for medical and underwriting users.

Conclusion: -This study provides insight to develop algorithms to set underwriter-friendly calculators for more accurate risk estimations that can be used to rationalize insurance pricing for breast cancer survivors. This study supports the development of a more inclusive underwriting based on models that can encompass the heterogeneity of several malignancies such as breast cancer.

Objectives: -To document the various laboratory and demographic/historical correlates of NT-proBNP levels in applicants for life insurance, and to explore the accuracy of a prediction model based on those variables.

Method: -NT-proBNP blood test results were obtained from 1.34 million insurance applicants between the age of 50 and 85 years, beginning in 2003. Exploratory data analysis was carried out to document correlations with other laboratory variables, sex, age, and the presence of relevant diseases. Further, predictive models were used to quantify the proportion of the variance of NT-proBNP, which can be explained by a combination of these other, easier to determine variables.

Results: -NT-proBNP shows the expected, negative correlation with estimated glomerular filtration rate (eGFR) is markedly higher in those with a history of heart disease and is somewhat higher in those with a history of hypertension. A strong, unexpected, negative correlation between NT-proBNP and albumin was discovered. Of the variables evaluated, a multivariate adaptive regression spline (MARS) model automated selection procedure selected 7 variables (age, sex, albumin, eGFR, BMI, systolic blood pressure, cholesterol, and history of heart disease). Variable importance evaluation determined that age, albumin and eGFR were the 3 most important continuous variables in the prediction of NT-proBNP levels. An ordinary least squares (OLS) model using these same variables achieved a R-squared of 24.7%.

Conclusion: -Expected ranges of NT-proBNP may vary substantially depending on the value of other variables in the prediction equation. Albumin is significantly negatively correlated with NT-proBNP levels. The reasons for this are unclear.

Breast cancer remains the most common non-cutaneous malignancy in women in both Europe and the United States and the second leading cause of cancer-related deaths. In this breast cancer mortality and survival study, a US retrospective population-based analysis of 656,501 microscopically confirmed breast cancer cases, 1975-2019, data is derived from the NCI Surveillance Epidemiology & End Results Program, SEER*Stat 8.4.0.1.

As the COVID-19 pandemic reaches the end of its third year, and as COVID-related mortality in North America wanes, long Covid and its disabling symptoms are attracting more attention. Some individuals report symptoms lasting more than 2 years, and a subset report continuing disability. This article will provide an update on long Covid, with a particular focus on disease prevalence, disability, symptom clustering and risk factors. It will also discuss the longer-term outlook for individuals with long Covid.