Computerized medical modeling of group life insurance using medical claims data
First Claim
1. A method of developing a model to estimate life insurance exposure for a group of individuals to be underwritten for a coverage period comprising:
- providing medical claim data comprising a plurality of medical claims made by a first model population having at least a respective plurality of first model population members;
providing life insurance claim data comprising a plurality of life insurance claims made by a second model population having at least a respective plurality of second model population members, which optionally may partially or wholly overlap with the first model population;
providing a clinical medical condition classification system that assigns corresponding medical condition causes to life insurance claims based on medical condition information included in life insurance claims;
applying the clinical medical condition classification system to the life insurance claim data for the second model population to generate a plurality of life insurance claims classified by medical condition;
categorizing the life insurance claims classified by medical condition, where each morbidity category comprises one or more medical conditions, to form a plurality of morbidity categories of life insurance claims;
calculating, for each of the morbidity categories of life insurance claims classified by medical condition, the proportion of life insurance claims for each morbidity category;
applying the clinical medical condition classification system to the medical claim data for the first model population to generate a plurality of medical claims classified by medical condition;
categorizing the medical claims classified by medical condition to form a plurality of morbidity categories of medical claims classified by medical condition;
calculating, for each of the morbidity categories of medical claims classified by medical condition, the proportion of medical claims arising for each of the morbidity categories;
calculating, for each of the morbidity categories, a probability of having a life claim during the coverage period using at least one conditional probability, the conditional probability being based on at least the proportion of life insurance claims and the proportion of medical claims for each of the morbidity categories; and
combining the probability of having a life claim given a morbidity category with the expected cost of the life claim to calculate the expected life exposure for the morbidity category.
1 Assignment
0 Petitions
Accused Products
Abstract
A method of model development for use in underwriting group life insurance for a policy period includes collecting medical claims data for the group to be underwritten, where each medical claim being related to a particular employee of the group. Morbidity categories are provided that categorize the medical claims in the medical claims data. A conditional probability model is developed and applied to the morbidity categories for each employee in the group using his medical claims, thereby calculating the expected conditional probability for each employee dying during the policy period. For each employee, an estimate of the expected life claim cost is estimated using an index of the life coverage to salary. Combining the expected conditional probability for each employee dying during the policy period with the estimate of the expected claim cost of death gives an estimate of the group'"'"'s total life exposure.
-
Citations
9 Claims
-
1. A method of developing a model to estimate life insurance exposure for a group of individuals to be underwritten for a coverage period comprising:
-
providing medical claim data comprising a plurality of medical claims made by a first model population having at least a respective plurality of first model population members;
providing life insurance claim data comprising a plurality of life insurance claims made by a second model population having at least a respective plurality of second model population members, which optionally may partially or wholly overlap with the first model population;
providing a clinical medical condition classification system that assigns corresponding medical condition causes to life insurance claims based on medical condition information included in life insurance claims;
applying the clinical medical condition classification system to the life insurance claim data for the second model population to generate a plurality of life insurance claims classified by medical condition;
categorizing the life insurance claims classified by medical condition, where each morbidity category comprises one or more medical conditions, to form a plurality of morbidity categories of life insurance claims;
calculating, for each of the morbidity categories of life insurance claims classified by medical condition, the proportion of life insurance claims for each morbidity category;
applying the clinical medical condition classification system to the medical claim data for the first model population to generate a plurality of medical claims classified by medical condition;
categorizing the medical claims classified by medical condition to form a plurality of morbidity categories of medical claims classified by medical condition;
calculating, for each of the morbidity categories of medical claims classified by medical condition, the proportion of medical claims arising for each of the morbidity categories;
calculating, for each of the morbidity categories, a probability of having a life claim during the coverage period using at least one conditional probability, the conditional probability being based on at least the proportion of life insurance claims and the proportion of medical claims for each of the morbidity categories; and
combining the probability of having a life claim given a morbidity category with the expected cost of the life claim to calculate the expected life exposure for the morbidity category. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
-
Specification