A Report on the Actuarial, Marketing, and Legal Analyses of the CLASS Program. Data

10/14/2011

To accomplish these goals, we contacted major private LTC insurance companies currently selling in the market to solicit their participation in the study. We asked them to provide us with data on the total number of individuals that had applied for insurance between January 1, 2009 and June 30th, 2010 and had not been accepted into the risk pool due to reasons related to medical underwriting. For each individual we requested the following:

  • Date of application
  • Company to which individual is applying for LTC insurance
  • Age at application
  • Gender
  • Marital status at application
  • Employment status: A few companies were able to provide this data
  • Functional status: Results of any functional screens applied
    • ADL status
    • IADL status
  • Cognitive status: Results of any cognitive screens applied
  • Medical Status: Primary and secondary diagnoses identified

The following companies participated in the study and agreed to provide information on as many of the data elements that they capture in their underwriting and policyholder administration systems:

  • Bankers Life and Casualty
  • Blue Cross and Blue Shield of Alabama
  • GenworthFinancial
  • John Hancock
  • Knights of Columbus
  • MedAmerica
  • MetLife
  • Sterling Life Insurance

These companies accounted for roughly 70% of all new sales over the study period. In total, these companies contributed a sample of 55,070 individuals who applied for LTC insurance and did not pass the medical underwriting screens used by the companies.

This data was also supplemented with contextual information derived from a survey of 21 private LTC insurers focused on their underwriting practices. The study, entitled “Results of the Long-Term Care Underwriting Survey for the Individual Market in 2009” summarizes in detail the way in which companies conduct the business of underwriting.

Table 1 arrays the data elements according to the number of valid cases in the data file. Companies vary in the extent to which they capture all of the data that they actually use in the underwriting decision making process. What is common across all companies however is that information on medical diagnoses is captured. For that reason, while we have some level of detail on all 55,070 individuals, not all information is uniform. Some of the analyses will exclude large numbers of individuals. Even so, given the size of the sample, the smallest cells still contain over 18,000 observations.

TABLE 1: Sample Size by Data Element
Data Element   Number of Cases  
With Information
  Percent of  
All Cases
Age 54,638 99%
Gender 46,172 84%
Marital Status 34,455 63%
Employment Status 18,494 33%
Functional Status    
   ADL Status 23,006 42%
   IADL status 21,106 38%
Cognitive Status 34,360 62%
Medical Status (Primary Diagnosis)   53,782 98%
Total Cases 55,070 100%

Because companies do not use conventional standards for summarizing diagnostic information, clinical underwriting staff at LifePlans reviewed all of the cases to assure that appropriate and broad diagnostic categories could be used to characterize the entire sample. In the analyses that follow, thirteen broad diagnostic categories are used, thus ensuring consistency across the entire sample.

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