16.2.9 Insurance Coverage

Insurance Coverage is a factor that may be a proxy for other identifiers. For example, employment-based payers may provide information about a person’s job status. Other types of payers, such as Medicaid, may provide information about a person’s income. There is demographic data that indicates populations by income level in the public domain as published by the U.S. Census Bureau, as well as public information related to various jobs and employment status through labor agencies. Given the opportunities to use information about the payer in combination with other public information, this variable is given a risk score. The risk is scored as below given the member size of the Insurance Coverage in the various categories.

Table 22: Insurance Coverage

Characteristic	Score
Coverage with >2,000,000 members	-5
Coverage with 1,000,001 - 2,000,000 members	-3
Coverage with 560,001 - 1,000,000 members	-1
Coverage with 250,001 - 560,000 members	0
Coverage with 100,001 - 250,000 members	+1
Coverage with 50,001 - 100,000 members	+3
Coverage with 20,001 - 50,000 members	+4
Coverage with ≤ 20,000 members	+5

See Appendix I for more details on scoring scenarios involving the overlap of Insurance Coverage, Expected Payer/Public Assistance and Means-Tested Programs, and Geography. Below are three key points that summarize all the scenarios:

1. If the data is ONLY related to Residence or Service Geography, then DO NOT USE Insurance Coverage or Means-Tested Tables.

2. Means-Tested Programs—Only add interaction if enrollment in the Public Assistance program is 10 million or fewer people. No interaction is needed for Medi-Cal as the current enrollment is approximately 14 million, which exceeds 10 million.

3. If the number of members enrolled in Insurance Coverage is less than the population of the geographic subdivision, then use the Insurance Table. If the number of members enrolled in Insurance Coverage is greater than or equal to the population of the geographic subdivision, then use the Geography Table.