Insurance Coverage and Viral Suppression Among People with HIV, 2018
Coverage Data on General Population
All general population coverage data, except for marketplace coverage, is limited to adults and comes from KFF analysis of the 2018 American Community Survey (ACS).
General population marketplace coverage is an estimate based off the number of nonelderly adults with effectuated marketplace enrollment in 2018. Overall marketplace enrollment in 2018 was 9,895,197. The share estimated to be nonelderly adults was based off data on characteristics of individuals who selected a marketplace plan, whereby 9% of marketplace plan selectors were under 18. We assumed that age characteristics of those with effectuated marketplace enrollment were similar to those who had selected plans and subtracted 9% (890,568) from the effectuated enrollment total to obtain an estimated adult marketplace enrollment of 9,004,629 or 4% of the non-elderly adult ACS population (242,620,816).
Data on People with HIV
Data on people with HIV are based on 2015-2018 data from the Medical Monitoring Project (MMP), a Centers for Disease Control and Prevention (CDC) surveillance system which produces national and state-level representative estimates of behavioral and clinical characteristics of adults with diagnosed HIV in the United States.
Between 2015 and 2018, MMP employed a two-stage, complex sampling design. First, jurisdictions are selected from all U.S. states, the District of Columbia, and Puerto Rico using a probability proportional to size sampling strategy based on AIDS prevalence at the end of 2002, such that areas with higher prevalence had a higher probability of selection. Next, adults (aged 18 years and older) with diagnosed HIV were sampled from selected jurisdictions from the National HIV Surveillance System (NHSS), a census of US persons with diagnosed HIV. During 2015-2018, data come from: California (including the separately funded jurisdictions of Los Angeles County and San Francisco), Delaware, Florida, Georgia, Illinois (including the separately funded jurisdiction of Chicago), Indiana, Michigan, Mississippi, New Jersey, New York (including the separately funded jurisdiction of New York City), North Carolina, Oregon, Pennsylvania (including the separately funded jurisdiction of Philadelphia), Puerto Rico, Texas (including the separately funded jurisdiction of Houston), Virginia, and Washington.
Data used in this analysis were collected via telephone or face-to-face interviews and medical record abstractions during the following periods.
- 2015 data was collected between June 1, 2015 – May 31, 2016
- 2016 data was collected between June 1, 2016 – May 31, 2017
- 2017 data was collected between June 1, 2017- May 31, 2018
- 2018 data was collected between June 1, 2018 – May 31, 2019
In 2018, the primary year of analysis, of 9,700 sampled persons, 4,050 participated. Adjusted for eligibility, the response rate was 45%. Data were weighted based on known probabilities of selection at state or territory and patient levels. In addition, data were weighted to adjust for non-response using predictors of person-level response, and post-stratified to NHSS population totals by age, race/ethnicity, and sex at birth. Although characteristics associated with nonresponse varied among states and territories, the weighting classes for the national data were informed by sex at birth, age of most recent contact information, and the person’s frequency of receipt of care (as indicated by NHSS records). This analysis includes information on 4,050 participants who represent all adults with diagnosed HIV in the United States and Puerto Rico.
For all respondents in MMP, we examined self-reported insurance coverage. Response options included insurance programs (Medicaid, Medicare, private insurance – employer and marketplace -, Ryan White HIV/AIDS Program – Ryan White or the AIDS Drug Assistance Program-, Veteran’s Administration, Tricare or CHAMPUS coverage, other public insurance, and other unspecified insurance). “Other specify” responses were recoded to reflect the most accurate coverage type when possible. It is important to note that respondents may not be aware of all the services they receive that are paid for by the Ryan White HIV/AIDS Program (the program provides funding directly to service organizations in many cases) and therefore, the estimates of the number of individuals who receive Ryan White HIV/AIDS Program services is likely an underestimate.
We estimated weighted percentages of individuals with the following types of health care coverage: no coverage (uninsured), private insurance (with breakouts for employer coverage and marketplace coverage), Medicaid, Medicare, and other. Because respondents in MMP may indicate more than one type of coverage, we relied on a hierarchy to group people into mutually exclusive coverage categories. Specifically, the hierarchy groups people into coverage types in the following order:
- Private coverage overall (with breakouts for employer coverage and marketplace coverage)
- Medicaid coverage, including those dually eligible for Medicare
- Medicare coverage only
- Other public coverage, including Tricare/CHAMPUS, Veteran’s Administration, or city/county coverage
In most cases, this hierarchy classified individuals according to the coverage source that served as their primary payer. People who did not report any of the sources of insurance coverage were classified as uninsured. We separately assess weighted percentages of persons receiving assistance through the Ryan White HIV/AIDS Program by health coverage type.
Statistical comparisons were made using Rao-Scott chi-square tests to account for complex survey design.
MMP only allows for extrapolation to the national level when using the full sample. Similar extrapolation is not possible when examining coverage changes in and contrasting Medicaid expansion states and non-expansion states. The Medicaid expansion and non-expansion coverage data presented here are representative only of the subset of states sampled that fell into each group. Insurance coverage data is self-reported by respondents and not verified. By relying on a hierarchy to group individuals into coverage categories, it is possible individuals were grouped into a coverage category that was not their dominant payer over the course of a year.