Return of Health Discrimination to Insurance Markets Could Affect Millions of People

Return of Health Discrimination to Insurance Markets Could Affect Millions of People

With the Trump administration’s challenge to invalidate the Affordable Care Act (ACA) having moved to the Supreme Court in the midst of nomination fight, there has been a renewed focus on the number of people with pre-existing health conditions and how they might be treated in health insurance markets if the administration’s arguments prevail. Prior to the ACA, people with pre-existing health conditions could be denied coverage or charged higher premiums if they sought coverage outside of their workplace, and small employers could be charged much higher premiums if their workers or their family members had or developed serious or chronic health conditions. If the law is overturned, these practices may return. A substantial share of non-elderly adults have pre-existing health conditions that would see them declined for coverage under pre-ACA medical screening rules in the non-group market. In a previous study, we found that 27% of non-elderly adults, almost 54 million people, had a declinable pre-existing medical condition in 2018. Some groups are at higher risk; for example:

Older adults are more likely to have declinable conditions than younger people

Age
Share with a Pre-Existing Condition

Ages 18 to 34
18%

Ages 35 to 44
24%

Ages 45 to 54
29%

Ages 55 to 64
44%

Source: KFF analysis of 2018 National Health Interview Survey. See Methodology below.

Women, particularly younger women, are more likely than men to have declinable conditions, in part because pregnancy was considered a pre-existing condition

Gender
Age
Share with a Pre-Existing Condition

Female
Ages 18 to 34
22%

Male
Ages 18 to 34
15%

Female
Ages 35 to 44
27%

Male
Ages 35 to 44
20%

Female
Ages 45 to 54
32%

Male
Ages 45 to 54
27%

Female
Ages 55 to 64
44%

Male
Ages 55 to 64
44%

Source: KFF analysis of 2018 National Health Interview Survey. See Methodology below.

Adults living in non-metropolitan counties are more likely to have declinable conditions than people in metropolitan areas

Metro Status
Share with a Pre-Existing Condition

Live in Metro County
26%

Live in Non-Metro County
32%

Source: KFF analysis of 2018 National Health Interview Survey and 2018 Behavioral Risk Factor Surveillance Survey. See Methodology below.

Without the ACA, there is nothing in federal law to assure people with pre-existing health conditions access to affordable non-group coverage should they need it. The President recently instructed his administration to work with Congress to find ways to protect people with pre-existing conditions, but no concrete proposals were included. Were the Court to overturn the ACA provisions relating to pre-existing conditions, millions of people could face discrimination in health insurance markets unless or until the federal or state governments fashion new protections.

Methodology

The methods are the same as we used here.
To calculate nationwide prevalence rates of declinable health conditions, we reviewed the survey responses of nonelderly adults for all question items shown in Methods Table 1 using the CDC’s 2018 National Health Interview Survey (NHIS).  Approximately 27% of 18-64 year olds, or 54 million nonelderly adults, reported having at least one of these declinable conditions in response to the 2018 survey.  The CDC’s National Center for Health Statistics (NCHS) relies on the medical condition modules of the annual NHIS for many of its core publications on the topic; therefore, we consider this survey to be the most accurate means to estimate both the nationwide rate and weighted population.
Since the NHIS does not include state identifiers nor sufficient sample size for most state-based estimates, we constructed a regression model for the CDC’s 2018 Behavioral Risk Factor Surveillance System (BRFSS) to estimate the prevalence of any of the declinable conditions shown in Methods Table 1 at the state level.  This model relied on three highly significant predictors: (a) respondent age; (b) self-reported fair or poor health status; (c) self-report of any of the overlapping variables shown in the left-hand column of Methods Table 1.  Across the two data sets, the prevalence rate calculated using the analogous questions (i.e. the left-hand column of Methods Table 1) lined up closely, with 21% of 18-64 year old survey respondents reporting at least one of those declinable conditions in the 2018 NHIS and 23% of 18-64 year olds in the 2018 BRFSS.  Applying this prediction model directly to the 2018 BRFSS microdata yielded a nationwide prevalence of any declinable condition of 29%, a near match to the NHIS nationwide estimate of 27%.
In order to align BRFSS to NHIS overall statistics, we then applied a Generalized Regression Estimator (GREG) to scale down the BRFSS microdata’s prevalence rate and population estimate to the equivalent estimates from NHIS, 27% and 54 million.  Since the regression described in the previous paragraph already predicted the prevalence rate of declinable conditions in BRFSS by using survey variables shared across the two datasets, this secondary calibration solely served to produce a more conservative estimate of declinable conditions by calibrating BRFSS estimates to the NHIS.  After applying this calibration, we calculated state-specific prevalence rates and population estimates off of this post-stratified BRFSS sample.

 

 

Via Source link