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Choosing To Be Uninsured:
Determinants and Consequences of the Decision to
Decline Employer-Sponsored Health Insurance
October 1999 Peter J. Cunningham
ABSTRACT
Objective. (1) To identify the factors associated with the
decision to decline employer-sponsored health insurance, and (2) to
compare health care access and use of uninsured persons who declined
employer-sponsored insurance with health care access and use of other
uninsured and insured persons.
Data Source.1996-97 Community Tracking Study Household
Survey.
Study Design. Potential determinants of the decision to decline
employer-sponsored coverage were identified as (1) those relating to the
cost of insurance to the individual (e.g., family income, job
characteristics, types of plans offered); (2) availability of free sources
of health care in the community (e.g., public hospitals, community health
centers); and (3) factors that reflect individuals’ need and preferences
for insurance (e.g., health status, demographics, attitudes toward risk).
Measures of access to care and health care use include usual source of
care, difficulty obtaining needed medical services, the volume and pattern
of ambulatory medical care use and the rate of inpatient utilization.
Data Collection. A survey, primarily by telephone, of households
in 60 communities, defined as metropolitan statistical areas and
nonmetropolitan areas.
Principal Findings. Factors that reflect the cost of insurance
to individuals were strong determinants of the decision to decline
coverage in favor of being uninsured, while the availability of free
sources of health care in the community had little effect. Health status
was not significantly related to the decision to decline coverage,
although other individual characteristics, such as age, race/ethnicity,
education and attitudes toward risk had significant effects. Uninsured
persons with access to employer-sponsored insurance were similar to other
uninsured persons in their health care use and access.
Conclusions. Individuals are not motivated to decline
employer-sponsored insurance because they are able to achieve relatively
good access to care without insurance, but appear to be motivated mostly
by concerns about the affordability of insurance and, to some extent,
individual preferences. The decision to decline insurance (in favor of
being uninsured) appears to have serious consequences regarding access to
care and health care use. Policy implications regarding the use of tax
incentives to encourage individuals to purchase insurance are
discussed.
Key Words. Uninsured, employer-sponsored health insurance,
take-up, access
INTRODUCTION Employer-sponsored private
insurance is the most common source of health coverage for non-elderly
persons. While the vast majority of persons who are offered coverage by
their employers accept that coverage, concern about the relatively small
number of persons who refuse coverage may be justified for at least two
reasons. First, the "take-up" rate (percentage of workers who accept
coverage when offered and eligible) decreased from 88 percent in 1987 to
80 percent in 1996, and appears to be a major reason for the overall
decline in employer-sponsored coverage during that period (Cooper and
Schone 1997). Second, even a low rate of declining coverage among all
workers may still result in a substantial number of uninsured persons who
have access to employer-sponsored coverage coverage, either through their
own employer or as a dependent of a family member who is offered coverage
(Thorpe and Florence 1999). If more of these individuals could be
encouraged to accept insurance when offered, then a sizeable reduction in
the number of uninsured persons might be achieved at lower public cost
than other options.
Nevertheless, little is known about what causes individuals to decline
employer-sponsored coverage–especially when the result of that decision is
to be uninsured–and what are the consequences of that decision regarding
access to care and health care use. The few studies that exist on the
topic have been concerned primarily with estimating the rate at which
individuals take up or decline employer-sponsored health insurance (Cooper
and Schone 1997; Thorpe and Florence 1999; Gabel et al. 1999; Long and
Marquis 1993). These studies have also shown that take-up rates tend to be
lower for young adults (age 19-24), blacks and Hispanics, low-wage
workers, part-time workers and workers employed in smaller firms (Cooper
and Schone 1997; Thorpe and Florence 1999; Gabel et al. 1999).
However, these analyses were descriptive only; they did not include
multivariate analyses showing the unique effects of a much broader range
of individual and employer characteristics that reflect individual
preferences, need for health care and the affordability of coverage to the
individual. In addition, the availability of free sources of health care
in the community–such as public hospitals and community health centers–may
be a significant deterrent to enrolling in employer-sponsored health
insurance coverage. In other words, some individuals may decline
employer-sponsored health insurance if other sources of health care are
available in the community, enabling them to achieve reasonably good
access to care without health insurance. This would not only imply that
the phenomenon of declining employer-sponsored coverage is a less serious
concern than has been assumed, but it would also suggest that efforts to
expand direct care services to the uninsured via the health care safety
net may have the unintended consequence of increasing the number of
uninsured (and those who depend on the public sector for health care
rather than the private sector).
This study has two basic objectives. Based on a multivariate analysis
that includes a broad range of factors, we first identify the factors that
determine whether individuals decline employer-sponsored coverage. In
addition to those factors that reflect costs, individual preferences and
the need for health care (i.e., health status), we explicitly examine
whether the availability of free sources of care in the community (e.g.,
public hospitals, community health centers) affects the decision to enroll
in employer-sponsored health insurance.
The second objective is to examine the consequences of declining health
insurance regarding access to care and the use of health services. This is
done by comparing the health care utilization and access of uninsured
persons who decline coverage with other uninsured persons (i.e., those who
do not have access to employer-sponsored) and with insured persons. Better
access to care and higher health care use among those uninsured who
decline employer-sponsored coverage (compared to the uninsured who are not
offered coverage) would suggest a rational decision to opt out of coverage
because these individuals are apparently able to obtain health care either
through the free care system or by paying out of pocket. In this event, it
is doubtful that policy interventions are necessary or would do any good.
However, similar or worse access, compared with uninsured who are not
offered insurance, would suggest that the decision to decline coverage has
serious consequences regarding access to care. In this case, policies that
provide incentives for individuals to enroll in coverage may be warranted
and effective.
DATA AND METHODS
Data Source The Community Tracking Study (CTS) is a major
initiative of The Robert Wood Johnson Foundation to track changes in the
health care system over time and to gain a better understanding of how
health system changes are affecting people. A more detailed discussion of
the design and scope of the study is provided elsewhere (Kemper et al.
1996; Metcalf et al. 1996). Data collection is focused on 60 randomly
selected communities, or sites, nationwide. Sites were defined as counties
or groups of counties based on Metropolitan Statistical Areas (for
metropolitan sites) and Bureau of Economic Analysis Economic Areas (for
nonmetropolitan sites). Nonmetropolitan sites include areas contiguous
with MSAs and isolated sites clustered around economic centers too small
to be designated as MSAs. The 60 sites were randomly selected with
probability in proportion to population to ensure representation of the
U.S. population. Sites were stratified by region and size to ensure
diversity in these areas.
Households were randomly selected within each of the 60 CTS study
sites. While random-digit dialing was the primary sampling method, a small
field sample was also included to represent households with no telephones
or with intermittent telephone service. Information was obtained about all
adults in the household and one randomly selected child within each family
in the household (all families within a household were interviewed
separately). Interviews were conducted in Spanish for family respondents
who were not fluent in English. For more detail on survey methods and
procedures, see Strouse et al. (1998).
The final sample for the 60 sites include 30,787 families and 54,371
individuals. The overall response rate was 65 percent for families. The
potential for bias in estimates resulting from survey nonresponse cannot
be assessed directly since no information was collected on families that
refused to participate in the survey. Person-level weights used for making
population estimates were post-stratified to correct for any differences
in nonresponse based on age, gender, race/ethnicity and education.
All estimates are weighted to be representative of the civilian
noninstitutionalized population of the continental U.S. and for each of
the 60 communities. Standard errors used in tests of statistical
significance were computed using the SUDAAN software and take into account
the complex survey design, including the clustering of the sample in the
60 sites, the inclusion of multiple families within a household, sampling
multiple adults within families and the random selection of one child.
(Shah et al. 1996).
Methodology for Examining the Determinants of Declining
Coverage The first part of this analysis involves a logistic
regression model to identify the factors associated with an individual
declining employer-sponsored insurance and ending up as uninsured. The
sample for this analysis includes all employed persons between 18 and 64
years of age who are offered and eligible for health insurance coverage at
their workplace (ascertained during the interview) (n=19,324).
Workers who are offered and eligible for coverage essentially have
three options: (1) They can accept the coverage offered by their
employers; (2) they can decline coverage in favor of other private or
public coverage (e.g., accept coverage offered through a spouse’s job,
purchase a nongroup policy or enroll in Medicaid or other public coverage
if eligible); or (3) they can decline coverage and end up as uninsured.
For this analysis, we are primarily interested in examining the factors
that influence the decision to decline coverage specifically when the
result of that decision is to be uninsured (i.e., the third group). Thus,
the dependent variable is coded as 1 if a worker declined coverage and was
uninsured (the third group), and is coded 0 for all other workers who were
offered and eligible for coverage (the first and second groups). While
there may be differences between workers who accept coverage offered by
employers (the first group) and workers who decline coverage in favor of
various other types of insurance (the second group), modeling the full
array of health insurance options (both employer-sponsored and others) is
much more complex and is not central to the objectives of this study,
which is to understand why individuals opt out of employer-sponsored
coverage in favor of being uninsured.
Independent variables were selected that correspond to three general
categories: (1) factors associated with the relative cost to the
individual of employer-sponsored coverage; (2) variables that reflect
individuals’ need and preferences for being insured; and (3) availability
of free sources of health care in the community.
Unfortunately, there are no direct measures of the cost of
employer-sponsored coverage in the survey, such as the amount of the
employees’ share of premiums for employer-sponsored health plans. However,
the survey includes a number of variables that directly or indirectly
reflect the relative cost to the individual of employer-sponsored
coverage. Chief among these is the family income of the worker. Because
the relative cost of coverage to the individual is much higher for
low-income workers, we expect that they will be more likely to decline
coverage when offered. The cost of insurance to workers is also higher
among certain types of employers, either because there is a smaller group
of workers with whom to spread medical risk (e.g., in the case of small
firms), or because firms with certain characteristics have traditionally
been less generous with respect to health benefits (and therefore have
higher employee cost-sharing). Small employers, firms that employ
primarily low-wage workers and industries like agriculture, forestry,
retail sales and certain services are less likely to offer any health
benefits (Cooper and Schone 1997; Long and Marquis 1993; Cantor et al.
1995; Swartz et al. 1993; Gabel et al. 1999), and hence may be less
generous when they do offer health insurance. In fact, employee premium
contributions have been shown to be higher in small firms and firms that
employ primarily low-wage workers (Gabel et al. 1997; Gabel et al.
1999).
Having a choice of health plans may also indirectly reflect differences
in the cost of health insurance to the worker, since having a choice of
more than one plan increases the likelihood that at least one plan will be
attractive to the employee, whether it has lower premium costs or offers
benefits that suit their needs. Firms with multiple plan offerings may
also be inherently more generous with respect to employee health benefits
than firms that offer only a single plan, which may also influence workers
to accept coverage. While there is only limited information in the survey
on characteristics of plans offered by the employer, we distinguish among
workers who are offered (1) a choice of HMO and non-HMO options, (2) a
choice of multiple HMO options, (3) a choice of multiple non-HMO options,
(4) a choice of one HMO plan and (5) a choice of one non-HMO plan.
Economic considerations in deciding whether to enroll in
employer-sponsored coverage are also important to the extent that free
sources of health care are available to uninsured persons in the
community. These are typically referred to as "safety net providers" and
include public and teaching hospitals, community health centers and other
free clinics and hospital emergency rooms. The number and type of safety
net providers varies considerably across communities (Baxter and Feldman
1999; Lipson and Naierman 1996), and it is expected that individuals would
be more likely to decline employer-sponsored coverage in communities where
safety net providers are more extensive. In this study, data from the
American Hospital Association annual survey are used to measure the supply
of public and teaching hospitals in the county of residence (measured as
the number of beds), as well as the number of hospital emergency
departments (EDs), while data from the Bureau of Primary Health Care are
used to measure the number of physicians practicing at federally funded
community health centers in the county. These measures are standardized
relative to the number of low- income persons in the county.
Aside from strictly economic considerations, the decision to forgo
coverage also depends on how salient health care and health insurance
coverage is to the individual and his or her family, and how risk-averse
the individual is with respect to having to incur large health care
expenses because of a sudden illness or accident. We identify a number of
factors that reflect individuals’ need and preferences for having
insurance coverage. These include a measure of the extent to which the
individual perceives himself/herself as being more of a risk-taker than
the average person. A measure of perceived general health is included to
reflect the need for health insurance (because of higher than average
health care use). We include a measure to reflect both the health status
of the individual and a measure that indicates whether any other member of
the individual’s immediate family (i.e., those who could be covered as a
dependent) is in fair or poor health. Need and preferences for health
insurance may also be related to other characteristics of the individual,
including age, gender, educational attainment, race/ethnicity and family
composition (i.e., marital status and whether there are children in the
family).
Controls for the metropolitan status of the area and the nine census
divisions are also included in the model.
Methodology for Examining the Consequences of Declining
Coverage The second objective of this study is to compare the
health care utilization and access of uninsured individuals who decline
employer-sponsored coverage with other uninsured individuals (i.e., those
who do not have access to employer-sponsored coverage) and insured
persons. Because the potential consequences of declining
employer-sponsored coverage also apply to those dependents (i.e., spouses,
children) of workers who decline coverage, we compare all uninsured
persons who have access to employer-sponsored coverage (defined below)
with uninsured persons who do not have access to employer-sponsored
coverage. The sample for this analysis includes all persons under the age
of 65 (n=53,270).
The key independent variable in this analysis–insurance status–is
defined for each individual using the following categories: (1) any form
of private insurance (employer-sponsored or purchased on the individual
market) or military insurance (CHAMPUS); (2) any form of public coverage,
including Medicaid, Medicare or other state program; (3) uninsured with
access to employer-sponsored coverage; and (4) uninsured with no access to
employer-sponsored coverage. Uninsured persons are considered to have
access to employer-sponsored coverage if they are offered and eligible for
coverage through their own job, or they are a dependent (i.e., spouse,
child) of someone in the family who is offered and eligible for
employer-sponsored coverage.
Differences between the four insurance groups on commonly used measures
of access to care and utilization are examined. These include whether or
not the individual has a usual source of care, which is considered
important for facilitating entry into the health care system (Starfield
1992). We also use direct measures of whether the individual reported some
difficulty in obtaining needed medical care in the previous year,
including whether they were not able to get needed care (unmet need),
whether they put off or delayed getting medical care, and whether they
reported any difficulty (unmet need or delayed care-seeking) specifically
due to the cost of care. Ambulatory health care use (from all sources) is
also examined, including the likelihood of having an ambulatory care
visit, the average number of ambulatory care visits (for persons with any
use), and the proportion of ambulatory care visits made to hospital
emergency rooms. Relatively greater use of the hospital ED would suggest
less access to more appropriate sources of primary care, such as a
physician’s office or clinic. Differences in the likelihood of having an
inpatient hospital stay in the past year are also examined. Consistent
with other research on these measures, we expect the findings to reflect
lower access and health care use for uninsured persons as a group
(Cunningham and Kemper 1998; Donelan et al. 1996; Berk et al. 1995;
Cunningham and Whitmore 1998; Krauss et al. 1999).
Because health care utilization and access are strongly related to
other characteristics of individuals, estimates of access and use for each
of the insurance groups were computed while adjusting for other individual
factors. These include age, gender, health status, race/ethnicity, family
income and education. These adjustments were made by estimating regression
equations in which the access and use variables were included as dependent
variables, and the insurance groups and other individual characteristics
were included as independent variables. Logistic regressions were used for
dichotomous dependent variables, while ordinary least squares analysis was
used for the average number of ambulatory visits and the percentage of
visits to a hospital ED.
Predicted values for each insurance group were computed while holding
constant the values of all other independent variables equal to their
population mean. For the logistic regressions, the predicted values were
then transformed back into probabilities to reflect percentages.
RESULTS
Number and Percentage Who Decline Employer-Sponsored
Coverage Overall, 80.3 percent of workers who are offered coverage
through their employer take up that coverage, which is consistent with
other studies (Table 1). Most workers who decline coverage do so in favor
of other health insurance, including private insurance offered through a
spouse’s employer, private insurance purchased in the individual market or
public coverage. Only 4 percent of workers (3.2 million) who are offered
coverage decline that coverage and end up as uninsured.
However, when uninsured dependents of these workers are also included
(i.e., spouses or children who could be covered through a family policy),
findings show that 7.3 uninsured persons have access to employer-sponsored
insurance, either through their own job or through a spouse’s or parent’s
job. These individuals represent about one-fifth of all uninsured persons,
according to the CTS Household Survey data.
Table 1. Number and percentage of workers who decline
employer-sponsored coverage.
| |
Number |
Percent |
|
All workers (age 18-64) offered and eligible for coverage |
79,557,000 |
100.0 |
|
Accept coverage |
63,877,000 |
80.3 |
|
Decline coverage in favor of
other coverage1 |
12,513,000 |
15.7 |
|
Decline coverage and are
Uninsured |
3,167,000 |
4.0 |
1Includes employer-sponsored coverage obtained through a
spouse’s employer, direct purchase of nongroup private insurance,
Medicaid, Medicare, CHAMPUS and other public coverage.
Factors Associated with the Decision to Decline Coverage (in Favor of
Being Uninsured) Table 2 shows the results of the logistic
regression analysis for the likelihood of declining employer-sponsored
coverage in favor of being uninsured. For this analysis, we focus on the
sample of workers from Table 1 who are offered and eligible for coverage
through their employer. As expected, factors related to the relative cost
of employer-sponsored coverage to the individual appear to be highly
salient in the decision to accept or decline coverage. The likelihood of
declining coverage (and being uninsured) is much greater for poor and
low-income workers, and decreases sharply as the family income of the
worker increases. The likelihood of declining coverage is also much higher
for low-wage workers (independent of income), which may reflect either an
additional income effect, or the fact that health benefits are typically
less generous in firms that employ primarily low-wage workers (Gabel et
al. 1999). Workers in traditionally "high uninsurance" industries (e.g.,
retail sales, some services, agriculture, construction) were more than
twice as likely to decline coverage as workers in other industries, which
also suggests that these industry types offer less generous health
benefits.
The number and types of employer offerings have substantial effects on
the decision to enroll in coverage. Compared with persons who have
multiple plan offerings that include at least one HMO plan, those offered
only one plan or a choice of only non-HMO plans are two to three times
more likely to decline coverage. Thus, the key aspect of choice appears to
be multiple plan offerings that involve at least one HMO plan, which may
reflect the fact that HMO plans have generally lower premiums and are
frequently offered by employers to decrease their overall health benefit
costs and to give employees a lower-cost alternative. Alternatively,
employers that offer a diverse set of health plans may be inherently more
generous with respect to employee health benefits than firms that offer
only a single plan.
The effects of firm size on the decision to decline were not
statistically significant, despite the fact that descriptive results from
the CTS data and other studies do show that workers in smaller firms are
more likely to decline coverage (Cooper and Schone 1997). Further analysis
revealed that hourly wage, industry and the number and types of plans
offered by the employer appear to account for the association between firm
size and the decision to decline coverage. When these variables were
excluded from the model, the odds ratio for firm size decreased from the
.92 shown in Table 2 to .75 (an 18 percent decrease) and was highly
significant at the .01 level. Thus, workers in smaller firms are more
likely to decline coverage, not because of the size of the firm per se,
but because they are more likely to be low-wage employees, offered less
choice of plans and employed in typically "high uninsurance"
industries.
In general, availability of safety net providers in the community
appears to have little effect on the decision to decline coverage. Persons
living in counties with a relatively large public hospital capacity are
significantly more likely to decline coverage, although a one standard
deviation increase in public hospital capacity is associated with only a
1.1 percent increase in the likelihood of declining coverage. Even this
small effect appears to be offset by the availability of teaching
hospitals and hospital EDs (i.e., a higher supply of these providers is
associated with a lower likelihood of declining coverage), although these
effects were not statistically significant.
Table 2. Logistic regression analysis of the likelihood of declining
employer-sponsored private insurance in favor of being uninsured.
| |
Odds ratios |
95% Confidence
Intervals |
|
Intercept |
0.30** |
0.12 — 0.74 |
|
Factors that reflect affordability to individuals |
|
|
|
Family income
LT 100% of poverty
100-149% of poverty
150-199% of poverty
200-299% of poverty
300-399% of poverty
400% and above |
1.00
0.56
0.59
0.38
0.30
0.23 |
0.35 — 0.90
0.40 — 0.88
0.25 — 0.60
0.18 — 0.49
0.16 — 0.34 |
|
Hourly wage (+1 S.D.) |
0.34** |
0.21 — 0.44 |
|
Firm size (+1 S.D.) |
0.92 |
0.85 — 1.00 |
|
High uninsurance industry |
2.35** |
2.00 — 2.77 |
|
Employer offerings (number and type)
Multiple plans, both HMO and non-HMO
Multiple plans, HMO only
Multiple plans, non-HMO only
Single plan—HMO
Single plan—non-HMO |
1.00
1.04
2.01**
2.35**
3.20** |
0.63 — 1.72
1.41 — 2.85
1.78 — 3.09
2.43 — 4.22 |
| |
|
|
|
Availability of free sources of health care |
|
|
|
Number of public hospital beds in county (+1 S.D.) |
1.10* |
1.00 -- 1.20 |
|
Number of teaching hospital beds in county (+1 S.D.) |
0.91 |
0.80 -- 1.05 |
|
Number of CHC physicians in county (+1 S.D.) |
1.00 |
0.97 — 1.03 |
|
Number of hospital EDs in county (+1 S.D.) |
0.94 |
0.86 — 1.02 |
| |
|
|
|
Factors related to individual need and preferences |
|
|
|
Risk-averseness
Not a risk-taker
Somewhat of a risk-taker
Strong risk-taker
Unknown |
1.00
1.04
1.34*
0.85 |
0.79 — 1.37
1.05 — 1.72
0.36 — 2.02 |
|
Age
19-24
25-34
35-44
45-54
55 and over |
1.00
0.85
0.60**
0.40**
0.23** |
0.64 — 1.12
0.44 — 0.82
0.27 — 0.60
0.14 — 0.36 |
|
Race/ethnicity
White (reference group)
Black
Hispanic
Other |
1.00
1.59**
1.68*
0.59 |
1.21 — 2.10
1.12 — 2.52
0.35 — 1.00 |
|
Gender (1=male) |
1.14 |
0.89 — 1.45 |
|
Health status of individual
Excellent or very good
Good
Fair
Poor |
0.71
0.72
0.79
1.00 |
0.34 — 1.51
0.34 — 1.49
0.31 — 1.98 |
|
Other family member in fair or poor health |
1.14 |
0.83 — 1.57 |
|
Education
LT 9th grade
9-11th grade
Completed high school
13-15th grade
16th and over |
2.26**
1.48*
1.00
0.67**
0.58** |
1.08 — 4.72
1.02 — 2.14
0.54 — 0.84
0.42 — 0.79 |
|
Family composition
Single
Married, no kids
Single with kids
Married with kids |
1.00
0.53**
0.74
0.40** |
0.37 — 0.75
0.53 — 1.05
0.29 — 0.56 |
| |
|
|
|
Geographic factors |
|
|
|
Place of residence
Large MSA (> 200,000 persons)
Small MSA
Non-MSA |
1.19
0.88
1.00 |
0.90 — 1.57
0.54 — 1.44 |
|
Census Division
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific |
0.80
1.24
1.00
0.60
1.19
0.86
1.63**
1.12
1.04 |
0.51 — 1.24
0.89 — 1.75
0.29 — 1.26
0.76 — 1.86
0.63 — 1.17
1.20 — 2.20
0.78 — 1.59
0.76 — 1.44 |
| |
|
|
* p < .05
** p < .01
Sample includes all employed persons (ages 18-64) who are offered and
eligible for employer-sponsored private insurance (n=19,324).
Factors related to individual need and preferences for being insured
appear to be significantly related to the decision to decline coverage.
While one would certainly expect poor health of the worker or a family
member to strongly decrease the likelihood of declining coverage (because
of greater need for health care and financial protection from high health
expenditures), the results actually show that persons in the best health
were least likely to decline coverage in favor of being uninsured,
although the results for health status were not statistically significant.
It is unclear why the direction of the effect of health status (although
not statistically significant) was the opposite of what was expected. It
is possible that poor health in this analysis is picking up some
unmeasured aspect of wealth, such as high instability of income or the
cumulative effects of economic deprivation over a long period of time due
to disability or chronic illness. Nevertheless, the notion that those who
opt of out health insurance do so because they have very low need for care
is not supported by this analysis.
As one would expect, individuals who considered themselves strong
risk-takers were 1.3 times more likely to decline coverage than persons
who did not consider themselves to be risk-takers. The likelihood of
declining coverage decreases monotonically with age, with young adults
(age 18-24) being the most likely to decline coverage among all age
groups. The much higher likelihood of declining coverage for young adults
may reflect both lower expected health care use (across all levels of
health status) and having fewer financial assets to protect.
Even after controlling for factors related to employment and
socioeconomic status, blacks and Hispanics were more than 1.5 times as
likely to decline coverage as whites. Persons with lower educational
attainment were more likely to decline coverage than more highly educated
persons. Differences in the likelihood of declining coverage by
race/ethnicity and education–controlling for other socioeconomic and
employer characteristics–may reflect differences in the relative
importance of health benefits among these groups, although it is difficult
to determine the specific reasons for these different preferences. It is
also important to point out that these preferences may reflect some
selection into the types of jobs for which health benefits tend to be more
or less generous. For example, employers with a large number of highly
educated workers (e.g., a college or university) may respond to employee
preferences by offering more generous benefits, thereby increasing the
likelihood that these benefits will be accepted.
Family composition also plays a role in the decision to decline
coverage, as married families with children are the least likely to
decline coverage in favor of being uninsured and single individuals are
the most likely to decline coverage. These findings suggest that health
benefits are perceived as more salient to married families and families
with children. However, the marital status effect appears to be stronger
than the effect of having children in the family, given that the odds
ratio for single-parent families was not as strong in magnitude as it was
for married families and was not statistically significant. It is possible
that the somewhat higher rate of refusal among single parents (compared
with married families) is due to having fewer options (i.e., they do not
have spouses who are also offered employer-sponsored coverage), or that
single mothers tend to be employed in jobs that are not typically generous
with respect to health benefits.
There were virtually no significant differences by size of MSA or
Census Division in the decision to decline coverage. Individuals in the
East South Central region were 1.6 times more likely to decline coverage
in favor of being uninsured than persons in the East North Central
region.
Consequences of Being Uninsured When Coverage is
Declined Table 3 shows the adjusted means for health care
utilization and access by insurance status. As expected, uninsured persons
in general (compared with both private and publicly insured) are less
likely to have a usual source of care, more likely to have difficulty
getting health care, have generally lower utilization of all types of
services and have a higher proportion of ambulatory care visits in
hospital emergency departments.
However, the findings provide little evidence that uninsured persons
with access to employer-sponsored coverage differ fundamentally from other
uninsured in their access to and use of health care services, and that, in
fact, the decision to decline coverage appears to have consequences for
their ability (and the ability of other family members) to get medical
care. This is seen most explicitly by the fact that uninsured persons with
access to employer-sponsored coverage are just as likely to have
difficulty getting medical care (either not getting or delaying care) as
other uninsured persons, and have much greater difficulty than insured
persons. There are no significant differences in any type of health care
use between uninsured adults with access to employer-sponsored coverage
and other uninsured adults.
The same is largely true for uninsured children with access to
employer-sponsored coverage, although their proportion of ambulatory
visits at hospital emergency rooms is similar to privately insured and
publicly insured children, and significantly less than children with no
access to employer-sponsored private insurance. This suggests that
children with access to employer-sponsored private insurance are better
able to obtain care in appropriate primary care settings than other
uninsured children, possibly because children are often the focus of
direct care services provided through publicly sponsored community and
school-based clinics. However, while this may influence to some extent the
parent’s decision to decline insurance, overall service use and access of
these children is still significantly below that of insured children.
Table 3. Differences in access to care and health care use for the
nonelderly, by insurance status.
| |
|
Difficulty getting care in past year |
Ambulatory care use in past year2 |
|
| |
% with no usual source of care |
% with unmet need |
% who delayed care |
% with any difficulty due to cost1 |
% with any use |
Average number of visits3 |
% of visits at hospital ED3 |
% with any inpatient stay |
|
Adults (18—64) |
|
|
|
|
|
|
|
|
|
Private coverage |
10.1* |
4.4* |
17.4* |
7.7* |
83.1* |
5.2* |
8.6* |
8.4* |
|
Public coverage |
11.1* |
4.9* |
15.3* |
6.5* |
86.3* |
7.6* |
10.3* |
10.6* |
|
Uninsured—no access to ESPI |
28.0 |
13.2 |
34.6 |
31.0 |
64.2 |
4.1 |
17.1 |
6.7 |
|
Uninsured—has access to ESPI |
27.3 |
13.3 |
33.7 |
32.0 |
64.3 |
3.7 |
15.9 |
6.5 |
| |
|
|
|
|
|
|
|
|
|
Children (LT 18) |
|
|
|
|
|
|
|
|
|
Private coverage |
3.2* |
1.9* |
4.0* |
2.2* |
87.1* |
4.6* |
8.9 |
4.7 |
|
Public coverage |
1.8* |
2.5* |
5.3* |
1.7* |
92.1* |
5.1* |
9.9 |
6.3 |
|
Uninsured—no access to ESPI |
13.5 |
8.6 |
13.1 |
12.4 |
71.7 |
3.1 |
12.8* |
3.2 |
|
Uninsured—has access to ESPI |
11.0 |
7.5 |
14.2 |
13.3 |
74.0 |
3.8 |
8.6 |
2.5 |
*Difference with "uninsured–has access to ESPI" is statistically
significant at .05 level.
Access to ESPI— Employment-sponsored private insurance is offered by
the person’s employer or the spouse’s employer (for adults), or through a
parent’s employer (for children).
1 Includes persons who reported that they were not able to get
needed services in the past year, or they had to put off getting services
in the past year due to concerns about the cost of care.
2 Includes visits to physicians and nonphysicians at all sites,
including physician offices, hospital outpatient clinics and EDs, clinics
and urgent care centers.
3 Includes only persons with one or more ambulatory visits.
All estimates were adjusted to control for differences across insurance
groups on the following factors: age, gender, health status,
race/ethnicity, family income and education. The adjusted means and
percentages were computed using multiple regression analysis.
CONCLUSION To what extent should policy
makers be concerned about individuals who decline employer-sponsored
coverage? On the one hand, very few with access to employer-sponsored
coverage (through their own job or a spouse’s) decline this coverage, and
most who opt out do so in favor of other private or public coverage. While
previous research indicates that the percentage of persons declining
employer-offered coverage is increasing (Cooper and Schone 1997), it is
unclear whether the growing number of those who decline coverage are able
to find other health insurance or they become uninsured.
On the other hand, those uninsured with access to employer-sponsored
coverage (more than 7 million) comprise one-fifth of the total number of
uninsured. Thus, 100 percent acceptance of employer-sponsored coverage
would do more to decrease the number of uninsured persons than the
incremental insurance expansions that have been passed in recent years or
are under consideration, such as the Health Insurance Portability and
Accountability Act, the State Children’s Health Insurance Program and the
proposed Medicare buy-ins for the near-elderly.
One could also argue that declining employer-sponsored coverage–even if
the result is to be uninsured–is not a problem when it represents a
rational choice. That is, persons decline coverage either because they
don’t need health care or because they are able to obtain needed care
without insurance. However, the findings from this study strongly refute
this. First, persons in the best health (i.e., those with presumably the
fewest health care needs) were actually less likely to decline
coverage than those in the poorest health, although this finding was not
statistically significant. Second, uninsured persons with access to
employer-sponsored coverage reported as much difficulty in obtaining
needed care as other uninsured persons, and both groups of uninsured have
much greater difficulty getting care than privately or publicly insured
persons. For the most part, levels of service use were also comparable for
both groups of uninsured, suggesting neither greater access nor lower
demand among those uninsured with access to employer-sponsored insurance.
Thus, the decision to decline employer-sponsored coverage in favor of
being uninsured appears to have the same negative consequences regarding
access to care as it does for all other uninsured persons.
The findings also provided very little evidence that a large safety net
capacity in an area induces individuals to decline employer-sponsored
coverage, presumably because free sources of health care mitigate the need
for insurance. While much concern has been expressed about the potential
for private insurance "crowd-out" stemming from expansions in Medicaid and
the State Children’s Health Insurance Program, similar concerns about
"safety net crowd-out" of private insurance are not warranted by these
findings. In fact, safety net providers often serve as the focal point of
outreach efforts in communities to enroll low-income persons in health
insurance coverage for which they are eligible, although much of this
effort is directed at public programs such as Medicaid. Given their
tenuous dependence on public funds and the financial pressures many are
currently experiencing in providing uncompensated care, safety net
providers have a vested interest in getting their patients enrolled in
private insurance plans that would give providers important new sources of
revenue.
Thus, declining employer-sponsored coverage is an important matter for
policy makers to consider. But given the already high rates of acceptance
of employer-sponsored coverage, is it reasonable to expect that 100
percent enrollment could be attained? Without additional financial
incentives and/or mandates, probably not. As indicated by the findings in
this study, most of the strongest determinants of whether coverage was
declined reflected the cost to the individual or family, and low-income
and low-wage workers were far more likely to decline coverage than other
workers. While policy makers are currently considering the use of tax
credits to provide financial incentives for uninsured persons to purchase
coverage, it is notable that many low-income persons decline
employer-sponsored coverage despite the already significant financial
incentives of employer-subsidized premiums, tax exclusions on the employer
share of the premium and group rates. Nevertheless, refundable tax credits
would provide an additional incentive to low-income persons to enroll in
employer-sponsored insurance, since they currently pay little or no tax
and, therefore, they currently benefit little from the exclusions from
taxes of employer-paid premiums.
One important limitation of this study is that we were unable to
directly assess the effects of premium costs or plan benefits on the
decision to decline coverage, although the fact that workers were three
times more likely to decline coverage when offered only a single non-HMO
plan (compared with workers offered a choice of HMO and non-HMO plans)
suggests that the mix of benefits and level of employee cost-sharing is
relevant. Future research should examine this more explicitly, since
refusing plans with high deductibles and limited benefits may be
understandable for some workers, especially low-income and young adult
workers who have few assets to protect and limited income with which to
pay the potentially substantial out-of-pocket costs. From a policy
perspective, it is unclear how much better off these workers would be (in
terms of access and health care use) by accepting such plans, and
providing financial incentives to workers to take up these types of plans
may not be particularly meaningful if workers perceive them to be of
limited value.
Nonetheless, individual differences in how much value and importance is
placed on health insurance–regardless of the benefits package–also plays a
role, and there will always be some who opt out as long as health
insurance is strictly voluntary. Even individual assessments of whether
they can afford health insurance depend in part on how willing and able
they are to forgo other goods and services that could be purchased with
the money used to pay premiums. But while individuals differ in this
economic calculation–which is especially difficult for low-income
persons–those who opt out still face the same problems that all other
uninsured persons have, which is greatly diminished access to health care
services.
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The author would like to thank Paul Ginsburg, Peter Kemper, Chris
Hogan, and Sally Trude for reviewing an earlier version of the manuscript
and providing helpful comments. Beny Wu of Social and Scientific Systems,
Bethesda, Md., provided excellent programming assistance. |



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