Who funds their health savings account and why?

Int J Health Care Finance Econ (2013) 13:219–232DOI 10.1007/s10754-013-9131-8

Who funds their health savings account and why?

Song Chen · Anthony T. Lo Sasso · Aneesh Nandam

Received: 17 May 2012 / Accepted: 30 August 2013 / Published online: 22 September 2013© Springer Science+Business Media New York 2013

Abstract Health savings account (HSA) enrollment has increased markedly in the last sev-eral years, but little is known about the factors affecting account funding decisions. We use aunique data set containing from a bank that exclusively services HSA funds linked to healthstatus, benefit design, plan coverage, and enrollee characteristics from a very large nationalhealth insurance company to examine the factors associated with HSA contribution. Wefound that even small employer contributions had an apparently large effect on the decisionto open an account: the account-opening rate was 50 % higher when employers contributedto the account. Conditional on opening an HSA, employee contributions were negativelyassociated with the amount of employer contribution, contributions rose with age, income,education, and health care need.

Keywords High deductible health insurance · Consumer driven health insurance ·Health insurance benefit design

Introduction

According to the most recent Kaiser Family Foundation and Health Research and Educa-tional Trust (2011) employer benefit survey, 18 % of firms offering health benefits offered ahealth savings account (HSA) and 9 % of all covered employees were enrolled in an HSA.

S. ChenUnitedHealth Group, Minnetonka, MN, USAe-mail: [email protected]

A. T. Lo Sasso (B)Division of Health Policy and Administration, School of Public Health, University of Illinois at Chicago,1603 W. Taylor Street, Chicago, IL 60612, USAe-mail: [email protected]

A. NandamIcahn School of Medicine at Mount Sinai, New York, NY, USAe-mail: [email protected]

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Advocates have singled out HSAs as mechanisms to turn price-insensitive patients into moreprice sensitive consumers of health care by making health care prices more salient via highdeductible insurance paired with a savings account that can only be used for qualified healthcare purchases. Based on a survey of individuals with high deductible insurance coveragecoverage, Fronstin (2012) estimated that in 2011 there was $12.4 billion in account-basedhigh deductible insurance1 spread across 8.4 million accounts with an average account bal-ances of $1,470. There is a considerable body of work examining spending associated withHSA plans and use of particular services (Steinorth 2011; Buntin et al. 2011; Waters et al.2011; Chen et al. 2010; Lo Sasso et al. 2010a; Cress 2009; Greene et al. 2008; Rowe et al.2008). However, little work has examined the use of HSAs as a mechanism for precautionarysaving for health care needs. Our goal is to study the factors associated with employee HSAfunding decisions.

HSA plan designs for calendar year 2012 have a statutorily required a minimum annualdeductible of $1,200 for self-only coverage and $2,400 for family coverage and annual out-of-pocket maximum expenses (deductibles, copayments, coinsurance, though not premiums)cannot exceed $6,050 for self-only coverage and $12,100 for family coverage. The annuallimit on contribution of pre-tax dollars to the savings account in 2012 was $3,100 for self-only coverage and $6,250 for family coverage. Persons aged 55 and over may contribute anadditional $1,000 as so-called “catch-up” contributions. Funds withdrawn from the accountsfor non-qualified health care purchases are taxed and subject to a 10 % penalty for individ-uals under age 65, the penalty is waived for those aged 65 and over (though not the tax).The accounts are portable and owned by the employee. Additionally, accounts earn interestand funds can be invested (though banks typically require a minimum cash balance in theaccounts); any capital gains and interest earned are also untaxed. Unspent account balancesat the end of the policy year can be carried over into the subsequent year. Thus, unlike flexiblespending accounts, there is no “use it or lose it” rule with HSAs. Moreover, the accounts areowned by the employees; thus if the employee experiences a job separation, he or she canmaintain coverage and potentially carry the HSA into subsequent employment.

HSA holders use funds to pay for qualified health care services without federal tax liabilityor penalty. Prior to the deductible being met, enrollees pay the full (contract) price for healthcare services. Should the account be exhausted prior to reaching the deductible, enrolleespay the full price of their health care needs out-of-pocket until the deductible is met. Afterthe deductible is met, members may be responsible for coinsurance and other forms ofcost-sharing until the plan’s out-of-pocket maximum is met. If HSA funds remain after thedeductible has been met funds can be used for payment of post-deductible cost-sharing.

Often, employers make contributions to the account, though they are not obligated tocontribute. Employers can contribute in a lump sum or in any amounts or frequency theywish, as long as the combination of employer and employee contributions does not exceed theIRS annual maximums over the course of the year. The level of employer contributions aretypically comparable (e.g., in the same dollar amount or same percentage of the employee’sdeductible) for all employees in the same class, and may be varied for full-time versus part-time employees, and employees with self-only coverage versus family coverage. Thoughstill rare, an increasing number of employers vary contribution levels based on employees’compensation. Some prior industry studies have suggested that employer contributions tothe HSA are associated with higher HSA enrollment rates (Hewitt Associates 2007; AHIP2010). The previously noted Fronstin (2012) study examined several correlates of funding

1 This figure included both HSAs and Health Reimbursement Arrangements (HRAs), the latter being purelynotional accounts lacking portability and enrollee ownership.

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Who funds their health savings account and why? 221

behavior, but the author lacked key information on employer contributions and, moreover,did not examine differences between individuals in HSAs and HRAs.

The present study adds substantially to the limited literature on the subject by integratinghealth plan data with the bank account balance data provided by the United Health Group(UHG) and OptumHealth Bank (OHB). UHG is one of the largest insurers in the US andalso one of the largest players in the HSA market. UHG serves more than 75 million peopleworldwide, including over two million HSA members in the US. OHB, a UHG fully-ownedbank, is a leading custodian on HSAs with nearly 600,000 accounts. Our data are augmentedby proxy measures for income, wealth, education, and race/ethnicity; such information israrely available when using administrative insurance data.

Conceptual framework

Funding an HSA has similarities to both purchasing more health insurance and precaution-ary saving. We therefore hypothesize that factors affecting HSA funding decisions closelymirror the demand for insurance and the motivators of saving. In this spirit, individualsexpecting to use more health care services due to illness or chronic conditions are likelyto contribute more to their HSAs. Older individuals and subscribers with family coverageare expected to contribute more to their accounts. Clearly the tax treatment of the accountsis crucial: the higher are marginal tax rates for the individual, the greater is the implicitsubsidy. Therefore, higher income individuals can be expected to contribute more to theirHSAs. Individuals with less generous health insurance benefits, as measured with higherdeductibles, coinsurance, and copayments are expected to contribute more to their accounts.When employers make contributions to employee accounts we anticipate that employer dol-lars should substitute for employee dollars and therefore lead to a lower contribution level byemployees.

Data and methods

Study population

Our study sample was generated by first identifying subscribers who enrolled in an HSA planin September 2010 offered by an employer with 100 or more employees (considered largegroup). Enrollees in this context can be a family or an individual. Identified subscribers werematched to bank records for active customers in September 2010. HSA enrollees can openaccounts at banks other than OHB, but we do not observe such subscribers. Because we onlyobserve OHB customers, individuals are unobserved to us either because, (1) they did notopen an HSA anywhere or (2) they opened an account with another bank. As a result, much ofour analysis is restricted to individuals that open accounts with OHB (regardless of whetherthe employer or the employee contributes to the account). By focusing on accounts at OHB,there is risk that we are undercounting individuals who chose not to contribute to the HSA.The concern about under-counting zeros must be balanced against the risk of misclassifyingindividuals as not opening HSAs when they did in fact open them. In the analysis that followswe condition our analysis on opening an HSA with OHB, but we provide descriptive statisticson the broader sample of individuals working for employers that offered HSAs in Appendix.The final study population was composed of 307,756 employees of which 164,297 openedaccounts with OHB across 359 employers.

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222 S. Chen et al.

Key measures

The primary outcome measures are whether the enrollee opened an HSA and, conditional onopening an account, the annual amount contributed by employees to their HSA. The fundinginformation comes directly from OHB data for calendar year 2010, which categorizes allaccount credits and debits and allows for the clear identification of employee contributions.

Among the primary independent variables of interest is the employer contribution to theHSA. As with the employee contribution the annual amount that an employer contributedto an account holder was ascertained from bank records. We also measure a number ofkey benefit design characteristics, including the annual deductible, office visit copayment,and coinsurance (percent of eligible expenses after satisfying the annual deductible untilout-of-pocket is reached) for inpatient services. This coinsurance rate fell into three lev-els:2 0, 10, and 20 %. We also constructed an indicator variable for whether the subscriberhad 100 % preventive care coverage (zero copayment and zero coinsurance for wellnessvisits); this typically includes physician office services such as routine physical examina-tions, cancer screening, well-baby and well-child care, vision and hearing screenings, andimmunizations.

We measured for the type of contract3 for a subscriber (single, single + 1, or family)and whether a subscriber had 12-month enrollment in a HSA in the calendar year of 2010(full vs. partial year). We obtained demographic information such as subscriber’s age andgender from enrollment data. Additional measures not typically available from insuranceenrollment data were obtained via a vendor skilled at large-scale data mining, matching,and imputation strategies (KBM Group). Characteristics obtained from the vendor included:race/ethnicity of subscriber (African American, Asian, Caucasian, or Hispanic), highest edu-cation level in the family (high school or lower, college, or graduate), family net worth(<$250,000, $250,000–$499,999, $500,000–$749,999, $750,000–$999,999, ≥$1 million),and family income (<$50,000, $50,000–$74,999, $75,000–$99,999, $100,000–$149,999,≥$150,000). While we consider these measures proxies for the underlying variable of inter-est, such measures, even in proxy form, are of particular interest given their likely importancein affecting HSA funding decisions.

To account for health status, we controlled for the highest co-morbidity risk score inthe household. The risk scores were computed with Episode Risk Groups (ERG) softwareusing enrollment data and medical and pharmacy claims. ERG is derived from the EpisodeTreatment Group (ETG) methodology, which is a widely used software product for illnessclassification and episode building.4 Higher risk scores imply higher illness burden. A scoreof 1.00 indicates risk comparable to that of the average person for the large managed carepopulation that was used to develop ERG; a score of 1.10 indicates 10 % greater risk, and soforth.5 We used ETG-derived variables to identify the presence of several chronic conditions

2 In our study population, the coinsurance for hospitalizations was 0, 10, or 20 % in most cases but mightbe 5, 15 %, or higher than 20 % in rare cases (together accounted for two percent of the total population). Wejoined 5 % into the 10 % category, all levels higher than 10 % into the 20 % category.3 Single contracts include employee-only plans. Single + 1 contracts include two-person plans, such asemployee and domestic partner, employee and one child, employee and spouse. Family contracts includethree people or more plans, such as employee and children; employee, spouse, and one child; employee,spouse, and children; and spouse and children.4 Both ERGs and ETGs are products of OptumInsight, a subsidiary of UHG.5 The literature reports that ERG risk scores highly correlate with other risk-adjusted measures of practiceefficiency, such as Adjusted Clinical Groups, Burden of Illness Score, Clinical Complexity Index, DiagnosticCost Groups, and General Diagnostic Groups (Thomas et al. 2004).

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in the family: asthma or chronic obstructive pulmonary disease (COPD), coronary arterydisease (CAD), and diabetes.

Statistical analysis

We use ordinary least squares (OLSs) to study the factors associated with employee contri-bution levels to their HSA conditional on the account being opened OHB. The dependentvariable is the amount of annual employee contribution in 2010 and only account hold-ers were included in the analysis. The OLS model controls for the employer contributionamount in 2010, other health plan characteristics, and the subscriber-level explanatory vari-ables described above. We also include employer fixed effects in the model to control forunobserved company-level factors. Robust standard errors are clustered at the employer level.

Results

Descriptive analysis of study population

The study population included 359 employers, among which 284 (79 %) made contributionsto their employees’ accounts and 75 (21 %) did not fund. Of those that funded, 115 (32 %of total employers) contributed on average more than $1,000 to their employers annually, 67(19 %) contributed between $650 and $999 annually, 63 (18 %) contributed between $350 and$649 annually, and 39 (11 %) contributed between $60 and $349 annually. Nearly two-thirdsof the employers offered HSAs as an option (vs. full replacement) in 2010 (62 %). Over halfof the employers used fully insured plans6 (56 %) in contrast to using administrative servicesonly (ASO).7

The study population was composed of 307,756 subscribers under age 65 who worked forthe studied employers and also were enrolled in an HSA plan provided by UHG in September2010. Among these subscribers 164,297 (53 %) opened their accounts at OHB. The accountopen rate was significantly lower when employers did not fund (34 %) and was much higherwhen employer contributed (84 %). What is noticeable about the contrast between employercontributors and employer non-contributors is that the rate of account opening by employeesis strikingly stable across employer funding levels, suggesting that roughly 15 % of enrolleesare likely to open accounts at banks other than OHB given that employees are unlikely toleave employer-contributed HSA funds “on the table” by not opening an account. Moreover,if we assume the same rate of non-OHB use among employer non-contributors of 15 %,implying approximately 50 % of HSA enrollees open accounts when their employer does notcontribute, the results suggest that even quite small contributions by employers apparently“nudge” employees to open accounts for their HSAs (Table 1).

In general, enrollees who opened HSAs with OHB were more likely to be younger(between 25 and 54 years), have college education, family net worth lower than $250,000,family income higher than $75,000, lower illness burden, higher deductibles, and greatertendency to have a family contract relative to non-OHB openers. A side-to-side comparisonon characteristics between OHB account openers and non-openers is available in Appendix.As discussed, because it is not possible to distinguish between individuals who chose not

6 A fully insured plan is where an employer contracts with UHG to assume financial responsibility forenrollees’ claims and for all incurred administrative costs.7 ASO is an arrangement in which an employer hires UHG to deliver administrative services such as claimsprocessing to the employer, but the insurer in such scenarios bears no risk.

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224 S. Chen et al.

Table 1 Account open amongeligible HSA subscriber

By employer annual contributionamount (n = 307,756)*** p < 0.001

Employer contribution level*** N Percent

Funders 117,040 84

$1000+ 22,775 83

$650–$999 54,806 85

$350–$649 24,707 84

$60–$349 14,752 84

Non-funders 190,716 34

05

1015

2025

Per

cent

0 5000 10000 15000

Enrollee HSA Contributions ($)

Fig. 1 Histogram of employee HSA contributions among account openers

to open an HSA and those who chose to open an account with a bank other than OHB, wecondition our remaining analyses on opening an HSA with OHB. We have no reason tosuspect, however, that behavior among OHB customers and customers of other banks shoulddiffer in terms of their response to various measured characteristics. One possible reasonindividuals might have an account at another bank is that they already had an HSA from aprevious employer. Again, however, the potential for selection bias is not obvious.

Figure 1 displays a histogram of account contributions by enrollees opening accountswith OHB. The descriptive analysis of employee contribution among OHB account openersis displayed in Table 2. For continuous explanatory variables, we report means and standarddeviations, as well as their correlation with employee contributions. For categorical variables,we reported their frequency distribution and the average employee contribution for eachcategory. We observe a negative relationship between employee and employer contributions(−0.19, p < 0.001). We also observe that employee contributions were higher in olderage groups ($508 for under 25 years old age group, $1,103 in 25–34 group, $1,937 in 35–44 group, and $2,534 in 55 and above, p < 0.001), among women relative to men, albeitslightly ($2,035 vs. $2,003, p < 0.001). Contributions increased with higher education($1,545, $,2,165, and $2,678 for high school or lower, college, and graduate school education,respectively), higher family net worth (average employee contribution among people withnet worth over $1 million was twice of that among people with net worth under $250,000,p < 0.001), and higher family income (average employee contribution among people with

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123

226 S. Chen et al.

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123


family income over $100,000 was more than twice of that among people with family incomeunder $50,000, p < 0.001).

We also found a positive correlation between employee contribution and illness burden(0.18, p < 0.001) as well as the presence of several chronic conditions such as asthma orCOPD ($2,652 vs. $1,934, p < 0.001), CAD ($2,691 vs. $1,973, p < 0.001), or diabetes($2,459 vs. $1,982, p < 0.001).

In addition, we found employee contribution is positively correlated with deductible (0.26,p < 0.001), although the relationship between HSA contributions and coinsurance went theopposite direction ($2,203, $1,976, and $1,945 for 0, 10, and 20 % coinsurance, respec-tively, p < 0.001). A negligible correlation with office visit copayment levels was observed(−0.01, p < 0.001). We also found that employee contribution was higher for people withnon-single contracts ($1,019, $2,310, and $2,699 for single, single+1, and family contracts,respectively, p < 0.001) and full year plan coverage ($2,065 vs. $1,824, p < 0.001).

Factors affecting employee contribution

OLS estimates of the factors affecting employee contribution, controlling for employer fixedeffects, are reported in Table 3. We found a negative relationship between employer andemployee contribution: each additional dollar contributed by the employer reduced theemployee’s contribution by 35 cents (p < 0.001). No other plan design characteristicachieved statistical significance, but the coefficient for deductible suggests that a $1 increasein the deductible leads to 13 cent larger HSA contribution (p = 0.11), as predicted by ourconceptual model. Not surprisingly, higher employee HSA contribution was associated withhaving a family contract ($1,182, p < 0.001) or single + 1 contract ($721, p < 0.001)relative to single contract, and having full year plan coverage compared with a partial yearcoverage ($263, p < 0.001).

Employee contribution was strongly associated with demographic and health status vari-ables. We found a positive relationship between employee contribution and older age. Morespecifically, people aged 55 and over contributed $945 more than people younger than 25years of age, some of which could reflect that those 55 and over can make “catch-up” contri-butions to their accounts. The education proxy measures performed in the expected direction:employee contributions were higher among people with college ($106, p < 0.001) or grad-uate school education ($329, p < 0.01) compared with those with high school or lower edu-cation. All else constant, African Americans and Hispanics contributed less to their accountsrelative to Caucasians while Asians contributed more. As had been observed in the bivariateanalysis, both net worth asset and family income were positively associated with employeecontributions. In addition, employee contribution was also higher for people with higherillness burden ($45 for each one unit increase of ERG risk score, p < 0.001) or chronicconditions such as asthma or COPD ($218, p < 0.001) and diabetes ($56, p < 0.05).

Discussion

HSAs represent an increasing fraction of private health plan membership in the US. AlthoughHSAs have become popular among consumers, our study is the first to highlight the factorsassociated with employee funding levels. Our findings suggested that the account open rateincreased substantially even when employers funded at a modest level—as low as $5 permonth—though we acknowledge that account openings are only partially observed in ourdata. Conditional on opening an account, the negative effect of employer funding is not

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228 S. Chen et al.

Table 3 OLS estimates for employee HSA contribution among account openers (n = 164,297)

Explanatory variables† Estimates ($) SE ($) Significance

Benefit design and plan coverage

Employer contribution −0.35 0.05 ***

Deductible 0.128 0.081

Inpatient coinsurance (ref: 0 %)

10 % −161 246

20 % −210 224

Office visit copay (scaled by $10) 32 28

Free preventive care (vs. non-free) −193 122

Contract type (ref: single)

Single + 1 721 133 ***

Family 1,182 140 ***

Full year plan coverage (vs. partial year) 263 67 ***

Demographic

Age (ref: under 25 years)

25–34 212 35 ***

35–44 431 48 ***

45–54 646 46 ***

55–64 945 58 ***

Female (vs. male) 5 8

Education (ref: high school)

College 106 20 ***

Graduate school 329 104 **

Ethnicity (ref: Caucasian)

African American −205 27 ***

Asian 142 46 **

Hispanic −277 17 ***

Family net worth (ref: under $250,000)

$250,000–$499,999 175 19 ***

$500,000–$749,999 316 22 ***

$750,000–$999,999 363 42 ***

$1 Million and above 471 46 ***

Family income (ref: under $50,000)

$50,000–$74,999 65 11 ***

$75,000–$99,999 137 21 ***

$100,000–$149,999 289 24 ***

$150,000 and above 440 38 ***

Health status

Co-morbidity score 56 6 ***

Asthma/COPD (vs. no) 218 19 ***

CAD (vs. no) 49 29

Diabetes (vs. no) 56 24 *

∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001; † Regression model includes employer fixed effects

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necessarily surprising and somewhat mechanical given the annual contribution limit, it isnevertheless perhaps surprising that the effect is less than dollar-for-dollar. The findingssuggest that employees could be using their accounts as a tax-free hedge against futurereductions in employer health insurance benefit generosity.

Consistent with expectations, contributions increased with the amount of the impliedtax subsidy: our family income, net worth, and education proxies all suggested a pos-itive and significant relationship with account contribution. Contributions were higheramong individuals with greater health care needs. Contributions also increased consis-tently with age; some of this increase is likely due to greater health care need amongolder individuals, but some is also likely due to the provision of the law allowinggreater contributions for enrollees aged 55 and over. Also of note, African Americansand Hispanic enrollees appeared to have lower contribution levels than whites, all elseconstant.

Our study has important implications to employers and insurers. Small contributions byemployers to their employees’ accounts do appear to “nudge” employees to open accounts,though the advantages of large contributions by the employer are not obvious. Moreover,the effect of increased HSA contributions overall would only appear to increase the poten-tial for moral hazard in consumption of health care. Lo Sasso et al. (2010b) found thatfor each additional dollar placed in the account, another dollar of health care was con-sumed. Though it is possible that the act of opening the account and monitoring its bal-ance provides the mechanism for salience of actual health care prices to affect behav-ior. Insurers argue that this “engagement” is a key determinant in a virtuous cycle ofsavings and active “consumerism” with respect to health care purchasing decisions. The“engagement” versus moral hazard hypothesis is clearly beyond the scope of the presentresearch. Lastly, our findings highlight the potential role for HSAs in serving as a methodto subsidize health care services for individuals with high illness burden, chronic condi-tions, low incomes, and less generous plan benefit and coverage. Direct subsidies to anaccount could be far preferable in efficiency terms than coverage mandates or communityrating (Pauly 1970).

There are some important limitations of our study. The adoption rate that we reportlikely under-represents the true adoption rate since HSA subscribers could have opened theiraccounts at banks other than OHB. By conditioning our analysis on opening an accountwith OHB, regardless of how much was contributed (e.g., some people might not con-tribute anything in year 2010), we missed people who did not open accounts at OHBand who also had zero contribution. The mean account contribution level in our condi-tional analysis is therefore high relative to the overall (unconditional) mean. Another lim-itation is that we did not have information on whether firms offered plans from other car-riers. While this is unlikely to affect the internal validity of our findings, caution shouldbe taken in generalizing our results to employers using other insurance carriers or tosmall groups. Although our employers were from different regions and different indus-tries, all firms provided UHG products, which could be different from the products ofother health insurers. That being said, given that more than 20 % of HSA enrollees nation-ally are covered by UHG, our work is certainly broadly representative of HSA enrolleesnationally.

Appendix

See Table 4.

123

230 S. Chen et al.

Tabl

e4

Com

pari

son

onch

arac

teri

stic

sbe

twee

nac

coun

tope

ners

with

Opt

umH

ealth

Ban

kan

dno

n-op

ener

s(n

=30

7,75

6)

Exp

lana

tory

vari

able

sN

on-o

pene

rs(n

=14

3,45

9)O

pene

rs(n

=16

4,29

7)E

xpla

nato

ryva

riab

les

Non

-ope

ners

(n=

143,

459)

Ope

ners

(n=

164,

297)

Dem

ogra

phic

Hea

lthst

atus

Age

grou

p(i

nye

ars)

***

Co-

mor

bidi

tysc

ore*

**2.

06(3

.43)

1.82

(2.7

4)

Und

er25

(%)

32

Ast

hma/

CO

PD**

*

25–3

4(%

)13

19N

o(%

)92

89

35–4

4(%

)14

25Y

es(%

)8

11

45–5

4(%

)17

31C

AD

55–6

4(%

)53

23N

o(%

)91

94

Gen

der*

**Y

es(%

)9

6

Fem

ale

(%)

5249

Dia

bete

s***

Mal

e(%

)48

51N

o(%

)90

93

Edu

catio

n***

Yes

(%)

107

Hig

hsc

hool

(%)

2622

Ben

efitd

esig

nan

dpl

anco

vera

ge

Col

lege

(%)

7478

Ded

uctib

le**

*($

)2,

070

(1,0

41)

2,93

5(1

,394

)

Gra

duat

esc

hool

(%)

0.17

0.24

Inpa

tient

coin

sura

nce

Eth

nici

ty**

*0

%8

24%

Afr

ican

Am

eric

an(%

)8

510

%78

%38

%

Asi

an(%

)4

520

%14

%38

%

Cau

casi

an(%

)79

80O

ffice

visi

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ay**

*($

)0.

85(4

.58)

2.24

(7.1

9)H

ispa

nic

(%)

66

Prev

entiv

eca

reco

vera

ge**

*

123


Tabl

e4

cont

inue

d

Exp

lana

tory

vari

able

sN

on-o

pene

rs(n

=14

3,45

9)O

pene

rs(n

=16

4,29

7)E

xpla

nato

ryva

riab

les

Non

-ope

ners

(n=

143,

459)

Ope

ners

(n=

164,

297)

Fam

ilyne

twor

th**

*N

on-f

ree

(%)

313

Und

er$2

50,0

00(%

)41

50Fr

ee(%

)97

87

$250

,000

–$49

9,99

9(%

)27

27C

ontr

actt

ype*

**

$500

,000

–$74

9,99

9(%

)16

13Si

ngle

(%)

5135

$750

,000

–$99

9,99

9(%

)7

5Si

ngle

+1

(%)

3023

$1M

illio

nan

dab

ove

(%)

105

Fam

ily(%

)19

42

Fam

ilyin

com

e***

Full

year

plan

cove

rage

***

Und

er$5

0,00

0(%

)21

15N

o(%

)15

20

$50,

000–

$74,

999

(%)

2627

Yes

(%)

8580

$75,

000–

$99,

999

(%)

2325

$100

,000

–$14

9,99

9(%

)25

28

$150

,000

and

abov

e(%

)5

5

∗∗∗ p

<0.

001

123

232 S. Chen et al.

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