a b s t r a c t

Context: The United States (US) is the only developed country that does not guarantee short-term or longer-term paid sick leave.

Objective: This study used a multiyear nationally representative database to examine the association between availability of paid sick leave and frequency of emergency department (ED) use among US private sector employees.

Study sample: We used the National Health Interview Survey data (2012-2014). The final study sample consists of 42,460 US adults between 18 and 64 years of age and working in nongovernmental private sector.

Results: Our results suggest that availability of paid sick leave is significantly associated with lower likelihood of ED use, for both moderate (1-3 times/year) and repeated users (4 or more times/year). After controlling for confounding factors, respondents with paid sick leave are 14% less likely to be moderate ED users (adjusted odds ratio, 0.86; 95% CI, 0.79-0.93) and 32% less likely to be repeated ED users (adjusted odds ratio, 0.68; 95% CI, 0.50-0.91). Discussion: Although expansion of health insurance coverage under the Affordable Care Act has not been shown to reduce utilization of high cost health care services such as the ED, our study suggests other factors such as the avail- ability of paid sick leave may do so, by allowing patients to seek care through other more cost-effective mechanisms (eg, primary care providers). To reduce ED utilization, health policymakers should consider alternative reforms in- cluding paid sick leave.

(C) 2016

1. Introduction

Emergency department (ED) use is a major contributor to health care costs in the United States (US). The Affordable Care Act has increased the number of Americans with health insurance through Medicaid expansion or health insurance exchanges [1]. However, the effect of increased access to health insurance on ED utilization remains unclear. Although there is some evidence of reduced ED utilization, especially among younger adults [2,3], high-volume ED use by the newly insured patients is an unaddressed concern [4]. Evidence from Massachusetts and Oregon suggests an increase in ED use after Medicaid expansion [5,6].

* Corresponding author at: Division of Health Systems Management and Policy, School of Public Health, The University of Memphis, Memphis, TN 38152. Tel.: +1 901 678 3740.

E-mail address: [email protected] (S.S. Bhuyan).

Improved access to health insurance through ACA may not reduce ED utilization unless other economic barriers to regular primary care ac- cess are addressed (eg, availability of paid sick leave). The US is the only industrialized country in the world that does not provide paid sick leave for employees [7]. It is estimated that more than 40 million private sec- tor workers in the US did not have access to paid sick leave in 2015 [8]. Although some US states and cities have passed regulations or are cur- rently proposing legislation to guarantee paid sick leave, there is no fed- eral requirement. On the eve of Labor Day, 2015, President Obama signed an executive order to enact a federal law requiring the private sector companies that work with the federal government to provide an- nual paid sick leave up to 7 days or more to employees, including paid leave allowing for Preventive care, family care, child care, and parent care [9].

Empirical research has shown that paid sick leave is associated with cost saving for employers, higher employee retention, healthier workforce, and overall job growth [10-14]. One recent survey found

http://dx.doi.org/10.1016/j.ajem.2015.12.089

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that 9 in 10 US workers, across all political affiliations, favor a law guaranteeing workers up to 7 paid sick days per year. Nearly 1 in 4 workers report that they have lost jobs or were threatened with job termination for taking time off due to personal or family illness [15]. Ev- idence also suggests that availability of paid sick leave allows employees to access preventive care and may reduce overall health costs and im- prove outcomes. One previous study found that US workers with paid sick leave were more likely to undergo screening for five different types of cancers [16]. Another recent study found that a higher percent- age of female US workers with paid sick leave received mammography as compared to those without paid sick leave [17]. Although paid sick leave can reduce the number of ED visits, mainly through allowing indi- viduals to see a regular provider and timely access to preventive care, the relationship is not very clear. A study conducted before ACA imple- mentation attempted to examine the relationship between paid sick days and ED visits for US working adults. However, the study did not find any significant relationship at that time. One important limitation of this study was that it included all US working adults. However, public sector employees are more likely (around 90%) to have paid sick leave benefits; therefore, including these public sector employees in the study sample likely diluted the effect of paid sick leave [18].

Our study uses a multiyear nationally representative database from

the years following the passage and implementation of the ACA to examine the association between availability of paid sick leave and ED utilization among US private sector employees. Guided by the Andersen Model for health services utilization, we hypothesize that the availability of paid sick leave is associated with a reduced frequency of ED utilization among US private sector employees.

1. Study data and methods
   1. Data and sample

We used the most recent 3 years (2012-2014) of data from the US National Health Interview Survey (NHIS), maintained by the National Center for Health Statistics. The NHIS is an annual cross-sectional house- hold survey that covers the civilian noninstitutionalized population re- siding in the US at the time of interview.

The NHIS collected household interview data from 2012 to 2014 and includes 105 779 adults (age >= 18 years). The sample is nationally representative and obtained by using a stratified multistage probability study design with unequal probabilities of selection. Specific subgroups of people are purposefully oversampled by the NHIS, including racial/ ethnicity minorities. New households are surveyed each year, with each year’s cohort selected to estimate health and health care character- istics of the entire US population. Strategies for sampling and methodol- ogies for data collection were very similar to maintain consistency and facilitate comparison throughout the selected NHIS years (http:// www.cdc.gov/nchs/nhis.htm).

We used 3 components of NHIS data linked together in the study, in- cluding adults sample file, person file, and family file. We further re- stricted our sample to current adult working population with age between 18 and 64 years in private sectors, and 47 888 adults were left. After deleting all observations with missing values, our final analyt- ical sample was 42 460.

Measures

Our outcome variable was the number of ED visits within past year. Respondents were asked the question “During the past 12 months, how many times have you gone to a hospital emergency department (this in- cludes emergency department visits the resulted in a hospital admis- sion)?,” with possible answers “none,” “1,” “2-3,” “4-5,” “6-7,” “8-9,”

“10-12,” “13-15,” “16 and more,” “don’t know,” and “refuse”. We divid- ed our respondents into 3 groups ordered by the frequency of ED use: nonusers (0 visits), moderate users (1-3 visits), and frequent users

(>= 4 visits). This classification is based on prior research that suggests 4 or more ED visits a year as frequent visitor [19-21]. The key indepen- dent variable in our study was whether employers in private sector of- fered paid sick leave benefits to the respondents. It is a dichotomized variable, based on survey question “Did you ever have paid sick leave on the job you held most recently?”

Based on Andersen Model of health services utilization, all the covar- iates were grouped under predisposing, enabling, and need factors [22]. Predisposing factors include demographic and sociocultural factors that may influence an individual’s need for health services, including respondents’ age, sex, marital status, and race/ethnicity. Age was cate- gorized into 3 groups as 18 to 34, 35 to 49, and 50 to 64 years old; sex, as male and female; marital status, as married and not currently mar- ried/never married; and race/ethnicity, as non-Hispanic White, non- Hispanic Black, Hispanic, and non-Hispanic others.

Enabling factors include the availability of resources at an individual or societal level to seek healthcare. Enabling factors included respon- dents’ educational attainment, poverty level, health insurance status, usual source of care, physician refusal to accept them as new patients or accept their insurance, respondents’ ability to afford mental health care, and use of Internet to access health information. Respondents’ ed- ucational attainment was categorized into less than high school, high school, and college and above. Poverty level was calculated by poverty-income ratio that was calculated as per the NHIS as the ratio of family income to the poverty threshold for a family of that size, with a poverty-income ratio less than 1 being defined as poverty. We categorized health insurance status into 3 groups as no insurance, private insurance, and Public insurance without private insurance. Usual source of care (having a place, rather than ED, that respondents usually go to when they are sick or need advice about health), physician refusal to accept them as new patients or their health insurance, and respondents’ ability to afford needed mental care were all dichotomized.

Finally, the need factors refer to an individual’s knowledge and value about previous medical problems and attitude regarding whether or not they need health services. The need factors examined in this study in- cluded respondents’ number of comorbidity conditions, body mass index (BMI), smoking status, alcohol use, and number of physician office-based visits in last 12 months. The NHIS survey asked about spe- cific chronic disease conditions based on the relative prevalence in the US adult population and potential for increased primary care and ED uti- lization, including diabetes, heart disease, asthma, and cancer. We cate- gorized respondents into three groups: with no comorbidity, 1 comorbidity, and 2 or more comorbidities. We divided BMI into four quartiles for degree of obesity. Self-reported smoking status as current smoker vs. other and alcohol use as modest/heavy drinker vs. other were ascertained. NHIS did not reliably measure other types of sub- stance abuse. The number of physician office-based visits was catego- rized as no visit vs. 1 or more visits within past 12 months.

Analysis

The unit of analysis is the individual respondent. We conducted de- scriptive analyses comparing paid sick leave benefit, predisposing, en- abling, and need factors by frequency of ED visits. ?² Tests were used to examine bivariate association between frequency of ED visits and in- dependent variables. We further used multivariate logistic regressions to model the association between ED visits and paid sick leave, control- ling for other covariates. Two models were constructed, one with the outcome of interest being 1 to 3 ED visits (moderate) and the other with the outcome of interest being greater than or equal to 4 ED visits (repeated use). Both models had no ED visits as the reference group. The analyses were adjusted for the complex survey design to get nation- ally representative estimates. We performed all the statistical analyses using Stata SE 13.0 (College Station, TX).

1. Results

Of 42 460 respondents in our sample, 83% (n = 35 238) did not have any ED visits within the past year, approximately 16% (n = 6 614) re- ported having 1 to 3 ED visits, and less than 1% (n = 604) used ED ser- vices at least 4 times within the past year. Figure 1 presents bivariate association between paid sick leave benefit and frequency of ED visits. More than half (56.0%) of respondents who reported no use of ED ser- vices had paid sick leave, whereas less than one-third (32.5%) among those with at least 4 times of ED visits had paid sick leave.

Distributions of predisposing, enabling, and need factors with differ- ent frequency of ED visits are given in Table 1. We found that those who used more ED services tended to be younger, female, unmarried, and African American; have public insurance or no insurance; have a high school diploma; and have family income in the lower quartiles. For ex- ample, of respondents with 1 to 3 ED visits, 47.1% were 18 to 34 years old, whereas the proportion increased to 56.4% among those with at least 4 times of ED visits. Similarly, respondents with no insurance or public insurance used more ED services than those with private insur- ance, as proportion of private insurance decreased when frequency of ED visits increased. Respondents who had experienced physician refusal to treat them due to multiple reasons, such as not accepting new pa- tients or not accepting the patients’ insurance, were more likely to be frequent visitors to the ED. Interestingly, searching for health informa- tion on the Internet increased probability of using ED services (48.8% in the group with no ED visit group vs 59.7% in the group with at least 4 times of ED visits). Among health care-related need factors, higher BMI, smoking status, and presence of Multiple comorbidities were sig- nificantly associated with higher frequency of ED visits.

Table 2 presents association between frequency of ED visit and paid

sick leave benefit, after controlling for other confounding factors. Ad- justed odds ratios (AORs) and 95% confidence intervals (CIs) are report- ed for 2 models: moderate vs no use of ED services (model 1) and frequent vs no use of ED services (model 2). Model 1 shows that respondents with paid sick leave were 14% less likely to be moderate ED service users than those without paid leave after adjusting for all the covariates (AOR, 0.86; 95% CI, 0.79-0.93). The effect of paid sick leave was even stronger for repeated ED users. Similar to model 1, after adjusting all confounding factors, respondents with paid sick leave were 32% less likely to be repeated ED users (AOR, 0.68; 95% CI, 0.50-0.91).

Adjusted odds ratios of other key covariates suggest the same relationships to frequency of ED use as we found in bivariate analyses, such as comorbidities, physician acceptance of patients, or health insurance and others. For instance, those who looked on the Internet

for health information was more likely to use ED services (AOR: model 1 1.32 vs model 2 1.73). Higher family income was associated with lower probability of using ED visits (AOR: model 1 0.64 vs model 2 0.43).

1. Discussion

Using nationally representative data, we examined the association between availability of paid sick leave and frequency of ED use among US private sector working adults. After adjusting for possible confound- ing factors, our findings suggest that availability of paid sick leave is sig- nificantly associated with lower odds of ED use, for both moderate and frequent users. The effect of paid sick leave is stronger for Frequent ED users. To the best of our knowledge, this is the first post-health care re- form study to examine the association between paid sick leave and fre- quency of ED use among US private sector employees. Among the covariates, we found that adults with higher poverty level, having public or no insurances, multiple comorbidities, and certain aspects of Access to healthcare providers, are more likely to use the ED.

Reduction in high-cost health care utilization such as ED visits is a primary target for US health care policy makers. Despite the improved access to health insurance, the number of ED visits in the US continues to rise. One important determinant of timely access to health care ser- vices is availability of time to see a health care provider. The US is the only developed country without federal legislation guaranteeing paid sick leave [7]. Several cities including San Francisco, Washington DC, Se- attle, New York City, Jersey City, and others and states such as Connect- icut have recently passed laws ensuring mandatory paid sick leave for employees. A recent evaluation of the Connecticut’s sick leave law found that employment in certain sectors-including health services and hospitality-has increased with improved employee productivity and morale [13]. Another recent report examining San Francisco’s 727 employers evaluating the city’s 2006 Paid Sick Leave Ordinance found that approximately two-thirds of employers were supportive and one- third were very supportive of the law [23]. The study also found that employees reported benefitting from the sick leave law because their employer became more supportive of usage, the number of sick days provided increased, or they were better able to care for themselves or family members.

The ACA aims at improving access to health care services, mainly through expanding health insurance coverage. Although most states have now expanded their Medicaid programs, expansion alone does not guarantee access to care for new enrollees. Our study suggests that physicians not accepting new patients or physicians not accepting patients’ insurance are significantly associated with both moderate

Figure. Percentage of respondents with paid sick leave by frequency of ED visit, US, NHIS (2012-2014).

Table 1 Descriptive statistics of ED visits by paid sick leave, US, NHIS 2012 to 2014
	0 ED visits, % (95% CI)		1-3 ED visits, % (95% CI)		>= 4 ED visits, % (95% CI)	P
	n = 35 238		n = 6614		n = 608
Predisposing factors
Age (y)
18-34	40.2 (39.3-41.1)		47.1 (45.5-48.8)		56.4 (50.8-61.8)	b.001
35-49	33.6 (32.9-34.3)		30.8 (29.4-32.3)		25.0 (20.7-29.7)
50-64	26.2 (25.6-26.9)		22.1 (20.8-23.4)		18.7 (15.0-23.0)
Sex
Male	55.6 (54.9-56.3)	47.9 (46.4-49.5)		39.1 (33.5-44.9)		b.001
Female	44.4 (43.7-45.1)	52.1 (50.5-53.6)		60.9 (55.1-66.5)
Marital status
Not currently married/never married	46.6 (45.7-47.4)	55.4 (53.8-57.0)		61.6 (56.0-66.9)		b.001
Married	53.4 (52.6-54.3)	44.6 (43.0-46.2)		38.4 (33.1-44.0)
Race and ethnicity
White	64.6 (63.7-65.6)	63.6 (62.0-65.1)		60.2 (54.9-65.3)		b.001
African American	9.9 (9.5-10.4)	15.2 (14.1-16.4)		20.8 (17.5-24.6)
Hispanic	17.6 (16.8-18.4)	15.3 (14.1-16.5)		14.9 (11.6-19.0)
Other race	7.9 (7.5-8.3)	6.0 (5.3-6.7)		4.1 (2.6-6.4)
Enabling factors
Insurance status
No insurance	18.1 (17.5-18.8)	19.9 (18.6-21.2)		27.2 (22.9-32.0)		b.001
Private insurance	74.4 (73.7-75.1)	63.7 (62.1-65.2)		42.1 (36.7-47.7)
Public insurance	7.5 (7.1-7.9)	16.4 (15.3-17.6)		30.7 (26.2-35.6)
Education attainment
Less than high school	4.8 (4.4-5.2)	4.1 (3.5-4.7)		3.9 (2.4-6.2)		b.001
High school	29.4 (28.7-30.1)	36.2 (34.5-38.0)		46.0 (40.9-51.1)
College and above	65.9 (65.0-66.7)	59.7 (57.8-61.6)		50.2 (45.0-55.3)
Poverty level (ratio of family income to the poverty threshold)
Poverty level (low) (0-0.99)	9.2 (8.7-9.8)	16.1 (15.0-17.3)		29.8 (25.3-34.8)		b.001
Poverty level (moderate) (1.00-1.99)	15.6 (15.0-16.1)	21.5 (20.2-22.9)		25.3 (21.1-30.1)
Poverty level (high) (>= 2.00)	75.2 (74.4-76.0)	62.4 (60.7-64.0)		44.8 (39.6-50.1)
Usual source of care
Yes	79.5 (78.9-80.1)	79.5 (78.0-80.9)		76.3 (71.6-80.5)		.385
Look in the Internet for health information
Yes	48.8 (48.0-49.6)	55.4 (53.7-57.1)		59.7 (54.1-65.1)		b.001
Physician not accepting new patients
Yes	1.5 (1.3-1.6)	4.5 (3.9-5.1)		10.1 (7.4-13.7)		b.001
Physician not accepting new Insurance
Yes	1.9 (1.8-2.1)	5.4 (4.7-6.2)		8.1 (5.7-11.4)		b.001
Could not afford mental health care
Yes	1.6 (1.5-1.8)	3.7 (3.1-4.3)		9.0 (6.6-12.0)		b.001

Need factor Comorbidity

None	79.9 (79.4-80.5)	70.4 (69.0-71.8)	57.0 (51.4-62.4)	b.001
1	19.9 (19.3-20.4)	28.9 (27.5-30.4)	41.3 (36.0-46.9)
>= 2	0.2 (0.1-0.3)	0.7 (0.4-1.0)	1.7 (0.9-3.1)
BMI
BMI1 (quartile 1) (b23.73)	27.3 (26.6-28.0)	25.3 (24.0-26.7)	22.1 (17.6-27.3)	b.001
BMI2 (quartile 2) (23.73-27.11)	27.1 (26.5-27.7)	23.5 (22.1-24.9)	21.2 (16.8-26.3)
BMI3 (quartile 3) (27.12-31.68)	26.2 (25.5-26.8)	25.0 (23.6-26.3)	23.2 (19.3-27.6)
BMI4 (quartile 4) (N 31.69)	19.5 (18.9-20.1)	26.2 (24.9-27.6)	33.6 (29.1-38.3)
Current drinker (modest/heavy drinker) Yes	25.5 (24.8-26.1)	23.8 (22.4-25.3)	18.9 (14.8-23.8)	.005
Current smoker Yes	17.9 (17.4-18.5)	29.0 (27.5-30.5)	34.6 (29.4-40.3)	b.001
No. of office visit
No. of office-based visit within past 12 mo	26.1 (25.4-26.8)	10.8 (9.8-11.9)	8.7 (5.8-12.7)	b.001

and high frequency ED use. Our results support a previous study finding that perceived access rather than acuity is an important factor for ED uti- lization [24]. The US is suffering from chronic shortage and maldistribu- tion of physicians, specifically primary care providers [25].

Telemedicine technology is currently being explored to be used in EDs to reduce overcrowding, an important indicator for quality of care and patient satisfaction in EDs [26,27]. The EDs can also consider expanding these telemedicine services for patients requiring behavioral health counseling. Although telemedicine services would not be appro- priate for severe mental or behavioral health needs, they could relieve the burden on EDs for those who may seek mental or behavioral health counseling. Moreover, telemedicine services could also engage patients before they walk into an ED. For example, some patients visit ED for

immediate assurance or “NOWCARE,” and they may not require an ac- tive treatment. The effective use of Health information technology and electronic health records can provide the ED important tools for managing high-frequency ED users. Previous evidence shows that ma- jority of the interventions to reduce ED visits used Case management teams; however, not much emphasis was given to data or information sharing [28]. EDs can use the Health Information Exchanges (HIE) to share clinical information of frequent users and high-cost patients across different health care settings for care management. As of 2013, approximately 30% of the US hospitals are participating in HIE [29]. Hos- pital, especially non-for-profit hospitals, participation in HIE could be considered a community benefiting activity under Internal Revenue System guidelines [30].

Table 2

multivariate regression analysis of ED use by paid sick leave status, US, NHIS, 2012 to 2014

Model 1

(moderate ED visit vs none) (n = 41 852)

Model 2

(repeated ED visit vs none) (n = 35 846)

	OR	95% CI		OR	95% CI
Paid sick leave	0.86???	0.79-0.93	0.68??		0.50-0.91
Predisposing factors
Age (y)
18-34	Ref	Ref	Ref		Ref
35-49	0.86??	0.78-0.94	0.62??		0.47-0.83
50-64	0.75???	0.68-0.83	0.56???		0.40-0.76
Sex
Male	Ref	Ref	Ref		Ref
Female	1.08?	1.00-1.17	1.32?		1.02-1.70
Marital status
Not currently married/never married	Ref	Ref	Ref		Ref
Married	0.89??	0.82-0.96	0.96		0.74-1.23
Race and ethnicity
White	Ref	Ref	Ref		Ref
African American	1.35???	1.22-1.49	1.52??		1.15-2.00
Hispanic	0.89?	0.79-0.99	0.76		0.54-1.06
Other race	0.86?	0.74-0.99	0.64		0.38-1.07
Enabling factors
Insurance status
No insurance	Ref	Ref	Ref		Ref
Private insurance	0.90	0.82-1.00	0.58???		0.43-0.78
Public insurance (without private)	1.34???	1.19-1.51	1.84???		1.38-2.45
Education attainment
Less than high school	Ref	Ref	Ref		Ref
High school	0.87?	0.78-0.97	0.52???		0.38-0.71
College and above	1.44???	1.26-1.65	1.73??		1.25-2.39
Poverty level (ratio of family income to the poverty threshold)
Poverty level (low) (0-0.99)	Ref	Ref	Ref		Ref
Poverty level (moderate) (1.00-1.99)	0.91	0.80-1.03	0.71?		0.53-0.96
Poverty level (high) (>= 2.00)	0.64???	0.57-0.72	0.43???		0.31-0.59
Usual source of care
Yes	0.77???	0.69-0.86	0.80		0.59-1.08
Look in the Internet for health information
Yes	1.32???	1.21-1.44	1.73???		1.36-2.21
Physician not accepting new patients
Yes	1.78???	1.40-2.28	4.08???		2.34-7.14
Physician not accepting new insurance
Yes	1.56???	1.25-1.95	1.04		0.58-1.87
Could not afford mental health care
Yes	1.35??	1.09-1.68	2.22???		1.45-3.40

Need factors Comorbidity

None	Ref	Ref	Ref	Ref
1	1.45???	1.34-1.57	2.39???	1.87-3.05
>= 2	3.08???	1.72-5.50	8.37???	3.92-17.9
BMI
BMI1 (quartile 1) (b23.73)	Ref	Ref	Ref	Ref
BMI2 (quartile 2) (23.73-27.11)	1.04	0.94-1.14	1.15	0.77-1.74
BMI3 (quartile 3) (27.12-31.68)	1.14?	1.03-1.26	1.32	0.93-1.87
BMI4 (quartile 4) (N 31.69)	1.40???	1.27-1.54	1.86???	1.32-2.63
Current drinker (modest/heavy drinker)
Yes	0.96	0.88-1.05	0.83	0.59-1.17
Current smoker
Yes	1.77???	1.62-1.93	1.85???	1.35-2.52
No. of office visit No. of office-based visit within past 12 mo	0.27???	0.23-0.31	0.20???	0.13-0.30

Exponentiated coefficients.

* P b .05.

?? P b .01.

??? P b .001.

An increasing number of people in the US have access to smartphones and Internet. Our study findings suggest that respondents who look for health care information on the Internet are more likely to visit ED, with its effect being stronger for repeated ED use. Many unreg- ulated and unsupervised health information websites host disease diag- nosis and support forums. These website forums can be very beneficial and empower patients by providing valuable information on Disease progression, treatment effectiveness, and moral supports; however,

some inaccurate information or condition specific to one particular pa- tient could panic someone to seek medical attention promptly. Consid- ering that the US has significantly low health literacy rate, this excess but otherwise useful information may continue to play a major role in ED utilization. The first step to reduce ED visit among this population is to identify these “high-risk” patients and then empowering them with relevant health information. At discharge, patients may be provid- ed with a list of reputed online health information websites (Mayo

Clinic, WebMD, MedlinePlus from the US National Library of Medicine, familydoctor.org sponsored by the American Academy of Family Physi- cians, etc) and services such as Healthwise that delivers health-related information to patients on demand (http://www.healthwise.org/). Availability of health information from a reliable source may preclude the necessity of an ED visit.

Our results also show that respondents who could not afford mental health care in last 12 months were more likely to visit ED. EDs are often not prepared for even the most basic mental or behavioral Health care needs, as many do not have on-staff behaviorists or specialized rooms and beds needed for more severe cases. Similar to improving access to lower cost and preventive primary care services, paid sick leave could also allow patients greater access to mental and behavioral health care. Still, that those who cannot afford care in the last year are more likely to seek it at EDs belies multiple needs that require attention. As with physical health problems, mental and behavioral health issues only become more severe with time, and many of these conditions can greatly impact patients’ self-care and self-efficacy components of managing other chronic diseases [31]. Furthermore, despite Federal par- ity legislation surrounding behavioral health care, reimbursements for mental and behavioral health services often lag behind other physical health conditions making it increasingly difficult for providers to accept insurance. Consequently, increasing numbers of mental and behavioral health providers no longer accept public or even many forms of private insurance, thus creating a significant hurdle to patients being able to af- ford needed care. Finally, because mental and behavioral health condi- tions can be much more difficult to treat and because such treatment tends to be longer term with need for multiple repeat visits to providers, seeking care can be a significant barrier to those without paid sick leave. Our study has some limitations. First, we could not established cau- sality due to the cross-sectional nature of the data used in this study. Second, the NHIS is a self-reported data that may have some recall bias. Moreover, use of ED was measured over the 12 months; therefore, the respondents may report few ED visit due to long recall period. Third, paid sick leave policies may vary across different private sector compa- nies, and we did not know many details about it, such as how many paid

sick day respondents could have throughout the whole year.

1. Conclusion

Despite these limitations, our study findings contribute to current policy debate regarding the provision of paid sick leave in the US. In ab- sence of Federal regulations for paid sick leave, several states and cities have mandated or are currently proposing to pass laws to ensure paid sick benefits to their employees. Although there are concerns about fea- sibility of such policies, specifically from the small employers, previous evaluations of such sick leave laws found positive outcomes including employee satisfaction and overall job growth. In our study, we found a significant relationship between availability of paid sick leave and use of EDs among US private sector workers.

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