HEALTH ECONOMICS Health Econ. 25: 529–542 (2016) Published online 25 February 2015 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/hec.3164

COPAYMENTS AND EMERGENCY DEPARTMENT USE AMONG ADULT MEDICAID ENROLLEES LINDSAY M. SABIKa,* and SABINA OHRI GANDHIb a

Department of Healthcare Policy and Research, Virginia Commonwealth University, Richmond, VA, USA b Health Care Financing and Payment Program, RTI International, Washington, DC, USA

ABSTRACT A number of state Medicaid programs have recently proposed or implemented new or increased copayments for nonemergent emergency department (ED) visits. Evidence suggests that copayments generally reduce the level of healthcare utilization, although there is little specific evidence regarding the effectiveness of copayments in reducing nonurgent ED use among Medicaid enrollees or other low-income populations. Encouraging efficient and appropriate use of healthcare services will be of particular importance for Medicaid programs as they expand under the Patient Protection and Affordable Care Act. This analysis uses national data from 2001 to 2009 to examine the effect of copayments on nonurgent ED utilization among nonelderly adult enrollees. We find that visits among Medicaid enrollees in state-years where a copayment is in place are significantly less likely to be for nonurgent reasons. Our findings suggest that copayments may be an effective tool for reducing use of the ED for nonurgent care. Copyright © 2015 John Wiley & Sons, Ltd. Received 1 November 2013; Revised 10 October 2014; Accepted 22 January 2015 KEY WORDS:

copayment; cost sharing; emergency department; Medicaid

1. INTRODUCTION The Medicaid population is known to use the emergency department (ED) at more than twice the rate of the privately insured population (Zuckerman and Shen, 2004; Mortensen and Song, 2008; Tang et al., 2010), and it may cost the Medicaid program significantly more to treat conditions that could be treated in other ambulatory care settings in the ED (Baker and Baker, 1994). Growing pressure on state budgets has led state Medicaid programs to consider tools to increase efficiency and decrease costs. Efficiency and cost concerns in Medicaid will become more pressing as the Patient Protection and Affordable Care Act (ACA) is implemented and many states expand their Medicaid programs. The ACA is moving millions of new enrollees into the Medicaid program and increasing state and federal spending on Medicaid (Holahan et al., 2012). In trying to address ED use among Medicaid populations, some states have implemented cost-sharing requirements for adult enrollees who visit an ED for a nonemergent reason.1 While some states have had copayments for nonemergent ED use in place for years, a number of states have also recently proposed new or increased copayments. In recent years, several states have proposed waivers to charge copayments exceeding

*Correspondence to: Department of Healthcare Policy and Research, Virginia Commonwealth University, PO Box 980430, Richmond, VA 23238, USA. E-mail: [email protected] 1

The federal government has not explicitly defined nonemergent use for purposes of determining Medicaid cost-sharing. (The term ‘emergency’ is defined in the context of the federal Emergency Medical Treatment and Active Labor Act.) For Medicaid copayment determinations, each state decides what constitutes an emergency.

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federal limits2 for adult Medicaid recipients with incomes less than 150% of the federal poverty level (Centers for Medicare and Medicaid Services, 2013a). For example, California submitted a waiver to implement a $15 copayment for nonemergency use of the ED for Medicaid managed care recipients (Galewitz and Fleming, 2012), while Florida submitted a proposal to implement a $100 copayment (Kaiser Family Foundation, 2012). While these proposals have not been implemented, they highlight the interest states have in using cost sharing to discourage nonemergent ED use among Medicaid populations.3 The federal government has also shown an interest in promoting cost sharing as a tool to curb utilization and contain costs, and in 2013, the Centers for Medicare and Medicaid Services increased the maximum allowed amount for Medicaid ED copayments to $8 (Health and Human Services, 2013). Further, a number of states seeking approval to expand Medicaid to adults under the ACA through nontraditional demonstration programs have emphasized cost sharing for Medicaid enrollees in their proposals to the Centers for Medicare and Medicaid Services (Saloner et al., 2014). Existing research, primarily among privately insured patients, provides some evidence on the effects of patient cost sharing on healthcare utilization, although there is little research on the effects of cost sharing for ED use among Medicaid or other low-income patient populations. The benchmark study regarding the effect of cost sharing on health care utilization and cost is the RAND Health Insurance Experiment (HIE), which randomly assigned families to health insurance plans with various levels of cost sharing and found that those facing greater out-of-pocket costs had significantly lower healthcare use (Newhouse and Rand Corporation Insurance Experiment Group, 1993). Among individuals involved in the RAND HIE, those with no cost sharing (free care) had 42% higher ED expenses than those who had to pay part of the cost (O’Grady et al., 1985). Subsequent studies also found an effect of cost sharing on ED utilization. Research on populations that were transitioned into a high-deductible health plan (HDHP) found that enrollment in a HDHP was associated with a reduction in ED visits, with the decrease driven primarily by a decline in repeat ED visits for lowseverity conditions (Wharam et al., 2007). Similarly, research since the HIE has found that copayments for ED visits have reduced ED utilization, with effects increasing in magnitude and significance as the urgency of the presenting condition declined. Further, residents of poor neighborhoods who faced a copayment reduced their utilization more relative to controls than did residents of higher income neighborhoods who faced a copayment (Selby et al., 1996). These findings suggest that patients who use the ED, and for nonurgent reasons in particular, respond to increases in cost sharing. One study considering effects of ED copayments found a reduction in ED visit rates without any change in unfavorable clinical events after an increase in ED copayments (Hsu et al., 2006). While this suggests that ED copayments may be a useful tool for encouraging efficient and appropriate use of healthcare, the majority of these studies consider well-insured populations. In fact, Hsu and colleagues warn that their ‘findings may not be applicable to more indigent populations, e.g., the Medicaid-eligible … or to less integrated systems’, and suggest that ‘future studies are needed to examine effects within high-risk populations’ (Hsu et al., 2006, p. 1817). Given high rates of ED use and low incomes among the Medicaid population, Medicaid enrollees may be even more price sensitive than the privately insured. Few studies specifically consider the effects of ED copayments on utilization among Medicaid enrollees and none that we know of reliably assess the effects on emergent versus nonemergent use, which is likely to reflect the appropriateness of visiting the ED as opposed to other ambulatory care settings. One existing study considers the effect of Medicaid copayments for nonemergent ED visits on overall and nonemergent utilization of the ED (Mortensen, 2010). The study assesses the impacts of changes in copayments in nine states between 2001 and 2006 on the number of ED visits. This earlier research does not find an effect of copayments on In fiscal year 2013, the maximum allowable copayment for nonemergency use of the emergency department (ED) was $3.90 for noninstitutionalized adult enrollees with incomes less than 100% federal poverty level (FPL) and $7.80 for those with incomes from 101–150% FPL. There was no limit for those with incomes greater than 150% FPL. 3 Generally, Medicaid cost-sharing rules apply to all Medicaid enrollees except children, terminally ill adults, and individuals residing in an institution, as these groups are specifically exempted by law. Thus, we focus our analysis on nonelderly adults. 2

Copyright © 2015 John Wiley & Sons, Ltd.

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number of ED visits, although the data rely on self-reported measures of whether the ED visit was emergent. Responses from individual patients may not reflect the assessment by a healthcare provider as to whether a visit is for an emergency and may, in fact, be related to whether the individual was charged a copayment. Further, the earlier study uses data only through 2006, while there have been a number of more recent changes in copayment levels across multiple states. This paper adds to the existing literature by including more recent ED data that also include the assessment of triage status by a healthcare provider. We examine whether changes over a 9-year period in state Medicaid copayment policies for ED use affect the likelihood that ED visits among adult Medicaid enrollees are for nonurgent reasons. Our results are robust across a number of specifications and suggest that when states have a copayment policy in place, visits to the ED by adult Medicaid enrollees are less likely to be for nonurgent reasons.

2. DATA 2.1. State-level data Our key independent variable of interest is an indicator for whether a state has a policy in place in a given year requiring a copayment be paid by adult Medicaid enrollees in the state’s standard fee-for-service Medicaid program when they visit the ED for nonemergent care. State-level copayment data for the years 2001–2009 come from a number of sources, including the Kaiser Family Foundation (2011), the Government Accountability Office (2004), and earlier published research (Mortensen, 2010). We used state Medicaid websites, Medicaid state plans, policy handbooks, provider handbooks, administrative codes or rules, and beneficiary handbooks to fill in missing information and resolve discrepancies between sources. When sources were in conflict, we used state Medicaid information (state plans, policy handbooks, provider handbooks, or administrative rules) to make final determinations. Available sources on state policies generally included complete information for the years 2003, 2004, 2006, and 2008–2010. When information for a given year was not available for a state, we imputed the indicator for the state’s copayment status based on information for surrounding years.4 In addition to information on Medicaid copayments for nonemergent ED use, we also tracked information on whether the state had a policy to charge coinsurance for such visits, which is the case in six states for at least some of the years in our study period (including states with policies that the enrollee must pay the total cost of a nonemergent visit out of pocket). We also compiled state-year data on the percentage of Medicaid enrollees in managed care plans based on information from the Kaiser Family Foundation (Kaiser Family Foundation, 2010) to capture the percentage of enrollees that may not have been directly affected by the state’s copayment policy. We constructed variables representing the following: (i) the percentage of Medicaid enrollees in any type of managed care plan (including both comprehensive managed care, or enrollment in a risk-based managed care organization, and more limited managed benefits) and (ii) the percentage of Medicaid enrollees in comprehensive managed care plans only. These data are available for the years 2003–2009, therefore we use them as additional controls in secondary analyses limited to these years. 2.2. Emergency department visit data Data on ED visits come from the National Hospital Ambulatory Medical Care Survey (NHAMCS) from 2001 to 2009. The NHAMCS comprises a national probability sample of outpatient visits to noninstitutional general 4

In over 97% of instances in which we could not identify information on copay status for a given state-year, the copayment status (having a copayment or not) did not change from the previous year to the subsequent year. In three instances where the copay status differed for surrounding years, we coded the state as not having a copayment in the imputed year in our main analyses. We also conducted sensitivity analyses dropping years for which 20 or more states had imputed values.

Copyright © 2015 John Wiley & Sons, Ltd.

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and short-stay hospitals with at least six staffed beds, located in the 50 states and the District of Columbia (CDC, 2013). State-identified NHAMCS data were accessed through the National Center for Health Statistics Research Data Center. State variables in the NHAMCS were used by National Center for Health Statistics staff to merge data on Medicaid cost sharing and managed care penetration. Randomized versions of the state variables were substituted after the merge, which allowed us to control for state fixed effects. The final sample includes observations from 44 states.5 Our outcome variable is an indicator of whether the visit was categorized as nonurgent.6 We use a triage measure indicating the immediacy with which a patient should be seen as determined by a medical professional (e.g., triage nurse). We categorize visits assigned a value of ‘>2 to 24 hours’ as nonurgent and all other visits as urgent, dropping visits with a value of ‘unknown/no triage’. The collection and processing of this item changed in 2009, and we assign a value of 1 for our outcome variable to visits categorized as ‘nonurgent’ under the new collection format in that year. We use data on individual demographic characteristics including age, sex, and race (defined as White, Black, or other) from the NHAMCS as well. Finally, additional variables used in sensitivity analyses measure key hospital characteristics and include hospital ownership (nonprofit, government, or for-profit) and an indicator for whether the hospital is located in a metropolitan statistical area.

3. METHODS 3.1. Empirical model We use a quasi-experimental design to examine how changes in Medicaid ED copayment policies affect nonurgent ED use. Our identification strategy exploits variation in whether a state requires a copayment for nonemergent ED visits across states and over time to identify the relationship between copayments and nonurgent ED utilization in the Medicaid population. Our sample includes ED visits by adult Medicaid enrollees ages 19–64 years. We exclude individuals younger than 19 years because they are considered children under the Medicaid program and cannot generally be charged cost sharing if categorically eligible (Centers for Medicare and Medicaid Services, 2013b). We restrict the sample to nonelderly adults because those ages 65 years and older are likely to be covered by Medicare. We categorize individuals as Medicaid enrollees if Medicaid is listed as the primary expected source of payment for the ED visit.7 We include all Medicaid visits with nonmissing information for our variables of interest. Specifically, we estimate visit-level linear probability models of the following form: Y ijt ¼ α þ β COPAYjt þ γX ijt þ τt þ δj þ εijt where Yijt is an indicator for whether ED visit i was assessed to be a nonurgent visit by the triage clinician, COPAYjt is an indicator for whether state j has a copayment in place in year t, Xijt is a vector of individual patient characteristics, τ t represents a set of year fixed effects, and δj are state fixed effects. State fixed effects control for any time-invariant differences in utilization that may result from state-specific demographic or healthcare system factors, and year fixed effects control for any overall trends in ED utilization. In separate models we control for the following: (i) an indicator for whether the state has a coinsurance policy in place for use of the ED by Medicaid enrollees and (ii) key hospital characteristics (ownership and whether the 5

Because of restrictions under the data use agreement to maintain confidentiality, we are unable to identify the specific states in the data. We refer to our outcome variable as an indicator of a ‘nonurgent’ visit to align with language used in the National Hospital Ambulatory Medical Care Survey (NHAMCS) categorizing visits assessed as not needing attention within 2 hours. When referring to copayment guidelines, we refer to ‘nonemergent’ visits because that is the language used in defining Medicaid policy around ED copayments. 7 In survey year 2005 onward, the data also include information on whether the patient is covered by Medicaid even if Medicaid is not listed as the primary expected source of payment. We conduct sensitivity analyses including the small number of nonelderly Medicaid enrollees for whom Medicare is listed as the primary payer (3.6% of the overall Medicaid sample), although our results are not sensitive to this change. 6

Copyright © 2015 John Wiley & Sons, Ltd.

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hospital is located in a metropolitan statistical area). All analyses employ survey weights to account for the complex sampling strategy of the NHAMCS.8 3.2. Robustness tests We test the robustness of our main results to the inclusion of additional controls and to the restriction of our sample to different populations or years in order to address other factors that may affect our results. First, we examine the sensitivity of our results to the inclusion of controls for Medicaid managed care penetration in the given state and year. Medicaid beneficiaries enrolled in managed care plans may not be subject to the same cost-sharing requirements as individuals in traditional fee-for-service Medicaid. Ideally, we would limit our sample to adults in fee-for-service Medicaid, but information on whether individuals are enrolled in feefor-service Medicaid or a managed care plan is not available in the NHAMCS, as is the case in most survey data. We attempt to account for the potential effect of managed care by controlling for Medicaid managed care penetration in the state using either one of two variables: (i) the percentage of state Medicaid enrollees in any form of managed care in the given year and (ii) the percentage of state Medicaid enrollees in comprehensive managed care in the given year. Medicaid managed care penetration data were only available for the complete set of states for year 2003 onward, so specifications including these variables used the sample of visits from 2003 to 2009. We estimate our baseline model for the years 2003–2009 for comparison. Next, we restrict our sample to test the robustness of our results when estimated for subsets of ED visits or years. First, we restrict the sample to male adult Medicaid enrollees. Medicaid is a major source of coverage for pregnant women (Markus and Rosenbaum, 2010), and pregnancy-related services are not subject to the same cost-sharing rules as other services for nondisabled adults in Medicaid. We cannot precisely identify all ED visits by pregnant women in the NHAMCS data. Instead, we test a specification limited to men, who are more likely to be subject to any required copayment. Second, we drop observations from Tennessee from our model because it is the one state that enrolls all of its Medicaid beneficiaries in managed care. Further, cost-sharing requirements differ for adults in Tennessee based on income and eligibility, but we are not able to differentiate between these groups in the NHAMCS data.9 Third, in addition to Tennessee, we drop all observations for any state that has a policy requiring Medicaid enrollees to pay coinsurance for an ED visit at any point during our study period. While we control for an indicator of such policies in some specifications, two of these states require the patient to pay the full cost of the visit for nonemergent ED use, which may affect utilization differently than the copayment policies that are of primary interest in this analysis. Fourth, we exclude observations from 2001, 2002, 2005, and 2007 from our sample because copayment data was imputed for 20 or more states in these years. Fifth, we exclude survey year 2009 from our sample because the collection of information on triage status changed from previous years. Finally, we estimate our main model using a logit specification to test the sensitivity of our results to our use of linear models. We also implement a placebo test, estimating our main model for a sample of privately insured nonelderly adults, whose ED utilization patterns we would not expect to change in response to Medicaid copayment policies. 4. RESULTS 4.1. Descriptive statistics Table I presents information on whether each state charged a copayment to noninstitutionalized adults in Medicaid for nonemergent ED visits for each year from 2001 to 2009. There were 22 states with no copayment 8 9

While our analysis focuses on ED visits, we accessed both the ED and outpatient department files of the NHAMCS and combined the two in order to correctly apply survey weights from the full NHAMCS sample in our analysis. Tennessee has an approved Section 1115 waiver under which it serves two distinct populations. Adults in TennCare Medicaid were not subject to copayments for ED use during our study period, so in our analysis, we code Tennessee as not requiring a copayment. Adults in TennCare Standard with incomes at or above 100% FPL were subject to either a $25 or $50 copayment depending on income.

Copyright © 2015 John Wiley & Sons, Ltd.

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Table I. States charging a copayment to adults in Medicaid for nonemergent emergency department (ED) visits (2001-2009) State

2001

2002

2003

2004

2005

2006

2007

2008

2009

AL AKa AZ AR CA CO CT DE DC FLa GA HI ID IL IN IA KS KYa LA ME MD MA MI MN MS MO MT NE NV NH NJa NM NY NC ND OH OK OR PA RI SC SDa TNb TX UT VTa VA WA WV WI WY

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X X

X X

X X

X X

X X

X X

X X

X X

X X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X X X X X X

X X X X X X X

X X X X X

X X X X X

X X X X X

X X X X X X X X X

X X X X X X X X X

X X X X X X X X X

X X X

X X X

X X X

X X X X

X X X

X X X

X X X

X X X

X X X

X

X

X X

X X

X X X X

X X X X X

X X X X X

X X X X X X X X X

X

X

X

X

X

X

X

X

X

X

X

X X

X X

X X

X X

X X

X X

X X X X X

X X X X X

X X X X X

X X X X X

X X X X X

‘X’ indicates that a copayment was required for nonemergency use of the ED by nondisabled adults in the state’s standard Medicaid program in the given year. Policy data is based on information from the Kaiser Family Foundation, the Government Accountability Office, and state Medicaid websites and publications. Our sample of ED visits includes observations from 44 states, and because of data restrictions, we are unable to identify the specific states in the data. a Indicates states with coinsurance at some point during this time period. We classified states that indicated adult Medicaid enrollees were responsible for paying some percentage of the cost of nonemergent ED visits (including, in three cases, 100% of costs) as having coinsurance. b Tennessee is omitted from some specifications because of nonstandard Medicaid policies. All Medicaid enrollees in Tennessee are enrolled in managed care. Beneficiaries in Traditional Medicaid (TennCare) are only required to pay copayments for prescription drugs. Beneficiaries in the 1115 waiver expansion population with incomes at or above 100% federal poverty level (TennCare Standard) are required to pay a copayment for nonemergency use of the ED, based on income. Because the standard Medicaid population is not subject to a copayment, we code Tennessee as not having a copayment for these services and test the robustness of our results to excluding Tennessee from the sample. Copyright © 2015 John Wiley & Sons, Ltd.

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in place in any year during the study period. Among the remaining states, 18 charged a copayment for nonemergent ED use during the entire study period. The other 11 states changed their copayment status at some point during the period, with most of these states implementing a copayment when there had previously been no copayment for ED use. Among states that had copayments in place at some point over our study period, the copayment amounts ranged from $0 to $6 with a median value of $3 (see Table AI for more detail on copayment amounts). Summary statistics for the sample of ED visits among Medicaid enrollees ages 19–64 years and subsamples of visits in state-years with and without a copayment are presented in Table II. Our sample includes almost 34,000 Medicaid ED visits, with approximately 60% of these in state-years for which a Medicaid copayment was in place. Overall, 13% of visits are classified as nonurgent, although the percentage is lower in state-years with a copayment than without. Patient demographics are similar across state-years with and without copayments, with an average patient age of 37 years and about 31% to 32% of Medicaid visits by male patients and 63% to 64% by White patients. 4.2. Baseline regression results Our main results, presented in column 1 of Table III, show that in state-years with a copayment required for nonemergent ED use by adult Medicaid enrollees, visits among this population were significantly less likely to be nonurgent. When we consider all years from 2001 to 2009, our results suggest a statistically significant 6.3 percentage point (p = 0.02) decrease in the probability that a given visit is nonurgent when a copayment is in place relative to when there is no copayment policy. This is in line with our descriptive results that show a 5.3 percentage point difference in urgent visit status across state-years with and without an ED copayment in place. Columns 2 and 3 of Table III present results controlling for other factors that may be correlated with nonurgent visit status. Column 2 includes a control for whether the state had an ED coinsurance policy in place in the given year. Column 3 includes controls for hospital ownership and whether the hospital is located in a metropolitan statistical area. Across these specifications, our estimate of the effect of having a copayment on nonurgent visit status remains statistically significant and indicates a 6 percentage point decrease in the probability of a nonurgent visit when a copayment is in place, as in our baseline model. 4.3. Robustness tests Table IV presents regression results from sensitivity analyses including controls for Medicaid managed care penetration in the state-year. Data on Medicaid managed care penetration are available for all states for the years 2003–2009. Column 1 estimates our baseline model (as in column 1 of Table III) but without data for 2001–2002. We see that when the sample is limited to this later period, the estimated effect of having a copayment on nonurgent visit status increases in absolute magnitude to approximately 8 percentage points. The second and third columns include controls for the overall and comprehensive Medicaid managed care Table II. Descriptive statistics for National Hospital Ambulatory Medical Care Survey emergency department Medicaid visits

Unweighted N Weighted number of visits Visit status Nonurgent (%) Patient demographics Age (mean (SE)) Male (%) White (%) Black (%) Other race (%)

All Medicaid visits

Visits in state-year with copayment

Visits in state-year with no copayment

33,932 101,547,055

20,428 56,277,028

13,504 45,270,027

12.85

10.48

15.81

36.78 (0.12) 31.58 63.49 33.16 3.35

37.02 (0.15) 31.83 63.70 32.15 4.15

36.49 (0.20) 31.27 63.24 34.41 2.35

Copyright © 2015 John Wiley & Sons, Ltd.

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Table III. Results from regression of nonurgent emergency department visit status on state copayment indicator Nonurgent visit indicator

State copayment policy Age Male Black Other race 2002 2003 2004 2005 2006 2007 2008 2009

Baseline model

With control for coinsurance

With controls for hospital characteristics

0.0629** (0.0270) 0.0013*** (0.0002) 0.0010 (0.0052) 0.0110 (0.0098) 0.0357*** (0.0116) 0.0242 (0.0162) 0.0119 (0.0220) 0.0037 (0.0190) 0.0275 (0.0227) 0.0227 (0.0207) 0.0324* (0.0188) 0.0316 (0.0204) 0.0507** (0.0203)

0.0617** (0.0273) 0.0013*** (0.0002) 0.0009 (0.0052) 0.0111 (0.0098) 0.0353*** (0.0116) 0.0245 (0.0162) 0.0118 (0.0219) 0.0021 (0.0194) 0.0254 (0.0231) 0.0186 (0.0216) 0.0356* (0.0196) 0.0341 (0.0208) 0.0534** (0.0209) 0.0529 (0.0557)

0.0640** (0.0273) 0.0013*** (0.0002) 0.0020 (0.0052) 0.0088 (0.0095) 0.0340*** (0.0113) 0.0246 (0.0164) 0.0109 (0.0219) 0.0007 (0.0191) 0.0255 (0.0228) 0.0200 (0.0205) 0.0343* (0.0189) 0.0344* (0.0206) 0.0534*** (0.0206)

Coinsurance indicator Government, nonprofit ownership Proprietary ownership Hospital MSA status Observations Weighted observations

33,932 101,547,055

33,932 101,547,055

0.0314** (0.0153) 0.0207 (0.0215) 0.0245 (0.0209) 33,932 101,547,055

Survey-weighted standard errors in parentheses. All models also include state fixed effects. Omitted ownership category is private, nonprofit. ***p < 0.01,**p < 0.05,*p < 0.1.

penetration rates in the state, respectively. The estimated effect of having a copayment in place is similar to the baseline model for 2003–2009 when we control for managed care penetration. In an alternative set of models, we stratified states by whether they were above or below median Medicaid managed care penetration and by quartile of managed care penetration in 2006, and results for all groups with the exception of quartile 3 were similar to those in Table III (see Table AII). Table V presents results restricting the sample of observations in different ways to test the robustness of our estimates. First, we exclude women in order to limit the sample to those who cannot be subject to restrictions on cost sharing due to pregnancy. In the male sample, our coefficient of interest remains approximately 6 percentage points and is marginally significant (p = 0.07) despite the substantial reduction in sample size. Second, we exclude Tennessee because it has different cost-sharing requirements for individuals in different parts of its Medicaid program and all enrollees are in managed care. Our coefficient is unchanged from baseline models. Third, we exclude states with coinsurance policies, as well as Tennessee. Our results are again unchanged. Fourth, we exclude 2009 from the analysis because of the change in the triage question in that year. The results are again similar, suggesting a statistically significant 7.0 percentage point decline in the probability that a visit Copyright © 2015 John Wiley & Sons, Ltd.

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Table IV. Results from regressions of nonurgent emergency department visit status on state copayment indicator, controlling for medicaid managed care penetration (years 2003–2009) Nonurgent visit indicator

State copayment policy Age Male Black Other race

Baseline regression for 2003–2009

Control for % of Medicaid enrollees in any type of managed care

Control for % of Medicaid enrollees in comprehensive managed care

0.0808** (0.0324) 0.0014*** (0.0002) 0.0010 (0.0057) 0.0063 (0.0104) 0.0405*** (0.0122)

0.0839** (0.0336) 0.0014*** (0.0002) 0.0009 (0.0056) 0.0063 (0.0104) 0.0404*** (0.0122) 0.0289 (0.0502)

0.0817** (0.0335) 0.0014*** (0.0002) 0.0010 (0.0057) 0.0062 (0.0104) 0.0405*** (0.0122)

Medicaid managed care penetration (all) Medicaid managed care penetration (comprehensive) Observations Weighted observations

0.0103 (0.0431) 28,228 85,854,402

28,228 85,854,402

28,221 85,832,044

Survey-weighted standard errors in parentheses. All models also include state and year fixed effects (not shown). ***p < 0.01,**p < 0.05,*p < 0.1.

Table V. Sensitivity analyses based on sample exclusions Nonurgent visit indicator

Copayment indicator Age

Exclude females

Exclude TN

Exclude TN and coinsurance states

Exclude year 2009

Exclude years 2001, 2002, 2005, and 2007

0.0595* (0.0328) 0.0014*** (0.0004)

0.0620** (0.0271) 0.0013*** (0.0002) 0.0003 (0.0052) 0.0109 (0.0100) 0.0354*** (0.0116) 33,068 99,421,285

0.0635** (0.0274) 0.0012*** (0.0002) 0.0001 (0.0057) 0.0088 (0.0107) 0.0302** (0.0124) 30,414 90,136,427

0.0698** (0.0324) 0.0012*** (0.0002) 0.0028 (0.0057) 0.0167 (0.0115) 0.0353*** (0.0129) 29,387 85,024,150

0.0593* (0.0324) 0.0015*** (0.0003) 0.0018 (0.0074) 0.0138 (0.0117) 0.0426*** (0.0127) 19,748 61,464,176

Male Black Other race Observations Weighted observations

0.0070 (0.0114) 0.0010 (0.0195) 11,206 32,067,483

Survey-weighted standard errors in parentheses. All models also include state and year fixed effects (not shown). ***p < 0.01,**p < 0.05,*p < 0.1.

is nonurgent. Finally, we exclude years 2001, 2002, 2005, and 2007 because ED copayment information was imputed for 20 or more states for these years. For this limited set of years, the results still suggest approximately a 6 percentage point decrease in the probability a visit is nonurgent when a copayment is in place. The significance is reduced somewhat, likely because of the decrease in sample size, although the estimate remains marginally significant (p = 0.07). We also estimate nonlinear models to test the robustness of our estimates. Results from a logit model are similar and suggest a statistically significant 5.1 percentage point decline (p = 0.03) in the probability that a visit is nonurgent. In addition, we implement a placebo test, using a sample of privately insured nonelderly patients. Table VI reports the results of this placebo test, showing that the magnitude of the estimate is much smaller Copyright © 2015 John Wiley & Sons, Ltd.

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Table VI. Placebo results from regression of nonurgent emergency department visit status on state copayment indicator for privately insured patients Nonurgent visit indicator 0.0240 (0.0216) 0.0011*** (0.0002) 0.0061* (0.0031) 0.0359*** (0.0076) 0.0041 (0.0090) 63,409 212,642,186

State copayment policy Age Male Black Other race Observations Weighted observations

Survey-weighted standard errors in parentheses. All models also include state and year fixed effects. ***p < 0.01,**p < 0.05,*p < 0.1.

than for the Medicaid population and the coefficient is not statistically significantly different from zero. This provides further evidence that the effect we see in the Medicaid population is not driven by other simultaneous changes affecting ED access and utilization.

5. DISCUSSION Understanding how Medicaid enrollees respond to copayments for ED use is important for structuring state policies in order to maximize access and efficiency given budget constraints. State budgets have been strained in recent years, and as many states implement a significant expansion of their Medicaid programs under the ACA, they are increasingly seeking ways to decrease costs and increase the efficiency of care delivered. ED visits have been on the rise in the USA over the past decade, increasing concerns about costs and overcrowding (Tang et al., 2010). Policy should aim to improve access to emergent care through EDs and decrease ED use for nonurgent visits. Taken together, our results suggest that copayments for nonemergent use of the ED may be successful at deterring visits for nonurgent conditions. Based on our main regression model, the predicted probability that a given visit is nonurgent is 10.1% when a copayment is in place and 16.3% when no copayment is in place. While this represents a substantial percentage increase, this magnitude is plausible given the low baseline rate of nonurgent visits, which is consistent with other research based on the triage measure of urgency (Horwitz and Bradley, 2009) and with literature on nonurgent use more broadly (Medicaid and CHIP Payment and Access Commission, 2014). We focus specifically on visits given a nonurgent triage assessment in order to capture a group of visits for which we would expect a substantial response. The effect on borderline cases in which the patient or provider has difficulty categorizing the visit as urgent or nonurgent is likely to be smaller. Nonetheless, our estimates could potentially be biased upward if there are simultaneous changes in state Medicaid programs or populations that we do not capture in our data that influence nonurgent ED utilization. First, if states that implement copayments for nonemergent ED visits simultaneously implement other programs or initiatives aimed at reducing nonemergent ED use in the Medicaid population (e.g., increasing the availability of primary care or redirecting patients to other ambulatory care settings), we would be estimating the combined effect of all such changes. We are not aware of specific state initiatives systematically implemented alongside ED copayments, but we cannot fully account for the possibility of such programs. Second, the adult Medicaid population may change over time within a state. Changes in cost sharing may affect eligible individuals’ decisions about whether to remain enrolled or take up Medicaid. We control for basic demographics in Copyright © 2015 John Wiley & Sons, Ltd.

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order to account for any changes in the Medicaid population, although there may be unobserved changes associated with both cost sharing and ED utilization. Nonetheless, our results suggest that among those who enroll in Medicaid before and after a change in state copayment policy, nonurgent utilization is significantly lower when a copayment is required. To our knowledge, this is the first analysis of the effect of Medicaid copayments on nonurgent use of the ED using a measure of nonurgent use based on provider report rather than self-report (which may be driven in part by whether cost sharing was charged). We also make use of a longer and more recent time period than earlier research considering the effects of Medicaid copayments on overall ED use. We find a significant, negative effect of the presence of a Medicaid copayment policy in a given state-year on the likelihood that an ED visit is nonurgent. An advantage of our models is that we include state and year fixed effects, which control for any time-invariant state differences and unmeasured time factors that are common to all states. Our results are also robust to controlling for other time-variant state factors, such as other cost-sharing requirements and Medicaid managed care penetration, as well as hospital characteristics. Our analysis faces a few main limitations. First, we only observe information on individuals who present at an ED, and we are not able to examine rates of overall ED use in these data. Because of the detailed visit information including the triage assessment, these are among the best available data for examining urgent and nonurgent use. Because we cannot account for changes in the overall number of visits per Medicaid enrollee, our results could theoretically reflect a variety of compositional changes including an increase in the number of urgent visits rather than a decrease in nonurgent visits, although this increase would have to correspond with changes in state-year copayment policies to impact our results. Given that we control for time-invariant state characteristics as well as overall time trends and that there is no theoretical reason to expect an association between copayments for nonemergent visits and quantity of urgent cases, this is unlikely. Further, other research suggests that copayments do not have a significant effect on overall rates of ED use (Mortensen, 2010), and a recent study shows no significant changes in national nonemergent visit rates for Medicaid enrollees over this period (Gandhi et al., 2014). Second, the data consist of repeated cross-sectional surveys of ED visits and do not follow the same individuals across waves. Thus, we are not able to examine how individual behavior changes when a state’s copayment policy changes. Further, unobserved changes in the Medicaid population could bias our results. We control for individual-level demographic factors available in the NHAMCS in order to account for any changes in the Medicaid population over this period. Third, many states have moved a growing number of their Medicaid enrollees into managed care plans over recent years, which may not include the same cost-sharing requirements as traditional Medicaid. We account for differences in Medicaid managed care by estimating separate specifications of our model including two different measures of Medicaid managed care penetration at the state-year level. We also explore stratifying our sample by state Medicaid managed care penetration. While it is not possible to identify whether individual patients are in Medicaid managed care in our data, our main results are robust to controlling for or stratifying by managed care penetration, suggesting that copayment policies may have an effect in those states that rely heavily on managed care in their Medicaid programs. Our estimates capture the effect of changes in state policy regarding copayments for ED use. We are not able to account for whether or how widely these policies are enforced and whether copayments are actually collected from Medicaid enrollees who use the ED. Nonetheless, even if policies are not consistently enforced in all states, they may still have an effect on behavior if patients are aware of the copayment policy and take it into account in deciding whether or not to visit the ED. Our estimates suggest that having a policy requiring a copayment affects how Medicaid enrollees use the ED. The magnitudes of our estimates are substantial given the seemingly small copayment amounts ($3 in most states with a copayment, and a maximum of $6), although this is consistent with previous research that suggests even nominal copayments of $1–$3 can significantly affect utilization among Medicaid enrollees (Ku and Wachino, 2005). Recent research regarding the effects of sliding-scale premiums in Medicaid also finds the largest effects on enrollment when comparing those with no premium to those facing the minimum premium of $10 per month (Dague, 2014). There is strong evidence that any level of cost sharing, including small out-of-pocket amounts, can substantially affect Medicaid enrollees’ healthcare decisions. Copyright © 2015 John Wiley & Sons, Ltd.

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Categorizing visits as nonemergent is not straightforward or without controversy (O’Brien et al., 1996; Guttman et al., 2003; Ragin et al., 2005; Redstone et al., 2008). A situation that may clearly seem nonurgent ex post on the basis, for example, of diagnosis codes for a visit, could have seemed like a potential emergency to the patient ex ante. The use of triage assessments by medical professionals should provide some consistency in categorizing patients, although there is no perfect measure of whether a visit to the ED is appropriate. We categorize those visits with a triage time of 2 hours or more as nonurgent in order to capture patients who were least likely to have conditions that truly necessitated ED utilization. Future research should examine the relationship between Medicaid ED copayments and the number of nonurgent ED visits using individual-level healthcare utilization data combined with detail on the ED visit, such as claims data. Such data could also address the question of whether changes in nonurgent ED visits reflect more appropriate use of ambulatory care in other settings or a decrease in the number of Medicaid enrollees seeking care overall. Most importantly, future research should assess the health consequences of these changes in cost sharing. Decreases in the number of nonurgent visits could reflect more appropriate use of care that, if better coordinated, could lead to improved health outcomes. On the other hand, if patients fail to seek care for conditions that require treatment, outcomes could worsen. These issues are beyond the scope of this study but are at the heart of determining whether these Medicaid cost-sharing policies improve social welfare. The current findings suggest that copayments may be an effective tool for reducing the use of the ED for nonurgent care among the nonelderly adult Medicaid population. While previous studies have found that copayments are effective at reducing ED use among privately insured populations, to our knowledge, this is the first study to find an effect of copayments on ED utilization in the Medicaid program. Our results provide some support for recent state efforts to implement or increase copayments for ED use in Medicaid in order to decrease costs and encourage more appropriate use of ambulatory care. If Medicaid enrollees are unable to access primary care, though, decreasing the use of EDs may not have the intended effect on overall healthcare use and health outcomes. Understanding the collective impact of changes in eligibility and cost sharing in Medicaid under the ACA will be important for assessing its effectiveness and efficiency in providing healthcare for low-income populations.

APPENDIX TABLE AI: COPAYMENT AMOUNTS FOR STATES WITH ANY COPAYMENT (2001–2009) States with a change in copayment

States with a constant copayment

State

Year of change

Change in copayment

AZ GA ID MD MA MI MN ND OH OR SC WA WV

2009 2007 2007 2005 2007 2006 2004 2005 2006 2003 2004 2003 2005

$5 to $1 $3 to $0 $0 to $3 * $0 to $6 $3 to $0 $0 to $3 $0 to $6 $3 to $6 $0 to $3 $0 to $3 $0 to $3 $0 to $3 $0 to $3

State AL CA CO IN MS MO MT NY NC OK PA RI UT VA WI WY

Copayment amount $3 $5 $3 $3 $3 $3 $5 $3 $3 $3 $3 $3 $6 $3 $3 $6

Based on information from the Kaiser Family Foundation, the Government Accountability Office, and state Medicaid websites and publications. * Maryland reverted to a $0 copay in 2007.

Copyright © 2015 John Wiley & Sons, Ltd.

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TABLE AII: REGRESSION RESULTS STRATIFIED BY LEVEL OF MEDICAID MANAGED CARE PENETRATION IN THE STATE (1)

(2)

Less than median MMC

Greater than median MMC

**

0.0963 (0.0396) *** 0.0013 (0.0003) 0.0011 (0.0084) 0.0023 (0.0160) ** 0.0349 (0.0153) 16,965 45,566,440

State copayment policy Age Male Black Other race Observations Weighted observations

*

0.0960 (0.0582) *** 0.0014 (0.0003) 0.0009 (0.0077) 0.0102 (0.0120) *** 0.0612 (0.0211) 11,263 40,287,962

(3)

(4)

(5)

(6)

Q1 MMC

Q2 MMC

Q3 MMC

Q4 MMC

0.0812 (0.0538) *** 0.0023 (0.0006) 0.0172 (0.0125) 0.0245 (0.0281) 0.0472 (0.0674) 4,669 18,092,952

0.0994 (0.0607) ** 0.0008 (0.0004) 0.0100 (0.0101) 0.0221 (0.0138) * 0.0240 (0.0136) 12,296 27,473,488

0.0462 (0.0678) *** 0.0018 (0.0005) 0.0022 (0.0095) 0.0037 (0.0218) *** 0.0900 (0.0235) 5,431 20,582,311

0.0896 (0.0662) 0.0010** (0.0004) 0.0004 (0.0132) 0.0154 (0.0154) 0.0183 (0.0386) 5,832 19,705,651

Survey-weighted standard errors in parentheses. All models also include state fixed effects. ***

p < 0.01,

**

*

p < 0.05, p < 0.1

CONFLICT OF INTEREST The Virginia Commonwealth University IRB determined that this study qualified for exemption. The authors have no conflicts of interest to disclose. ACKNOWLEDGEMENTS

We thank Stephanie Hochhalter and Lauren Grant for excellent research assistance. We also thank the National Center for Health Statistics for access to and assistance with data. The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the Research Data Center, the National Center for Health Statistics, or the Centers for Disease Control and Prevention. This project was supported by CTSA award no. UL1TR000058 from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. REFERENCES

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SUPPORTING INFORMATION Additional supporting information may be found in the online version of this article at the publisher's website. Copyright © 2015 John Wiley & Sons, Ltd.

Health Econ. 25: 529–542 (2016) DOI: 10.1002/hec

Copayments and Emergency Department Use Among Adult Medicaid Enrollees.

A number of state Medicaid programs have recently proposed or implemented new or increased copayments for nonemergent emergency department (ED) visits...
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