Emergency department use among young adult Medicare beneficiaries with autism and intellectual disabilities

Research in Autism Spectrum Disorders 70 (2020) 101470

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Emergency department use among young adult Medicare beneficiaries with autism and intellectual disabilities

T

Teal W. Benevidesa,*, Henry J. Carrettab, Katelyn Y. Gravesb, Veronica Sikkac a

Augusta University, College of Allied Health Sciences, Department of Occupational Therapy, 987 St. Sebastian Way, EC-2324, Augusta, GA 30912, United States Florida State University, College of Medicine, Department of Behavioral Sciences and Social Medicine, P.O. Box 3064300, Tallahassee, FL 323064300, United States c VA Sunshine Healthcare Network (VISN8), 140 Fountain Parkway, Ste 600 St. Petersburg , FL 33716 United States b

ARTICLE INFO

ABSTRACT

Keywords: Emergency department Utilization Autism spectrum disorder Medicare Young adult Intellectual disability Health services

Background: Individuals on the autism spectrum are at greater risk for a variety of co-occurring psychiatric and medical conditions, which could result in greater emergency department (ED) use. We aimed to identify rates of ED utilization among transition-age young adults with autism and examine predictors of utilization in a U.S. national data source. Methods: We conducted a retrospective analysis of Centers for Medicare and Medicaid 2010 Limited Data Set claims from Inpatient and Outpatient files. Medicare beneficiaries aged 18–25 years from three groups were included: autism spectrum disorder (ASD) and no intellectual disability (ID), ASD and ID, and ID-only. Primary outcomes were annual ED visit counts and dichotomous presence of ED visit in claim year. Results: Between 43–54% of adults with ASD had an ED visit in the past claim year. Significant predictors of greater ED utilization among adults with ASD included: intellectual disability (IRR=1.19, 95%CI:1.09–1.30), psychiatric utilization in the claim year (IRR=1.42, 95%CI:1.28–1.57), and greater comorbidities as assessed with ACG® risk score (IRR=1.18, 95%CI:1.15–1.20). Minority status was associated with less ED utilization among adults with ASD (IRR=0.86, 95%CI:0.78–0.94). Adults with ASD had significantly fewer annual ED visits than adults with ID-only after controlling for other variables. Conclusions: Prevention efforts to reduce ED utilization, especially for those with ID and ASD with co-occurring psychiatric conditions, is warranted. Primary care providers and case managers should develop care plans to reduce the likelihood for emergency psychiatric utilization and ensure alternative care pathways. ED clinicians may require additional training to address the needs of this population when they present to the ED in crisis.

1. Introduction Autism spectrum disorder (ASD) is a lifelong developmental condition which globally impacts functioning (American Psychiatric Association, 2013). As individuals on the autism spectrum age into adulthood, obtaining regular healthcare is a challenge, with adults reporting high rates of unmet need for medical and mental health care as compared to non-autistic adults (Nicolaidis et al., 2013). Weiss et al. (2018) found that young adults with ASD were significantly more likely to have psychiatric-related ED utilization

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Corresponding author. E-mail addresses: [email protected], [email protected] (T.W. Benevides).

https://doi.org/10.1016/j.rasd.2019.101470 Received 17 April 2019; Received in revised form 17 October 2019; Accepted 25 October 2019 1750-9467/ © 2019 Elsevier Ltd. All rights reserved.

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compared to same aged peers with other developmental disabilities (DD), but those with DD had overall higher ED utilization. Understanding the reasons for emergency department care can inform efforts to reduce this type of high-cost utilization, and improve care pathways for individuals who may be best treated in other settings. In the pediatric and adolescent autism literature, psychiatric conditions, including suicidal ideation, contributes to increased risk of experiencing psychiatric hospitalization or emergency department (ED) use (Schlenz, Carpenter, Bradley, Charles, & Boan, 2015; Cidav, Lawer, Marcus, & Mandell, 2013; Croen, Najjar, Ray, Lotspeich, & Bernal, 2006; Iannuzzi, Cheng, Broder-Fingert, & Bauman, 2015; Kalb, Stuart, Freedman, Zablotsky, & Vasa, 2012; Wu, Kung, Li, & Tsai, 2015). Other factors may contribute to greater utilization in adolescence; Hand and colleagues (2019) found that the presence of intellectual disability and being publicly insured was associated with greater ED visits. Very few studies examine characteristics and risk factors contributing to ED utilization in adulthood. Among published studies examining ED use among adults on the spectrum, the three most common reasons for presenting to the ED include psychiatric disorders, injuries, and epilepsy (e.g. Iannuzzi et al., 2015; Vohra, Madhavan, & Sambamoorthi, 2016). These reasons for visiting an ED occur at much higher rates for those on the spectrum than same-aged peers without ASD. Additionally, increased psychiatric visits to the ED also result in higher rates of inpatient hospitalization among adults with ASD, and expenditures resulting from ED care are significantly greater as compared to non-ASD adults (Vohra et al., 2016). These studies are a first step in identifying medical and psychiatric factors that contribute to increased ED utilization and costs among adults with ASD, however, two primary gaps exist which impact the ability to understand the needs of this population, as related to emergency department use. First, few adult studies have examined the contribution that intellectual disability status has on ED utilization. Second, the majority of the studies that examine ED utilization use samples that are not publicly-insured, which skews our understanding of utilization towards those who have private healthcare coverage. Population-based samples suggest that approximately 29–35 % of children with ASD in the U.S. are covered by public insurance (Zablotsky et al., 2015). Hand and colleagues (2019) identified in a single state data source that the majority of their adolescent sample of individuals on the autism spectrum were publicly insured. However, literature on the transition from pediatric care to adult care is less clear regarding how healthcare is paid for, or what percentage of the adult autism population receives public benefits. Recent studies suggest that U.S. public or governmental benefit programs, such as Medicaid or Medicare, insured approximately 20–80 % of adults with ASD in clinical or survey samples (Croen et al., 2015; Nicolaidis et al., 2013; Vohra et al., 2016). At the present time, no studies have examined a publicly insured U.S. national sample of adults on the autism spectrum presenting to the emergency department. Additionally, few studies explicitly examine the influence of an intellectual disability on use of healthcare among adults on the spectrum, despite early prevalence reports that suggest that approximately 44% of children on the spectrum in 2002, who are now adults aging into adulthood, have co-occurring ID (Centers for Disease Control & Prevention, 2007). Some literature suggests that health outcomes and costs may be driven by a co-occurring intellectual disability (ID) status, rather than ASD per se. Buescher and colleagues, in producing estimates of lifetime expenditures, suggest that the presence of an ID doubles the healthcare expenditures over the lifetime (Buescher, Cidav, Knapp, & Mandell, 2014). Describing the influence of ID status on utilization will contribute to our understanding of potential factors that should be considered when developing patient-centered interventions to improve healthcare outcomes (Hand, Boan, Bradley, Charles, & Carpenter, 2019). The purpose of this study was to identify rates of emergency department utilization among young adult Medicare beneficiaries aged 18–25 years with ASD and examine the contribution of intellectual disability to ED use. The specific research questions were: (1) Within the ASD sample, what differences exist in ED utilization between those with and without ID? (2) Within the ASD sample, what demographic factors and comorbidities are associated with greater ED utilization? (3) Among young adults with ASD as compared to those with ID-only, what differences exist in ED utilization? We hypothesized that: young adults with ASD + ID would have greater ED utilization than young adults with ASD-only (H1); after adjusting for demographic characteristics, previous psychiatric utilization and a higher comorbidity burden would significantly be associated with greater ED utilization across all samples (H2); and young adults with ASD + ID would have similar ED utilization as young adults with ID-only (H3). 2. Methods 2.1. Design and data source We conducted a retrospective cross-sectional analysis of national Centers for Medicare and Medicaid (CMS) claims 2010 Limited Data Set (LDS). We chose to evaluate adult claims using Medicare source data primarily because this data reflects a consistent eligibility approach for all U.S. citizens, and coverage of healthcare is also consistent across all states. This contrasts with Medicaid data, for which samples differ by states based on eligibility and coverage due to state policy. Only Medicare FFS claims were available, as no encounter records from Medicare Advantage (Part C) private plans are collected by CMS. Medicare Part D prescription drug claims were not available for this analysis. An existing Data Use Agreement was on file with CMS for the conduct of this study using this data, and the study received ethical review and approval prior to analysis. CMS files were developed from provider claim submissions in the fee-for-service (FFS) program and were provided to researchers organized by claim type files for: 1) inpatient services, 2) outpatient services, 3) home health, 4) hospice care, 5) skilled nursing facility and 6) professional services files. The first five files are a 100% sample of all FFS beneficiary claims by year. The professional services file included a 5% sample of existing CMS beneficiaries. Professional services include care received in community (non-hospital) settings, such as provider offices and community health clinics. The LDS data includes a denominator file for all Medicare beneficiaries covered for at least one month in the 2

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calendar year and contains demographic information, geographic identifiers and programmatic information including months of enrollment, state Medicaid buy-in indicators and other information. We linked the denominator data to other files using a unique beneficiary identifier that is stable across all three years and claim type (Research Data Assistance Center (ResDAC) (2016)). 2.2. ASD and ID case identification Our sampling frame was all disabled Medicare beneficences from < 1 to 64 years of age in the LDS calendar year files for 2008, 2009 and 2010. We applied a case definition to identify eligible beneficiaries in 2008-2010. Once identified as a case in any year, all claims associated with the unique beneficiary identifier were included in the analyses of 2010 data. We made the decision to identify cases across three years of data to maximize case identification for adults, for whom a claim may not always reflect an ASD or ID diagnosis in a single year, but chose to restrict ED analyses to the 2010 files, in order to use the most recent claim data available to us. ASD cases were identified if a single claim included an ICD-9-CM diagnosis of 299.xx (‘autism spectrum disorder’) in any claim year. ID cases were identified if any claim included an ICD-9-CM diagnosis of 317.xx, 318.xx or 319.xx (‘intellectual disability’ coded as mild, moderate or severe) in any claim year. Our use of one claim for case identification was based on our previous work (Benevides, Carretta, & Graves, 2019). We were interested in the transition to adulthood period, and therefore beneficiaries were excluded if they were younger than age 18 years or greater than 25 years when first identified in the data. We also excluded those with less than 12 months of FFS enrollment in 2010 to ensure our sample had a regular source of Medicare coverage during the analytic period. We also excluded those with high utilization due to end stage renal disease. Lastly, we were interested in ensuring our sample was well-characterized, and excluded those with a racial/ethnic categorization labeled as “unknown”. 2.3. Calculation of new derived variables Variables of interest for this study across all six claims files include codes for identifying ICD-9-CM diagnosis, Healthcare Common Procedure Coding System/Current Procedure Terminology (HCPCS/CPT) procedures and modifiers, revenue center, place of service, provider specialty codes, and all demographic information available. Variables were selected for inclusion based on our literature review. Variable naming was harmonized across all source files, and the 2010 data source was used for all reported analyses. CMS race and ethnicity codes are contained in a single variable so we were unable to examine racial categories by Hispanic ethnicity. Many of the smaller racial minority groups had low frequency counts and therefore racial categories were dichotomized into minority status (white versus all other minorities). A variable for dual-eligibility with Medicaid was derived from the state Medicaid buy-in indicator for persons with one or more months of state Medicaid buy-in. At the time our data were collected (2010), state Medicaid expansion for individuals with autism had occurred in very few states, thus the variable was included as a proxy for socioeconomic status in the absence of other income data. We recorded age in the last month of eligibility in 2010 data. For regression models, age was dichotomized into a younger cohort (18–21 years) and an older cohort (22–25 years). No missingness was present in demographic data. 2.4. Utilization associated with comorbid psychiatric claims and injuries We evaluated utilization specific to psychiatric and injury visits in the 2010 analytic year given previous research suggesting these were common reasons for presenting to the ED among adults on the autism spectrum. We used the Agency for Healthcare Research and Quality (AHRQ) H-CUP Clinical Classification Software (CCS) to identify visits associated with psychiatric events for each beneficiary in the entire 2010 claim year. Single-level CCS diagnosis codes 650–653, 656–663, 670 were used to identify psychiatric comorbidities by category. We excluded “654” and “655” (‘developmental disorders’ and ‘disorders usually diagnosed in infancy, childhood or adolescence’) from this identification process to avoid identification of psychiatric utilization associated with the ASD or ID diagnosis. Very few beneficiaries had a primary diagnosis classified as ‘654’ (n=175) or ‘655’ (n=270) in the ED claim record, suggesting that the primary reason for ED presentation was not usually attributed to the individual’s developmental condition. We created a variable associated with a psychiatric condition occurring as the primary diagnosis associated with an ED visit (“Psychiatric-related ED Visit”). CCS codes were also used to identify claims resulting in injuries (Agency for Health Care Research and Quality, 2015). CCS uses a combination of ICD-9-CM diagnosis codes in any diagnostic field plus E-Codes to identify visits associated with an injury. We used single-level diagnosis CCS codes 225–236, 239–244, 260, 2601–2615, 2618–2620 to identify injuries by categories. Use of injury ECodes are not required for claim payment, so use of the CCS algorithm is advantageous for complete identification of injury events and categorizing injuries into logical groups. We created a variable reflecting injuries occurring as the primary diagnosis associated with an ED visit (“Injury-related ED visit”). 2.5. Identification of emergency department (ED) visits ‘Treat-and-release’ ED visits were identified in the Outpatient claims file and were identified using the Revenue Center codes attached to each claim (i.e. codes 0450, 0451, 0452, 0456, & 0459). Patient discharge status was used to ensure that we included claims in which the beneficiary was discharged to home. ED visits that resulted in an inpatient admission to the same hospital were identified in the inpatient file using the admission source code that indicated the patient was transferred from an ED. Both types of ED 3

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utilization were flagged for creation of two derived variables: ED counts, which were summed counts of unique encounters for each beneficiary during the claim year in either the inpatient or outpatient files; and ED dichotomous, which provided an indicator of whether each unique beneficiary experienced any ED utilization in the claim year as reflected in the inpatient or outpatient files. 2.6. Risk adjustment Comorbidities contribute to greater likelihood of utilization. We adjusted for disease burden using Johns Hopkins Adjusted Clinical Groups (ACG) Case-Mix System, Version 11 (2014b, Johns Hopkins University, 2014b). The ACG® system assigns beneficiaries to clinical groups based on a variety of factors, including number and type of comorbidities, using a patented algorithm. The unscaled concurrent weights assigned to each beneficiary were used to adjust for differences in disease burden between beneficiaries (Johns Hopkins University, 2014a), and were based on all available claim records for that beneficiary in the 2010 claim year. 2.7. Analytic approach We conducted bivariable descriptive statistics for the analytic sample using Stata 14.1 (StataCorp, 2013). Demographic variables of interest included: age, sex, minority status (white vs non-white), Hispanic status, ACG® risk, and state Medicaid buy-in months. Dichotomous outcome variables including ED visit in past year, Injury-related ED-visits and Psychiatric-related ED visits were examined using Pearson chi-square tests of proportions. Based on the distribution of the count data, nonparametric Pearson chi-square tests of equality of medians were used to identify differences in ED counts for each dichotomous demographic variable. For multivariable regressions examining ED count data, there were several regression approaches considered a priori including Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial. We examined the ED visit count for excessive zeroes (over dispersion) commonly found in count data. A zero-inflated negative binomial (ZINB) was identified as the best approach, and we tested this assumption with the Vuong test to determine whether a negative binomial or ZINB model was appropriate. We examined model fit with Akaike’s information criterion (AIC) to compare models and determine the predictors that were included in the final model (Burnham & Anderson, 2004). This form of model testing allowed us to reduce the number of potential variables based on hypothesized predictors and model fit. The two-step ZINB models were first inflated (Step 1) on all model variables and then reduced (Step 2) based on evaluation of significant log-alpha (p < .05) to ensure model fit. In most cases, the heteroscedasticity of the models was best adjusted with the robust option. We calculated predicted probabilities of ED events for each group adjusted for all model covariates using predictive margins option in Stata. 3. Results Demographic characteristics for our study sample by year are presented in Table 1. In 2010, we identified n=3499 young adults with ASD-only, n=2048 with ASD + ID, and n=13,178 with ID-only. Consistent with existing literature, there were significantly more males than females with either ASD-only or ASD + ID, as Table 1 Demographic Characteristics of ASD-only, ASD and ID, and ID-only Groups in 2010.

Age in years, Mean (SD) Male sex, f (%) Race, f (%)a White Black Asian North American Native Other Ethnicity, f (%) Non-Hispanic Hispanic Medicaid state-buy-in (months) Median Mean (SD) Unscaled ACG® Concurrent Risk Score Median Mean (SD)

ASD-only (n = 3499)

ASD + ID (n = 2048)

ID-only (n = 13,178)

p-value

23.26 (2.41)

23.60 (2.32)

23.99 (2.29)

F(2,18722) = 149.32, p < .001

2,737 (78.22)

1,519 (74.17)

7,196 (54.61)

2,619 (74.38) 533 (15.14) 83 (2.36) 43 (1.22) 53 (1.51)

1,346 (65.59) 424 (20.66) 41 (2.00) 26 (1.27) 25 (1.22)

8,491 (64.31) 2,951 (22.35) 195 (1.48) 226 (1.71) 147 (1.11)

χ2=813.02, p < .001 χ2=195.28, p < .001

3,331 (95.20) 168 (4.80)

1,862 (90.92) 186 (9.08)

12,010 (91.14) 1,168 (8.86)

12 9.55 (4.36)

12 10.28 (3.84)

12 10.38 (3.68)

Median test, p < .001

1.14 1.76 (2.52)

1.76 2.65 (3.51)

1.27 2.56 (3.77)

Median test, p < .001

χ2=63.89, p < .0001

Abbreviations: ACG® Adjusted Clinical Groups; ASD Autism Spectrum Disorder; ID Intellectual Disability. Beneficiaries with 12 months fee-for-service, no end-stage renal disease, no missing race/ethnicity data. Data Source: Centers for Medicare and Medicaid, Limited Data Sets 2010. a Race variable does total 100% because claims data classify race and ethnicity in one variable, thus Hispanic ethnicity was derived from race. 4

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Table 2 Unadjusted Emergency Department Utilization among Young Adults with ASD-only, ASD and ID, and ID-only.

Any ED Visit in Past Yeara f % [95% CI] Any Injury ED visit in Past Yearb f % [95% CI] Any Psych ED visit in Past Yearb f % [95% CI] Count of Annual ED Visits Per Beneficiary Median Mean (SD) Range

ASD-only (n = 3499)

ASD + ID (n = 2048)

ID-only (n = 13,178)

p-value

1,504 42.98 [41.34, 44.64]

1,109 54.15 [51.96, 56.33]

7,459 56.60 [55.75, 57.45]

χ2=206.40, p < .0001

623 17.81 [16.55, 19.11]

560 27.34 [25.42, 29.33]

3,712 28.17 [27.40, 28.94]

χ2=155.51, p < .0001

628 17.95 [16.69, 19.26]

498 24.32 [22.47, 26.23]

3,321 25.20 [24.46, 25.95]

χ2=80.73, p < .0001

0 1.08 (2.92) 0–69

1 1.57 (3.33) 0–64

1 2.04 (4.36) 0–105

Median test χ2=224.34, p < .001

Abbreviations: ASD, Autism Spectrum Disorder; ID, Intellectual Disability. Beneficiaries with 12 months fee-for-service, no end-stage renal disease, no missing race/ethnicity. Data Source: Centers for Medicare and Medicaid, Limited Data Sets 2010. a Denominator is total unique beneficiaries in group. b Denominator is total unique beneficiaries in group in past year with an ED visit.

compared to the sex distribution within the ID-only group. Minority status differed by intellectual disability status. Specifically, there were significantly more minority and Hispanic young adults with either ASD + ID or ID-only, as compared to the ASD-only group. Median Medicaid state-buy-in months were significantly lower for the ASD-only group as compared to the other two groups. The ASD + ID group had higher comorbidity as indicated by significantly greater median ACG® concurrent risk score than either of the other groups. 3.1. Research questions 1 and 2: autism group emergency department utilization Our first hypothesis concerned the young adults with ASD in our dataset; these analyses compared young adults with ASD-only (n = 3499) to those with ASD + ID (n = 2048). Count data for ED utilization were highly skewed; descriptive statistics are presented in Table 2. Median tests of 2010 ED counts suggest that individuals with ASD + ID are significantly more likely to have ED counts above the median than individuals with ASD-only. Multivariable ZINB regressions to examine differences in ED counts between ASD beneficiaries with and without ID suggest that young adult beneficiaries with ASD + ID were at greater risk for having more ED visits in 2010 than those with ASD-only (Table 3). Having a primary psychiatric diagnosis increased an individual’s risk of more ED visits, as did having a higher ACG® score. Minority beneficiaries with ASD were at lower risk for having ED visits than white beneficiaries. Females and those dual-eligible for Medicaid were significantly more likely to have had an ED visit in the past year. Age was a non-significant predictor of ED visits. None of the 5 interaction models to examine the interaction of group (ASD-only and ASD + ID) with age category, sex, minority status, dual eligibility with Medicare, or primary psychiatric diagnosis were significant (models not presented). Table 3 Factors Associated with Emergency Department Counts among Young Adults with ASD-Only and ASD + ID. IRR (SE) Diagnosis group: ASD + ID Age group: 22-25 years Racial/ethnic group: Non-white Sex: Female Dual-eligibility: Medicaid 1-12 months Primary Psychiatric Claim Unscaled Concurrent ACG® Score

1.19 0.99 0.86 1.10 1.16 1.42 1.18

a

(0.05) (0.05) (0.04) (0.05) (0.08) (0.07) (0.01)

95% CI

p-value

1.10–1.30 0.90–1.09 0.78–0.94 1.00–1.21 1.02–1.33 1.28–1.57 1.16–1.20

< .0001* 0.89 0.001* 0.04* 0.02* < .0001* < .0001*

Abbreviations: ACG: Adjusted Clinical Groups; ASD: Autism Spectrum Disorder; CI: Confidence Interval; ID: Intellectual Disability; IRR: Incidence rate ratio. Reference group was: ASD-only, 18–21 years, white, male, No dual Medicaid coverage, No primary psychiatric claim in past year. Data Source: Centers for Medicare and Medicaid, Limited Data Sets 2010. a Zero observations=2934; Non-zero observations =2613. Model inflated on: Unscaled concurrent ACG® Score. * p < .05. 5

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Table 4 Factors Associated with Emergency Department Counts Among ASD-Only, ASD + ID, and ID-Only. IRR (Robust SE) ASD-only ASD + ID Age group: 22–25 years Race/ethnicity group: Non-white Sex: Female Dual-eligibility: Medicaid 1–12 months Primary Psychiatric Claims Unscaled Concurrent ACG® Score

0.67 0.80 1.01 0.95 1.16 1.19 1.06 1.10

a

(0.02) (0.03) (0.03) (0.02) (0.03) (0.05) (0.004) (0.004)

95%CI

p-value

0.62–0.72 0.74–0.85 0.95–1.07 0.90–0.99 1.10–1.22 1.09–1.30 1.05–1.07 1.09–1.10

< .0001* < .0001* 0.98 0.04* < .0001* < .0001* < .0001* < .0001*

Abbreviations: ACG: Adjusted Clinical Groups; ASD: Autism Spectrum Disorder; CI: Confidence Interval; ID: Intellectual Disability; IRR: Incidence rate ratio; SE: Standard error. Reference group: ID-only, 18–21 years, white, male, No dual Medicaid coverage, No primary psychiatric claim in past year. Data Source: Centers for Medicare and Medicaid, Limited Data Sets 2010. a Zero observations = 8652; Non-zero observations = 10,072. Model inflated on Medicaid coverage, documented injury visit in claim year, Unscaled concurrent ACG® Score. * p < .05.

3.2. Research question 3: dichotomous emergency department utilization in the full sample Table 2 presents unadjusted frequencies and percentages of ED visits among unique beneficiaries from each ASD group and the IDonly group; across all groups, nearly 43–57 % of beneficiaries experienced at least 1 ED visit in the past year. Among those beneficiaries with at least one ED-visit in the past year, approximately 18–28 % of those visits resulted from injury and 18–25 % of EDvisits were associated with a psychiatric diagnosis (Table 2). No differences in injury-related or psychiatric-related ED visits were found between the three groups. 3.3. Research question 3: differences in ED counts between ASD group compared to ID-only group Young adults with ASD-only and ASD + ID had significantly fewer annual ED visits than young adults with ID-only after controlling for other demographic and comorbidity risk variables (Table 4). Predictive margins indicate that among those with at least 1 ED visit in the past claim year, young adults with ASD-only had the fewest predicted annual ED events (2.35, 95%CI:1.65-3.05), followed by young adults with ASD + ID (2.80, CI:1.97-3.63), and young adults with ID-only (3.52, CI:2.50-4.53). 4. Discussion This study specifically aimed to evaluate emergency department utilization differences in a U.S. national Medicare sample of young adults on the autism spectrum with and without intellectual disability, and identify factors associated with greater ED utilization. Approximately 43% of beneficiaries with an autism spectrum disorder in the claim year had at least one emergency department visit. When beneficiaries with autism also had co-occurring intellectual disability in the claim record, their risk for experiencing an ED visit increased by 19%. Our findings point to the need for emergency physicians and practitioners to develop skills in working with and addressing the complex care needs of this population across the lifespan. Adults on the autism spectrum benefit from use of non-speaking approaches for communication, reduced environmental stimulation, and increased time to respond and comply with requests (e.g. Nicolaidis et al., 2015), aspects of the care environment that are not frequently possible in emergency departments. Some work has been done to educate emergency department personnel regarding the needs of those on the autism spectrum (e.g. McGonigle, Migyanka, & Glor-Scheib, 2014). However, much more work is needed to address the training competencies and available tools to assist Emergency Medicine practitioners in working with these patients. Our study found that those with a claim of intellectual disability, and no autism claim, were significantly more likely to use the ED than those with a claim for autism spectrum disorder. Hand and colleagues (2019) also found this same pattern in ED utilization among adolescents with ASD-only, ASD + ID, and ID-only in a state-level administrative claims source. Intellectual disability is frequently associated with additional diagnoses (e.g. dysphagia, congenital conditions), which contribute to greater healthcare utilization (e.g. Boat & Wu, 2015). In line with this literature, we found that the ID-only group had significantly greater median ACG® risk scores than the two autism spectrum groups. This variable was important in our analyses for adjusting for co-occurring conditions increasing the likelihood of ED utilization. Future work could use these ACG® variables to further explore the constellation of factors that precipitate ED visits. This could contribute to the development of targeted interventions that can address the specific needs of this intellectual disability population (Balogh et al., 2016). We also found that any primary psychiatric diagnosis in the claim year results in approximately 40% greater risk of having an ED visit as compared to those without a primary psychiatric diagnosis. Adults on the spectrum frequently report that their mental health care needs are not addressed by care providers (e.g. Camm-Crosbie, Bradley, Shaw, Baron-Cohen, & Cassidy, 2019). The ED is being used often by the publicly insured young adult Medicare sample we examined. However, it is likely not appropriate for meeting the needs of this sensitive patient population, as evidenced by Lunsky, Paquette-Smith, Weiss, and Lee (2015), who found that 6

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approximately 23% of the adults receiving services in the ED required restraint. The goal of emergency medicine is episodic management with admission or discharge. This approach may not work with individuals with autism and/or intellectual disability as the ED lacks other resources (e.g. funding, housing, social supports) to address their psychiatric and medical needs after discharge. One approach used for ‘super-utilizer’ publicly insured patients, who also have complex medical, psychiatric, and social factors which increase use of hospital resources, are interventions that combine a personalized approach to identifying and connecting the patient to community and medical providers immediately after hospital visits (e.g. Grinberg, Hawthorne, LaNoue, Brenner, & Mautner, 2016; Wiest, Yang, Wilson, & Dravid, 2019). These evaluated interventions are built on a meaningful and trusting relationships, and differ from standard care coordination in that they involve an interprofessional care team to understand and address both medical and social factors contributing to utilization. This is very difficult to achieve in the ED (e.g. Wiest et al., 2019). These approaches also help to address the social factors which may contribute to increased utilization, such as those found by Lunsky et al. (2015) as being associated with emergency department care, including lack of structured daytime activities, previous ED use, and history of hurting others. From an emergency medicine standpoint, if patients with developmental conditions and co-occurring psychiatric or medical comorbidities are discharged without the appropriate coordinated care, the rates of return to the ED are likely going to be high with poor outcomes. Future work to translate interventions used to reduce ED visits in other complex patient populations for individuals with intellectual and developmental conditions, such as those in our study, may improve care and reduce high-cost health care use. Additionally, future research could examine factors such as the chronological proximity of non-emergent psychiatric utilization to psychiatric ED events, which would help clarify the potential role of mental health management in preventing such ED utilization for adults with intellectual and developmental disorders. Another approach for addressing high ED utilization in non-autism samples includes use of alternative crisis settings for addressing psychiatric emergencies, which may address some of the sensory over-responsivity described by those on the autism spectrum in healthcare settings (e.g. Nicolaidis et al., 2013). For non-autism populations, the use of alternative care settings for crisis visits has mixed evidence supporting its use. Heyland and Johnson (2017) found that the use of a community crisis setting reduced ED visits in a psychiatric population who frequently were being treated at an ED. However, a randomized controlled trial by Currier, Fisher, and Caine (2010) for non-autistic adults with suicide risk found no reduction in ED visits after providing case management follow up and either a mobile crisis unit or an outpatient treatment setting for high-risk patients. Future work to co-develop approaches in collaboration with the autistic adult population to translate effective care models in the ED setting is needed. We found that among those with ASD-only and ASD + ID specifically, between 43–50 % had at least one ED visit in the claim year. Other recent studies estimate that 20% to 27% of adults on the spectrum use the ED, although these studies rely on privatelyinsured claims and self-reported data (Liu, Pearl, Kong, Leslie, & Murray, 2017). In a well-characterized Medicaid and state health plan dataset, McDermott et al. (2015) identified that approximately 19% of young adults on the autism spectrum used the ED. It is unclear at this time whether our findings of higher ED utilization are due to potential differences in a Medicare-insured sample as compared to the samples in these other studies, or some other reason. Our sample possibly became eligible for Medicare by virtue of a disability determination, but the Medicare claim record lacks Social Security Administration reasons for eligibility, and other characteristics related to severity or functional limitation which might help us better characterize this sample from the Limited Data Set. Our findings reflect an important need to better understand publicly-insured adult beneficiaries with ASD in comparison to other adult ASD samples. 4.1. Limitations Several limitations to our work deserve mention. Our findings only apply to the population of young adults with autism spectrum disorder who are transition-age Medicare beneficiaries between 18–25 years old. To our knowledge, this publicly-insured sample has not yet been described in the literature and thus our work requires replication with other age groups, as well as additional investigation to understand how these beneficiaries came to be recipients of Medicare. It may be conjectured that those receiving a disability determination and subsequent eligibility for Medicare at a young age are ‘more severe’ in their functional limitations than other young adults on the autism spectrum with no disability determination. However, the specific conditions associated with the disability determination are not provided with the claims data. Likewise, the available variables do not inform our understanding of the functional abilities of those in our sample. This makes it challenging to compare this sample to other autism samples. Our data contributes to understanding of utilization of U.S. adults with autism in this public payer system, although eventual work should aim to include all-payer claims from both public and private insurers for adults with and without autism. We specifically included those in our sample with at least 1-claim of ASD, which requires additional validation methodologically as to sensitivity and specificity of using 1 versus 2 claims for case identification. Our data also did not include information about beneficiary socioeconomic status such as income or educational attainment, which were not available in the dataset. We were able to include U.S. state Medicaid buy-in indicator as a proxy for receipt of Medicaid, which typically is used to suggest low income and thus socioeconomic status. However, this dual-eligibility indicator may underestimate the true number of individuals who are dually eligible for Medicaid and Medicare benefits (Koroukian, Dahman, Copeland, & Bradley, 2010). Additionally, our analyses were restricted to comparisons among same-aged young adults with intellectual disability; a non-disabled young adult population is not available in Medicare claims. Lastly, our analyses did not extract specific comorbidities that were available in the diagnosis billing fields. This has been an important part of previously published work on young adults with ASD, and a future step for our research team. Our analyses sought to adjust for the presence of co-morbidities solely through ACG® risk scores as opposed to individual dichotomous variables. 7

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5. Implications Practitioners, policymakers, and funders addressing needs of young adults with ASD between 18–25 years should be aware of the high rates of emergency department utilization among young adults with ASD and intellectual disability. It is concerning within our data that any psychiatric utilization within the claim year was highly associated with ED utilization across all study groups. For youth and adults on the autism spectrum with co-occurring psychiatric conditions, case management and primary care providers should develop care plans to reduce the likelihood for emergency psychiatric utilization and ensure appropriate or alternative care pathways. Greater attention to interventions and supports such as referral to social work or other case management to reduce ED utilization is imperative. EDs are not ideal for mental health management especially for those diagnosed with ASD and/or intellectual disability. Patients who present to the ED for acute management of chronic conditions are often lost to follow-up and deserve coordinated care to appropriately manage their condition. This paper highlights the ED utilization of these patients and associated factors with utilization for this sensitive patient population in a high intensity, acute environment. Meetings This work has been presented as a poster at the following conferences: International Meeting for Autism Research, Baltimore, MD, May 2016; American Occupational Therapy Association National Conference, Philadelphia, PA, April 2017. Funding This study was supported by grant R40MC28854, MCH Research Program, from the Maternal and Child Health Bureau, Health Resources and Services Administration, Department of Health and Human Services. The funder did not play a role in the design, data analysis, or interpretation of this study. Declaration of Competing Interest The authors declare that no conflicts of interest exist for Teal Benevides, Henry Carretta, Katelyn Graves, or Veronica Sikka, and that the funder did not play a role in the design, data analysis, or interpretation of this study. References American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: Author. Balogh, R., McMorris, C. A., Lunsky, Y., Ouellette-Kuntz, H., Bourne, L., Colantonio, A., & Goncalves-Bradley, D. C. (2016). Organising healthcare services for persons with an intellectual disability. The Cochrane Database of Systematic Reviews, 4. https://doi.org/10.1002/14651858.CD007492.pub2 CD007492. Benevides, T. W., Carretta, H. J., & Graves, K. J. (2019). Case Identification and Characterization of Autistic Young Adults in 2010 Medicare Fee-for-Service Claims. Autism in Adulthood: online ahead of printhttps://doi.org/10.1089/aut.2018.0036. 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