Barriers to Timely Medical Care for Older Adults by Disability Status and Household Composition

Abstract

Living arrangements are often influenced by disability status, and co-resident caregivers may facilitate access to health care, especially for community-dwelling older adults with disabilities. Despite this, we know very little about how disability status and household composition work together to affect health services use. Using data from the National Health Interview Survey (2009–2011; n = 16,720), this study investigates (a) how access to medical care varies by disability status and household composition and (b) whether the relationship between household composition and health care access differs by disability status. We find that the risk of delayed care due to cost or lack of transportation is highest for older adults living alone or with non-spousal others. Older adults living alone without disabilities have lower odds of delayed care due to difficulty making a timely appointment than older adults living with a spouse. Furthermore, we find that older adults living alone with disabilities have elevated odds of delayed care for any reason. These findings can help target interventions to improve health care access through programs such as home- and community-based care and non-emergency medical transportation.

Keywords

access to care living arrangements disability

Most older adults want to remain in their homes and communities as long as possible (AARP Public Policy Institute, 2010), and access to timely medical care is essential to supporting them in doing so, especially if they have a disability. Yet, older adults often face barriers to care, such as high health care costs and lack of accessible transportation. This is especially true for older adults with disabilities, who may be limited in the kind and amount of activities they are able to do outside of the home, including visiting the doctor. For older adults living with others, access to care may be facilitated by co-resident caregivers. Older adults living alone may need assistance from outside the home to access care. This assistance may be especially important for older adults with disabilities who have complex health care needs and may face additional barriers to accessing care. Unfortunately, there is very little research that investigates the joint role of disability status and household composition in accessing medical care for older adults. This article addresses that gap by examining barriers to timely medical care among community-dwelling older adults by disability status and household composition.

Policy interventions such as the Olmstead v. LC decision (which requires states to provide care in integrated community settings vs. institutional settings), Medicaid home- and community-based service waiver programs, and Money Follows the Person demonstration projects (which provide support for moving from institutional to community-based settings) make it increasingly possible for older adults with disabilities to age in their communities rather than in institutional settings (Fields, Anderson, & Dabelko-Schoeny, 2011; Redfoot & Hauser, 2010). Therefore, it is important to understand the social and economic challenges that come with aging in the community, including barriers to accessing health care. Living arrangements are an important component of this research, because whom one lives with shapes social, physical, and financial support and can affect health, mortality, and psychological well-being (Henning-Smith, 2016; Rogers, 1996; Roy, FitzGibbon, & Haug, 1996). Household composition may be particularly important for older adults with disabilities and complex health care needs, as they are more likely to rely on co-resident family and friends to act as caregivers, to provide physical and social support, and to assist with daily activities (Johnson & Wiener, 2006).

As of 2012, more than half (57%) of non-institutionalized Americans aged 65 and older lived with a spouse, and another one third (28%) lived alone (Administration on Aging, 2012). The rest (15%) lived with other people, most commonly other relatives such as adult children and grandchildren (Administration on Aging, 2012). While living with a spouse remains the most common living arrangement for older adults, there has been a recent increase in multigenerational households (Taylor et al., 2010). This is due, in part, to the recent economic recession and housing crisis (Keene & Batson, 2010) along with the growing ranks of adults with disabilities living in non-institutional settings who require co-resident caregiving (Redfoot & Hauser, 2010). Declining health, subsequent needs for care, and the death of a spouse are all associated with increased odds of older adults moving in with adult children (Compton & Pollak, 2013; Keene & Batson, 2010). Ideally, co-resident caregivers in these situations would help facilitate access to timely medical care.

Access to Care and Disability Status

Access to care is a multifaceted concept, involving allocation of services for whole populations, regional- and systems-level provision of services, insurer and provider regulations, and individual-level receipt of care. Most simply, “access to care” measures whether people who need medical care receive it (Aday & Anderson, 1974). Whether individuals receive appropriate care is determined by a complicated process, however, involving individual motivation and behavior to seek health care (Aday & Anderson, 1974), availability of services, affordability of services, physical proximity to and accessibility of care, and relevancy and acceptability of services to potential patients (Gulliford et al., 2002; Penchansky & Thomas, 1981). Here, we conceptualize access to care as an individual-level phenomenon measuring whether people received care they perceived they needed in a subjective timely fashion.

A growing body of research documents the relationship between disability status and access to care. With a few exceptions (Altman & Bernstein, 2008; Parish & Saville, 2006; Wisdom et al., 2010), people with disabilities are less likely to receive various preventive services (Chevarley, Thierry, Gill, Ryerson, & Nosek, 2006; Parish & Saville, 2006; Ramirez, Farmer, Grant, & Papachristou, 2005; Trani et al., 2011; Veltman, Stewart, Tardif, & Branigan, 2001; Wisdom et al., 2010). Problems accessing timely medical care for people with disabilities can be partly attributed to structural and environmental barriers, such as the lack of accessible transportation (Drainoni et al., 2006; Henning-Smith, McAlpine, Shippee, & Priebe, 2013; Hyde & Livermore, 2016; Scheer, Kroll, Neri, & Beatty, 2003).

While this is a growing area of research, there are limitations to the current literature. First, much of the prior research examining health services use for people with disabilities lacks a comparison group of individuals without disabilities. Second, the aforementioned studies were not specific to older adults and, in some cases, excluded them entirely. Higher prevalence of disability in older ages, combined with older adults’ unique and near-universal access to health insurance (through Medicare), necessitates research specific to the older adult population.

Access to Care and Living Arrangements

Much less research has focused on how household composition affects older adults’ access to health care. The few studies that examine the relationship between household composition and health care utilization among older adults find a positive relationship between living alone and receiving paid in-home care (Langa, Chernew, Kabeto, & Katz, 2001) and physician use (Rosner, Namazi, & Wykle, 1988). However, these studies did not examine how specific barriers to care vary by disability status and household composition. A more recent study found a link between living arrangements and use of preventive care among adults aged 65 and older in the Medical Expenditure Panel Survey. In their study, Lau and Kirby found that older adults living alone or with their adult children were less likely than those living with a spouse to receive recommended preventive care, including influenza vaccinations, cholesterol and cancer screenings, and routine physical and dental exams (Lau & Kirby, 2009). Another study found that veterans with dementia were more likely to receive specialty care if they lived with their primary caregiver (Thorpe, Van Houtven, & Sleath, 2009).

While these studies suggest differences in access to health care by living arrangement, they do not investigate specific barriers to receiving care that might be addressed by policy or programmatic interventions, nor do they investigate how the relationship between household composition and barriers to care varies by disability status. Given the evidence of more difficulty accessing care among older adults with disabilities and among older adults living alone or with non-spousal others, we hypothesize that older adults with disabilities and older adults living alone or with others besides a spouse will experience more barriers to care. Furthermore, we expect to see variation in the relationship between household composition and access to care by disability status. Results from this work will indicate who is at greatest risk of experiencing barriers to care, which is important for public health planning and policy making.

Method

Data

Data are from the Integrated Health Interview Series, a version of the National Health Interview Survey (NHIS) that is integrated and harmonized across years (Minnesota Population Center and State Health Access Data Assistance Center, 2012). Conducted annually by the National Center of Health Statistics (NCHS), the NHIS is a nationally representative survey of the U.S. civilian non-institutionalized population and serves as one of the country’s most comprehensive resources on the nation’s health (National Center for Health Statistics, 2013). The family core questionnaire records basic health and disability information for each household member while a single random adult in each household is selected for a detailed interview on pertinent health information, including access and barriers to health care. All responses are self-reported in a face-to-face interview with an NCHS surveyor. We used a pooled sample of adults aged 65 and older from 2009 to 2011 who answered questions on delayed medical care and who did not have missing data on any covariates (n = 16,720).

The primary dependent variable was whether the respondent delayed medical care at any point in the 12 months prior to the interview for the following reasons: concern about cost, difficulty making a timely appointment, or lack of transportation. These three variables allowed us to assess financial, scheduling, and structural barriers to care. Respondents were not provided a definition for “delay”; however, they were told to exclude delays in dental care. We treated each reason as a binary outcome, with “1” indicating that the respondent experienced that type of delay at least once in the 12 months prior to the survey; “0” meaning otherwise. We also created a composite measure of any delayed care, coded “1” if respondents reported delayed care for one or more reasons and “0” if the respondent did not report any delayed care in the previous 12 months.

Disability was assessed with a combination of questions asking respondents if they are limited in their personal care needs (activities of daily living), in handling routine tasks (instrumental activities of daily living), in remembering, in walking without using any special equipment, or in any other way because of a physical, mental, or emotional problem. Similar to other disability studies on older adults using the NHIS (Freedman et al., 2013; Martin, Freedman, Schoeni, & Andreski, 2010), this composite variable was coded as a binary measure, with “1” indicating the presence of a disability if the respondent said yes to any of the above; “0” indicating otherwise. Household composition was coded as living with a spouse (with or without others present), living alone, or living with others (Administration on Aging, 2012). In sensitivity analyses, we separated older adults living with a spouse and others from older adults living with others only and found that results were similar. Individuals living with an unmarried partner (3% of the total population identified as living with a spouse/partner) were included with older adults living with a spouse. The data also included information on the respondent’s relationship to the household head (self, spouse, unmarried partner, parent, child, sibling, grandparent, aunt/uncle, niece/nephew, other relative, or unrelated other). Because of collinearity with living arrangements, these were not included in multivariate analyses but were used to describe the composition of households for those individuals living with non-spousal others.

Covariates included the following sociodemographic characteristics associated with disability, household composition, and access to care: gender, age, race/ethnicity (White, African American/Black, Hispanic, and Asian/all other), ratio of family income to the federal poverty threshold (<100%, 100%–199%, 200%–399%, and 400% or more), educational attainment (less than high school, high school degree, some college, and college degree and beyond), employment status (employed vs. unemployed/not in the labor force), and insurance status (private, Medicare only, Medicaid only, Medicare/Medicaid, and uninsured). Any combination of public and private insurance was categorized as private, and private insurance included supplemental Medi-gap and Medicare Advantage plans (see Note 1). Of respondents with private insurance, 94% were also enrolled in Medicare.

Analysis

We used chi-square tests to determine significant differences in bivariate analyses. To assess the odds of each type of delayed care, we used logistic regression, controlling for key socioeconomic and demographic characteristics. Next, we included interaction terms between disability and household composition to detect whether there was significant variation. We do not report those results, given the difficulty in interpreting odds ratios (OR) from interaction terms in non-linear models (Karaca-Mandic, Norton, & Dowd, 2012). Instead, we stratified our analyses by disability status to determine how the relationship between household composition and delayed care differs by disability status. Because of high rates of missing data on household income, we used the NHIS-provided imputed income files to construct poverty ratios. For all other variables, we dropped observations with missing data (5% of the initial sample of 17,663), leaving a final sample size of 16,720. We used the “mi” family of commands in Stata to estimate models with imputed data and employed survey weights to approximate nationally representative estimates and adjusted standard errors.

Results

Sample characteristics are provided in Table 1. Nearly 25% of the sample had a disability. Fifty-six percent of respondents lived with a spouse, 32% lived alone, and 12% lived with other non-spousal family members or friends (without a spouse present). These arrangements differed by disability status, as older adults with disabilities were more likely to live alone or with others. Respondents with disabilities were more likely to be female, older, poor, and out of the labor force; to have less than a high school degree; and to be dually enrolled in Medicare and Medicaid than their counterparts without disabilities. We also found racial differences by disability status; older adults with disabilities were more likely to be Black and less likely to be White than those without disabilities.

Table 1.

Sample Characteristics.

Characteristic	Full sample^a (%)	Without disability^b (%)	With disability^c (%)	p value
Has a disability	24.5
Living arrangement				<.001
Living with a spouse/partner	56.2	61.8	39.2
Living alone	32.2	29.0	41.9
Living with others only	11.6	9.2	19.0
Female	56.2	54.2	62.6	<.001
Age in years (M)	74.3	73.2	77.6	<.001
65–74	56.0	61.6	34.6
75–84	33.3	31.7	38.3
85+	11.7	6.7	27.1
Race/ethnicity				<.001
White	80.3	81.2	77.5
Black/African American	8.6	7.7	11.3
Hispanic	7.1	7.0	7.5
Asian/all other	4.1	4.2	3.7
Ratio to federal poverty threshold (%)				<.001
<100	9.7	7.3	17.3
100–199	21.7	19.2	29.5
200–399	43.5	45.0	38.6
400 or higher	25.2	28.6	14.7
Educational attainment				<.001
<High school	19.8	16.7	29.4
High school degree	34.3	34.2	34.5
Some college	23.3	24.1	20.8
College and beyond	22.6	25.0	15.4
Employed	14.9	18.8	3.0	<.001
Insurance status				.063
Private coverage	51.4	51.8	49.2
Medicare only	38.1	38.0	39.0
Medicaid only	0.6	0.7	0.6
Dual Medicaid and Medicare	8.9	8.7	10.5
Uninsured	0.9	0.9	0.8
Self-reported health status				<.001
Very good/excellent	42.9	51.3	17.0
Good	33.8	34.7	31.3
Fair/poor	23.2	14.0	51.7

Source. Authors’ calculations of 2009–2011 Integrated Health Interview Series.

Note. The p value indicates significant difference between respondents with and without a disability.

n = 16,720. ^bn = 12,200. ^cn = 4,520.

To better describe the household composition for those individuals who were living with “others,” we examined the relationship of the survey respondent to the household head. Older adults with disabilities living with others were much less likely to be the household head than those without disabilities (43.3% vs. 65.3%). Respondents with disabilities were more likely to be parents living in their children’s home than those without disabilities (41.3% vs. 23.7%). Differences between those with disabilities and those without were significant at p < .001. Other, less common, household arrangements included living with siblings, grandparents, aunts or uncles, other family, or unrelated adults (roommates).

Overall, the most common reasons for delaying care were cost and difficulty making a timely appointment. Older adults with disabilities had higher rates of all types of delayed care than those without disabilities, with 18.3% delaying care in the past 12 months for any reason (vs. 10.6% of those without disabilities, p < .001). Specifically, older adults with disabilities were much more likely to delay care due to cost (7.3% vs. 3.4%; p < .001), difficulty making a timely appointment (4.7% vs. 3.7%; p < .05), or lack of transportation (4.9% vs. 0.8%; p < .001).

Rates of delayed care differed by household composition (see Figure 1); 14.5% of respondents living alone—and 15.1% of respondents living with others—delayed care for any reason, compared with 10.9% of respondents living with a spouse. Older adults living alone were the most likely to have delayed care due to cost (6.6%), followed by older adults living with others (5.3%). Older adults living with others were the most likely to report delayed care due to lack of transportation (4.0%), followed by those living alone (2.9%). The most common reason for delayed care differed by living arrangement. For those living with a spouse, the most common reason for delaying care was difficulty making a timely appointment, while for those living alone or with others it was cost. This may be attributed to differences in socioeconomic status between those living alone or with others versus those living with a spouse; older adults living with a spouse tend to be more affluent.

Figure 1.

Delayed care by living arrangement.

In fully adjusted multivariate models (see Table 2), having a disability was associated with significantly higher odds of each type of delayed care. The odds of delayed care by disability status were highest for delayed care due to lack of transportation (OR = 3.7, p < .001) and delayed care due to cost (OR = 1.8, p < .001). Living alone and living with others were associated with higher odds of delayed care due to cost (OR = 2.2, p < .001 and OR = 1.4, p < .05, respectively) and lack of transportation (OR = 2.6, p < .001 and OR = 2.9, p < .001), compared with older adults living with a spouse. Living alone was associated with lower odds of delayed care due to difficulty getting a timely appointment (OR = 0.8, p < .05). Among covariates, being female, Hispanic, or Asian, having an income less than 400% of the federal poverty threshold, having some college, and being in fair/poor health were all associated with higher odds of experiencing any delayed care. In contrast, older age was associated with lower odds of delayed care for any reason.

Table 2.

Odds of Delayed Care by Reason for Delay.

Characteristic	Delay reason			Any delay
Characteristic	Cost	Difficulty obtaining timely appointment	Lack of transportation	Any delay
Presence of a disability	1.78***	1.30*	3.73***	1.71***
Living arrangement
With a spouse/partner (ref.)	1.00	1.00	1.00	1.00
Alone	2.18***	0.79*	2.61***	1.29***
With others only	1.42*	1.10	2.86***	1.18
Female	1.06	1.27*	1.28	1.15*
Age	0.91***	0.96***	0.97**	0.95***
Race/ethnicity
White (ref.)	1.00	1.00	1.00	1.00
Black/African American	1.23	0.65*	1.29	1.02
Hispanic	1.28*	1.11	1.74**	1.29**
Asian/all other	0.84	1.48*	1.39	1.37*
Ratio to federal poverty threshold (%)
400 or higher (ref.)	1.00	1.00	1.00	1.00
<100	2.72***	1.03	2.54**	1.40**
100–199	3.61***	1.20	2.97**	1.75***
200–399	2.16***	1.11	1.50	1.26*
Educational attainment
High school degree (ref.)	1.00	1.00	1.00	1.00
<High school	1.08	1.20	1.05	1.08
Some college	1.26*	1.42**	1.02	1.17*
College and beyond	1.22	1.52**	0.96	1.14
Employed	1.46**	1.30	0.74	1.19
Insurance status
Private coverage (ref.)	1.00	1.00	1.00	1.00
Medicare only	1.08	1.03	0.75	0.98
Medicaid only	1.30	0.81	0.98	0.91
Dual Medicaid/Medicare	0.98	1.22	0.85	1.13
Uninsured	1.08	1.03	0.96	1.07
Fair/poor health	2.31***	1.78***	1.82***	1.74***

Source. Authors’ calculations of 2009–2011 Integrated Health Interview Series.

Note. Sample n = 16,720; population N = 36,172,254. Results are presented as adjusted odds ratios.

p < .05. **p < .01. ***p < .001.

Results from our models including interaction terms showed significant associations between disability status and household composition interacted together for each type of delayed care. Therefore, we ran subgroup analyses stratified by disability status; results are presented in Table 3. Compared with older adults with disabilities living with a spouse, older adults with disabilities living alone or with non-spousal others faced higher odds of delayed care due to cost, lack of transportation, or for any other reason. We found similar patterns among older adults without disabilities: They were more likely to delay care due to lack of transportation if they were living alone or with others and more likely to delay care due to cost or for any other reason if they were living alone. However, older adults without disabilities living alone were less likely than older adults without disabilities living with a spouse to delay care due to difficulty getting a timely appointment.

Table 3.

Odds of Delayed Care, by Disability Status and Reason for Delay.

Characteristic	Reason for delay: No disability group^a				Reason for delay: Disability group^b
Characteristic	Cost	Difficulty getting timely appointment	Lack of transportation	Any delay	Cost	Difficulty getting timely appointment	Lack of transportation	Any delay
Living arrangement
With a spouse/partner (ref.)	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00
Alone	2.29***	0.70**	3.35***	1.20*	2.04***	1.00	2.18**	1.49**
With others only	1.07	1.14	4.34***	1.03	1.80*	1.10	2.17*	1.48*
Female	1.16	1.30*	1.24	1.23**	0.94	1.22	1.29	1.03
Age	0.91***	0.96**	0.97	0.96***	0.92***	0.95***	0.97**	0.94***
Race/ethnicity
White (ref.)	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00
Black/African American	1.00	0.62*	1.53	0.97	1.27	0.69	1.20	1.08
Hispanic	1.26	1.23	2.11**	1.27*	1.34	0.88	1.46	1.32
Asian/all other	1.16	1.50	2.06	1.51*	0.28**	1.42	1.05	1.08
Ratio to federal poverty threshold (%)
400 or higher (ref.)	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00
<100	3.23***	1.17	3.06*	1.36*	2.16*	0.86	2.11	1.50
100–199	3.58***	1.10	4.14**	1.67***	3.33**	1.38	2.20	1.97**
200–399	2.36***	1.10	1.32	1.22*	1.65	1.16	1.47	1.39
Educational attainment
High school degree (ref.)	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00
<High school	1.11	1.07	1.60	1.10	1.02	1.40	0.87	1.03
Some college	1.37*	1.37*	1.28	1.21*	1.11	1.57	0.90	1.08
College and beyond	1.33	1.60**	1.18	1.17	1.05	1.20	0.88	1.07
Employed	1.44*	1.33	0.73	1.24*	2.00*	1.18	0.92	1.08
Insurance status
Private coverage (ref.)	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00
Medicare only	1.22	1.07	0.48	1.03	0.91	0.88	0.93	0.89
Medicaid only	1.79**	0.73	0.71	0.95	0.71	0.97	1.17	0.82
Dual Medicaid/Medicare	1.14	1.10	0.39	1.13	0.78	1.42	1.16	1.12
Uninsured	0.99	1.19	0.69	1.13	1.21	0.67	1.14	0.98
Fair/poor health	2.98***	1.98***	1.98**	2.02***	1.66**	1.54*	1.70**	1.44**

Source. Authors’ calculations of 2009–2011 Integrated Health Interview Series.

Note. Sample n = 16,720; population N = 36,172,254. Results are presented as adjusted odds ratios.

n = 12,200. ^bn = 4,520.

p < .05. **p < .01. ***p < .001.

The association of covariates with delayed care also differed by disability status. For respondents without disabilities, being female, Hispanic or Asian, poor, having some college, and being employed were all associated with higher odds of delayed care for any reason, whereas those relationships were not significant for respondents with disabilities. However, the direction of effect for covariates was similar across disability status. For respondents with disabilities, those who had an income of 100% to 199% of the federal poverty level (FPL) were more likely to have delayed care for any reason, while that association was not significant for respondents with disabilities at any other FPL. Respondents with disabilities at 100% to 199% of the FPL were more likely to have Medicare only than any other group (45.6% of this group have Medicare only, vs. <40% of every other FPL level). They were also significantly less likely to have private coverage than individuals at 200% or more of the FPL (41.5% vs. 58.0% of individuals with disabilities at 200%–399% of FPL and 62.1% of individuals with disabilities at 400%+ of FPL).

Discussion

Timely medical care is crucial for the health of older adults, many of whom manage chronic conditions (Jacobzone, 2000; Neri & Kroll, 2003). Our findings provide evidence that for older adults, access to timely health care is associated with disability status and living arrangements. Although the sample is almost universally insured, we found that one in 10 older adults without disabilities and nearly one in five older adults with disabilities experienced at least one barrier to care in the past 12 months. This suggests that factors beyond having health insurance create barriers to health care, and that the experience of accessing care differs by disability status. Our results also suggest that not all living arrangements are equally supportive in facilitating access to care, and that the relationship between household composition and delayed care varies by disability status. In particular, in the full sample we find that older adults living alone or with non-spousal others were more likely to experience delayed care due to cost and lack of transportation than older adults living with a spouse only. In fact, the risk of delayed care due to lack of transportation was highest among respondents living with non-spousal others, indicating that shared resources within a household are not always sufficient to meet the needs of older adults.

There are myriad programmatic and policy levers that can be used to alleviate these barriers. High health care costs reflected through premiums, co-pays, and out-of-pocket expenditures in the Medicare program, for instance, may deter some enrollees from maintaining regular screenings and provider visits (Davis, Stremikis, Doty, & Zezza, 2012). In addition, loss of a driver’s license or limited access to affordable public or non-emergency medical transportation may be particular barriers to older adults living alone. Transportation policies should take into consideration the health care needs of older adults, especially as state and local governments conduct urban planning evaluations and expand public transportation systems. Interestingly, older adults living alone faced lower odds of delayed care due to difficulty making a timely appointment than those living with a spouse. This may be suggestive of time constraints on older adults living with a spouse, especially if they are providing care to a spouse with disabilities.

Differences in Access to Care by Disability Status

In subgroup analyses, older adults living alone with disabilities had higher odds of experiencing any delayed care, compared with their counterparts living with a spouse. For older adults living alone without disabilities, there was no difference in the overall odds of delayed care, compared with older adults without disabilities living with a spouse. This suggests a particular disadvantage for older adults with disabilities who live alone that does not exist for older adults without disabilities who live alone; this should concern policy makers. Furthermore, living alone in the community may mean different things for older adults, including living in congregate housing sites or independent living. Future research should examine heterogeneity in the experience of older adults living alone. In addition, while we do not do so in this article, it would be useful to investigate how differences in access to care vary by disability status of spousal units, comparing couples where one spouse has a disability with couples where both spouses have a disability. In particular, future research should investigate whether there is still better access for spousal couples where both have a disability and if not, why not? This knowledge would be useful in suggesting policy implications for these situations, such as scheduling appointments at the same time or doubling up on resources in other ways.

In addition to overall differences in delayed care, we found differences in the experience of specific barriers to care by household composition and disability status. While these findings were relatively consistent by disability status for delayed care due to cost or lack of transportation, only older adults without a disability who were living alone experienced lower odds of delayed care due to difficulty making a timely appointment. The finding about lack of transportation suggests limited resources for those without a spouse or partner, regardless of disability status. While older adults with disabilities may require specialized transportation to travel to the doctor’s office, the robustness of this finding to disability status suggests that transportation concerns go beyond issues of physical accessibility. The finding about making a timely appointment reinforces the notion that older adults living alone are less likely to face time constraints and may have more flexible schedules than older adults living with a spouse, but that this only applies to older adults without disabilities. Older adults with disabilities who live alone may require more frequent health care visits, so they may not have the ability to wait for an appointment, regardless of their household composition. In addition, individuals with disabilities spend more time on health-related activities in general (Anand & Ben-Shalom, 2014), so it makes sense that they may face time constraints in trying to fit in additional health care visits.

Study Limitations

While this study provides important contributions to the literature on access to care, the findings are subject to several data limitations. First, the data are cross-sectional, so we were not able to make causal inferences between living arrangements, disability, and access to care. Second, our disability measure is broad, but we believe that an expansive definition is useful in capturing the diverse nature of disability among older adults. A third limitation relates to our measure of access to care. Our measures of delayed care are also broad, defining delayed care as a binary experience of ever versus never experiencing delays in the past 12 months. In addition, there may be recall bias in reporting delayed care in the previous 12 months, especially for adults with a cognitive disability. To the extent that there is error in reporting delayed medical care, our findings might underestimate the true prevalence of delayed care. While the measure we use is comparable with those used in previous studies (Chevarley et al., 2006; Hyde & Livermore, 2014), future research should collect more detailed measures that capture a broader range of experiences related to accessing care.

The data preclude knowing the exact nature of particular living arrangements, including limited information on housing type (e.g., no way to specify assisted living facilities) and limited information on household composition for respondents living with others. The sample was restricted to non-institutionalized individuals; however, it is not possible to clearly identify types of community-based congregate housing sites. Furthermore, while we can identify with whom older adults live and what their relationship is to the household head, there was limited information on other relationships within the household. This is a particular problem in determining whether the older adult was providing or receiving care within the household, both of which could affect access to care. Similarly, the data are limited to household-level information and do not provide information on whether the older adult has children or other family and friends nearby who may provide care to, or receive care from, the older adult. Finally, the data do not include measures of metropolitan status, although there are likely urban/rural differences in the relationship between household composition and access to care.

Despite these limitations, this study provides insight into how disability status and household composition affect specific barriers to care for older adults. Policies have made it increasingly possible for older adults with disabilities to age in the community. Partly owing to this fact, patterns of living arrangements for older adults have changed in recent decades, with a growing number of older adults living alone or in multigenerational households and a decline in the use of nursing homes or other institutionalized settings (Redfoot & Hauser, 2010; Taylor et al., 2010). Within community-dwelling arrangements, older adults are often acting as caregivers (e.g., for spouses or grandchildren) and are receiving care themselves (e.g., from spouses and adult children; Institute of Medicine [IOM], 2008). Despite evidence of these changing patterns and complex roles, there is limited research on how disability status and household composition together affect health services use, and this study addressed that gap in the literature.

Policy Implications

Our findings have implications for existing disability policies that intersect with home and community-based services (HCBS) settings, for health care providers that serve older adults with disabilities as their patient base, and for funding and policy change. A number of state and federal programs aim to help older adults with disability age in place. For example, Money Follows the Person aims to provide greater coordination of housing, community living, and social supports for older adults to age in the community. Our findings could help target consumers especially at risk for not getting the services they need based on their combination of living arrangement and disability profile. Also, as part of the Affordable Care Act (ACA) funding for expanded HCBS options, Aging and Disability Resource Centers (ADRCs), and Centers for Independent Living (CILs) provide information and referrals related to community living, transportation, social participation, and employment opportunities for older adults with disabilities. Several states are using CILs and peer mentors to support consumers in navigating complex housing and community living systems and programs. Such programs could be especially helpful for older adults with disabilities living alone or older adults living with others who also have disabilities themselves. Our findings could be informative for these and similar programs about the role of living arrangements in shaping the needs of older adults with disabilities. Also, ADRCs can be more proactive when working with older adults with disabilities who live alone by actively trying to address the barriers identified in our study (e.g., contacting health care providers about transportation and scheduling) and by educating older adults about their rights to accessible care under federal law.

Second, health care providers who work with older adults with disabilities may benefit from greater knowledge about the complex interplay between living arrangements and disability for accessing care. Steps could be taken to increase provider awareness of accessibility issues in the clinical environment and to help them become familiar with the social service systems that serve the needs of older adults (e.g., agencies that provide transportation). Health professionals could be essential in ensuring that older adults with disabilities who match the risk profile (e.g., live alone or live with others) know about transportation options or get extra help with scheduling for the next appointment while still in the office. Thus, improving provider knowledge about barriers to care faced by individuals with disabilities as a function of their living arrangements and training them to better communicate with these patients so they can effectively assess their needs could be instrumental in reducing some of the disparities identified in this study.

Finally, our findings have implications for federal funding and policy. Federal investments in medical homes are a promising step toward improving access to care and coordination of care for older adults living with disabilities (Starfield & Shi, 2004). Whenever possible, health centers providing coordinated and comprehensive health care and social services should be built in centrally located areas accessible by public transportation. Finally, health center policies could include more flexible office hours and home visits to accommodate time and transportation constraints of individuals who are caring for others. Furthermore, respite care services for caregivers may allow older adults caring for others to take time to attend to their own health care needs (Schultz & Martire, 2004).

Conclusion

Our findings provide evidence that disability status and living arrangements together affect timely access to medical care. Older adults with disabilities were more likely to experience each barrier to care studied. Regardless of disability status, older adults who lived alone and with non-spousal others were more likely to report barriers to care related to cost and lack of transportation compared with those with a spouse. Meanwhile, older adults without disabilities who lived alone were less likely to experience barriers related to scheduling, compared with their counterparts living with a spouse.

As states implement a wide variety of home- and community-based service expansions (Harrington, Ng, Laplante, & Kaye, 2012), policy makers and health care providers should consider social and structural measures to reduce barriers to seeking medical care. Currently, a key assumption of the policy shift away from institutional care is that informal caregivers, often co-resident spouses, will provide the bulk of care to older adults with disabilities. This assumption leaves older adults living alone, without co-resident caregivers, especially vulnerable to structural and financial barriers to care. Future research should examine differences in health status and health service use by disability status for older adults who live alone. Given the growing population and health care needs of older adults and the focus on aging in the community for individuals with disabilities, the need for research, policy, and programmatic attention to the interplay between these issues has never been more urgent.

Footnotes

Authors’ Note

An earlier version of this article was presented at the March 4, 2014 Minnesota Health Services Research Conference, St. Paul, Minnesota, where it won First Place in the Student Paper Competition, and as a podium presentation at the Academy Health Annual Research Meeting on June 10, 2014 in San Diego, California.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This manuscript was supported by the Integrated Health Interview Series project at the Minnesota Population Center (NIH Grants R01HD046697 and R24HD041023), funded through grants from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD) and by the Interdisciplinary Doctoral Fellowship from the University of Minnesota.

Notes

References

AARP Public Policy Institute. (2010). Housing policy solutions to support aging in place. Washington, DC: Author.

Aday

L. A.

Anderson

(1974). A framework for the study of access to medical care. Health Services Research, 9, 208–220.

Administration on Aging. (2012). A profile of older Americans: 2012. Washington, DC: U.S. Department of Health and Human Services.

Altman

Bernstein

(2008). Disability and health in the United States, 2001–2005. Hyattsville, MD: National Center for Health Statistics.

Anand

Ben-Shalom

(2014). How do working-age people with disabilities spend their time? New evidence from the American Time Use Survey. Demography, 51, 1977–1998.

Chevarley

F. M.

Thierry

J. M.

Gill

C. J.

Ryerson

A. B.

Nosek

M. A.

(2006). Health, preventive health care, and health care access among women with disabilities in the 1994–1995 National Health Interview Survey, supplement on disability. Women’s Health Issues, 16, 297–312.

Compton

Pollak

R. A.

(2013). Proximity and coresidence of adult children and their parents in the United States: Description and correlates (IZA Discussion Paper No. 7431). Bonn, Germany: Institute for the Study of Labor.

Davis

Stremikis

Doty

M. M.

Zezza

M. A.

(2012). Medicare beneficiaries less likely to experience cost- and access-related problems than adults with private coverage. Health Affairs (Project Hope), 31, 1866–1875.

Drainoni

Lee-Hood

Tobias

Bachman

S. S.

Andrew

Maisels

(2006). Cross-disability experiences of barriers to health-care access. Journal of Disability Policy Studies, 17, 101–115.

10.

Fields

N. L.

Anderson

K. A.

Dabelko-Schoeny

(2011). Ready or not: Transitioning from institutional care to community care. Journal of Housing for the Elderly, 25(1), 3–17.

11.

Freedman

V. A.

Spillman

B. C.

Andreski

P. M.

Cornman

J. C.

Crimmins

E. M.

Kramarow

. . . Waidmann

T. A.

(2013). Trends in late-life activity limitations in the United States: An update from five national surveys. Demography, 50, 661–671.

12.

Gulliford

Figueroa-Munoz

Morgan

Hughes

Gibson

Beech

Hudson

(2002). What does “access to health care” mean? Journal of Health Services Research & Policy, 7, 186–188.

13.

Harrington

Laplante

Kaye

H. S.

(2012). Medicaid home- and community-based services: Impact of the Affordable Care Act. Journal of Aging & Social Policy, 24, 169–187.

14.

Henning-Smith

(2016). Quality of life and psychological distress among older adults: The role of living arrangements. Journal of Applied Gerontology, 35, 39–61. doi:10.1177/0733464814530805

15.

Henning-Smith

McAlpine

Shippee

Priebe

(2013). Delayed and unmet need for medical care among publicly insured adults with disabilities. Medical Care, 51, 1015–1019.

16.

Hyde

J. S.

Livermore

G. A.

(2016). Gaps in timely access to care among workers by disability status: Will the patient protection and affordable care act reforms change the landscape? Journal of Disability Policy Studies, 26, 221–231. doi:10.1177/1044207314542005

17.

Institute of Medicine. (2008). Retooling for an aging America: Building the healthcare workforce. Washington, DC: National Academies Press.

18.

Jacobzone

(2000). Coping with aging: International challenges. Health Affairs (Project Hope), 19, 213–225.

19.

Johnson

R. W.

Wiener

J. M.

(2006). A profile of frail older Americans and their caregivers. Washington, DC: Urban Institute.

20.

Karaca-Mandic

Norton

E. C.

Dowd

(2012). Interaction terms in nonlinear models. Health Services Research, 47(1, Pt. 1), 255–274.

21.

Keene

J. R.

Batson

C. D.

(2010). Under one roof: A review of research on intergenerational coresidence and multigenerational households in the United States. Sociology Compass, 4, 642–657.

22.

Langa

K. M.

Chernew

M. E.

Kabeto

M. U.

Katz

S. J.

(2001). The explosion in paid home health care in the 1990s: Who received the additional services? Medical Care, 39, 147–157.

23.

Lau

D. T.

Kirby

J. B.

(2009). The relationship between living arrangement and preventive care use among community-dwelling elderly persons. American Journal of Public Health, 99, 1315–1321.

24.

Martin

L. G.

Freedman

V. A.

Schoeni

R. F.

Andreski

P. M.

(2010). Trends in disability and related chronic conditions among people ages fifty to sixty-four. Health Affairs (Project Hope), 29, 725–731.

25.

Minnesota Population Center and State Health Access Data Assistance Center. (2012). Integrated Health Interview Series: Version 5.0. Minneapolis: University of Minnesota.

26.

National Center for Health Statistics. (2013). Health, United States: 2012: With special features on emergency care. Hyattsville, MD: Author.

27.

Neri

M. T.

Kroll

(2003). Understanding the consequences of access barriers to health care: Experiences of adults with disabilities. Disability and Rehabilitation, 25(2), 85–96.

28.

Parish

S. L.

Saville

A. W.

(2006). Women with cognitive limitations living in the community: Evidence of disability-based disparities in health care. Mental Retardation, 44, 249–259.

29.

Penchansky

Thomas

J. W.

(1981). The concept of access: Definition and relationship to consumer satisfaction. Medical Care, 19, 127–140.

30.

Ramirez

Farmer

G. C.

Grant

Papachristou

(2005). Disability and preventive cancer screening: Results from the 2001 California Health Interview Survey. American Journal of Public Health, 95, 2057–2064.

31.

Redfoot

D. L.

Hauser

(2010). More older people with disabilities living in the community: Trends from the national long-term care survey, 1984–2004. Washington, DC: AARP Public Policy Institute.

32.

Rogers

R. G.

(1996). The effects of family composition, health, and social support linkages on mortality. Journal of Health and Social Behavior, 37, 326–338.

33.

Rosner

T. T.

Namazi

K. H.

Wykle

M. L.

(1988). Physician use among the old-old: Factors affecting variability. Medical Care, 26, 982–991.

34.

Roy

A. W.

FitzGibbon

P. A.

Haug

M. M.

(1996). Social support, household composition, and health behaviors as risk factors for four-year mortality in an urban elderly cohort. Journal of Applied Gerontology, 15, 73–86.

35.

Scheer

J. M.

Kroll

Neri

M. T.

Beatty

(2003). Access barriers for persons with disabilities: The consumer’s perspective. Journal of Disability Policy Studies, 14, 221–230.

36.

Schultz

Martire

L. M.

(2004). Family caregiving of persons with dementia: Prevalence, health effects, and support strategies. The American Journal of Geriatric Psychiatry, 12, 240–249.

37.

Starfield

Shi

(2004). The medical home, access to care, and insurance: A review of the evidence. Pediatrics, 113(Suppl.), 1493–1498.

38.

Taylor

Passel

Fry

Morin

Wang

Velasco

Dockterman

(2010). The return of the multi-generational family household. Washington, DC: Pew Research Center.

39.

Thorpe

J. M.

Van Houtven

C. H.

Sleath

B. L.

(2009). Barriers to outpatient care in community-dwelling elderly with dementia: The role of caregiver life satisfaction. Journal of Applied Gerontology, 28, 436–460.

40.

Trani

J.-F.

Browne

Kett

Bah

Morlai

Bailey

Groce

(2011). Access to health care, reproductive health and disability: A large scale survey in Sierra Leone. Social Science & Medicine, 73, 1477–1489.

41.

Veltman

Stewart

D. E.

Tardif

G. S.

Branigan

(2001). Perceptions of primary healthcare services among people with physical disabilities: Part 1. Access issues. MedGenMed: Medscape General Medicine, 3(2), 18.

42.

Wisdom

J. P.

McGee

M. G.

Horner-Johnson

Michael

Y. L.

Adams

Berlin

(2010). Health disparities between women with and without disabilities: A review of the research. Social Work in Public Health, 25, 368–386.