Comparison of Healthcare Utilization Between Informal Caregivers and Non-Caregivers: An Analysis of the Health Information National Trends Survey

Abstract

Objective: The demands of providing unpaid care for someone with a disabling health condition (i.e., informal caregiving) can limit attention to one’s own health needs. Using a nationally representative survey, this study examines whether caregivers report different healthcare utilization relative to non-caregivers. Method: Participants in the Health Information National Trends Survey 5, Cycle 1 reported whether they provided unpaid care and healthcare utilization outcomes. Logistic regressions and chi-square tests with jackknife variance estimation were used. Results: Caregivers (N = 391) did not differ from non-caregivers (N = 2,894) in time since routine checkup or number of healthcare appointments in the past year (p values > .25). Among caregivers, number of healthcare appointments differed according to caregivers’ relationship to the care recipient (p = .04). Discussion: Findings suggest that informal caregivers access routine healthcare at a frequency similar to non-caregivers. Further research should determine whether this utilization is optimal, or whether increased utilization during caregiving might help attenuate caregivers’ longer term morbidity.

Keywords

caregivers health services accessibility caregiving burden

Introduction

More than 43 million Americans provided uncompensated care to close individuals (e.g., family members or close friends) with serious physical health conditions in 2015 (National Association for Caregiving [NAC] & AARP, 2015). This often-unrecognized care provided by these informal caregivers provides patients with essential emotional, practical, and medical care and is critical to the sustainability of the U.S. health care system (Reinhard, Feinberg, Choula, & Houser, 2015). The caregiving role, however, often places significant strain on caregivers and increases their risk for developing physical and mental health conditions (Buyck et al., 2013; Ji, Zöller, Sundquist, & Sundquist, 2012; Shaffer, Kim, Carver, & Cannady, 2017b). Routine and appropriate access to healthcare may help attenuate the distress and premature physical morbidity observed among informal caregivers (Bass, Noelker, & Rechlin, 1996).

At a population level, the prevalence rates of serious health conditions are higher among individuals with a caregiving history, including a higher rate of cerebrovascular and cardiovascular diseases (Buyck et al., 2013; Ji et al., 2012). Psychoneuroimmunological research has demonstrated pro- and anti-inflammatory dysregulation among informal caregivers that can last for years, even after their caregiving responsibilities conclude (Kiecolt-Glaser et al., 2003; Rohleder, Marin, Ma, & Miller, 2009). Distressed and spousal caregivers appear at highest risk for developing physical health problems (Kim, Carver, Shaffer, Gansler, & Cannady, 2015; Schulz & Beach, 1999; Shaffer, Kim, Carver, & Cannady, 2017a; Shaffer et al., 2017b). Despite these risks, caregivers report multiple practical and psychological barriers that interfere with their ability to access appropriate healthcare services, frequently including scheduling difficulty, limited time, and prioritizing patients’ needs above their own (Applebaum, Farran, Marziliano, Pasternak, & Breitbart, 2014; Shaw et al., 2013). In addition, caregivers have previously been shown to be more likely to lack health insurance coverage compared with non-caregivers due to caregiving-associated employment disruptions (Ho, Collins, Davis, & Doty, 2005).

Other research suggests that, given the demanding nature of caregiving, healthier individuals may be more likely to “select in” to caregiving responsibilities, detailed by the “healthy caregiver hypothesis” (Fredman, Doros, Ensrud, Hochberg, & Cauley, 2009). Indeed, physically healthier individuals are more likely on average to take up and persist with caregiving responsibilities (McCann, Hebert, Bienias, Morris, & Evans, 2004). Some epidemiological research suggests caregivers may even report extended longevity compared with non-caregivers (Fredman, Lyons, Cauley, Hochberg, & Applebaum, 2015; Roth, Fredman, & Haley, 2015; Roth et al., 2013). However, other population-based surveys across Europe have found that, while caregivers who do not reside with the care recipient are generally healthy with milder effects to their long-term health, caregivers who co-reside with the care recipient (and likely have less choice in assisting with care) are in poorer health and experience more health decline over the course of caregiving (Kaschowitz & Brandt, 2017).

Findings among extant literature about healthcare utilization among informal caregivers have been mixed. Large population-based surveys have alternatively reported higher outpatient healthcare (Chan, Malhotra, Malhotra, Rush, & Østbye, 2013) and mental healthcare (Cochrane, Goering, & Rogers, 1997) usage among caregivers relative to non-caregivers, while others have suggested no differences in healthcare utilization (George & Gwyther, 1986). Studies using matched samples similarly find conflicting results: higher utilization (Haley, Levine, Brown, Berry, & Hughes, 1987), no differences (Baumgarten et al., 1997; Bigatti & Cronan, 2002; Burton, Newsom, Schulz, Hirsch, & German, 1997; Kiecolt-Glaser et al., 1987), or lower utilization (Pruchno & Potashnik, 1989) in caregivers relative to demographically comparable non-caregivers. Another study suggests that healthcare utilization is suboptimal particularly among women who are actively providing care, but that their utilization normalized several years after caregiving responsibilities concluded (Zwart, Bakx, & Doorslaer, 2017). Much of this work has been conducted among samples of caregivers exclusively for people with dementia (Bremer et al., 2015; George & Gwyther, 1986; Haley et al., 1987; Kiecolt-Glaser et al., 1987; Pruchno & Potashnik, 1989), who experience particularly high-burden and chronic caregiving. Moreover, much of this work has had methodological limitations, including inadequate sample sizes, lack of confounder control, and sociodemographically homogeneous samples (Baumgarten, 1989; Roth et al., 2013).

As such, the current study sought to address these limitations of and discrepancies within the literature by using a large, nationally representative dataset that includes a broad range of potential barriers and facilitators to healthcare utilization among informal caregivers and non-caregivers. In addition to addressing limitations observed in previous studies, this is the first study to compare healthcare utilization among caregivers and non-caregivers since the passage of the Affordable Care Act (ACA; The Patient Protection and Affordable Care Act, 2010). The ACA provided an opportunity for those who may have been previously uninsured, such as caregivers (Ho et al., 2005), to gain access to healthcare, and is responsible for drastically increasing healthcare coverage in the United States: Within 1 year of the ACA taking effect, there was an approximately 8% increase in insurance coverage (Sommers, Gunja, Finegold, & Musco, 2015), 12 million fewer uninsured Americans in 2014 alone as a direct result of the ACA (Blumenthal & Collins, 2014). Consequently, passage of the ACA may have decreased the healthcare coverage gap between caregivers and non-caregivers, potentially affecting healthcare access and utilization. In the present study, it was first tested whether caregivers differed from non-caregivers in time since their last routine checkup or total number of healthcare appointments attended in the past year. It was next examined whether factors about the caregiving experience affect these measures of healthcare utilization.

Method

Study Design and Participants

The Health Information National Trends Survey (HINTS), 2017 (Nelson et al., 2004) Version 5, Cycle 1 is a nationally representative survey of civilian, non-institutionalized adults aged 18 and older in the United States. Conducted by the National Cancer Institute (NCI), this survey assesses Americans’ access to and use of health information. HINTS was reviewed and approved by the Institutional Review Boards of NCI’s Special Studies and the main contractor (Westat, Inc.). Additional methodology details may be found in the HINTS 5 methodology report (https://hints.cancer.gov/docs/methodologyreports/HINTS5_Cycle_1_Methodology_Rpt.pdf).

As described in the HINTS methodology report, the sampling frame comprised non-vacant residential addresses in the United States. Two sampling strata divided sampling frames of addresses according to areas with high concentrations of Hispanic and African American individuals versus low concentrations, according to data from Census tracts-level characteristics from the 2011-2015 American Community Survey. Surveys were distributed by mail between January 2017 and May 2017. Surveys were mailed using a modified Dillman approach (Dillman et al., 2009): All households selected for inclusion in the sample received an initial mailing and a reminder postcard; non-responding households received up to two additional follow-up mailings. A Spanish version of the questionnaire was provided to households registered with a Hispanic surname. To maximize the response rate, a prepaid incentive was provided with the first mailing, multiple non-response follow-ups were made, and one of the non-response follow-ups utilized express delivery.

HINTS 5, Cycle 1 is the first HINTS survey to systematically assess caregiving status and related information. Informal caregivers self-identified as a caregiver for an adult by answering affirmatively to the item: “Are you currently caring for or making health care decisions for someone with a medical, behavioral, disability, or some other condition?” Informal caregiving surveys typically focus on informal care provided to individuals 18 years of age and older given the anomalous, age-discordant nature of this caregiving experience (e.g., AARP & Project Catalyst, 2016; NAC & AARP, 2015). As such, for the current analysis, 189 participants exclusively reporting caregiving for a child were not included, resulting in a final caregiver sample size of 391.

Measures

The specific wording of all measures reported in this study may be found at https://hints.cancer.gov/docs/Instruments/HINTS5_Cycle1_Annotated_Instrument_English.pdf.

Healthcare utilization

Participants indicated the time since their last routine checkup. A “routine checkup” was defined in the survey as “a general physical exam, not an exam for a specific injury, illness, or condition.” Responses were “Within the past year,” “1-2 years ago,” “3-5 years ago,” “More than 5 years ago,” “Never,” and “Don’t know.” Responses for 1-2, 3-5, and 5 or more years ago were collapsed for the present analyses (i.e., received last routine checkup 1 or more years ago). For both caregiver and non-caregiver samples, fewer than 2% of participants responded “Never” or “Don’t know”; as such, these responses were excluded from the current analyses.

Participants also indicated their number of healthcare visits in the past year. A “health care visit” was defined in the survey as “not counting times you went to an emergency room, how many times [you went] to a doctor, nurse, or other health professional to get care for yourself.” Responses were “None,” “1 time,” “2 times,” “3 times,” “4 times,” “5-9 times,” and “10 or more times.” For the present analyses, responses for 1 and 2 times were collapsed (i.e., 1-2 visits in past year), as were responses for 3, 4, 5-9, and 10 or more times (i.e., 3 or more visits).

Caregiving factors

Caregivers reported their relationship to the care recipient (if caring for a single care recipient) or whether they cared for multiple care recipients. Caregivers also reported the number of conditions affecting the care recipient and number of hours spent caregiving per week (response options were “less than 5 hr per week,” “5-14 hr per week,” “15-20 hr per week,” “21-34 hr per week,” and “35 or more hr per week”). Responses for 5-14 hr, 15-20 hr, and 21-34 hr were collapsed (i.e., 5-34 hr per week).

Covariates

Participants reported their age, gender, occupational status, marital status, and education. Rurality of the participants’ address was determined according to the National Center for Health Statistics Urban-Rural Classification Scheme for Counties. Participants also reported whether they had health insurance; their perceived general health; whether a doctor had ever diagnosed them with diabetes, hypertension, a heart condition, lung disease, arthritis, depression, or anxiety; level of distress (using the Patient Health Questionnaire [PHQ]-4 [Löwe et al., 2010] sum score); whether they had at least one person available to provide them emotional support or practical support if needed; number of days engaging in any moderate or vigorous physical activity; and whether they had a smoking history.

Analytic Strategy

All analyses accounted for the complex sampling design of the HINTS survey by using the full-sample weights provided in the public use datasets, yielding nationally representative estimates. Jackknife variance estimation with repeated replications was used to estimate standard errors, reducing estimate bias, and, therefore, risk of Type I error. These procedures are in accordance with published HINTS analysis recommendations (NCI, 2017). Alpha of .05 was used to determine significance for all tests.

To test whether caregiver status was associated with healthcare utilization variables, logistic regression analyses using SAS 9.4 SURVEYREG were used. Binary logistic regression was used for time since last checkup (past year vs. 1 or more years ago); multinomial logistic regression was used for number of healthcare visits in past year (1-2 times vs. 3 or more times or none). Covariates were added in sequential blocks: First, only caregiving status was included as a predictor. Next, demographic covariates were added to the model (age, gender, occupational status, marital status, education, rurality, born in the United States). Then, general health covariates were added (health insurance, general health, diabetes, hypertension, heart disease, lung disease, arthritis). Last, psychosocial covariates were added (depression/anxiety, distress, emotional support, practical support, physical activity, smoking history). With the given sample size and alpha, and adjusting for design effect and survey weighting, the minimally detectable odds ratios (minimum if Odds Ratio [OR] > 1; maximum if OR < 1) with 80% power for time since last checkup would be 1.76 or 0.53, for 1-2 healthcare appointments versus 3 or more would be 1.82 or 0.56, and for 1-2 healthcare appointments versus none would be 2.14 or 0.42.

For comparing healthcare utilization outcomes with caregiving factors, chi square tests of independence with SAS 9.4 SURVEYFREQ were used. In the event of a significant (p = .05) comparison for tests with more levels than 2 × 2, follow-up analyses were planned as follows: For healthcare appointments, 1-2 times would be compared versus 3 or more times and none, in keeping with the multinomial logistic regression comparisons. For caregiving factors, those caring for spouses only would be compared versus the other caregiving relationships, and caregivers reporting providing care for 35 hr or more would be compared with those caring for fewer hours. These reference categories were chosen due to their noted relationship with poorer caregiver health (Pinquart & Sörensen, 2007).

Results

Of 13,360 surveys mailed, 3,285 valid surveys were returned. As further described in the HINTS methodology report, the response rate was 32.4%, as calculated using the RR2 formula of the American Association of Public Opinion Research and weighting for oversampling in high-minority areas. Selection weights were calibrated using data from the 2015 American Community Survey to compensate for non-response and coverage error, permitting generalizations of results to the national population. In addition to the full-sample weight, 50 replicate weights were provided to enable delete-one jackknife variance estimation. Sample descriptives are presented in Table 1. On average, relative to non-caregivers, the caregiver sample was older and had a higher proportion of individuals who were female, partnered, and diagnosed with arthritis (p values < .05).

Table 1.

Sample Description.

	Non-caregivers (N = 2,894)n (w%)/M (SD)	Caregivers (N = 391)n (w%)/M (SD)	Difference testχ²(1, 49) or t(3,284)
Demographic factors
Age	46.56 (0.41)	51.80 (1.24)	3.05**
Gender (Female)	1,662 (49.9)	252 (60.8)	6.37**
Occupational Status (Employed)^a	1,423 (59.2)	166 (51.4)	3.62
Marital Status (Partnered)^b	1,495 (53.9)	256 (65.8)	8.79**
Education (High school or less)	747 (31.9)	86 (29.2)	0.52
Rurality (Metropolitan)	2,518 (86.0)	330 (84.5)	0.23
Born in the United States (Yes)	2,433 (85.7)	327 (84.7)	0.15
General health factors
Health Insurance (Yes)	2,719 (91.6)	370 (92.8)	0.17
General Health (Fair/Poor)	517 (16.9)	68 (17.9)	0.08
Diabetes (Yes)	582 (17.1)	79 (20.6)	0.96
Hypertension (Yes)	1,286 (37.5)	174 (39.0)	0.15
Heart Condition (Yes)	295 (7.8)	30 (8.7)	0.16
Lung Disease (Yes)	376 (11.2)	52 (13.4)	0.81
Arthritis (Yes)	873 (22.3)	135 (29.8)	5.85*
Psychosocial factors
Depression/Anxiety (Yes)	620 (22.4)	110 (29.2)	2.98
Distress^c	2.02 (0.10)	2.46 (0.30)	1.80
Emotional Support (Yes)	2,503 (87.5)	322 (84.6)	1.31
Practical Support (Yes)	2,269 (82.6)	290 (78.3)	1.99
Physical Activity Days Per Week (0)	801 (25.4)	104 (27.9)	0.43
Smoking History (<100 cigarettes)	1,755 (62.7)	230 (55.6)	2.56

Note. Columns present weighted percentages (w%) or means and standard deviations. Difference test compares Non-caregivers and Caregivers.

“Not Employed” comprises positive responses to unemployed, homemaker, student, retired, disabled, and other.

“Partnered” comprises responses to married, living as married; “Not partnered” comprises responses to divorced, widowed, separated, single.

Patient Health Questionnaire-4 sum score.

p < .05. *p < .01.

Caregiver Status and Healthcare Utilization Variables

Blocked logistic regression analyses indicated that there were no differences between caregivers’ and non-caregivers’ reported time since their last routine checkup, either when testing caregiver status as the only predictor (OR within past year vs. ≥ 1 year ago: 0.97; 95% Confidence Interval [CI] = [0.62, 1.58]) or when sequentially controlling for demographic, general health, or psychosocial covariates (see Table 2 for caregiver status OR and 95% CI).

Table 2.

OR for Caregiver Status Predicting Time Since Last Checkup and Number of Healthcare Appointments in the Past Year.

Model	Time since checkup		Healthcare appointments in past year
	Past year vs. ≥ 1 year(s)		1-2 times vs. none		1-2 times vs. ≥ 3 times
	OR	95% CI	OR	95% CI	OR	95% CI
Caregiver status only (Yes)	0.97	[0.62, 1.58]	1.29	[0.75, 2.23]	1.22	[0.85, 1.74]
Caregiver status + demographic factors	0.77	[0.49, 1.21]	1.55	[0.90, 2.68]	1.20	[0.84, 1.71]
Caregiver status + demographic factors + general health factors	0.82	[0.51, 1.32]	1.37	[0.81, 2.32]	1.20	[0.84, 1.69]
Caregiver status + demographic factors + general health factors + psychosocial factors	0.83	[0.50, 1.36]	1.28	[0.73, 2.22]	1.09	[0.75, 1.56]

Note. OR = odds ratio; CI = confidence interval.

Blocked multinomial regression analyses indicated that there were no differences between caregivers’ and non-caregivers’ reported number of healthcare visits in the past year, either when testing caregiver status as the only predictor (OR 1-2 visits vs. ≥ 3 visits: 1.22; 95% CI = [0.85, 1.74]; OR 1-2 visits vs. no visits: 1.29; 95% CI = [0.75, 2.23]) or when sequentially controlling for demographic, general health, or psychosocial covariates (see Table 2).

Caregiving Factors and Healthcare Utilization

Examining caregivers only, time since last checkup was not associated with caregiving factors (p values > .36; see Table 3). Caregivers’ number of healthcare appointments in the past year was not associated with number of caregiving hours per week (p = .81) or number of conditions affecting the care recipient (p = .87).

Table 3.

Caregiving Factors Associated with Caregivers’ Healthcare Utilization.

	Time since checkup		Healthcare appointments in past year
	Past year n (w%)	≥1 year(s) n (w%)	1-2 times n (w%)	≥3 times n (w%)	None n (w%)
Relationship to Care Recipient	F(6, 49) = 1.13, p = .36		F(6, 49) = 2.37, p = .04
Other person only	56 (68.2)	23 (31.8)	19 (17.1)	51 (66.9)^a	12 (16.1)
Multiple recipients	25 (75.0)	5 (25.0)	9 (37.2)	16 (37.8)	7 (25.0)
Parent only	118 (61.5)	34 (38.5)	63 (36.1)	72 (39.0)	20 (24.9)
Spouse only	97 (80.7)	21 (19.3)	44 (43.2)	63 (46.4)	11 (10.4)
Hours Caregiving/Week	F(2, 49) = 0.98, p = .38		F(4, 49) = 0.39, p = .81
Less than 5	103 (74.9)	28 (25.1)	44 (34.4)	71 (44.4)	20 (21.3)
5 to less than 35	112 (63.6)	32 (36.4)	56 (36.7)	76 (44.2)	13 (19.1)
≥35 or more	60 (76.7)	18 (23.3)	24 (32.1)	44 (53.7)	13 (14.1)
Care Recipient Conditions	F(2, 49) = 0.36, p = .55		F(2, 49) = 0.14, p = .87
Single condition	100 (72.9)	29 (27.1)	42 (36.1)	67 (43.6)	24 (20.3)
Multiple conditions	184 (68.7)	49 (31.3)	87 (35.0)	126 (47.4)	23 (17.6)

Note. Columns present weighted percentages (w%).

Post hoc pairwise tests revealed that, compared with caregivers for a spouse only, caregivers for another person only were more likely to report 3 or more healthcare appointments (vs. 1-2 healthcare appointments) in the past year (p = .005).

The caregivers’ relationship to the care recipient was associated with number of healthcare appointments (p = .04). To explain this relationship, we completed planned post hoc analyses. There were differences between the caregiver relationship types with the likelihood of reporting 1-2 appointments versus 3 or more appointments, F(3, 49) = 3.06, p = .04, but not versus no appointments, F(3, 49) = 2.42, p = .08. Further analysis compared caregivers reporting providing care to a spouse only versus caregivers reporting providing care to another individual or multiple individuals: Compared with caregivers for a spouse only, individuals caring for a care recipient of a different relationship were more likely to endorse having 3 or more appointments in the past year than 1-2 appointments, F(1, 49) = 8.58, p = .005. Caregivers for a spouse only did not differ from caregivers for a parent only F(1, 49) = 0, p = .99, or for multiple care recipients, F(1, 49) = 0.01, p = .93.

Discussion

This analysis of a large, nationally representative survey found no differences in the time since last routine checkup or in the total number of healthcare appointments during the last year between informal caregivers and non-caregivers. These results are the first to compare healthcare utilization metrics between caregivers and non-caregivers in the United States following the passage of the ACA (The Patient Protection and Affordable Care Act, 2010), which significantly increased insurance coverage and access to routine healthcare among Americans. Survey results suggest that more than two thirds of both caregivers and non-caregivers had their last routine checkup within the past year, and more than one third of both caregivers and non-caregivers had one or two appointments in the past year. Notably, these metrics of healthcare utilization also did not tend to differ within caregivers according to different caregiving experience factors.

Findings that recency and frequency of non-emergency healthcare did not differ between caregivers and non-caregivers fit with most prior studies examining this research question (Baumgarten et al., 1997; Bigatti & Cronan, 2002; Burton et al., 1997; George & Gwyther, 1986; Kiecolt-Glaser et al., 1987). Prior literature has suggested a “healthy caregiver effect,” or that healthier individuals may be more prone to choose to take on caregiving compared with less healthy individuals (Fredman et al., 2009; Kaschowitz & Brandt, 2017; McCann et al., 2004; Zwart et al., 2017). To that end, one possibility for the pattern of no differences in healthcare utilization between the caregiver and non-caregiver samples analyzed here may be due to the fact that the caregivers sampled already have optimal healthcare practices to which they adhere regardless of additional demands from caregiving. Or, given that about one in five caregivers reported that their caregiving responsibilities caused them to delay and/or forego medical care (Mazanec, Daly, Douglas, & Lipson, 2011), it is possible that the caregiving sample was previously more engaged with healthcare relative to the general population, and the impacts of caregiving shifted these caregivers’ average engagement to be comparable with non-caregivers. One significant assumption of the healthy caregiver hypothesis, however, is that caregivers predominantly self-select into caregiving, yet about 45% of caregivers perceive they had little choice in becoming a caregiver (Schulz et al., 2012). With those caregivers reporting they were obligated to provide care demonstrating the poorest psychosocial outcomes (Schulz et al., 2012), future research should test the extent to which the healthy caregiver effect may explain caregivers’ healthcare utilization patterns by including assessments related to caregivers’ perceived choice in taking on the responsibility.

Examining patterns of healthcare utilization within caregivers, neither time spent caregiving per week nor number of healthcare conditions affecting the care recipient were associated with their time since last checkup or number of appointments in the past year. These results are at odds with findings from a large survey conducted by Bremer and colleagues across several European countries (Bremer et al., 2015), which demonstrated that more time spent caregiving was associated with increased healthcare utilization among informal caregivers for individuals with dementia. Importantly, however, Bremer and colleagues’ findings also differed substantially across countries, likely due to regional differences in cultural expectations and public policy (Calvó-Perxas et al., 2018). Future examination of the extent to which regional differences in healthcare systems, work-leave policies, politics, and culture affect caregivers’ healthcare utilization and access may highlight important discrepancies in caregivers’ experiences in the U.S. healthcare climate as well. There was a difference detected in the likelihood of attending multiple healthcare appointments in the past year: Compared with caregivers for a spouse only, those who reported a relatively more distant relationship with the care recipient (e.g., sibling, friend) were more likely to have attended three or more healthcare appointments in the past year than one to two appointments. No other differences were detected between healthcare utilization and caregiving relationship. Further research is warranted to determine whether this effect is robust, and, if so, to understand what factors may underlie this association.

An important issue raised with these analyses, and pervasive across caregiving literature (e.g., Kent et al., 2016; Romito, Goldzweig, Cormio, Hagedoorn, & Andersen, 2013), is the issue of adequately defining who constitutes a caregiver. The HINTS survey used definitions from existing authoritative national surveys on caregiving (e.g., NAC & AARP, 2015), yet likely identified a sample of individuals quite diverse in terms of their caregiving experiences. Similarly, the U.S. federal government has defined caregivers as “an adult family member or other individual who has a significant relationship with, and who provides a broad range of assistance to, an individual with a chronic or other health condition, disability, or functional limitation,” with the Senate’s passage of the Recognize, Assist, Include, Support, and Engage (RAISE) Family Caregivers Act of 2017. Definitions from the National Alliance for Caregiving (2015) and the NCI (2012) define caregivers similarly, emphasizing components of helping another individual care for themselves in a broad variety of ways, and that a caregiver may or may not live locally to the care recipient. The National Alliance for Caregiving also specifies that care must be “unpaid,” to differentiate professional from informal caregiving, yet recent initiatives allowing informal family caregivers to receive payment for their role (e.g., Caregivers and Veterans Omnibus Health Services Act of 2010) complicates this criterion. Perhaps most challenging to this issue of defining the caregiving population is that many of the individuals identified by researchers as “caregivers” based on their involvement in a close individual’s care may not self-identify as a caregiver (e.g., Amaro, 2015), but rather that they are fulfilling the spousal or filial responsibilities. Still, there is no singular authoritative definition for informal caregiving, and so it is possible that results from this study differ from prior studies due to variation in the nature of the samples. The significant diversity of experiences and responsibilities contained under the umbrella term of “caregiver” suggest the importance of further research to carefully define these differing caregiving permutations and to examine how different caregiving experiences may be associated with caregivers’ vulnerability for long-term physical health decline.

Regardless, the promising results that caregivers appear to sustain typical engagement with primary healthcare suggest that dissemination of caregiving-related resources via primary care may be an effective way to reach caregivers. Prior studies of primary-care-based interventions support the potential effectiveness of this strategy to improve caregiver well-being, particularly among the most distressed caregivers (Mitchell, Girgis, Jiwa, Sibbritt, & Burridge, 2010; Mitchell et al., 2013). Identifying effective models of care delivery for caregivers is important, not only to improve caregivers’ own well-being, but also to that of patients and, ultimately, to key healthcare system goals (Kent et al., 2016; Longacre, Ridge, Burtness, Galloway, & Fang, 2012).

Strengths and Limitations

Strengths of this study include the use of a large, nationally representative dataset with the ability to control for a broad range of potential confounders; however, the HINTS survey was not designed to specifically address research questions for the current study. Limitations arising from this include the limited assessment of the caregiving experience—for instance, the duration of caregiving was not assessed, which may be pertinent to understanding whether caregiving could have affected time since last checkup. It should be noted, however, that only two caregivers reported caring for a person with an acute condition (e.g., broken bone), while more chronic conditions of dementia, cancer, and aging-related issues were most frequently endorsed. Another limitation of the caregiving assessment is that individuals self-identified as “providing care for or making healthcare decisions for” another close individual. As such, the caregiving sample may comprise a wide range of levels of caregiving responsibilities—from remote healthcare proxies to individuals living with, and providing daily care for, the care recipient. However, our inclusion of caregiving factors helps to differentiate effects between these potentially discrepant caregiving groups. In addition, caregiving assessments that are inclusive of individuals providing a broad range of care tasks provide useful information to inform public health policy or intervention approaches applicable to a large population of heterogeneous caregivers.

There was no measurement of type of healthcare visits utilized—prior studies indicate that although overall, healthcare use may not differ between caregivers and non-caregivers, types of appointments may differ, with caregivers using more mental healthcare services relative to non-caregivers (Baumgarten et al., 1997; Cochrane et al., 1997). In addition, the survey response rate of 32% may limit generalization of findings; however, use of survey weighting helps to limit potential bias in results, and this response rate is comparable with other major surveys of cancer patients and caregivers (e.g., American Cancer Society’s Study of Cancer Survivors-I 34% response rate [Smith et al., 2007]). Last, findings are from a cross-sectional study. A longitudinal study, particularly one that captures healthcare utilization both before and after the caregivers’ assumption of the caregiving role, would be best situated to answer how caregiving alters one’s healthcare utilization, and whether caregivers’ healthcare utilization is optimal.

Conclusion

Overall, there was no evidence for differences in healthcare utilization between informal caregivers and non-caregivers who responded to a national health survey, controlling for a wide variety of potential confounding factors. Future research should examine whether caregivers are accessing adequate mental and physical healthcare to manage their overall health needs, and whether additional preventive care would help mitigate the known health disparities between caregivers and non-caregivers. Given that caregivers appear to sustain routine contact with primary care, disseminating caregiver resources via primary care may represent an effective way to reach caregivers.

Footnotes

Acknowledgements

We gratefully acknowledge the support of Fabian Camacho, MS, MA, for his help conducting power analyses for this article.

Declaration of Conflicting Interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Institutes of Health, National Cancer Institute (T32 CA009461 [Principal Investigator: Jamie Ostroff] and Cancer Center Support Grant P30 CA008748 [Principal Investigator: Craig Thompson]).

ORCID iD

Kelly M. Shaffer

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