Adverse Consequences of Unmet Needs for Care in High-Need/High-Cost Older Adults

Adverse Consequences of Unmet Needs for Care in High-Need/High-Cost Older Adults Abstract Objectives We explore adverse consequences of unmet needs for care among high-need/high-cost (HNHC) older adults. Method Interviews with 4,024 community-dwelling older adults with ADL/IADL/mobility disabilities from the 2011 National Health and Aging Trends Study (NHATS). Reports of socio-demographics, disability compensatory strategies, and adverse consequences of unmet needs in the past month were obtained from older adults with multiple chronic conditions (MCC), probable dementia (DEM), and/or near end-of-life (EOL) and compared older adults not meeting these criteria. Results Older adults with MCC (31.6%), DEM (39.6%), and EOL (48.7%) reported significantly more adverse consequences than low-need older adults (21.4%). Persons with MCC and DEM (53.4%), MCC, and EOL (53.2%), and all three (MCC, DEM, EOL, 65.6%) reported the highest levels of adverse consequences. HNHC participants reported more environmental modifications, assistive device, and larger helper networks. HNHC status independently predicted greater adverse consequences after controlling for disability compensatory strategies in multivariate models. Discussion Adverse consequences of unmet needs for care are prevalent among HNHC older adults, especially those with multiple indicators, despite more disability-related compensatory efforts and larger helper networks. Helping caregivers provide better informal care has potential to contain healthcare costs by reducing hospitalization and unplanned readmissions. Alzheimer’s disease, Caregiving, Death and dying, Disability Introduction Informal caregivers play a critical role in maintaining the health of loved ones who suffer from chronic illness or disability (Schulz & Eden, 2016). While many informal family caregivers adequately meet the needs of disabled or chronically ill older adults, this may not always be the case. There is a growing literature on the prevalence and correlates of unmet needs for help with basic activities of daily living (ADL) and instrumental activities of daily living (IADL) among disabled older adults (Allen & Mor, 1997; DePalma et al., 2013; Desai, Lentzner, & Weeks, 2001; Hass, DePalma, Craig, Xu, & Sands, 2017; He et al., 2015; Kennedy, 2001; Lima & Allen, 2001; Newcomer, Kang, LaPlante, & Kaye, 2005; Sands et al., 2006; Xu, Covinsky, Stallard, Thomas, & Sands, 2012). While prevalence of unmet needs for specific ADL/IADL tasks varies widely, a few early studies using national probability samples found overall prevalence for any unmet need during the past month of approximately 20% (Desai et al., 2001; Kennedy, 2001; Newcomer et al., 2005). A consistent finding across these studies was that higher levels of disability were associated with more unmet needs—the greater the needs for assistance, the less likely they were to be completely met (Allen & Mor, 1997; Desai et al., 2001; Kennedy, 2001; Lima & Allen, 2001; Newcomer et al., 2005). Other correlates of unmet needs included low income/poverty, living alone, minority status, and poor overall health. More recently, research has linked unmet needs with increased risk of hospitalizations (Sands et al., 2006; Xu et al., 2012), hospital re-admissions (DePalma et al., 2013), emergency department admissions, particularly for falls and injuries (Hass et al., 2017), and mortality (He et al., 2015). This article examines adverse consequences of unmet needs for care among older adults with disability form the National Health and Aging Trends Study (NHATS). This contrasts with the literature reviewed above, which examined unmet (or undermet) needs for care, but not specific consequences of unmet need. Existing frameworks in the caregiving literature emphasize functional disability of the patient as a primary driver of caregiver and patient outcomes. Thus, adverse caregiving effects are often attributed to the tasks and time demands associated with the functional disability of the patient (Pearlin, Mullan, Semple, & Skaff, 1990; Pinquart & Sörensen, 2003). More recently, this approach has been augmented by longitudinal perspectives of the caregiving experience which emphasize the cumulative nature of disease and disability and the associated caregiving experience. Over time, caregiving becomes more complex and challenging because of increasing chronic disease burden, disability, and ultimately terminal illness (Schulz & Eden, 2016). This perspective has been further advanced by policy driven approaches which emphasize the need to differentiate between those caregivers and patients who have the greatest need for support, and/or who incur the highest health care costs (Blumenthal & Abrams, 2016; Blumenthal, Chernof, Fulmer, Lumpkin, & Selberg, 2016). This article builds on these approaches by examining adverse consequences of unmet needs for care among high-need, high-cost (HNHC) older adults and the additive effects of meeting multiple high-need, high-cost criteria. We defined high-need/high cost older adults as meeting the following criteria in addition to a functional limitation with at least one ADL/IADL task: (1) patients who have three or more chronic diseases (Hayes et al., 2016); (2) patients with a diagnosis of probable dementia (DEM); and (3) patients at the end of life. Together, these three groups represent some of the highest cost patients in the United States, accounting for the majority of health and long-term care expenditures (Hogan, Lunney, Gabel, & Lynn, 2001; Hurd, Martorell, & Langa, 2013; Kelley, McGarry, Gorges, & Skinner, 2015; Riley & Lubitz, 2010; Schulz et al., 2018). We focus not only on the three types of HNHC older adults in isolation, but we also examine the additive effects of meeting more than one of the three HNHC criteria on adverse consequences of unmet needs for care. The group of older adults with difficulty or needing help with at least one ADL/IADL but not meeting any of the HNHC criteria (i.e., low need) serves as the comparison group. In a series of policy briefs, The Commonwealth Fund has documented HNHC patient socio-demographic characteristics, healthcare spending, and experiences with the healthcare system in the United States. (Hayes et al., 2016; Ryan, Abrams, Doty, Shah, & Schneider, 2016; Salzberg et al., 2016). They found that HNHC patients—defined in their work as having three or more chronic health conditions plus at least one functional limitation—were more likely to be low income, have higher out-of-pocket health costs, more emergency department visits and hospital stays, and more doctor visits and paid home health care days (Hayes et al., 2016). In terms of healthcare experiences, HNHC patients (especially those with private insurance) were more likely to report unmet medical needs and less likely to report good patient-provider communication (Salzberg et al., 2016). Ryan et al. (2016) found that HNHC patients were more likely to be socially isolated and living in poverty and were less likely to experience timely and convenient access to care. HNHC patients were also unlikely to have an informed care coordinator and reported needing more help with ADL/IADL activities (assessed with a single summary question) than they were currently receiving (Ryan et al., 2016). Other research has focused on care management models for HNHC patients, including development and evaluation of programs designed to improve health outcomes and reduce costs (Anderson et al., 2015; Bleich et al., 2015; Blumenthal & Abrams, 2016; Blumenthal et al., 2016; Hong, Siegel, & Ferris, 2014; McCarthy, Ryan, & Klein, 2015). Successful approaches involve specific targeting of HNHC patients for intervention, comprehensive assessment of patient risks and needs, care planning and routine patient monitoring, care coordination and communication among providers and the patient, and facilitation of transitions of care from hospital to home or post-acute care (Anderson et al., 2015; McCarthy et al., 2015). Another recommendation from this work is the promotion of patients’ and family caregivers’ engagement in patient self-care. Family caregivers are critical for fostering patient self-care (Schulz & Eden, 2016). Family members oftentimes serve as liaison between doctors and patients and work with patients to implement care strategies. They can also promote preventative health and influence health behaviors of patients. These efforts may reduce health care costs and utilization by improving patient health. The role of family caregivers in the care of HNHC patients is of central interest in this article. In sum, HNHC patients and older adults are of great concern due to poor health outcomes, high healthcare utilization rates, and resulting high health care costs. Researchers, health care providers, and policy makers are trying to implement evidence-based practices to improve HNHC health outcomes and reduce costs. Other research on unmet needs for ADL/IADL assistance among disabled older adults shows that those who lack the help they need from informal caregivers are also at higher risk for poor health, increased health care utilization, and high costs. Interestingly, some of the same correlates—poverty, social isolation—have been found for HNHC patients and disabled older adults with unmet needs for informal help. In addition, while studies of unmet need are consistent in finding that greater disability is associated with more unmet need—the greater the need, the less likely it is to be fully met—researchers have not explicitly linked HNHC status with unmet ADL/IADL needs in a detailed way. This article adds to the HNHC and unmet needs literature in several ways. It explores in detail explicit linkages between HNHC status and adverse consequences of unmet needs. Second, the analysis includes indicators of disability-related compensatory strategies as potential mediators of adverse consequences of unmet needs, including environmental accommodations, use of mobility devices, paid home caregiver use, and detailed information about informal caregiver network size and composition. These strategies are conceptualized as accommodations in the disability conceptual framework proposed by Freedman (2009), which guided the design of The National Health and Aging Trends Study (NHATS). This article uses NHATS data (see below), which provided detailed assessments of the disability compensation strategies. We hypothesized that HNHC older adults would use more of these strategies and also explore whether environmental accommodations, use of mobility devices, paid home caregiver use, and large informal caregiver networks prevent or reduce (i.e., mediate) adverse consequences of unmet need. Third, we further refine the HNHC construct by focusing on older adults who meet more than one of the three criteria just mentioned—we examine the potential additive effects of combinations of multiple chronic conditions (MCCs), DEM, and end-of-life on use of disability compensatory strategies and adverse consequences of unmet needs. The results of these analyses can further inform the design of interventions for HNHC older adults and caregivers aiming to improve health outcomes and reduce healthcare costs. We provide an analysis of adverse consequences of unmet needs among HNHC older adults in a nationally representative, population-based study—The National Health and Aging Trends Study (NHATS). Freedman and Spillman (2014) analyzed the NHATS sample and found that 31.8% of older adults with ADL/IADL difficulty or needing help reported at least one adverse consequence related to unmet needs for care within the past month. The most common adverse consequences were wet or soiled clothing, having to stay inside, limited mobility inside one’s home/building, and medication errors. Beach and Schulz (2017) linked adverse consequences of unmet needs among NHATS care recipients with the characteristics of their informal caregivers from the companion National Study of Caregiving (NSOC). They found that older adults reporting multiple adverse consequences had caregivers who were more likely to spend >100 h/month caregiving, help with skin care and wounds, report caregiving as emotionally and physically difficult, and report restricted participation in valued activities. They concluded that caregivers experiencing high levels of burden, stress, and negative physical and psychosocial impacts may provide substandard/poor care to older adults, which may be a risk factor for neglect. We use the same data to further examine the relationship between health conditions and adverse consequences of unmet needs by distinguishing between three different types of HNHC groups, and also identifying individuals with different combinations of HNHC. We examine these groups to see how they compare in terms of socio-demographic characteristics, compensatory and caregiving strategies used to accommodate disabilities, and number and types of adverse consequences of unmet needs. We then use multivariate logistic regression models to examine the relationship between each HNHC group and number and type of adverse consequences of unmet needs. The results of these analyses can further inform the design of interventions for HNHC older adults and caregivers aiming to improve health outcomes and reduce healthcare costs by highlighting the groups at greatest risk of adverse consequences of unmet needs. Methods Data The data used in this study are publicly available, do not contain individual identifiers, and are, therefore, exempt from institutional review board review. A detailed description of the data sources for this study was provided in recent publications (Beach & Schulz, 2017; Freedman & Spillman, 2014) and portions of this section are repeated from these sources. The NHATS is nationally representative of Americans 65 years and older. The first round of NHATS took place in 2011 with a national sample of older adults drawn from the Medicare enrollment file. This article presents analyses of this baseline assessment. In-person interviews were conducted with study participants or with proxy respondents if the participant was unable to respond. In all, 7,609 in-person interviews were completed, including 583 with proxy respondents. (An additional 468 nursing home residents were enrolled in the study but are not included in these analyses.) Study participants were asked whether and how they performed daily activities in the month before the interview. This article focuses on the subset of 4,024 NHATS participants who reported they had at least some difficulty and/or were receiving help with at least 1 of 12 ADL/mobility/IADL tasks (toileting, eating, bathing, dressing, getting out of bed, getting outside, getting around inside, doing laundry, shopping, making hot meals, paying bills/banking, managing medications). The vast majority of the sample (91.8%) had at least one informal caregiver providing help with at least one ADL/mobility/IADL task (8.2% reported receiving no help), with 36.5% reporting one helper, 29.4% two helpers, 14.9% three helpers, and 11% four or more helpers. Measures High-need, high-cost (HNHC) groups Three main HNHC groups were used: (1) multiple chronic conditions (MCC), defined as having at least three of seven self-reported chronic conditions (heart attack/heart disease/high blood pressure, arthritis, osteoporosis, diabetes, lung disease, stroke, cancer); (2) probable dementia (DEM), based on a combination of self-/proxy-report and performance-based cognitive testing from NHATS (Kasper, Freedman, & Spillman, 2013); and (3) end-of-life (EOL), participants who had died within 1 year of the baseline assessment, as confirmed by NHATS code of deceased at the wave 2 assessment. Recall that all study participants had a functional limitation with at least one ADL/IADL task. Thus, the HNHC groups include functional limitations in addition to MCC, DEM, and EOL. The “low need” comparison group consists of older adults with functional limitations who do not meet any of the HNHC criteria. The seven chronic conditions used were those available in the NHATS data set, and we should note that these differ slightly from some previous definitions (Hayes et al., 2016). The NHATS classification of DEM required a self- or proxy report that a doctor told the sample person that he/she had dementia or Alzheimer’s; or (in the absence of this) scoring at least 1.5 SDs below the mean on at least two of the following in cognitive domains—memory, orientation, and executive functioning (Kasper, Freedman, & Spillman, 2013). A proxy report on the AD8 Dementia Screening Interview (Galvin et al., 2005; Galvin, Roe, Xiong, & Morris, 2006) of two or higher (i.e., meeting dementia criteria) was also used to classify DEM. Participants were classified as possible dementia when there was no self-reported diagnosis, but who scored at 1.5 SDs below the mean on one of the three cognitive domains. Note that our HNHC dementia criteria was a DEM classification in NHATS—possible dementia cases were not included. An older adult was considered HNHC if they fell into one or more of these three groups. We also examined overlap among the three HNHC groups, summarized in Figure 1, which includes unweighted sample sizes and estimated population sizes. For example, 1,564 NHATS participants met our definition of MCC only, with another 396 having both MCC and DEM, 98 also being EOL, and 96 meeting all three criteria. Figure 1. View largeDownload slide Three overlapping high need patient populations. National Health and Aging Trends Study (NHATS, 2011). CHRONIC CONDS = at least three chronic conditions and one ADL/IADL limitation. END OF LIFE = died within 1 year of baseline assessment and one ADL/IADL limitation. DEMENTIA = diagnosis of probable dementia and one ADL/IADL limitation. NONE OF THE ABOVE = N = 1,379; 6.2M; has at least one ADL/IADL limitation. Figure reports unweighted sample size, and estimated weighted population size. Figure 1. View largeDownload slide Three overlapping high need patient populations. National Health and Aging Trends Study (NHATS, 2011). CHRONIC CONDS = at least three chronic conditions and one ADL/IADL limitation. END OF LIFE = died within 1 year of baseline assessment and one ADL/IADL limitation. DEMENTIA = diagnosis of probable dementia and one ADL/IADL limitation. NONE OF THE ABOVE = N = 1,379; 6.2M; has at least one ADL/IADL limitation. Figure reports unweighted sample size, and estimated weighted population size. Adverse consequences of unmet needs Respondents were asked single questions (for each ADL/mobility/IADL task) assessing whether during the past month they experienced a negative consequence because there was no one there to help (for those reporting that they never performed the task without help in a prior question); or it was too difficult to do by themselves without additional help (for those reporting that they performed the task by themselves rarely, sometimes, or most times) (see Table 3 for specific consequences of unmet needs). Adverse consequences of unmet needs are analyzed using both summary indicators (i.e., any adverse consequences, any ADL/mobility/IADL adverse consequences) and individually (e.g., wet or soiled clothing, had to stay inside). The individual adverse consequences items had very low levels of missing data (range n = 0–10 missing); and all cases were included in the summary indicator analyses. Socio-demographics We examined gender, age, race/ethnicity, income (quartiles based on the entire n = 7,609 NHATS baseline sample), and living arrangements—whether the older adult lived alone and whether he/she lived in a residential care (non-nursing home) setting. Responses were obtained or calculated for all 4,024 participants on all socio-demographic variables except for race (missing for n = 46). The multivariate model race dummy variables (see below) include the missing cases in the reference group, and this does not affect the key results (i.e., no difference when the 46 cases are dropped). Disability compensatory strategies Environmental modifications were assessed with self-reports of the following added to the home in the last year: a ramp, elevator, stair lift, shower grab bars, shower/tub seat, raised toilet seat, and toilet grab bars. For analysis, we examined whether any of these environmental modifications had been added in the previous year. Mobility device use was assessed with questions asking whether any of the following were present: uses a cane, uses a walker, uses a wheelchair, has a wheelchair at home, uses a scooter, has a scooter at home. For analysis, we examined whether any of these mobility device use indicators were present. The informal helper network was assessed for those who reported receiving help with each ADL/IADL task. A detailed helper roster lists the relationship and specific activities for each person providing assistance. For analysis, we used the total number of informal helpers listed, plus the presence of various helper relationship types (e.g., at least one of the helpers was a spouse, daughter, son, etc.). We also examined the presence of any paid informal caregivers, which was also measured through the detailed helper roster. Data on the informal helper network was missing for eight cases, and these were not included in the multivariate models described below. Data Analysis and Estimation We first describe the mutually exclusive and exhaustive HNHC groups (as shown in Figure 1) in terms of socio-demographic variables and disability compensatory strategies. We use percentages and logistic regression models to compare groups, with a focus on contrasts to the “low need” disabled older adults not meeting HNHC criteria. We then use the same percentages and logistic methods to describe and compare HNHC groups in terms of adverse consequences of unmet needs (summary indices and individual adverse consequences). Then, multivariate logistic regression models are tested with summary measures of adverse consequences of unmet needs (any adverse consequences, any IADL, any mobility, any ADL) as outcomes and the seven mutually exclusive HNHC groups (single criteria, two criteria, all three criteria) as the key predictors (using the low need group as the reference). These models control for all socio-demographic and disability compensatory strategies and provide tests of independent HNHC—adverse consequences of unmet needs links, net of all other variables. The model also tests whether the disability compensatory strategies serve to reduce or eliminate (i.e., mediate) any HNHC—adverse consequences relationships. Finally, a series of multivariate models (included as Supplementary Appendices) are tested with HNHC group (plus socio-demographics and disability compensatory strategies) predicting each of the 12 specific ADL/mobility/IADL adverse consequences of unmet needs. (Models using socio-demographics to predict HNHC group membership; and models using HNHC groups to predict disability compensatory strategies are available from the author upon request.) These models are used to create summary profiles of each HNHC group/combination. Observations from the NHATS are weighted to produce nationally representative estimates. Survey weights, released with the NHATS public data use files that adjust for differential probabilities of selection and survey non-response, were used for all analyses. All analyses were conducted with statistical software (STATA, Version 14; StataCorp) using survey sampling weights and variance estimation procedures that account for the complex sampling strategy. Results Figure 1 shows unweighted sample sizes and weighted population estimates for each HNHC group or combination. These data are repeated in the first two rows of Table 1, which compares the HNHC groups on socio-demographic variables. The HNHC groups include an estimated 10.5 million older adults (age 65 and older), which represents 62.8% of the 16.7 million disabled older adults in NHATS. Note that the largest HNHC group by far is the MCC only group, with an estimated 6.7 million older adults. As shown in Table 1, The HNHC groups were more likely to be female, with the exception of the EOL and DEM + EOL groups. The HNHC groups are also older, as would be expected. Minority status is also related to HNHC group membership, with non-Hispanic Blacks being over-represented in the MCC and DEM groups, as well as the DEM + EOL, MCC + DEM, and the group with all three criteria. Hispanics were over-represented in the MCC + DEM group. HNHC status is associated with lower income. It is also associated with living in residential care settings (all socio-demographic differences, p < .001). There were no significant differences between the HNHC and low need groups in the prevalence of living alone. Table 1. Socio-demographic Characteristics by High Need Patient Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds+ dementia Chron Conds + died Dementia + Died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Population estimate (millions) 16.7 6.2 6.7 1.2 0.2 1.4 0.4 0.2 0.3 Gender  Male 37.1 44.1 30.5 36.4 46.5 34.5 37.1 50.6 40.4 Age  65–69 20.1 27.4 20.5 9.1 8.9 11.7 17.7 3.7 9.0  70–74 20.4 21.0 24.9 11.4 12.7 12.4 20.7 1.0 3.0  75–79 19.2 18.5 20.7 18.2 15.9 19.5 16.7 15.2 8.9  80–84 18.0 16.4 17.3 17.9 21.2 24.0 22.3 29.2 23.8  85–89 14.1 11.6 11.7 26.1 26.2 19.4 16.7 21.0 28.0  90 or older 7.4 5.2 4.8 17.4 15.2 13.0 5.9 29.9 27.3 Race  Non-Hispanic White 77.8 79.5 79.8 66.9 87.9 67.9 83.2 72.2 76.7  Non-Hispanic Black 9.4 7.8 10.1 13.2 5.5 11.4 4.8 13.1 10.2  Non-Hispanic other race 3.2 2.9 2.7 8.6 0.0 3.0 1.8 2.6 3.4  Hispanic 8.4 8.7 6.4 9.1 4.3 16.4 7.3 9.3 8.4 Income  Quartile 1 26.9 20.8 26.1 41.0 28.3 43.3 23.0 33.7 36.1  Quartile 2 28.0 26.5 27.6 29.6 24.2 28.4 41.5 39.9 38.3  Quartile 3 24.1 25.7 25.3 18.7 27.8 18.8 25.5 16.6 15.9  Quartile 4 21.0 27.1 21.1 10.8 19.8 9.4 9.9 9.9 9.7 Living arrangement  Living in residential care 10.4 8.1 8.5 22.9 15.7 13.1 12.6 27.1 18.0  Living alone 34.2 33.2 35.5 34.9 40.3 28.4 42.5 38.6 28.3 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds+ dementia Chron Conds + died Dementia + Died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Population estimate (millions) 16.7 6.2 6.7 1.2 0.2 1.4 0.4 0.2 0.3 Gender  Male 37.1 44.1 30.5 36.4 46.5 34.5 37.1 50.6 40.4 Age  65–69 20.1 27.4 20.5 9.1 8.9 11.7 17.7 3.7 9.0  70–74 20.4 21.0 24.9 11.4 12.7 12.4 20.7 1.0 3.0  75–79 19.2 18.5 20.7 18.2 15.9 19.5 16.7 15.2 8.9  80–84 18.0 16.4 17.3 17.9 21.2 24.0 22.3 29.2 23.8  85–89 14.1 11.6 11.7 26.1 26.2 19.4 16.7 21.0 28.0  90 or older 7.4 5.2 4.8 17.4 15.2 13.0 5.9 29.9 27.3 Race  Non-Hispanic White 77.8 79.5 79.8 66.9 87.9 67.9 83.2 72.2 76.7  Non-Hispanic Black 9.4 7.8 10.1 13.2 5.5 11.4 4.8 13.1 10.2  Non-Hispanic other race 3.2 2.9 2.7 8.6 0.0 3.0 1.8 2.6 3.4  Hispanic 8.4 8.7 6.4 9.1 4.3 16.4 7.3 9.3 8.4 Income  Quartile 1 26.9 20.8 26.1 41.0 28.3 43.3 23.0 33.7 36.1  Quartile 2 28.0 26.5 27.6 29.6 24.2 28.4 41.5 39.9 38.3  Quartile 3 24.1 25.7 25.3 18.7 27.8 18.8 25.5 16.6 15.9  Quartile 4 21.0 27.1 21.1 10.8 19.8 9.4 9.9 9.9 9.7 Living arrangement  Living in residential care 10.4 8.1 8.5 22.9 15.7 13.1 12.6 27.1 18.0  Living alone 34.2 33.2 35.5 34.9 40.3 28.4 42.5 38.6 28.3 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. View Large Table 1. Socio-demographic Characteristics by High Need Patient Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds+ dementia Chron Conds + died Dementia + Died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Population estimate (millions) 16.7 6.2 6.7 1.2 0.2 1.4 0.4 0.2 0.3 Gender  Male 37.1 44.1 30.5 36.4 46.5 34.5 37.1 50.6 40.4 Age  65–69 20.1 27.4 20.5 9.1 8.9 11.7 17.7 3.7 9.0  70–74 20.4 21.0 24.9 11.4 12.7 12.4 20.7 1.0 3.0  75–79 19.2 18.5 20.7 18.2 15.9 19.5 16.7 15.2 8.9  80–84 18.0 16.4 17.3 17.9 21.2 24.0 22.3 29.2 23.8  85–89 14.1 11.6 11.7 26.1 26.2 19.4 16.7 21.0 28.0  90 or older 7.4 5.2 4.8 17.4 15.2 13.0 5.9 29.9 27.3 Race  Non-Hispanic White 77.8 79.5 79.8 66.9 87.9 67.9 83.2 72.2 76.7  Non-Hispanic Black 9.4 7.8 10.1 13.2 5.5 11.4 4.8 13.1 10.2  Non-Hispanic other race 3.2 2.9 2.7 8.6 0.0 3.0 1.8 2.6 3.4  Hispanic 8.4 8.7 6.4 9.1 4.3 16.4 7.3 9.3 8.4 Income  Quartile 1 26.9 20.8 26.1 41.0 28.3 43.3 23.0 33.7 36.1  Quartile 2 28.0 26.5 27.6 29.6 24.2 28.4 41.5 39.9 38.3  Quartile 3 24.1 25.7 25.3 18.7 27.8 18.8 25.5 16.6 15.9  Quartile 4 21.0 27.1 21.1 10.8 19.8 9.4 9.9 9.9 9.7 Living arrangement  Living in residential care 10.4 8.1 8.5 22.9 15.7 13.1 12.6 27.1 18.0  Living alone 34.2 33.2 35.5 34.9 40.3 28.4 42.5 38.6 28.3 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds+ dementia Chron Conds + died Dementia + Died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Population estimate (millions) 16.7 6.2 6.7 1.2 0.2 1.4 0.4 0.2 0.3 Gender  Male 37.1 44.1 30.5 36.4 46.5 34.5 37.1 50.6 40.4 Age  65–69 20.1 27.4 20.5 9.1 8.9 11.7 17.7 3.7 9.0  70–74 20.4 21.0 24.9 11.4 12.7 12.4 20.7 1.0 3.0  75–79 19.2 18.5 20.7 18.2 15.9 19.5 16.7 15.2 8.9  80–84 18.0 16.4 17.3 17.9 21.2 24.0 22.3 29.2 23.8  85–89 14.1 11.6 11.7 26.1 26.2 19.4 16.7 21.0 28.0  90 or older 7.4 5.2 4.8 17.4 15.2 13.0 5.9 29.9 27.3 Race  Non-Hispanic White 77.8 79.5 79.8 66.9 87.9 67.9 83.2 72.2 76.7  Non-Hispanic Black 9.4 7.8 10.1 13.2 5.5 11.4 4.8 13.1 10.2  Non-Hispanic other race 3.2 2.9 2.7 8.6 0.0 3.0 1.8 2.6 3.4  Hispanic 8.4 8.7 6.4 9.1 4.3 16.4 7.3 9.3 8.4 Income  Quartile 1 26.9 20.8 26.1 41.0 28.3 43.3 23.0 33.7 36.1  Quartile 2 28.0 26.5 27.6 29.6 24.2 28.4 41.5 39.9 38.3  Quartile 3 24.1 25.7 25.3 18.7 27.8 18.8 25.5 16.6 15.9  Quartile 4 21.0 27.1 21.1 10.8 19.8 9.4 9.9 9.9 9.7 Living arrangement  Living in residential care 10.4 8.1 8.5 22.9 15.7 13.1 12.6 27.1 18.0  Living alone 34.2 33.2 35.5 34.9 40.3 28.4 42.5 38.6 28.3 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. View Large Table 2 shows relationships between HNHC status and various disability-related compensatory strategies. HNHC older adults were significantly more likely than low need persons to have had recent environmental modifications, to use mobility devices, and to use paid caregiving help (all p < .001). HNHC older adults also had significantly more informal helpers (p < .001). These differences are especially large for those meeting multiple HNHC criteria. In terms of presence of specific informal helper relationships, HNHC older adults were less likely to be cared for by a spouse (p < .001), and more likely to be cared for by daughters and sons (both p < .001). Adult children were most likely to be involved as caregivers when the older adult met multiple HNHC criteria. Grandchildren were also more likely to be involved as HNHC caregivers, especially when multiple criteria were met (p < .001). Those near the end-of-life had more friends as caregivers (p < .01). Table 2. Disability Compensatory Strategies by High Need Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia + died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Any environmental modifications 17.0 13.4 17.1* 17.3 21.0 26.3*** 27.5*** 14.2 28.8** Any mobility devices 44.8 30.6 48.1*** 46.5*** 67.9*** 68.6*** 68.0*** 74.8*** 79.4*** Number of helpers (mean) 1.8 1.5 1.8*** 2.1*** 1.8* 2.3*** 2.0* 2.7*** 2.6*** Any paid help 13.9 11.0 12.0 20.4*** 18.8 22.9*** 18.8* 28.1*** 30.4*** Caregiver relationship  Spouse 43.4 49.2 43.0* 33.9*** 31.9* 34.2*** 40.0 36.0 32.2**  Daughter 37.0 27.4 38.2*** 47.1*** 40.6* 54.8*** 40.9* 57.2*** 66.3***  Son 24.7 18.9 24.3*** 31.7*** 27.1 37.7*** 27.1 43.5*** 51.9***  Sibling 5.3 5.2 6.0 8.4* 3.6 1.5** 2.6 10.0 2.5  Grandchild 8.2 5.4 8.3** 11.0** 8.1 15.2*** 14.7** 9.4 10.0  Niece or nephew 3.1 2.5 2.5 5.5** 4.7 3.9 4.0 7.1** 6.4  Friend 11.1 10.9 12.5 8.1 21.9** 8.9 9.3 15.8 1.3***  Other family member 3.5 2.6 4.1 4.5 2.3 3.9 4.9 2.3 1.9  Other 9.4 9.3 9.0 9.5 8.9 9.5 11.8 6.2 15.6 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia + died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Any environmental modifications 17.0 13.4 17.1* 17.3 21.0 26.3*** 27.5*** 14.2 28.8** Any mobility devices 44.8 30.6 48.1*** 46.5*** 67.9*** 68.6*** 68.0*** 74.8*** 79.4*** Number of helpers (mean) 1.8 1.5 1.8*** 2.1*** 1.8* 2.3*** 2.0* 2.7*** 2.6*** Any paid help 13.9 11.0 12.0 20.4*** 18.8 22.9*** 18.8* 28.1*** 30.4*** Caregiver relationship  Spouse 43.4 49.2 43.0* 33.9*** 31.9* 34.2*** 40.0 36.0 32.2**  Daughter 37.0 27.4 38.2*** 47.1*** 40.6* 54.8*** 40.9* 57.2*** 66.3***  Son 24.7 18.9 24.3*** 31.7*** 27.1 37.7*** 27.1 43.5*** 51.9***  Sibling 5.3 5.2 6.0 8.4* 3.6 1.5** 2.6 10.0 2.5  Grandchild 8.2 5.4 8.3** 11.0** 8.1 15.2*** 14.7** 9.4 10.0  Niece or nephew 3.1 2.5 2.5 5.5** 4.7 3.9 4.0 7.1** 6.4  Friend 11.1 10.9 12.5 8.1 21.9** 8.9 9.3 15.8 1.3***  Other family member 3.5 2.6 4.1 4.5 2.3 3.9 4.9 2.3 1.9  Other 9.4 9.3 9.0 9.5 8.9 9.5 11.8 6.2 15.6 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. *p < .05, **p < .01, ***p < .001 in logistic regression with low need group as reference category. View Large Table 2. Disability Compensatory Strategies by High Need Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia + died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Any environmental modifications 17.0 13.4 17.1* 17.3 21.0 26.3*** 27.5*** 14.2 28.8** Any mobility devices 44.8 30.6 48.1*** 46.5*** 67.9*** 68.6*** 68.0*** 74.8*** 79.4*** Number of helpers (mean) 1.8 1.5 1.8*** 2.1*** 1.8* 2.3*** 2.0* 2.7*** 2.6*** Any paid help 13.9 11.0 12.0 20.4*** 18.8 22.9*** 18.8* 28.1*** 30.4*** Caregiver relationship  Spouse 43.4 49.2 43.0* 33.9*** 31.9* 34.2*** 40.0 36.0 32.2**  Daughter 37.0 27.4 38.2*** 47.1*** 40.6* 54.8*** 40.9* 57.2*** 66.3***  Son 24.7 18.9 24.3*** 31.7*** 27.1 37.7*** 27.1 43.5*** 51.9***  Sibling 5.3 5.2 6.0 8.4* 3.6 1.5** 2.6 10.0 2.5  Grandchild 8.2 5.4 8.3** 11.0** 8.1 15.2*** 14.7** 9.4 10.0  Niece or nephew 3.1 2.5 2.5 5.5** 4.7 3.9 4.0 7.1** 6.4  Friend 11.1 10.9 12.5 8.1 21.9** 8.9 9.3 15.8 1.3***  Other family member 3.5 2.6 4.1 4.5 2.3 3.9 4.9 2.3 1.9  Other 9.4 9.3 9.0 9.5 8.9 9.5 11.8 6.2 15.6 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia + died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Any environmental modifications 17.0 13.4 17.1* 17.3 21.0 26.3*** 27.5*** 14.2 28.8** Any mobility devices 44.8 30.6 48.1*** 46.5*** 67.9*** 68.6*** 68.0*** 74.8*** 79.4*** Number of helpers (mean) 1.8 1.5 1.8*** 2.1*** 1.8* 2.3*** 2.0* 2.7*** 2.6*** Any paid help 13.9 11.0 12.0 20.4*** 18.8 22.9*** 18.8* 28.1*** 30.4*** Caregiver relationship  Spouse 43.4 49.2 43.0* 33.9*** 31.9* 34.2*** 40.0 36.0 32.2**  Daughter 37.0 27.4 38.2*** 47.1*** 40.6* 54.8*** 40.9* 57.2*** 66.3***  Son 24.7 18.9 24.3*** 31.7*** 27.1 37.7*** 27.1 43.5*** 51.9***  Sibling 5.3 5.2 6.0 8.4* 3.6 1.5** 2.6 10.0 2.5  Grandchild 8.2 5.4 8.3** 11.0** 8.1 15.2*** 14.7** 9.4 10.0  Niece or nephew 3.1 2.5 2.5 5.5** 4.7 3.9 4.0 7.1** 6.4  Friend 11.1 10.9 12.5 8.1 21.9** 8.9 9.3 15.8 1.3***  Other family member 3.5 2.6 4.1 4.5 2.3 3.9 4.9 2.3 1.9  Other 9.4 9.3 9.0 9.5 8.9 9.5 11.8 6.2 15.6 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. *p < .05, **p < .01, ***p < .001 in logistic regression with low need group as reference category. View Large Table 3 shows differences between HNHC groups and low need groups on adverse consequences of unmet needs. The overall rate of adverse consequences is 31.8% (consistent with that previously reported by Freedman & Spillman, 2014), with 13.4% having adverse consequences of unmet IADL needs, 19.3% unmet mobility needs, and 12.6% unmet ADL needs. Results show that the HNHC groups have significantly more adverse consequences of unmet needs than their low need counterparts. The first row shows the prevalence of any (of 12) adverse consequences in the month prior to the assessment. The prevalence of adverse consequences of unmet needs is elevated for all HNHC groups (p < .001) and exceeded 50% in the MCC + EOL, MCC + DEM, and the group meeting all three criteria, among whom nearly two-thirds (65.6%) reported at least one adverse consequence. These patterns are stronger for unmet mobility (p < .001) and ADL (self-care; p < .001) needs than for unmet IADL needs (p < .01). Older adults meeting multiple HNHC criteria were also much more likely to report specific adverse consequences of unmet needs, primarily ADL-related and mobility-related. For example, over a third of those (34%) meeting all three criteria reported wet or soiled clothing in the past month due to unmet toileting needs. About one-fourth of the MCC + EOL, MCC + DEM, and those meeting all three criteria reported having to stay inside, and 16.1% of the MCC + EOL older adults had to stay in bed due to unmet needs. Note that medication mistakes were more prevalent among DEM, MCC + DEM, and MCC + EOL older adults. Table 3. Unmet Needs by High Need Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia+ died Chron Conds + dementia+ died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Summary measures  Any unmet need 31.8 21.4 31.6*** 39.6*** 48.7*** 53.4*** 53.2*** 46.2*** 65.6***  Any IADL unmet need 13.4 11.4 13.9 13.4 15.5 18.2** 25.7*** 5.6 6.0  Any mobility unmet need 19.3 10.4 20.0*** 23.1*** 31.8*** 36.5*** 42.9*** 28.1*** 43.4***  Any ADL unmet need 12.6 5.6 12.3*** 17.8*** 12.7* 28.6*** 26.6*** 26.9*** 41.2*** ADL  Wet or soiled clothing (toileting) 8.1 3.7 6.1** 15.3*** 5.4 21.3*** 18.7*** 24.1*** 34.0***  Went without eating 0.5 0.3 0.4 0.3 0.0 2.5** 2.1* 0.0 0.0  Went without bathing, showering, cleaning up 4.3 1.7 5.3*** 3.6 5.0 8.8*** 7.0** 6.4* 11.0***  Went without getting dressed 2.8 0.8 3.5*** 2.0 4.1 6.4*** 8.9*** 5.3** 6.5*** Mobility  Had to stay in bed 4.8 2.0 4.6*** 4.8** 1.9 13.6*** 16.1*** 10.1a 8.7**  Had to stay inside 12.2 7.2 12.3*** 13.1** 21.9*** 26.3*** 24.7*** 10.0 24.4***  Did not go places in home or building 10.1 4.7 10.4*** 14.0*** 12.1* 20.0*** 23.8*** 20.3*** 28.5*** IADL  Went without clean laundry 1.8 1.0 1.9 1.7 5.1* 4.0** 4.3* 0.0 0.0  Went without groceries 3.1 2.1 3.8* 3.1 0.5 2.7 11.4*** 2.0 0.0  Went without a hot meal 4.0 2.4 5.5** 2.4 6.1 3.8 11.2*** 2.0 0.0  Went without paying bills 1.9 1.8 1.6 2.3 0.0 4.0* 3.3 0.6 0.0  Made mistake taking medicine 6.9 5.9 6.5 8.7 5.3 11.6** 9.4 5.2 6.0 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia+ died Chron Conds + dementia+ died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Summary measures  Any unmet need 31.8 21.4 31.6*** 39.6*** 48.7*** 53.4*** 53.2*** 46.2*** 65.6***  Any IADL unmet need 13.4 11.4 13.9 13.4 15.5 18.2** 25.7*** 5.6 6.0  Any mobility unmet need 19.3 10.4 20.0*** 23.1*** 31.8*** 36.5*** 42.9*** 28.1*** 43.4***  Any ADL unmet need 12.6 5.6 12.3*** 17.8*** 12.7* 28.6*** 26.6*** 26.9*** 41.2*** ADL  Wet or soiled clothing (toileting) 8.1 3.7 6.1** 15.3*** 5.4 21.3*** 18.7*** 24.1*** 34.0***  Went without eating 0.5 0.3 0.4 0.3 0.0 2.5** 2.1* 0.0 0.0  Went without bathing, showering, cleaning up 4.3 1.7 5.3*** 3.6 5.0 8.8*** 7.0** 6.4* 11.0***  Went without getting dressed 2.8 0.8 3.5*** 2.0 4.1 6.4*** 8.9*** 5.3** 6.5*** Mobility  Had to stay in bed 4.8 2.0 4.6*** 4.8** 1.9 13.6*** 16.1*** 10.1a 8.7**  Had to stay inside 12.2 7.2 12.3*** 13.1** 21.9*** 26.3*** 24.7*** 10.0 24.4***  Did not go places in home or building 10.1 4.7 10.4*** 14.0*** 12.1* 20.0*** 23.8*** 20.3*** 28.5*** IADL  Went without clean laundry 1.8 1.0 1.9 1.7 5.1* 4.0** 4.3* 0.0 0.0  Went without groceries 3.1 2.1 3.8* 3.1 0.5 2.7 11.4*** 2.0 0.0  Went without a hot meal 4.0 2.4 5.5** 2.4 6.1 3.8 11.2*** 2.0 0.0  Went without paying bills 1.9 1.8 1.6 2.3 0.0 4.0* 3.3 0.6 0.0  Made mistake taking medicine 6.9 5.9 6.5 8.7 5.3 11.6** 9.4 5.2 6.0 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. *p < .05, **p < .01, ***p < .001 in logistic regression with low need group as reference category. View Large Table 3. Unmet Needs by High Need Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia+ died Chron Conds + dementia+ died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Summary measures  Any unmet need 31.8 21.4 31.6*** 39.6*** 48.7*** 53.4*** 53.2*** 46.2*** 65.6***  Any IADL unmet need 13.4 11.4 13.9 13.4 15.5 18.2** 25.7*** 5.6 6.0  Any mobility unmet need 19.3 10.4 20.0*** 23.1*** 31.8*** 36.5*** 42.9*** 28.1*** 43.4***  Any ADL unmet need 12.6 5.6 12.3*** 17.8*** 12.7* 28.6*** 26.6*** 26.9*** 41.2*** ADL  Wet or soiled clothing (toileting) 8.1 3.7 6.1** 15.3*** 5.4 21.3*** 18.7*** 24.1*** 34.0***  Went without eating 0.5 0.3 0.4 0.3 0.0 2.5** 2.1* 0.0 0.0  Went without bathing, showering, cleaning up 4.3 1.7 5.3*** 3.6 5.0 8.8*** 7.0** 6.4* 11.0***  Went without getting dressed 2.8 0.8 3.5*** 2.0 4.1 6.4*** 8.9*** 5.3** 6.5*** Mobility  Had to stay in bed 4.8 2.0 4.6*** 4.8** 1.9 13.6*** 16.1*** 10.1a 8.7**  Had to stay inside 12.2 7.2 12.3*** 13.1** 21.9*** 26.3*** 24.7*** 10.0 24.4***  Did not go places in home or building 10.1 4.7 10.4*** 14.0*** 12.1* 20.0*** 23.8*** 20.3*** 28.5*** IADL  Went without clean laundry 1.8 1.0 1.9 1.7 5.1* 4.0** 4.3* 0.0 0.0  Went without groceries 3.1 2.1 3.8* 3.1 0.5 2.7 11.4*** 2.0 0.0  Went without a hot meal 4.0 2.4 5.5** 2.4 6.1 3.8 11.2*** 2.0 0.0  Went without paying bills 1.9 1.8 1.6 2.3 0.0 4.0* 3.3 0.6 0.0  Made mistake taking medicine 6.9 5.9 6.5 8.7 5.3 11.6** 9.4 5.2 6.0 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia+ died Chron Conds + dementia+ died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Summary measures  Any unmet need 31.8 21.4 31.6*** 39.6*** 48.7*** 53.4*** 53.2*** 46.2*** 65.6***  Any IADL unmet need 13.4 11.4 13.9 13.4 15.5 18.2** 25.7*** 5.6 6.0  Any mobility unmet need 19.3 10.4 20.0*** 23.1*** 31.8*** 36.5*** 42.9*** 28.1*** 43.4***  Any ADL unmet need 12.6 5.6 12.3*** 17.8*** 12.7* 28.6*** 26.6*** 26.9*** 41.2*** ADL  Wet or soiled clothing (toileting) 8.1 3.7 6.1** 15.3*** 5.4 21.3*** 18.7*** 24.1*** 34.0***  Went without eating 0.5 0.3 0.4 0.3 0.0 2.5** 2.1* 0.0 0.0  Went without bathing, showering, cleaning up 4.3 1.7 5.3*** 3.6 5.0 8.8*** 7.0** 6.4* 11.0***  Went without getting dressed 2.8 0.8 3.5*** 2.0 4.1 6.4*** 8.9*** 5.3** 6.5*** Mobility  Had to stay in bed 4.8 2.0 4.6*** 4.8** 1.9 13.6*** 16.1*** 10.1a 8.7**  Had to stay inside 12.2 7.2 12.3*** 13.1** 21.9*** 26.3*** 24.7*** 10.0 24.4***  Did not go places in home or building 10.1 4.7 10.4*** 14.0*** 12.1* 20.0*** 23.8*** 20.3*** 28.5*** IADL  Went without clean laundry 1.8 1.0 1.9 1.7 5.1* 4.0** 4.3* 0.0 0.0  Went without groceries 3.1 2.1 3.8* 3.1 0.5 2.7 11.4*** 2.0 0.0  Went without a hot meal 4.0 2.4 5.5** 2.4 6.1 3.8 11.2*** 2.0 0.0  Went without paying bills 1.9 1.8 1.6 2.3 0.0 4.0* 3.3 0.6 0.0  Made mistake taking medicine 6.9 5.9 6.5 8.7 5.3 11.6** 9.4 5.2 6.0 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. *p < .05, **p < .01, ***p < .001 in logistic regression with low need group as reference category. View Large Supplementary Table 1 summarizes the multivariate logistic regression models using HNHC group status as a predictor of summary measures of adverse consequences of unmet needs for informal care. Checks for multi-collinearity revealed no predictor correlations greater than 0.40, with many less than 0.10. Tests for influential cases using Cook’s influence statistics and DfBeta values revealed no influential cases. These models simultaneously control for all socio-demographic and disability-related compensatory strategy variables. The results show that HNHC older adults are significantly more likely to have adverse consequences of unmet needs in the past month, net of any effect of socio-demographics or other efforts to compensate for disability. Mirroring the results just presented for Table 3, results were strongest for adverse consequences of unmet mobility and ADL needs, with less consistent impact on adverse consequences of unmet needs for IADL assistance. Looking first at any adverse consequences (column 1), six of the seven HNHC groups had significantly higher risk than the low need patient groups (and the DEM + EOL group was marginally higher). The adjusted odds ratios also show the additive effects of meeting more than one HNHC criteria. While those with MCC had a 42% higher chance of reporting any adverse consequences of unmet needs in the past month, those with both MCC + EOL and MCC + DEM were 2–3 times as likely, and those meeting all three HNHC criteria were nearly four times as likely as low need persons to report adverse consequences of unmet needs, controlling for socio-demographics and disability compensatory strategies. Other significant predictors included younger age, low income, use of mobility devices, paid caregiver use, and having a spouse as an informal helper. HNHC group results for adverse consequences of unmet mobility and ADL needs are similar. In both models, six of the seven HNHC groups had significantly more adverse consequences, and the groups meeting multiple criteria have the highest rates. The pattern for IADL adverse consequences is distinct, as HNHC status does not generally predict these, except for the MCC + EOL group. In fact, the group meeting all three criteria is significantly less likely to have adverse consequences of unmet IADL needs relative to the low need group. Table 4 presents summary profiles of each of the seven HNHC patient groups examined in the paper in terms of key socio-demographics, disability-related compensatory strategies, and specific adverse consequences of unmet needs during the past month. Results are based on multivariate modeling, full details of which are available from the authors upon request. Entries in the socio-demographics column were significant (p < .05) predictors of specific HNHC group membership (versus not a member of the group) in multivariate logistic regression models including all demographic variables as predictors. The compensatory strategy entries are based on models in which each strategy was regressed on simultaneously entered indicators of HNHC status (with the “low need” group as the reference category), controlling for all socio-demographic variables. An entry is shown if that HNHC group was statistically significant (p < .05) in the model with the listed compensatory strategy as the outcome variable. Supplementary Tables 2 and 4 show the models used to derive the entries for the specific unmet needs column. A specific unmet need is listed if the HNHC group was a statistically significant (p < .05) predictor in the model, which controls for all socio-demographics and compensatory strategies. In sum, the analyses show that the MCC, DEM, and EOL only groups are somewhat distinct, with the only characteristic they share is unmet needs for mobility assistance resulting in having to stay inside. For example, the MCC group tends to be female, age 70–79, has made environmental modifications, uses mobility devices, has more informal helpers and has adult children as helpers. They are also more likely to report going without bathing, without getting dressed, having to stay in bed, stay inside, have limited mobility in the home, and go without hot meals. The DEM and EOL groups have different profiles. The table also shows that HNHC older adults, as might be expected, use high levels of disability compensatory strategies. They make environmental modifications to their homes, use mobility devices, hire paid caregivers, and tend to mobilize larger more diverse and inter-generational informal helper networks. Despite these efforts, as we have shown, they still report high levels of adverse consequences of unmet needs. Lastly, note that those with both MCC + DEM and MCC + EOL tended to have the most adverse consequences of unmet needs, and the MCC + DEM uses the most disability compensatory strategies and tends to have the most diverse informal helper networks. Table 4. Summary Profiles of High-Need Patient Groups Based on Multivariate Models Population estimate (millions) Socio-demographic characteristics Disability-related compensatory strategies Specific unmet needs At least three chronic conditions; plus at least one ADL/IADL limitation (MCC) 6.7 Female Age 70–79 Environmental modifications Use mobility device Has more total helpers Daughter(s) helping Son(s) helping Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without a hot meal Diagnosis of probable dementia (DEM) 1.2 Age 75 and older Black non-Hispanic Other race non-Hispanic Low income Residential care Has more total helpers Use paid help Spouse helping Daughter(s) helping Wet or soiled clothing Had to stay in bed Had to stay inside Limited home mobility Died within 1 year of baseline assessment (EOL) 0.2 Age 85 and older Use mobility device Friend(s) helping Had to stay inside Conditions + dementia 1.4 Age 75 and older Hispanic Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Grandchild(ren) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without clean laundry Went without a hot meal Conditions + died 0.4 White (>Black non-Hispanic) Environmental modifications Use mobility device Has more total helpers Use paid help Grandchild(ren) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without groceries Went without a hot meal Dementia + died 0.2 Male Age 80 and older Residential care Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Limited home mobility Conditions + dementia + died 0.3 Male Age 85 and older Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Population estimate (millions) Socio-demographic characteristics Disability-related compensatory strategies Specific unmet needs At least three chronic conditions; plus at least one ADL/IADL limitation (MCC) 6.7 Female Age 70–79 Environmental modifications Use mobility device Has more total helpers Daughter(s) helping Son(s) helping Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without a hot meal Diagnosis of probable dementia (DEM) 1.2 Age 75 and older Black non-Hispanic Other race non-Hispanic Low income Residential care Has more total helpers Use paid help Spouse helping Daughter(s) helping Wet or soiled clothing Had to stay in bed Had to stay inside Limited home mobility Died within 1 year of baseline assessment (EOL) 0.2 Age 85 and older Use mobility device Friend(s) helping Had to stay inside Conditions + dementia 1.4 Age 75 and older Hispanic Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Grandchild(ren) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without clean laundry Went without a hot meal Conditions + died 0.4 White (>Black non-Hispanic) Environmental modifications Use mobility device Has more total helpers Use paid help Grandchild(ren) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without groceries Went without a hot meal Dementia + died 0.2 Male Age 80 and older Residential care Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Limited home mobility Conditions + dementia + died 0.3 Male Age 85 and older Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Note: National Health and Aging Trends Study (NHATS, 2011). Population includes adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task and meet at least one high-need/high-cost criteria. Full models available as a Supplementary Appendix. View Large Table 4. Summary Profiles of High-Need Patient Groups Based on Multivariate Models Population estimate (millions) Socio-demographic characteristics Disability-related compensatory strategies Specific unmet needs At least three chronic conditions; plus at least one ADL/IADL limitation (MCC) 6.7 Female Age 70–79 Environmental modifications Use mobility device Has more total helpers Daughter(s) helping Son(s) helping Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without a hot meal Diagnosis of probable dementia (DEM) 1.2 Age 75 and older Black non-Hispanic Other race non-Hispanic Low income Residential care Has more total helpers Use paid help Spouse helping Daughter(s) helping Wet or soiled clothing Had to stay in bed Had to stay inside Limited home mobility Died within 1 year of baseline assessment (EOL) 0.2 Age 85 and older Use mobility device Friend(s) helping Had to stay inside Conditions + dementia 1.4 Age 75 and older Hispanic Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Grandchild(ren) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without clean laundry Went without a hot meal Conditions + died 0.4 White (>Black non-Hispanic) Environmental modifications Use mobility device Has more total helpers Use paid help Grandchild(ren) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without groceries Went without a hot meal Dementia + died 0.2 Male Age 80 and older Residential care Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Limited home mobility Conditions + dementia + died 0.3 Male Age 85 and older Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Population estimate (millions) Socio-demographic characteristics Disability-related compensatory strategies Specific unmet needs At least three chronic conditions; plus at least one ADL/IADL limitation (MCC) 6.7 Female Age 70–79 Environmental modifications Use mobility device Has more total helpers Daughter(s) helping Son(s) helping Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without a hot meal Diagnosis of probable dementia (DEM) 1.2 Age 75 and older Black non-Hispanic Other race non-Hispanic Low income Residential care Has more total helpers Use paid help Spouse helping Daughter(s) helping Wet or soiled clothing Had to stay in bed Had to stay inside Limited home mobility Died within 1 year of baseline assessment (EOL) 0.2 Age 85 and older Use mobility device Friend(s) helping Had to stay inside Conditions + dementia 1.4 Age 75 and older Hispanic Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Grandchild(ren) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without clean laundry Went without a hot meal Conditions + died 0.4 White (>Black non-Hispanic) Environmental modifications Use mobility device Has more total helpers Use paid help Grandchild(ren) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without groceries Went without a hot meal Dementia + died 0.2 Male Age 80 and older Residential care Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Limited home mobility Conditions + dementia + died 0.3 Male Age 85 and older Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Note: National Health and Aging Trends Study (NHATS, 2011). Population includes adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task and meet at least one high-need/high-cost criteria. Full models available as a Supplementary Appendix. View Large Discussion This article reports associations between HNHC patient status and adverse consequences of unmet needs in a nationally representative sample of adults age 65 and older. The key finding of the paper is that HNHC older adults report much higher levels of adverse consequences of unmet needs for ADL and mobility assistance than low need patients, despite more disability compensatory efforts, including environmental modifications, mobility device use, paid caregiver use, and larger informal helper networks. Those meeting multiple HNHC criteria—MCCs, dementia, and those near the end-of-life—are at even greater risk of adverse consequences. Among MCC only older adults—the most common definition of HNHC in prior research—31.6% reported at least one adverse consequence of unmet need compared to more than half of those with MCC + EOL (53.2%) and MCC + DEM (53.4%). Nearly two-thirds (65.6%) of persons meeting all three criteria had at least one adverse consequence in the month prior to the interview. The HNHC groups were less likely to report adverse consequences of unmet higher level IADL needs. In fact the group meeting all three criteria were actually less likely than the low need group to report adverse IADL consequences. This could be because these older adults are more likely to be bed bound or limited in their ability to get around, so there is less opportunity for unmet needs for things like laundry, shopping, groceries, etc. That is, the HNHC groups may be at much more advanced stages of the disability process and require only mobility and ADL care. Unmet needs for IADL care are much more relevant in the earlier stages of the disability and caregiving trajectory (Schulz & Eden, 2016). This may also explain the counterintuitive finding that younger age was associated with higher levels of unmet needs. The oldest old may be extremely limited in terms of mobility and thus have less opportunity for unmet needs and adverse consequences. This study thus replicates and extends previous research showing that greater levels of disability are associated more adverse consequences of unmet needs—the greater the need, the more likely that some needs will go unmet (Allen & Mor, 1997; Desai et al., 2001; Kennedy, 2001; Lima & Allen, 2001; Newcomer et al., 2005). It also extends the literature by using a more inclusive HNHC definition and exploring the additive effects of meeting multiple HNHC criteria. Results suggest that HNHC older adults’ informal caregivers have trouble meeting their needs in home and community settings. Recall that over 90 percent of the sample were receiving help from at least one caregiver. Thus, only a small portion of the adverse consequences of unmet needs reported were the result of having no one to help. These adverse consequences of unmet needs are in fact likely contributors to worsening health and thus ultimately higher costs. Follow-up studies are needed to explore such dynamics. Our analyses also show that the HNHC patient groups and combinations have somewhat distinct profiles. They differ in terms of socio-demographics (i.e., who they are), how they and their caregivers attempt to compensate for their disability, and in the specific types of adverse consequences of unmet needs they tend to report. Both older adults with MCCs and functional disability and those with dementia can be considered HNHC, but they present unique challenges, as do those who have both MCC and DEM. These HNHC profiles can help to further inform the design of successful care models aimed at improving health and reducing costs (Anderson et al., 2015; McCarthy et al., 2015). For example, the HNHC criteria and socio-demographic profiles can aid in the targeting of older adults most likely to benefit from interventions. The adverse consequences of unmet needs profiles can help to target intervention content and potentially improve self-care strategies and/or caregiver engagement in older adults’ care (McCarthy et al., 2015). The results also have important implications for the caregivers of HNHC older adults. Our results provide empirical evidence that despite caregivers’ effort to support the need of their care-recipients, care-recipients still report adverse consequences of unmet needs. Beach and Schulz (2017) reported that caregivers of older adults with multiple adverse consequences of unmet needs were themselves more likely to be stressed and burdened, which may put the patient at risk of poor care and/or neglect. A recent report from the National Academies of Sciences, Engineering, and Medicine (NASEM, Schulz & Eden, 2016) stressed the importance of transforming the policies and practices affecting support for families caring for disabled older adults. The report stressed the need for (1) identifying family caregivers and to comprehensively assess caregiver needs, risks, strengths and preferences in taking on the caregiving role within long-term services and supports (LTSS) system; (2) developing and implementing support/interventions programs to educate and assist caregivers with participation in patient care and coordination; and (3) enhancing the competencies of healthcare and LTSS providers to engage caregivers as partners in caring for patients. Note that these recommendations are consistent with the suggested promotion of patients’ and family caregivers’ engagement in patient self-care from the HNHC literature (e.g., McCarthy et al., 2015). By detailing the specific adverse consequences of unmet needs by each HNHC group, our results can inform evidence-based interventions to potentially improve caregivers’ abilities to better meet these complex needs. We cannot tell from these data why older adults with caregivers are not having their needs met and thus experiencing adverse consequences. Perhaps they need more hours of care than their family caregivers can provide. From a policy standpoint, this would mean that more resources need to be put into formal care to assist family caregivers. Alternatively, if caregivers are too stressed to perform all necessary care requirements, respite services might be what is needed to allow caregivers time to become refreshed and better able to manage the caregiving tasks or they may need other formal or informal caregivers to help with specific care tasks. Finally, if it is a lack of education or training that is the reason for these findings, then enhanced patient/caregiver training may be the answer. Which of these (or what combination) is the reason for the adverse consequences of unmet needs of the HNHC groups should be investigated in future work. Given limited health care and long-term care support resources, it is important to know both where investments should be made and where savings might be achieved. To achieve this, research needs to identify high need caregivers who need support and high cost patients for whom alternative care strategies might lower costs. This strategy is consistent with the recently released NASEM report (Schulz & Eden, 2016) that advocates a model of family and person centered care in which patient care is closely integrated with caregiver training and support. Developing new models of care for high need/high cost patients will be challenging but is likely to have the highest payoffs in terms of caregiver and patient outcomes as well as cost savings. This study has limitations that apply to any survey, including the sample design, participant nonresponse, and the specific questions asked. Missing data on some of the indicators and analyses may have biased the results somewhat. The small sample sizes in some of the HNHC groups (<100) is a limitation, and the findings will require replication in larger samples of HNHC sub-groups. The article also does not explicitly examine links between HNHC status and actual health outcomes and/or healthcare spending. Follow-up analyses are planned that will link HNHC status, adverse consequences of unmet needs for informal care, health outcome, and healthcare utilization and costs (using Medicare data linkage). On a related note, because the analyses are cross-sectional, we are unable to comment on the causal processes underlying the observed effects. That is, we cannot determine from these cross-sectional analyses whether HNHC status results in adverse consequences of unmet needs; or whether not meeting informal care needs results in HNHC status. This would require follow-up longitudinal analyses. Conclusions and Implications This article provides detailed evidence on high levels of adverse consequences of unmet needs for care among HNHC older adults, despite increased efforts to compensate for disability. Persons in different HNHC groups have specific profiles of socio-demographics, disability compensatory strategies, and specific adverse consequences of unmet needs. Those meeting multiple HNHC criteria tend to be at most risk for adverse consequences. The results have important implications for the design and implementation of care management and coordination plans for patients with complex medical needs. Healthcare providers and others in the LTSS who treat and interface with HNHC patients should assess for unmet informal care needs and resulting adverse consequences. Providers should also assess family caregivers’ needs and skills, and provide them with the support and partnering needed to ensure their loved ones receive care of the highest quality. As U.S. policymakers and providers seek to contain healthcare costs by reducing hospitalization and unplanned readmissions, addressing adverse consequences of unmet needs of HNHC older adults should be considered as an important component of these strategies. Supplementary Material Supplementary data is available at The Journals of Gerontology Series B: Psychological and Social Sciencesonline. 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Washington, DC : National Academies of Sciences, Engineering and Medicine, The National Academies . Google Scholar CrossRef Search ADS Xu , H. , Covinsky , K. E. , Stallard , E. , Thomas , J. III , & Sands , L. P . ( 2012 ). Insufficient help for activity of daily living disabilities and risk of all-cause hospitalization . Journal of the American Geriatrics Society , 60 , 927 – 933 . doi: 10.1111/ j.1532-5415.2012.03926.x Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journals of Gerontology Series B: Psychological Sciences and Social Sciences Oxford University Press

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Abstract

Abstract Objectives We explore adverse consequences of unmet needs for care among high-need/high-cost (HNHC) older adults. Method Interviews with 4,024 community-dwelling older adults with ADL/IADL/mobility disabilities from the 2011 National Health and Aging Trends Study (NHATS). Reports of socio-demographics, disability compensatory strategies, and adverse consequences of unmet needs in the past month were obtained from older adults with multiple chronic conditions (MCC), probable dementia (DEM), and/or near end-of-life (EOL) and compared older adults not meeting these criteria. Results Older adults with MCC (31.6%), DEM (39.6%), and EOL (48.7%) reported significantly more adverse consequences than low-need older adults (21.4%). Persons with MCC and DEM (53.4%), MCC, and EOL (53.2%), and all three (MCC, DEM, EOL, 65.6%) reported the highest levels of adverse consequences. HNHC participants reported more environmental modifications, assistive device, and larger helper networks. HNHC status independently predicted greater adverse consequences after controlling for disability compensatory strategies in multivariate models. Discussion Adverse consequences of unmet needs for care are prevalent among HNHC older adults, especially those with multiple indicators, despite more disability-related compensatory efforts and larger helper networks. Helping caregivers provide better informal care has potential to contain healthcare costs by reducing hospitalization and unplanned readmissions. Alzheimer’s disease, Caregiving, Death and dying, Disability Introduction Informal caregivers play a critical role in maintaining the health of loved ones who suffer from chronic illness or disability (Schulz & Eden, 2016). While many informal family caregivers adequately meet the needs of disabled or chronically ill older adults, this may not always be the case. There is a growing literature on the prevalence and correlates of unmet needs for help with basic activities of daily living (ADL) and instrumental activities of daily living (IADL) among disabled older adults (Allen & Mor, 1997; DePalma et al., 2013; Desai, Lentzner, & Weeks, 2001; Hass, DePalma, Craig, Xu, & Sands, 2017; He et al., 2015; Kennedy, 2001; Lima & Allen, 2001; Newcomer, Kang, LaPlante, & Kaye, 2005; Sands et al., 2006; Xu, Covinsky, Stallard, Thomas, & Sands, 2012). While prevalence of unmet needs for specific ADL/IADL tasks varies widely, a few early studies using national probability samples found overall prevalence for any unmet need during the past month of approximately 20% (Desai et al., 2001; Kennedy, 2001; Newcomer et al., 2005). A consistent finding across these studies was that higher levels of disability were associated with more unmet needs—the greater the needs for assistance, the less likely they were to be completely met (Allen & Mor, 1997; Desai et al., 2001; Kennedy, 2001; Lima & Allen, 2001; Newcomer et al., 2005). Other correlates of unmet needs included low income/poverty, living alone, minority status, and poor overall health. More recently, research has linked unmet needs with increased risk of hospitalizations (Sands et al., 2006; Xu et al., 2012), hospital re-admissions (DePalma et al., 2013), emergency department admissions, particularly for falls and injuries (Hass et al., 2017), and mortality (He et al., 2015). This article examines adverse consequences of unmet needs for care among older adults with disability form the National Health and Aging Trends Study (NHATS). This contrasts with the literature reviewed above, which examined unmet (or undermet) needs for care, but not specific consequences of unmet need. Existing frameworks in the caregiving literature emphasize functional disability of the patient as a primary driver of caregiver and patient outcomes. Thus, adverse caregiving effects are often attributed to the tasks and time demands associated with the functional disability of the patient (Pearlin, Mullan, Semple, & Skaff, 1990; Pinquart & Sörensen, 2003). More recently, this approach has been augmented by longitudinal perspectives of the caregiving experience which emphasize the cumulative nature of disease and disability and the associated caregiving experience. Over time, caregiving becomes more complex and challenging because of increasing chronic disease burden, disability, and ultimately terminal illness (Schulz & Eden, 2016). This perspective has been further advanced by policy driven approaches which emphasize the need to differentiate between those caregivers and patients who have the greatest need for support, and/or who incur the highest health care costs (Blumenthal & Abrams, 2016; Blumenthal, Chernof, Fulmer, Lumpkin, & Selberg, 2016). This article builds on these approaches by examining adverse consequences of unmet needs for care among high-need, high-cost (HNHC) older adults and the additive effects of meeting multiple high-need, high-cost criteria. We defined high-need/high cost older adults as meeting the following criteria in addition to a functional limitation with at least one ADL/IADL task: (1) patients who have three or more chronic diseases (Hayes et al., 2016); (2) patients with a diagnosis of probable dementia (DEM); and (3) patients at the end of life. Together, these three groups represent some of the highest cost patients in the United States, accounting for the majority of health and long-term care expenditures (Hogan, Lunney, Gabel, & Lynn, 2001; Hurd, Martorell, & Langa, 2013; Kelley, McGarry, Gorges, & Skinner, 2015; Riley & Lubitz, 2010; Schulz et al., 2018). We focus not only on the three types of HNHC older adults in isolation, but we also examine the additive effects of meeting more than one of the three HNHC criteria on adverse consequences of unmet needs for care. The group of older adults with difficulty or needing help with at least one ADL/IADL but not meeting any of the HNHC criteria (i.e., low need) serves as the comparison group. In a series of policy briefs, The Commonwealth Fund has documented HNHC patient socio-demographic characteristics, healthcare spending, and experiences with the healthcare system in the United States. (Hayes et al., 2016; Ryan, Abrams, Doty, Shah, & Schneider, 2016; Salzberg et al., 2016). They found that HNHC patients—defined in their work as having three or more chronic health conditions plus at least one functional limitation—were more likely to be low income, have higher out-of-pocket health costs, more emergency department visits and hospital stays, and more doctor visits and paid home health care days (Hayes et al., 2016). In terms of healthcare experiences, HNHC patients (especially those with private insurance) were more likely to report unmet medical needs and less likely to report good patient-provider communication (Salzberg et al., 2016). Ryan et al. (2016) found that HNHC patients were more likely to be socially isolated and living in poverty and were less likely to experience timely and convenient access to care. HNHC patients were also unlikely to have an informed care coordinator and reported needing more help with ADL/IADL activities (assessed with a single summary question) than they were currently receiving (Ryan et al., 2016). Other research has focused on care management models for HNHC patients, including development and evaluation of programs designed to improve health outcomes and reduce costs (Anderson et al., 2015; Bleich et al., 2015; Blumenthal & Abrams, 2016; Blumenthal et al., 2016; Hong, Siegel, & Ferris, 2014; McCarthy, Ryan, & Klein, 2015). Successful approaches involve specific targeting of HNHC patients for intervention, comprehensive assessment of patient risks and needs, care planning and routine patient monitoring, care coordination and communication among providers and the patient, and facilitation of transitions of care from hospital to home or post-acute care (Anderson et al., 2015; McCarthy et al., 2015). Another recommendation from this work is the promotion of patients’ and family caregivers’ engagement in patient self-care. Family caregivers are critical for fostering patient self-care (Schulz & Eden, 2016). Family members oftentimes serve as liaison between doctors and patients and work with patients to implement care strategies. They can also promote preventative health and influence health behaviors of patients. These efforts may reduce health care costs and utilization by improving patient health. The role of family caregivers in the care of HNHC patients is of central interest in this article. In sum, HNHC patients and older adults are of great concern due to poor health outcomes, high healthcare utilization rates, and resulting high health care costs. Researchers, health care providers, and policy makers are trying to implement evidence-based practices to improve HNHC health outcomes and reduce costs. Other research on unmet needs for ADL/IADL assistance among disabled older adults shows that those who lack the help they need from informal caregivers are also at higher risk for poor health, increased health care utilization, and high costs. Interestingly, some of the same correlates—poverty, social isolation—have been found for HNHC patients and disabled older adults with unmet needs for informal help. In addition, while studies of unmet need are consistent in finding that greater disability is associated with more unmet need—the greater the need, the less likely it is to be fully met—researchers have not explicitly linked HNHC status with unmet ADL/IADL needs in a detailed way. This article adds to the HNHC and unmet needs literature in several ways. It explores in detail explicit linkages between HNHC status and adverse consequences of unmet needs. Second, the analysis includes indicators of disability-related compensatory strategies as potential mediators of adverse consequences of unmet needs, including environmental accommodations, use of mobility devices, paid home caregiver use, and detailed information about informal caregiver network size and composition. These strategies are conceptualized as accommodations in the disability conceptual framework proposed by Freedman (2009), which guided the design of The National Health and Aging Trends Study (NHATS). This article uses NHATS data (see below), which provided detailed assessments of the disability compensation strategies. We hypothesized that HNHC older adults would use more of these strategies and also explore whether environmental accommodations, use of mobility devices, paid home caregiver use, and large informal caregiver networks prevent or reduce (i.e., mediate) adverse consequences of unmet need. Third, we further refine the HNHC construct by focusing on older adults who meet more than one of the three criteria just mentioned—we examine the potential additive effects of combinations of multiple chronic conditions (MCCs), DEM, and end-of-life on use of disability compensatory strategies and adverse consequences of unmet needs. The results of these analyses can further inform the design of interventions for HNHC older adults and caregivers aiming to improve health outcomes and reduce healthcare costs. We provide an analysis of adverse consequences of unmet needs among HNHC older adults in a nationally representative, population-based study—The National Health and Aging Trends Study (NHATS). Freedman and Spillman (2014) analyzed the NHATS sample and found that 31.8% of older adults with ADL/IADL difficulty or needing help reported at least one adverse consequence related to unmet needs for care within the past month. The most common adverse consequences were wet or soiled clothing, having to stay inside, limited mobility inside one’s home/building, and medication errors. Beach and Schulz (2017) linked adverse consequences of unmet needs among NHATS care recipients with the characteristics of their informal caregivers from the companion National Study of Caregiving (NSOC). They found that older adults reporting multiple adverse consequences had caregivers who were more likely to spend >100 h/month caregiving, help with skin care and wounds, report caregiving as emotionally and physically difficult, and report restricted participation in valued activities. They concluded that caregivers experiencing high levels of burden, stress, and negative physical and psychosocial impacts may provide substandard/poor care to older adults, which may be a risk factor for neglect. We use the same data to further examine the relationship between health conditions and adverse consequences of unmet needs by distinguishing between three different types of HNHC groups, and also identifying individuals with different combinations of HNHC. We examine these groups to see how they compare in terms of socio-demographic characteristics, compensatory and caregiving strategies used to accommodate disabilities, and number and types of adverse consequences of unmet needs. We then use multivariate logistic regression models to examine the relationship between each HNHC group and number and type of adverse consequences of unmet needs. The results of these analyses can further inform the design of interventions for HNHC older adults and caregivers aiming to improve health outcomes and reduce healthcare costs by highlighting the groups at greatest risk of adverse consequences of unmet needs. Methods Data The data used in this study are publicly available, do not contain individual identifiers, and are, therefore, exempt from institutional review board review. A detailed description of the data sources for this study was provided in recent publications (Beach & Schulz, 2017; Freedman & Spillman, 2014) and portions of this section are repeated from these sources. The NHATS is nationally representative of Americans 65 years and older. The first round of NHATS took place in 2011 with a national sample of older adults drawn from the Medicare enrollment file. This article presents analyses of this baseline assessment. In-person interviews were conducted with study participants or with proxy respondents if the participant was unable to respond. In all, 7,609 in-person interviews were completed, including 583 with proxy respondents. (An additional 468 nursing home residents were enrolled in the study but are not included in these analyses.) Study participants were asked whether and how they performed daily activities in the month before the interview. This article focuses on the subset of 4,024 NHATS participants who reported they had at least some difficulty and/or were receiving help with at least 1 of 12 ADL/mobility/IADL tasks (toileting, eating, bathing, dressing, getting out of bed, getting outside, getting around inside, doing laundry, shopping, making hot meals, paying bills/banking, managing medications). The vast majority of the sample (91.8%) had at least one informal caregiver providing help with at least one ADL/mobility/IADL task (8.2% reported receiving no help), with 36.5% reporting one helper, 29.4% two helpers, 14.9% three helpers, and 11% four or more helpers. Measures High-need, high-cost (HNHC) groups Three main HNHC groups were used: (1) multiple chronic conditions (MCC), defined as having at least three of seven self-reported chronic conditions (heart attack/heart disease/high blood pressure, arthritis, osteoporosis, diabetes, lung disease, stroke, cancer); (2) probable dementia (DEM), based on a combination of self-/proxy-report and performance-based cognitive testing from NHATS (Kasper, Freedman, & Spillman, 2013); and (3) end-of-life (EOL), participants who had died within 1 year of the baseline assessment, as confirmed by NHATS code of deceased at the wave 2 assessment. Recall that all study participants had a functional limitation with at least one ADL/IADL task. Thus, the HNHC groups include functional limitations in addition to MCC, DEM, and EOL. The “low need” comparison group consists of older adults with functional limitations who do not meet any of the HNHC criteria. The seven chronic conditions used were those available in the NHATS data set, and we should note that these differ slightly from some previous definitions (Hayes et al., 2016). The NHATS classification of DEM required a self- or proxy report that a doctor told the sample person that he/she had dementia or Alzheimer’s; or (in the absence of this) scoring at least 1.5 SDs below the mean on at least two of the following in cognitive domains—memory, orientation, and executive functioning (Kasper, Freedman, & Spillman, 2013). A proxy report on the AD8 Dementia Screening Interview (Galvin et al., 2005; Galvin, Roe, Xiong, & Morris, 2006) of two or higher (i.e., meeting dementia criteria) was also used to classify DEM. Participants were classified as possible dementia when there was no self-reported diagnosis, but who scored at 1.5 SDs below the mean on one of the three cognitive domains. Note that our HNHC dementia criteria was a DEM classification in NHATS—possible dementia cases were not included. An older adult was considered HNHC if they fell into one or more of these three groups. We also examined overlap among the three HNHC groups, summarized in Figure 1, which includes unweighted sample sizes and estimated population sizes. For example, 1,564 NHATS participants met our definition of MCC only, with another 396 having both MCC and DEM, 98 also being EOL, and 96 meeting all three criteria. Figure 1. View largeDownload slide Three overlapping high need patient populations. National Health and Aging Trends Study (NHATS, 2011). CHRONIC CONDS = at least three chronic conditions and one ADL/IADL limitation. END OF LIFE = died within 1 year of baseline assessment and one ADL/IADL limitation. DEMENTIA = diagnosis of probable dementia and one ADL/IADL limitation. NONE OF THE ABOVE = N = 1,379; 6.2M; has at least one ADL/IADL limitation. Figure reports unweighted sample size, and estimated weighted population size. Figure 1. View largeDownload slide Three overlapping high need patient populations. National Health and Aging Trends Study (NHATS, 2011). CHRONIC CONDS = at least three chronic conditions and one ADL/IADL limitation. END OF LIFE = died within 1 year of baseline assessment and one ADL/IADL limitation. DEMENTIA = diagnosis of probable dementia and one ADL/IADL limitation. NONE OF THE ABOVE = N = 1,379; 6.2M; has at least one ADL/IADL limitation. Figure reports unweighted sample size, and estimated weighted population size. Adverse consequences of unmet needs Respondents were asked single questions (for each ADL/mobility/IADL task) assessing whether during the past month they experienced a negative consequence because there was no one there to help (for those reporting that they never performed the task without help in a prior question); or it was too difficult to do by themselves without additional help (for those reporting that they performed the task by themselves rarely, sometimes, or most times) (see Table 3 for specific consequences of unmet needs). Adverse consequences of unmet needs are analyzed using both summary indicators (i.e., any adverse consequences, any ADL/mobility/IADL adverse consequences) and individually (e.g., wet or soiled clothing, had to stay inside). The individual adverse consequences items had very low levels of missing data (range n = 0–10 missing); and all cases were included in the summary indicator analyses. Socio-demographics We examined gender, age, race/ethnicity, income (quartiles based on the entire n = 7,609 NHATS baseline sample), and living arrangements—whether the older adult lived alone and whether he/she lived in a residential care (non-nursing home) setting. Responses were obtained or calculated for all 4,024 participants on all socio-demographic variables except for race (missing for n = 46). The multivariate model race dummy variables (see below) include the missing cases in the reference group, and this does not affect the key results (i.e., no difference when the 46 cases are dropped). Disability compensatory strategies Environmental modifications were assessed with self-reports of the following added to the home in the last year: a ramp, elevator, stair lift, shower grab bars, shower/tub seat, raised toilet seat, and toilet grab bars. For analysis, we examined whether any of these environmental modifications had been added in the previous year. Mobility device use was assessed with questions asking whether any of the following were present: uses a cane, uses a walker, uses a wheelchair, has a wheelchair at home, uses a scooter, has a scooter at home. For analysis, we examined whether any of these mobility device use indicators were present. The informal helper network was assessed for those who reported receiving help with each ADL/IADL task. A detailed helper roster lists the relationship and specific activities for each person providing assistance. For analysis, we used the total number of informal helpers listed, plus the presence of various helper relationship types (e.g., at least one of the helpers was a spouse, daughter, son, etc.). We also examined the presence of any paid informal caregivers, which was also measured through the detailed helper roster. Data on the informal helper network was missing for eight cases, and these were not included in the multivariate models described below. Data Analysis and Estimation We first describe the mutually exclusive and exhaustive HNHC groups (as shown in Figure 1) in terms of socio-demographic variables and disability compensatory strategies. We use percentages and logistic regression models to compare groups, with a focus on contrasts to the “low need” disabled older adults not meeting HNHC criteria. We then use the same percentages and logistic methods to describe and compare HNHC groups in terms of adverse consequences of unmet needs (summary indices and individual adverse consequences). Then, multivariate logistic regression models are tested with summary measures of adverse consequences of unmet needs (any adverse consequences, any IADL, any mobility, any ADL) as outcomes and the seven mutually exclusive HNHC groups (single criteria, two criteria, all three criteria) as the key predictors (using the low need group as the reference). These models control for all socio-demographic and disability compensatory strategies and provide tests of independent HNHC—adverse consequences of unmet needs links, net of all other variables. The model also tests whether the disability compensatory strategies serve to reduce or eliminate (i.e., mediate) any HNHC—adverse consequences relationships. Finally, a series of multivariate models (included as Supplementary Appendices) are tested with HNHC group (plus socio-demographics and disability compensatory strategies) predicting each of the 12 specific ADL/mobility/IADL adverse consequences of unmet needs. (Models using socio-demographics to predict HNHC group membership; and models using HNHC groups to predict disability compensatory strategies are available from the author upon request.) These models are used to create summary profiles of each HNHC group/combination. Observations from the NHATS are weighted to produce nationally representative estimates. Survey weights, released with the NHATS public data use files that adjust for differential probabilities of selection and survey non-response, were used for all analyses. All analyses were conducted with statistical software (STATA, Version 14; StataCorp) using survey sampling weights and variance estimation procedures that account for the complex sampling strategy. Results Figure 1 shows unweighted sample sizes and weighted population estimates for each HNHC group or combination. These data are repeated in the first two rows of Table 1, which compares the HNHC groups on socio-demographic variables. The HNHC groups include an estimated 10.5 million older adults (age 65 and older), which represents 62.8% of the 16.7 million disabled older adults in NHATS. Note that the largest HNHC group by far is the MCC only group, with an estimated 6.7 million older adults. As shown in Table 1, The HNHC groups were more likely to be female, with the exception of the EOL and DEM + EOL groups. The HNHC groups are also older, as would be expected. Minority status is also related to HNHC group membership, with non-Hispanic Blacks being over-represented in the MCC and DEM groups, as well as the DEM + EOL, MCC + DEM, and the group with all three criteria. Hispanics were over-represented in the MCC + DEM group. HNHC status is associated with lower income. It is also associated with living in residential care settings (all socio-demographic differences, p < .001). There were no significant differences between the HNHC and low need groups in the prevalence of living alone. Table 1. Socio-demographic Characteristics by High Need Patient Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds+ dementia Chron Conds + died Dementia + Died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Population estimate (millions) 16.7 6.2 6.7 1.2 0.2 1.4 0.4 0.2 0.3 Gender  Male 37.1 44.1 30.5 36.4 46.5 34.5 37.1 50.6 40.4 Age  65–69 20.1 27.4 20.5 9.1 8.9 11.7 17.7 3.7 9.0  70–74 20.4 21.0 24.9 11.4 12.7 12.4 20.7 1.0 3.0  75–79 19.2 18.5 20.7 18.2 15.9 19.5 16.7 15.2 8.9  80–84 18.0 16.4 17.3 17.9 21.2 24.0 22.3 29.2 23.8  85–89 14.1 11.6 11.7 26.1 26.2 19.4 16.7 21.0 28.0  90 or older 7.4 5.2 4.8 17.4 15.2 13.0 5.9 29.9 27.3 Race  Non-Hispanic White 77.8 79.5 79.8 66.9 87.9 67.9 83.2 72.2 76.7  Non-Hispanic Black 9.4 7.8 10.1 13.2 5.5 11.4 4.8 13.1 10.2  Non-Hispanic other race 3.2 2.9 2.7 8.6 0.0 3.0 1.8 2.6 3.4  Hispanic 8.4 8.7 6.4 9.1 4.3 16.4 7.3 9.3 8.4 Income  Quartile 1 26.9 20.8 26.1 41.0 28.3 43.3 23.0 33.7 36.1  Quartile 2 28.0 26.5 27.6 29.6 24.2 28.4 41.5 39.9 38.3  Quartile 3 24.1 25.7 25.3 18.7 27.8 18.8 25.5 16.6 15.9  Quartile 4 21.0 27.1 21.1 10.8 19.8 9.4 9.9 9.9 9.7 Living arrangement  Living in residential care 10.4 8.1 8.5 22.9 15.7 13.1 12.6 27.1 18.0  Living alone 34.2 33.2 35.5 34.9 40.3 28.4 42.5 38.6 28.3 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds+ dementia Chron Conds + died Dementia + Died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Population estimate (millions) 16.7 6.2 6.7 1.2 0.2 1.4 0.4 0.2 0.3 Gender  Male 37.1 44.1 30.5 36.4 46.5 34.5 37.1 50.6 40.4 Age  65–69 20.1 27.4 20.5 9.1 8.9 11.7 17.7 3.7 9.0  70–74 20.4 21.0 24.9 11.4 12.7 12.4 20.7 1.0 3.0  75–79 19.2 18.5 20.7 18.2 15.9 19.5 16.7 15.2 8.9  80–84 18.0 16.4 17.3 17.9 21.2 24.0 22.3 29.2 23.8  85–89 14.1 11.6 11.7 26.1 26.2 19.4 16.7 21.0 28.0  90 or older 7.4 5.2 4.8 17.4 15.2 13.0 5.9 29.9 27.3 Race  Non-Hispanic White 77.8 79.5 79.8 66.9 87.9 67.9 83.2 72.2 76.7  Non-Hispanic Black 9.4 7.8 10.1 13.2 5.5 11.4 4.8 13.1 10.2  Non-Hispanic other race 3.2 2.9 2.7 8.6 0.0 3.0 1.8 2.6 3.4  Hispanic 8.4 8.7 6.4 9.1 4.3 16.4 7.3 9.3 8.4 Income  Quartile 1 26.9 20.8 26.1 41.0 28.3 43.3 23.0 33.7 36.1  Quartile 2 28.0 26.5 27.6 29.6 24.2 28.4 41.5 39.9 38.3  Quartile 3 24.1 25.7 25.3 18.7 27.8 18.8 25.5 16.6 15.9  Quartile 4 21.0 27.1 21.1 10.8 19.8 9.4 9.9 9.9 9.7 Living arrangement  Living in residential care 10.4 8.1 8.5 22.9 15.7 13.1 12.6 27.1 18.0  Living alone 34.2 33.2 35.5 34.9 40.3 28.4 42.5 38.6 28.3 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. View Large Table 1. Socio-demographic Characteristics by High Need Patient Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds+ dementia Chron Conds + died Dementia + Died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Population estimate (millions) 16.7 6.2 6.7 1.2 0.2 1.4 0.4 0.2 0.3 Gender  Male 37.1 44.1 30.5 36.4 46.5 34.5 37.1 50.6 40.4 Age  65–69 20.1 27.4 20.5 9.1 8.9 11.7 17.7 3.7 9.0  70–74 20.4 21.0 24.9 11.4 12.7 12.4 20.7 1.0 3.0  75–79 19.2 18.5 20.7 18.2 15.9 19.5 16.7 15.2 8.9  80–84 18.0 16.4 17.3 17.9 21.2 24.0 22.3 29.2 23.8  85–89 14.1 11.6 11.7 26.1 26.2 19.4 16.7 21.0 28.0  90 or older 7.4 5.2 4.8 17.4 15.2 13.0 5.9 29.9 27.3 Race  Non-Hispanic White 77.8 79.5 79.8 66.9 87.9 67.9 83.2 72.2 76.7  Non-Hispanic Black 9.4 7.8 10.1 13.2 5.5 11.4 4.8 13.1 10.2  Non-Hispanic other race 3.2 2.9 2.7 8.6 0.0 3.0 1.8 2.6 3.4  Hispanic 8.4 8.7 6.4 9.1 4.3 16.4 7.3 9.3 8.4 Income  Quartile 1 26.9 20.8 26.1 41.0 28.3 43.3 23.0 33.7 36.1  Quartile 2 28.0 26.5 27.6 29.6 24.2 28.4 41.5 39.9 38.3  Quartile 3 24.1 25.7 25.3 18.7 27.8 18.8 25.5 16.6 15.9  Quartile 4 21.0 27.1 21.1 10.8 19.8 9.4 9.9 9.9 9.7 Living arrangement  Living in residential care 10.4 8.1 8.5 22.9 15.7 13.1 12.6 27.1 18.0  Living alone 34.2 33.2 35.5 34.9 40.3 28.4 42.5 38.6 28.3 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds+ dementia Chron Conds + died Dementia + Died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Population estimate (millions) 16.7 6.2 6.7 1.2 0.2 1.4 0.4 0.2 0.3 Gender  Male 37.1 44.1 30.5 36.4 46.5 34.5 37.1 50.6 40.4 Age  65–69 20.1 27.4 20.5 9.1 8.9 11.7 17.7 3.7 9.0  70–74 20.4 21.0 24.9 11.4 12.7 12.4 20.7 1.0 3.0  75–79 19.2 18.5 20.7 18.2 15.9 19.5 16.7 15.2 8.9  80–84 18.0 16.4 17.3 17.9 21.2 24.0 22.3 29.2 23.8  85–89 14.1 11.6 11.7 26.1 26.2 19.4 16.7 21.0 28.0  90 or older 7.4 5.2 4.8 17.4 15.2 13.0 5.9 29.9 27.3 Race  Non-Hispanic White 77.8 79.5 79.8 66.9 87.9 67.9 83.2 72.2 76.7  Non-Hispanic Black 9.4 7.8 10.1 13.2 5.5 11.4 4.8 13.1 10.2  Non-Hispanic other race 3.2 2.9 2.7 8.6 0.0 3.0 1.8 2.6 3.4  Hispanic 8.4 8.7 6.4 9.1 4.3 16.4 7.3 9.3 8.4 Income  Quartile 1 26.9 20.8 26.1 41.0 28.3 43.3 23.0 33.7 36.1  Quartile 2 28.0 26.5 27.6 29.6 24.2 28.4 41.5 39.9 38.3  Quartile 3 24.1 25.7 25.3 18.7 27.8 18.8 25.5 16.6 15.9  Quartile 4 21.0 27.1 21.1 10.8 19.8 9.4 9.9 9.9 9.7 Living arrangement  Living in residential care 10.4 8.1 8.5 22.9 15.7 13.1 12.6 27.1 18.0  Living alone 34.2 33.2 35.5 34.9 40.3 28.4 42.5 38.6 28.3 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. View Large Table 2 shows relationships between HNHC status and various disability-related compensatory strategies. HNHC older adults were significantly more likely than low need persons to have had recent environmental modifications, to use mobility devices, and to use paid caregiving help (all p < .001). HNHC older adults also had significantly more informal helpers (p < .001). These differences are especially large for those meeting multiple HNHC criteria. In terms of presence of specific informal helper relationships, HNHC older adults were less likely to be cared for by a spouse (p < .001), and more likely to be cared for by daughters and sons (both p < .001). Adult children were most likely to be involved as caregivers when the older adult met multiple HNHC criteria. Grandchildren were also more likely to be involved as HNHC caregivers, especially when multiple criteria were met (p < .001). Those near the end-of-life had more friends as caregivers (p < .01). Table 2. Disability Compensatory Strategies by High Need Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia + died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Any environmental modifications 17.0 13.4 17.1* 17.3 21.0 26.3*** 27.5*** 14.2 28.8** Any mobility devices 44.8 30.6 48.1*** 46.5*** 67.9*** 68.6*** 68.0*** 74.8*** 79.4*** Number of helpers (mean) 1.8 1.5 1.8*** 2.1*** 1.8* 2.3*** 2.0* 2.7*** 2.6*** Any paid help 13.9 11.0 12.0 20.4*** 18.8 22.9*** 18.8* 28.1*** 30.4*** Caregiver relationship  Spouse 43.4 49.2 43.0* 33.9*** 31.9* 34.2*** 40.0 36.0 32.2**  Daughter 37.0 27.4 38.2*** 47.1*** 40.6* 54.8*** 40.9* 57.2*** 66.3***  Son 24.7 18.9 24.3*** 31.7*** 27.1 37.7*** 27.1 43.5*** 51.9***  Sibling 5.3 5.2 6.0 8.4* 3.6 1.5** 2.6 10.0 2.5  Grandchild 8.2 5.4 8.3** 11.0** 8.1 15.2*** 14.7** 9.4 10.0  Niece or nephew 3.1 2.5 2.5 5.5** 4.7 3.9 4.0 7.1** 6.4  Friend 11.1 10.9 12.5 8.1 21.9** 8.9 9.3 15.8 1.3***  Other family member 3.5 2.6 4.1 4.5 2.3 3.9 4.9 2.3 1.9  Other 9.4 9.3 9.0 9.5 8.9 9.5 11.8 6.2 15.6 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia + died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Any environmental modifications 17.0 13.4 17.1* 17.3 21.0 26.3*** 27.5*** 14.2 28.8** Any mobility devices 44.8 30.6 48.1*** 46.5*** 67.9*** 68.6*** 68.0*** 74.8*** 79.4*** Number of helpers (mean) 1.8 1.5 1.8*** 2.1*** 1.8* 2.3*** 2.0* 2.7*** 2.6*** Any paid help 13.9 11.0 12.0 20.4*** 18.8 22.9*** 18.8* 28.1*** 30.4*** Caregiver relationship  Spouse 43.4 49.2 43.0* 33.9*** 31.9* 34.2*** 40.0 36.0 32.2**  Daughter 37.0 27.4 38.2*** 47.1*** 40.6* 54.8*** 40.9* 57.2*** 66.3***  Son 24.7 18.9 24.3*** 31.7*** 27.1 37.7*** 27.1 43.5*** 51.9***  Sibling 5.3 5.2 6.0 8.4* 3.6 1.5** 2.6 10.0 2.5  Grandchild 8.2 5.4 8.3** 11.0** 8.1 15.2*** 14.7** 9.4 10.0  Niece or nephew 3.1 2.5 2.5 5.5** 4.7 3.9 4.0 7.1** 6.4  Friend 11.1 10.9 12.5 8.1 21.9** 8.9 9.3 15.8 1.3***  Other family member 3.5 2.6 4.1 4.5 2.3 3.9 4.9 2.3 1.9  Other 9.4 9.3 9.0 9.5 8.9 9.5 11.8 6.2 15.6 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. *p < .05, **p < .01, ***p < .001 in logistic regression with low need group as reference category. View Large Table 2. Disability Compensatory Strategies by High Need Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia + died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Any environmental modifications 17.0 13.4 17.1* 17.3 21.0 26.3*** 27.5*** 14.2 28.8** Any mobility devices 44.8 30.6 48.1*** 46.5*** 67.9*** 68.6*** 68.0*** 74.8*** 79.4*** Number of helpers (mean) 1.8 1.5 1.8*** 2.1*** 1.8* 2.3*** 2.0* 2.7*** 2.6*** Any paid help 13.9 11.0 12.0 20.4*** 18.8 22.9*** 18.8* 28.1*** 30.4*** Caregiver relationship  Spouse 43.4 49.2 43.0* 33.9*** 31.9* 34.2*** 40.0 36.0 32.2**  Daughter 37.0 27.4 38.2*** 47.1*** 40.6* 54.8*** 40.9* 57.2*** 66.3***  Son 24.7 18.9 24.3*** 31.7*** 27.1 37.7*** 27.1 43.5*** 51.9***  Sibling 5.3 5.2 6.0 8.4* 3.6 1.5** 2.6 10.0 2.5  Grandchild 8.2 5.4 8.3** 11.0** 8.1 15.2*** 14.7** 9.4 10.0  Niece or nephew 3.1 2.5 2.5 5.5** 4.7 3.9 4.0 7.1** 6.4  Friend 11.1 10.9 12.5 8.1 21.9** 8.9 9.3 15.8 1.3***  Other family member 3.5 2.6 4.1 4.5 2.3 3.9 4.9 2.3 1.9  Other 9.4 9.3 9.0 9.5 8.9 9.5 11.8 6.2 15.6 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia + died Chron Conds + dementia + died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Any environmental modifications 17.0 13.4 17.1* 17.3 21.0 26.3*** 27.5*** 14.2 28.8** Any mobility devices 44.8 30.6 48.1*** 46.5*** 67.9*** 68.6*** 68.0*** 74.8*** 79.4*** Number of helpers (mean) 1.8 1.5 1.8*** 2.1*** 1.8* 2.3*** 2.0* 2.7*** 2.6*** Any paid help 13.9 11.0 12.0 20.4*** 18.8 22.9*** 18.8* 28.1*** 30.4*** Caregiver relationship  Spouse 43.4 49.2 43.0* 33.9*** 31.9* 34.2*** 40.0 36.0 32.2**  Daughter 37.0 27.4 38.2*** 47.1*** 40.6* 54.8*** 40.9* 57.2*** 66.3***  Son 24.7 18.9 24.3*** 31.7*** 27.1 37.7*** 27.1 43.5*** 51.9***  Sibling 5.3 5.2 6.0 8.4* 3.6 1.5** 2.6 10.0 2.5  Grandchild 8.2 5.4 8.3** 11.0** 8.1 15.2*** 14.7** 9.4 10.0  Niece or nephew 3.1 2.5 2.5 5.5** 4.7 3.9 4.0 7.1** 6.4  Friend 11.1 10.9 12.5 8.1 21.9** 8.9 9.3 15.8 1.3***  Other family member 3.5 2.6 4.1 4.5 2.3 3.9 4.9 2.3 1.9  Other 9.4 9.3 9.0 9.5 8.9 9.5 11.8 6.2 15.6 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. *p < .05, **p < .01, ***p < .001 in logistic regression with low need group as reference category. View Large Table 3 shows differences between HNHC groups and low need groups on adverse consequences of unmet needs. The overall rate of adverse consequences is 31.8% (consistent with that previously reported by Freedman & Spillman, 2014), with 13.4% having adverse consequences of unmet IADL needs, 19.3% unmet mobility needs, and 12.6% unmet ADL needs. Results show that the HNHC groups have significantly more adverse consequences of unmet needs than their low need counterparts. The first row shows the prevalence of any (of 12) adverse consequences in the month prior to the assessment. The prevalence of adverse consequences of unmet needs is elevated for all HNHC groups (p < .001) and exceeded 50% in the MCC + EOL, MCC + DEM, and the group meeting all three criteria, among whom nearly two-thirds (65.6%) reported at least one adverse consequence. These patterns are stronger for unmet mobility (p < .001) and ADL (self-care; p < .001) needs than for unmet IADL needs (p < .01). Older adults meeting multiple HNHC criteria were also much more likely to report specific adverse consequences of unmet needs, primarily ADL-related and mobility-related. For example, over a third of those (34%) meeting all three criteria reported wet or soiled clothing in the past month due to unmet toileting needs. About one-fourth of the MCC + EOL, MCC + DEM, and those meeting all three criteria reported having to stay inside, and 16.1% of the MCC + EOL older adults had to stay in bed due to unmet needs. Note that medication mistakes were more prevalent among DEM, MCC + DEM, and MCC + EOL older adults. Table 3. Unmet Needs by High Need Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia+ died Chron Conds + dementia+ died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Summary measures  Any unmet need 31.8 21.4 31.6*** 39.6*** 48.7*** 53.4*** 53.2*** 46.2*** 65.6***  Any IADL unmet need 13.4 11.4 13.9 13.4 15.5 18.2** 25.7*** 5.6 6.0  Any mobility unmet need 19.3 10.4 20.0*** 23.1*** 31.8*** 36.5*** 42.9*** 28.1*** 43.4***  Any ADL unmet need 12.6 5.6 12.3*** 17.8*** 12.7* 28.6*** 26.6*** 26.9*** 41.2*** ADL  Wet or soiled clothing (toileting) 8.1 3.7 6.1** 15.3*** 5.4 21.3*** 18.7*** 24.1*** 34.0***  Went without eating 0.5 0.3 0.4 0.3 0.0 2.5** 2.1* 0.0 0.0  Went without bathing, showering, cleaning up 4.3 1.7 5.3*** 3.6 5.0 8.8*** 7.0** 6.4* 11.0***  Went without getting dressed 2.8 0.8 3.5*** 2.0 4.1 6.4*** 8.9*** 5.3** 6.5*** Mobility  Had to stay in bed 4.8 2.0 4.6*** 4.8** 1.9 13.6*** 16.1*** 10.1a 8.7**  Had to stay inside 12.2 7.2 12.3*** 13.1** 21.9*** 26.3*** 24.7*** 10.0 24.4***  Did not go places in home or building 10.1 4.7 10.4*** 14.0*** 12.1* 20.0*** 23.8*** 20.3*** 28.5*** IADL  Went without clean laundry 1.8 1.0 1.9 1.7 5.1* 4.0** 4.3* 0.0 0.0  Went without groceries 3.1 2.1 3.8* 3.1 0.5 2.7 11.4*** 2.0 0.0  Went without a hot meal 4.0 2.4 5.5** 2.4 6.1 3.8 11.2*** 2.0 0.0  Went without paying bills 1.9 1.8 1.6 2.3 0.0 4.0* 3.3 0.6 0.0  Made mistake taking medicine 6.9 5.9 6.5 8.7 5.3 11.6** 9.4 5.2 6.0 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia+ died Chron Conds + dementia+ died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Summary measures  Any unmet need 31.8 21.4 31.6*** 39.6*** 48.7*** 53.4*** 53.2*** 46.2*** 65.6***  Any IADL unmet need 13.4 11.4 13.9 13.4 15.5 18.2** 25.7*** 5.6 6.0  Any mobility unmet need 19.3 10.4 20.0*** 23.1*** 31.8*** 36.5*** 42.9*** 28.1*** 43.4***  Any ADL unmet need 12.6 5.6 12.3*** 17.8*** 12.7* 28.6*** 26.6*** 26.9*** 41.2*** ADL  Wet or soiled clothing (toileting) 8.1 3.7 6.1** 15.3*** 5.4 21.3*** 18.7*** 24.1*** 34.0***  Went without eating 0.5 0.3 0.4 0.3 0.0 2.5** 2.1* 0.0 0.0  Went without bathing, showering, cleaning up 4.3 1.7 5.3*** 3.6 5.0 8.8*** 7.0** 6.4* 11.0***  Went without getting dressed 2.8 0.8 3.5*** 2.0 4.1 6.4*** 8.9*** 5.3** 6.5*** Mobility  Had to stay in bed 4.8 2.0 4.6*** 4.8** 1.9 13.6*** 16.1*** 10.1a 8.7**  Had to stay inside 12.2 7.2 12.3*** 13.1** 21.9*** 26.3*** 24.7*** 10.0 24.4***  Did not go places in home or building 10.1 4.7 10.4*** 14.0*** 12.1* 20.0*** 23.8*** 20.3*** 28.5*** IADL  Went without clean laundry 1.8 1.0 1.9 1.7 5.1* 4.0** 4.3* 0.0 0.0  Went without groceries 3.1 2.1 3.8* 3.1 0.5 2.7 11.4*** 2.0 0.0  Went without a hot meal 4.0 2.4 5.5** 2.4 6.1 3.8 11.2*** 2.0 0.0  Went without paying bills 1.9 1.8 1.6 2.3 0.0 4.0* 3.3 0.6 0.0  Made mistake taking medicine 6.9 5.9 6.5 8.7 5.3 11.6** 9.4 5.2 6.0 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. *p < .05, **p < .01, ***p < .001 in logistic regression with low need group as reference category. View Large Table 3. Unmet Needs by High Need Category Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia+ died Chron Conds + dementia+ died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Summary measures  Any unmet need 31.8 21.4 31.6*** 39.6*** 48.7*** 53.4*** 53.2*** 46.2*** 65.6***  Any IADL unmet need 13.4 11.4 13.9 13.4 15.5 18.2** 25.7*** 5.6 6.0  Any mobility unmet need 19.3 10.4 20.0*** 23.1*** 31.8*** 36.5*** 42.9*** 28.1*** 43.4***  Any ADL unmet need 12.6 5.6 12.3*** 17.8*** 12.7* 28.6*** 26.6*** 26.9*** 41.2*** ADL  Wet or soiled clothing (toileting) 8.1 3.7 6.1** 15.3*** 5.4 21.3*** 18.7*** 24.1*** 34.0***  Went without eating 0.5 0.3 0.4 0.3 0.0 2.5** 2.1* 0.0 0.0  Went without bathing, showering, cleaning up 4.3 1.7 5.3*** 3.6 5.0 8.8*** 7.0** 6.4* 11.0***  Went without getting dressed 2.8 0.8 3.5*** 2.0 4.1 6.4*** 8.9*** 5.3** 6.5*** Mobility  Had to stay in bed 4.8 2.0 4.6*** 4.8** 1.9 13.6*** 16.1*** 10.1a 8.7**  Had to stay inside 12.2 7.2 12.3*** 13.1** 21.9*** 26.3*** 24.7*** 10.0 24.4***  Did not go places in home or building 10.1 4.7 10.4*** 14.0*** 12.1* 20.0*** 23.8*** 20.3*** 28.5*** IADL  Went without clean laundry 1.8 1.0 1.9 1.7 5.1* 4.0** 4.3* 0.0 0.0  Went without groceries 3.1 2.1 3.8* 3.1 0.5 2.7 11.4*** 2.0 0.0  Went without a hot meal 4.0 2.4 5.5** 2.4 6.1 3.8 11.2*** 2.0 0.0  Went without paying bills 1.9 1.8 1.6 2.3 0.0 4.0* 3.3 0.6 0.0  Made mistake taking medicine 6.9 5.9 6.5 8.7 5.3 11.6** 9.4 5.2 6.0 Total Low needa Chron Conds (MCC) Dementia (DEM) Died (EOL) Chron Conds + dementia Chron Conds + died Dementia+ died Chron Conds + dementia+ died Sample size (unweighted) 4,024 1,379 1,564 359 66 396 98 66 96 Summary measures  Any unmet need 31.8 21.4 31.6*** 39.6*** 48.7*** 53.4*** 53.2*** 46.2*** 65.6***  Any IADL unmet need 13.4 11.4 13.9 13.4 15.5 18.2** 25.7*** 5.6 6.0  Any mobility unmet need 19.3 10.4 20.0*** 23.1*** 31.8*** 36.5*** 42.9*** 28.1*** 43.4***  Any ADL unmet need 12.6 5.6 12.3*** 17.8*** 12.7* 28.6*** 26.6*** 26.9*** 41.2*** ADL  Wet or soiled clothing (toileting) 8.1 3.7 6.1** 15.3*** 5.4 21.3*** 18.7*** 24.1*** 34.0***  Went without eating 0.5 0.3 0.4 0.3 0.0 2.5** 2.1* 0.0 0.0  Went without bathing, showering, cleaning up 4.3 1.7 5.3*** 3.6 5.0 8.8*** 7.0** 6.4* 11.0***  Went without getting dressed 2.8 0.8 3.5*** 2.0 4.1 6.4*** 8.9*** 5.3** 6.5*** Mobility  Had to stay in bed 4.8 2.0 4.6*** 4.8** 1.9 13.6*** 16.1*** 10.1a 8.7**  Had to stay inside 12.2 7.2 12.3*** 13.1** 21.9*** 26.3*** 24.7*** 10.0 24.4***  Did not go places in home or building 10.1 4.7 10.4*** 14.0*** 12.1* 20.0*** 23.8*** 20.3*** 28.5*** IADL  Went without clean laundry 1.8 1.0 1.9 1.7 5.1* 4.0** 4.3* 0.0 0.0  Went without groceries 3.1 2.1 3.8* 3.1 0.5 2.7 11.4*** 2.0 0.0  Went without a hot meal 4.0 2.4 5.5** 2.4 6.1 3.8 11.2*** 2.0 0.0  Went without paying bills 1.9 1.8 1.6 2.3 0.0 4.0* 3.3 0.6 0.0  Made mistake taking medicine 6.9 5.9 6.5 8.7 5.3 11.6** 9.4 5.2 6.0 Notes: National Health and Aging Trends Study (NHATS, 2011). Population includes 4,024 adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task. aDoes not meet high need criteria but has limitations in IADL and/or ADL. *p < .05, **p < .01, ***p < .001 in logistic regression with low need group as reference category. View Large Supplementary Table 1 summarizes the multivariate logistic regression models using HNHC group status as a predictor of summary measures of adverse consequences of unmet needs for informal care. Checks for multi-collinearity revealed no predictor correlations greater than 0.40, with many less than 0.10. Tests for influential cases using Cook’s influence statistics and DfBeta values revealed no influential cases. These models simultaneously control for all socio-demographic and disability-related compensatory strategy variables. The results show that HNHC older adults are significantly more likely to have adverse consequences of unmet needs in the past month, net of any effect of socio-demographics or other efforts to compensate for disability. Mirroring the results just presented for Table 3, results were strongest for adverse consequences of unmet mobility and ADL needs, with less consistent impact on adverse consequences of unmet needs for IADL assistance. Looking first at any adverse consequences (column 1), six of the seven HNHC groups had significantly higher risk than the low need patient groups (and the DEM + EOL group was marginally higher). The adjusted odds ratios also show the additive effects of meeting more than one HNHC criteria. While those with MCC had a 42% higher chance of reporting any adverse consequences of unmet needs in the past month, those with both MCC + EOL and MCC + DEM were 2–3 times as likely, and those meeting all three HNHC criteria were nearly four times as likely as low need persons to report adverse consequences of unmet needs, controlling for socio-demographics and disability compensatory strategies. Other significant predictors included younger age, low income, use of mobility devices, paid caregiver use, and having a spouse as an informal helper. HNHC group results for adverse consequences of unmet mobility and ADL needs are similar. In both models, six of the seven HNHC groups had significantly more adverse consequences, and the groups meeting multiple criteria have the highest rates. The pattern for IADL adverse consequences is distinct, as HNHC status does not generally predict these, except for the MCC + EOL group. In fact, the group meeting all three criteria is significantly less likely to have adverse consequences of unmet IADL needs relative to the low need group. Table 4 presents summary profiles of each of the seven HNHC patient groups examined in the paper in terms of key socio-demographics, disability-related compensatory strategies, and specific adverse consequences of unmet needs during the past month. Results are based on multivariate modeling, full details of which are available from the authors upon request. Entries in the socio-demographics column were significant (p < .05) predictors of specific HNHC group membership (versus not a member of the group) in multivariate logistic regression models including all demographic variables as predictors. The compensatory strategy entries are based on models in which each strategy was regressed on simultaneously entered indicators of HNHC status (with the “low need” group as the reference category), controlling for all socio-demographic variables. An entry is shown if that HNHC group was statistically significant (p < .05) in the model with the listed compensatory strategy as the outcome variable. Supplementary Tables 2 and 4 show the models used to derive the entries for the specific unmet needs column. A specific unmet need is listed if the HNHC group was a statistically significant (p < .05) predictor in the model, which controls for all socio-demographics and compensatory strategies. In sum, the analyses show that the MCC, DEM, and EOL only groups are somewhat distinct, with the only characteristic they share is unmet needs for mobility assistance resulting in having to stay inside. For example, the MCC group tends to be female, age 70–79, has made environmental modifications, uses mobility devices, has more informal helpers and has adult children as helpers. They are also more likely to report going without bathing, without getting dressed, having to stay in bed, stay inside, have limited mobility in the home, and go without hot meals. The DEM and EOL groups have different profiles. The table also shows that HNHC older adults, as might be expected, use high levels of disability compensatory strategies. They make environmental modifications to their homes, use mobility devices, hire paid caregivers, and tend to mobilize larger more diverse and inter-generational informal helper networks. Despite these efforts, as we have shown, they still report high levels of adverse consequences of unmet needs. Lastly, note that those with both MCC + DEM and MCC + EOL tended to have the most adverse consequences of unmet needs, and the MCC + DEM uses the most disability compensatory strategies and tends to have the most diverse informal helper networks. Table 4. Summary Profiles of High-Need Patient Groups Based on Multivariate Models Population estimate (millions) Socio-demographic characteristics Disability-related compensatory strategies Specific unmet needs At least three chronic conditions; plus at least one ADL/IADL limitation (MCC) 6.7 Female Age 70–79 Environmental modifications Use mobility device Has more total helpers Daughter(s) helping Son(s) helping Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without a hot meal Diagnosis of probable dementia (DEM) 1.2 Age 75 and older Black non-Hispanic Other race non-Hispanic Low income Residential care Has more total helpers Use paid help Spouse helping Daughter(s) helping Wet or soiled clothing Had to stay in bed Had to stay inside Limited home mobility Died within 1 year of baseline assessment (EOL) 0.2 Age 85 and older Use mobility device Friend(s) helping Had to stay inside Conditions + dementia 1.4 Age 75 and older Hispanic Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Grandchild(ren) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without clean laundry Went without a hot meal Conditions + died 0.4 White (>Black non-Hispanic) Environmental modifications Use mobility device Has more total helpers Use paid help Grandchild(ren) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without groceries Went without a hot meal Dementia + died 0.2 Male Age 80 and older Residential care Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Limited home mobility Conditions + dementia + died 0.3 Male Age 85 and older Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Population estimate (millions) Socio-demographic characteristics Disability-related compensatory strategies Specific unmet needs At least three chronic conditions; plus at least one ADL/IADL limitation (MCC) 6.7 Female Age 70–79 Environmental modifications Use mobility device Has more total helpers Daughter(s) helping Son(s) helping Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without a hot meal Diagnosis of probable dementia (DEM) 1.2 Age 75 and older Black non-Hispanic Other race non-Hispanic Low income Residential care Has more total helpers Use paid help Spouse helping Daughter(s) helping Wet or soiled clothing Had to stay in bed Had to stay inside Limited home mobility Died within 1 year of baseline assessment (EOL) 0.2 Age 85 and older Use mobility device Friend(s) helping Had to stay inside Conditions + dementia 1.4 Age 75 and older Hispanic Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Grandchild(ren) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without clean laundry Went without a hot meal Conditions + died 0.4 White (>Black non-Hispanic) Environmental modifications Use mobility device Has more total helpers Use paid help Grandchild(ren) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without groceries Went without a hot meal Dementia + died 0.2 Male Age 80 and older Residential care Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Limited home mobility Conditions + dementia + died 0.3 Male Age 85 and older Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Note: National Health and Aging Trends Study (NHATS, 2011). Population includes adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task and meet at least one high-need/high-cost criteria. Full models available as a Supplementary Appendix. View Large Table 4. Summary Profiles of High-Need Patient Groups Based on Multivariate Models Population estimate (millions) Socio-demographic characteristics Disability-related compensatory strategies Specific unmet needs At least three chronic conditions; plus at least one ADL/IADL limitation (MCC) 6.7 Female Age 70–79 Environmental modifications Use mobility device Has more total helpers Daughter(s) helping Son(s) helping Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without a hot meal Diagnosis of probable dementia (DEM) 1.2 Age 75 and older Black non-Hispanic Other race non-Hispanic Low income Residential care Has more total helpers Use paid help Spouse helping Daughter(s) helping Wet or soiled clothing Had to stay in bed Had to stay inside Limited home mobility Died within 1 year of baseline assessment (EOL) 0.2 Age 85 and older Use mobility device Friend(s) helping Had to stay inside Conditions + dementia 1.4 Age 75 and older Hispanic Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Grandchild(ren) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without clean laundry Went without a hot meal Conditions + died 0.4 White (>Black non-Hispanic) Environmental modifications Use mobility device Has more total helpers Use paid help Grandchild(ren) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without groceries Went without a hot meal Dementia + died 0.2 Male Age 80 and older Residential care Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Limited home mobility Conditions + dementia + died 0.3 Male Age 85 and older Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Population estimate (millions) Socio-demographic characteristics Disability-related compensatory strategies Specific unmet needs At least three chronic conditions; plus at least one ADL/IADL limitation (MCC) 6.7 Female Age 70–79 Environmental modifications Use mobility device Has more total helpers Daughter(s) helping Son(s) helping Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without a hot meal Diagnosis of probable dementia (DEM) 1.2 Age 75 and older Black non-Hispanic Other race non-Hispanic Low income Residential care Has more total helpers Use paid help Spouse helping Daughter(s) helping Wet or soiled clothing Had to stay in bed Had to stay inside Limited home mobility Died within 1 year of baseline assessment (EOL) 0.2 Age 85 and older Use mobility device Friend(s) helping Had to stay inside Conditions + dementia 1.4 Age 75 and older Hispanic Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Grandchild(ren) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without clean laundry Went without a hot meal Conditions + died 0.4 White (>Black non-Hispanic) Environmental modifications Use mobility device Has more total helpers Use paid help Grandchild(ren) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Went without groceries Went without a hot meal Dementia + died 0.2 Male Age 80 and older Residential care Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without getting dressed Had to stay in bed Limited home mobility Conditions + dementia + died 0.3 Male Age 85 and older Low income Environmental modifications Use mobility device Has more total helpers Use paid help Daughter(s) helping Son(s) helping Wet or soiled clothing Went without bathing Went without getting dressed Had to stay in bed Had to stay inside Limited home mobility Note: National Health and Aging Trends Study (NHATS, 2011). Population includes adults age 65 and older who report difficulty with/or receive help with at least one instrumental activity of daily living (IADL)/activity of daily living (ADL)/mobility task and meet at least one high-need/high-cost criteria. Full models available as a Supplementary Appendix. View Large Discussion This article reports associations between HNHC patient status and adverse consequences of unmet needs in a nationally representative sample of adults age 65 and older. The key finding of the paper is that HNHC older adults report much higher levels of adverse consequences of unmet needs for ADL and mobility assistance than low need patients, despite more disability compensatory efforts, including environmental modifications, mobility device use, paid caregiver use, and larger informal helper networks. Those meeting multiple HNHC criteria—MCCs, dementia, and those near the end-of-life—are at even greater risk of adverse consequences. Among MCC only older adults—the most common definition of HNHC in prior research—31.6% reported at least one adverse consequence of unmet need compared to more than half of those with MCC + EOL (53.2%) and MCC + DEM (53.4%). Nearly two-thirds (65.6%) of persons meeting all three criteria had at least one adverse consequence in the month prior to the interview. The HNHC groups were less likely to report adverse consequences of unmet higher level IADL needs. In fact the group meeting all three criteria were actually less likely than the low need group to report adverse IADL consequences. This could be because these older adults are more likely to be bed bound or limited in their ability to get around, so there is less opportunity for unmet needs for things like laundry, shopping, groceries, etc. That is, the HNHC groups may be at much more advanced stages of the disability process and require only mobility and ADL care. Unmet needs for IADL care are much more relevant in the earlier stages of the disability and caregiving trajectory (Schulz & Eden, 2016). This may also explain the counterintuitive finding that younger age was associated with higher levels of unmet needs. The oldest old may be extremely limited in terms of mobility and thus have less opportunity for unmet needs and adverse consequences. This study thus replicates and extends previous research showing that greater levels of disability are associated more adverse consequences of unmet needs—the greater the need, the more likely that some needs will go unmet (Allen & Mor, 1997; Desai et al., 2001; Kennedy, 2001; Lima & Allen, 2001; Newcomer et al., 2005). It also extends the literature by using a more inclusive HNHC definition and exploring the additive effects of meeting multiple HNHC criteria. Results suggest that HNHC older adults’ informal caregivers have trouble meeting their needs in home and community settings. Recall that over 90 percent of the sample were receiving help from at least one caregiver. Thus, only a small portion of the adverse consequences of unmet needs reported were the result of having no one to help. These adverse consequences of unmet needs are in fact likely contributors to worsening health and thus ultimately higher costs. Follow-up studies are needed to explore such dynamics. Our analyses also show that the HNHC patient groups and combinations have somewhat distinct profiles. They differ in terms of socio-demographics (i.e., who they are), how they and their caregivers attempt to compensate for their disability, and in the specific types of adverse consequences of unmet needs they tend to report. Both older adults with MCCs and functional disability and those with dementia can be considered HNHC, but they present unique challenges, as do those who have both MCC and DEM. These HNHC profiles can help to further inform the design of successful care models aimed at improving health and reducing costs (Anderson et al., 2015; McCarthy et al., 2015). For example, the HNHC criteria and socio-demographic profiles can aid in the targeting of older adults most likely to benefit from interventions. The adverse consequences of unmet needs profiles can help to target intervention content and potentially improve self-care strategies and/or caregiver engagement in older adults’ care (McCarthy et al., 2015). The results also have important implications for the caregivers of HNHC older adults. Our results provide empirical evidence that despite caregivers’ effort to support the need of their care-recipients, care-recipients still report adverse consequences of unmet needs. Beach and Schulz (2017) reported that caregivers of older adults with multiple adverse consequences of unmet needs were themselves more likely to be stressed and burdened, which may put the patient at risk of poor care and/or neglect. A recent report from the National Academies of Sciences, Engineering, and Medicine (NASEM, Schulz & Eden, 2016) stressed the importance of transforming the policies and practices affecting support for families caring for disabled older adults. The report stressed the need for (1) identifying family caregivers and to comprehensively assess caregiver needs, risks, strengths and preferences in taking on the caregiving role within long-term services and supports (LTSS) system; (2) developing and implementing support/interventions programs to educate and assist caregivers with participation in patient care and coordination; and (3) enhancing the competencies of healthcare and LTSS providers to engage caregivers as partners in caring for patients. Note that these recommendations are consistent with the suggested promotion of patients’ and family caregivers’ engagement in patient self-care from the HNHC literature (e.g., McCarthy et al., 2015). By detailing the specific adverse consequences of unmet needs by each HNHC group, our results can inform evidence-based interventions to potentially improve caregivers’ abilities to better meet these complex needs. We cannot tell from these data why older adults with caregivers are not having their needs met and thus experiencing adverse consequences. Perhaps they need more hours of care than their family caregivers can provide. From a policy standpoint, this would mean that more resources need to be put into formal care to assist family caregivers. Alternatively, if caregivers are too stressed to perform all necessary care requirements, respite services might be what is needed to allow caregivers time to become refreshed and better able to manage the caregiving tasks or they may need other formal or informal caregivers to help with specific care tasks. Finally, if it is a lack of education or training that is the reason for these findings, then enhanced patient/caregiver training may be the answer. Which of these (or what combination) is the reason for the adverse consequences of unmet needs of the HNHC groups should be investigated in future work. Given limited health care and long-term care support resources, it is important to know both where investments should be made and where savings might be achieved. To achieve this, research needs to identify high need caregivers who need support and high cost patients for whom alternative care strategies might lower costs. This strategy is consistent with the recently released NASEM report (Schulz & Eden, 2016) that advocates a model of family and person centered care in which patient care is closely integrated with caregiver training and support. Developing new models of care for high need/high cost patients will be challenging but is likely to have the highest payoffs in terms of caregiver and patient outcomes as well as cost savings. This study has limitations that apply to any survey, including the sample design, participant nonresponse, and the specific questions asked. Missing data on some of the indicators and analyses may have biased the results somewhat. The small sample sizes in some of the HNHC groups (<100) is a limitation, and the findings will require replication in larger samples of HNHC sub-groups. The article also does not explicitly examine links between HNHC status and actual health outcomes and/or healthcare spending. Follow-up analyses are planned that will link HNHC status, adverse consequences of unmet needs for informal care, health outcome, and healthcare utilization and costs (using Medicare data linkage). On a related note, because the analyses are cross-sectional, we are unable to comment on the causal processes underlying the observed effects. That is, we cannot determine from these cross-sectional analyses whether HNHC status results in adverse consequences of unmet needs; or whether not meeting informal care needs results in HNHC status. This would require follow-up longitudinal analyses. Conclusions and Implications This article provides detailed evidence on high levels of adverse consequences of unmet needs for care among HNHC older adults, despite increased efforts to compensate for disability. Persons in different HNHC groups have specific profiles of socio-demographics, disability compensatory strategies, and specific adverse consequences of unmet needs. Those meeting multiple HNHC criteria tend to be at most risk for adverse consequences. The results have important implications for the design and implementation of care management and coordination plans for patients with complex medical needs. Healthcare providers and others in the LTSS who treat and interface with HNHC patients should assess for unmet informal care needs and resulting adverse consequences. Providers should also assess family caregivers’ needs and skills, and provide them with the support and partnering needed to ensure their loved ones receive care of the highest quality. As U.S. policymakers and providers seek to contain healthcare costs by reducing hospitalization and unplanned readmissions, addressing adverse consequences of unmet needs of HNHC older adults should be considered as an important component of these strategies. Supplementary Material Supplementary data is available at The Journals of Gerontology Series B: Psychological and Social Sciencesonline. 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The Journals of Gerontology Series B: Psychological Sciences and Social SciencesOxford University Press

Published: Feb 17, 2018

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