Abstract Background and Objectives We explore how an understudied population of older individuals addresses their ongoing care needs when ineligible for Medicaid waiver services. Research Design and Methods Using regression techniques, we identified factors associated with service use and health outcomes among 1,008 older adults (60+) who applied for Medicaid waiver assistance. Exploratory follow-up interviews with eight waiver-ineligible rural-dwelling individuals identified strategies used for managing their care needs. Results Mortality was high among study participants. Specifically, being waiver-ineligible increased the risk of mortality. Waiver-ineligible individuals were more likely to access alternative services and supports. Rural-dwelling older adults were less likely to be waiver-eligible, but twice as likely to access alternative services and supports, compared to nonrural older adults. Participants interviewed had ongoing unmet needs, relied on family and community services, and used internal and external strategies to manage care needs. Discussion and Implications Having unmet needs increased the risk of mortality, whereas receiving full waiver services extended the lives of recipients. More generous services extend the lives of older, highly vulnerable, community-residing older people. Less generous services also extended life, but not to the same extent. Individuals without formal assistance relied on various strategies to confront ongoing daily challenges. Assisting a broader range of older adults with unmet needs is essential in addressing care needs and maintaining functional capacity to remain at home. Health, Home and community-based care and services, Long-term care, Poverty In the United States, older adults most often turn to family members for assistance when their personal care needs become too difficult to manage on their own (Silverstein & Wang, 2015). Even when family members provide help, older adults commonly report insufficient assistance with daily activities (Davey, Takagi, Sundström, & Malmberg, 2013; Kaye, Harrington, & LaPlante, 2010). Having unmet or under-met needs (i.e., receiving an insufficient amount of care) can lead to undesirable health outcomes that undermine older adults’ ability to manage their daily functioning. Although assistance is available in most communities through a continuum of community services, including programs supported through funds from the Older American’s Act (OAA) (Roberto, Weaver, & Wacker, 2014), the service system has been described as a “patchwork” of independent organizations (Achenbaum & Carr, 2014). This suggests the need to stitch together assistance from multiple agencies to obtain sufficient help to address functional care needs (e.g., dressing, bathing, toileting, eating, and transferring) and prevent adverse health outcomes. Challenges may be amplified for older adults living in rural areas who have been referred to as “vulnerable people in vulnerable places” (Keating & Fletcher, 2012). In part, this label reflects how rural populations are often older, poorer, and less healthy than nonrural populations (Hash, Jurkowski, & Krout, 2015). Historically, rural communities are economically disadvantaged (Lobao, Zhou, Partridge, & Betz, 2016), making it difficult for many persons to pay for help if they are not eligible for government assistance. Predisposing (e.g., age, marital status) and enabling factors (e.g., access to services, poverty-level) explain some of the rural–urban differences in formal home care use. In this study, we identify additional factors associated with having unmet needs among a low-income older adult population and how rural-dwelling older adults, in particular, manage unmet care needs. Although disability (i.e., limitations with personal care and other daily activities) is not inevitable in late life, the risk of disability associated with chronic conditions increases with age. When older adults seek long-term services and supports (LTSS) to help meet their care needs, these services are often intended to supplement care provided by family (Davey et al., 2013). Typical users of home and community-based services are older, have lower income, and are in poorer health than nonusers (Robinson, Sonnega, & Levy, 2015). Yet, the demand for programs that provide in-home LTSS often outstrips available funds for providing such services (Ng & Harrington, 2012). When older individuals receive insufficient assistance to meet their care needs, they develop alternative strategies to manage their daily lives. Self-management is a process by which individuals learn and use skills to improve their physical and emotional well-being, minimize decline in physical functioning (Cramm et al., 2012), and cope with psychosocial consequences of chronic health problems (Gallant, Spitze, & Prohaska, 2007). In late life, a low sense of personal control negatively influences health outcomes, whereas a high sense of personal control positively influences health outcomes (Umberson, Crosnoe, & Reczek, 2010). To maintain personal control over declining health circumstances and daily functioning, individuals often adjust their expectations and modify behaviors. For example, Remillard, Fausset, and Fain (2017) found that older adults preserved their ability to perform activities of daily living (ADL) by actively adapting their regular routines. We suspect self-management strategies may be particularly important among older adults receiving limited or no help with their daily care. When older adults have ongoing unmet functional needs, they are at risk for adverse health outcomes. For example, rural homebound older adults who expressed difficulty completing ADL (i.e., bathing, dressing, toileting, transferring, eating/feeding, bowel function, and bladder function) and instrumental ADL (IADL; e.g., meal preparation, household chores, grocery shopping, and transportation) tasks were more likely to report symptoms of depression compared with individuals who did not express difficulty (Tanner, Martinez, & Harris, 2014). Among older adults who struggled to maintain functional independence, having insufficient help with care needs increased risk of mortality (Carey et al., 2008; Li, Kyrouac, McManus, Cranston, & Hughes, 2012). Even having just one self-care need placed older adults at risk for negative health outcomes if that need remained unmet (Garfield, Young, Musumeci, & Reaves, 2015). Thus, to avoid adverse health outcomes, it is critical individuals receive sufficient help. Policy Context Services used by older adults to meet personal care needs can be influenced by federal and state-level policies and program criteria. Some older adults who receive Medicare (federal age-based health insurance) also may be eligible for government-funded community-based LTSS if they demonstrate financial need that qualifies them for Medicaid, the primary payer for LTSS (Reaves & Musumeci, 2015). Generally, older adults who qualify for Medicaid are frailer, in poorer health, and have greater mobility impairment compared to older adults ineligible for Medicaid (Watts, Cornachione, & Musumeci, 2016). Older individuals enrolled in both Medicare and Medicaid (i.e., dual-eligible beneficiaries) have increased vulnerabilities due to the complexity and high cost of their care needs. Prevalence of need for assistance with self-care, household tasks, and mobility was significantly greater among dual-eligible beneficiaries compared to individuals eligible for Medicare only (Allen, Piette, & Mor, 2014). Dual-eligible individuals also were more likely to have one or more self-care limitations (e.g., unable to get dressed; going without groceries; having to stay within the home). Since 1983, states have had authority to offer Home and Community-Based Services 1915(c) Medicaid waiver services to meet the needs of people who prefer to receive services and support in their homes or community. To qualify for waiver services, individuals must meet both state-specific income and care need criteria (Medicaid.gov, n.d.). States are not required, however, to offer waiver services in locations where it is financially unfeasible to provide these services (e.g., rural regions where certain types of providers are unavailable; Medicaid.gov, n.d.). This federal stipulation gives states flexibility to establish waiver program criteria that subsequently influence individuals’ eligibility to receive assistance. In Virginia, the Department of Medical Assistance Services (DMAS) is the agency that administers Medicaid and associated waiver programs. The Elderly and Disabled Consumer Directed (EDCD) waiver program provides assistance for all individuals who are financially eligible for Medicaid and meet criteria for a nursing facility level of care (DMAS, 2017). Services include but are not limited to adult day health care, personal care services, respite care, and personal emergency response systems. For functional eligibility, waiver applicants are assessed in the hospital by an approved acute-care hospital discharge planner or in their homes or at a community agency by health care professionals using the Uniform Assessment Instrument (UAI; Commonwealth of Virginia, 2005). The UAI is a standardized multidimensional comprehensive questionnaire used to assess an individuals’ level of care need. Standardized decision criteria require individuals demonstrate high level of need (i.e., 4+ ADL limitations) equivalent to nursing facility level of care. These criteria are more stringent than in most other states, which typically require individuals to have just two or more ADL limitations for eligibility. In addition, Virginia is one of 10 states that has more restrictive financial eligibility criteria for waiver programs (AARP, 2010). Based upon the assessment, individuals can be deemed waiver-eligible, waiver-ineligible but receive service referrals, or waiver-ineligible and do not receive service referrals. Another source of assistance for older adults in Virginia is available through the Department of Aging and Rehabilitative Services (DARS). DARS is a government-supported agency that, under the auspice of the OAA and in collaboration with community partners, provides resources and services (e.g., personal care, chore/homemaker help, and home-delivered meals) to enhance older adults’ independence (DARS, n.d.). Anecdotal agency data suggest that most individuals who do not qualify for Medicaid seek and receive some amount of help from DARS because DARS has less restrictive eligibility criteria than for the EDCD waiver. Guiding Theoretical Frameworks Andersen’s Behavioral Health Services Use Model provides a broad framework for examining factors that contribute to service use (Andersen, 1995). There are three domains that influence health behavior and use of services that ultimately influence health outcomes: (a) predisposing characteristics (e.g., age, sex, race/ethnicity), (b) enabling resources (e.g., income level; rurality; intrinsic or extrinsic support from self, family, and community), and (c) need-based factors, both perceived and evaluated functional limitations (e.g., difficulty performing IADL and ADL tasks). Study Purpose The purpose of this study was to assess service use and morality rate of a near-risk (i.e., financially eligible but not yet functionally eligible) population of low-income older adults who were deemed ineligible to receive Medicaid-funded assistance. Most prior research has focused on actual beneficiaries of Medicaid rather than individuals who were ineligible to receive assistance. We focused on a subpopulation that has generated little, if any, attention: older adults requesting need for paid LTSS, but who are evaluated as functionally ineligible for them. We first identified factors associated with service use and mortality and then explored how rural-dwelling older adults manage without needed services so that they are able to continue living in the community. Based on Andersen’s model, our primary research question was, How are enabling resources (place of residence) and need-based factors (waiver eligibility, site of assessment) associated with service use and death? We examined enabling and need-based factors associated with service use and mortality risk up to 2 years after individuals applied for waiver assistance. Controlling for predisposing characteristics (age, sex, and race), we hypothesized that the proportion of waiver-eligible individuals who died would be lower than waiver-ineligible individuals; rural-dwelling older adults would be less likely to be waiver-eligible, less likely to use alternative services, and have greater risk for mortality; and individuals assessed at a hospital for eligibility would more likely be waiver-eligible and less likely experience mortality. Site of assessment was conceptualized as a need-based predictor of adverse health outcomes that captures risks associated with recent hospitalization. Hospitalization, one of the most robust predictors of mortality of community-living older adults, occurs when a level of illness or injury acuity cannot be handled in the community setting; thus, assessment at a hospital reflects acuity of need. We were unaware of previous studies that examined the association between site of assessment (i.e., hospital vs home/community) and eligibility outcomes. To explore how rural older adults managed when deemed ineligible for assistance, the first author conducted follow-up interviews with eight original study participants. Considering the challenges of financial vulnerability in rural communities, we anticipated that individuals who were ineligible for waiver services would rely on their existing social networks and engage in self-management strategies to address their daily needs. Although this convenience sample may not be representative of the waiver-ineligible older adult population, information older adults shared provided initial insight into ways of managing daily life when ineligible for support services. The university’s institutional review board approved this study. Methods Study Sample and Procedures Two independent state agencies provided data: DMAS and DARS. The target population was adults aged 60 years and older who were financially eligible and receiving Medicaid who subsequently applied to receive services through the EDCD waiver program (N = 1,039). Participants were excluded from analysis if age, sex, or race/ethnicity were missing in the data set. Thus, the analytical sample included 1,008 participants. We obtained enrollment data for individuals who applied for the waiver between October 1, 2013 and September 30, 2015 from DMAS, as well as date of death (when applicable) through March, 2016. DARS provided information on whether these individuals accessed services during the same timeframe (October, 2013–September, 2015). Study Measures Outcome Variables Our primary outcome of interest was mortality which was coded to indicate whether death had not occurred (0) or occurred (1) during the study period. Secondary outcomes of interest related to service use were waiver eligibility and DARS access. Individuals were either waiver-ineligible (0) or waiver-eligible (1). DARS provided data on who did not (0) or did access (1) their services. Predictor Variables Based on available data, we identified enabling, need-based, and predisposing variables. The enabling variable county of residence was operationalized as rurality, coded as nonrural (0) and rural (1), based on the designation provided by the Consumer Financial Protection Bureau (2013). We created two need-based variables that served as proxy measures for functional ability. First, site of screening assessment (0 = hospital, 1 = home/community) indicated where individuals were assessed (i.e., in hospital or in their homes/at a community agency). Individuals assessed during a hospital stay are likely to have greater acute or long-term functional needs (Boyd et al., 2008) and be at risk of functional decline posthospitalization (Zisberg, Shadmi, Gur-Yaish, Tonkikh, & Sinoff, 2015). In order to be discharged from the hospital, assistance must be in place to adequately meet individualized care needs. Usually family or friends provide such assistance alone or in conjunction with a community service agency. If informal helpers or formal services are unavailable or unable to provide care, older persons typically are discharged to a nursing home for short-term rehabilitation (paid for by Medicare) and thus, not eligible for waiver services. Individuals received a service recommendation regarding their level of need (0 = waiver-ineligible and received no services, 1 = waiver-ineligible but received limited Medicaid services, 2= waiver-eligible and received services). We controlled for the predisposing variables of age (continuous), sex (0 = male, 1 = female), and race (0 = White, 1 = Black, 2 = Asian, 3 = Hispanic/Latino, 4 = other). When analyzing primary outcomes, secondary outcomes were included as predictors. Semistructured Follow-up Interviews We used a nested sampling strategy (Yin, 2009) where individuals from the analytical sample were identified for follow-up semistructured telephone interviews. We identified 102 participants in the sample who were deemed waiver-ineligible (i.e., functionally ineligible but financially eligible) and living in rural counties. Because many case files had little or no contact information, DMAS was able to provide contact information for only 64 of these individuals. Multiple strategies were employed to contact individuals, but invalid contact information made recruitment challenging. Eight of the 23 older persons who met the inclusion criteria agreed to be interviewed (Supplementary Material: Figure 1). Semistructured interviews were conducted October through December, 2016. Participants were sent an initial recruitment letter describing the research and a study consent form. The first author contacted individuals by telephone within 10 days of mailing the letter and followed standard practice for establishing rapport with participants and describing the study purpose (Patton, 2002). Before proceeding with the interview, participants were informed of the procedure and provided verbal informed consent and permission to audio-record the interview; manual notes were also taken. Interview questions focused on daily challenges and self-management strategies (intrinsic and extrinsic behavioral and environmental modification; receiving informal help). Specifically, participants were asked about ADL and IADL tasks for which they received assistance, who helped them, and how they managed if no or insufficient help was provided. We inquired about their most difficult challenge and expectations for help in the future. Interviews averaged 30 min (range: 13–75 min). Each participant received a $25 gift card in appreciation for their time. Data Analysis We computed summary statistics for categorical predictors and binary outcomes, examined bivariate correlations between all pairs of independent variables, and addressed collinearity among multiple variables by removing one or more variables from analyses. To estimate the effects of enabling and need-based variables on service use and mortality, we used logistic regression. This approach allowed us to determine likelihood of mortality during the study period. Based on variance inflation factor values for all analyses (range: 1.06–5.42), we were not concerned about problematic multicollinearity. We used IMB SPSS Version 22 software to run descriptive statistics (frequencies, percentages, means, correlations) to characterize the study sample and STATA 10 statistical package for regression analyses. Audio-recorded interviews were transcribed verbatim, verified for accuracy between the audio-recording and written transcription, de-identified for coding purposes, and assigned pseudonyms. We used content analysis procedures to analyze the interviews. After initial open coding, four iterations of coding yielded the final coding theme (LaRossa, 2005). Open codes were reduced to seven distinct categories through an in-depth process of axial coding. From these categories, four themes emerged. Potential validity concerns in data collection, analysis, and interpretation were addressed using various techniques (Creswell & Plano Clark, 2011). For example, the second author examined the data and verified the coding scheme. The authors established trustworthiness of the coding process through immersion in the data with close multiple readings of the transcripts; when codes did not align, discrepancies were discussed until we reached consensus. Results Demographic Characteristics The 1,008 older adults ranged in age from 62 to 105 years, with a mean of 80.08 years (SD = 1.04; Table 1). More than three-quarters of the participants were female (n = 757; 75.1%) and predominately Black (n = 471; 46.7%) or White (n = 400; 39.7%). Nearly 3 in 10 individuals were rural-dwelling (n = 296; 29.4%). Although all older adults were financially eligible for services, 365 were deemed waiver-ineligible because they did not meet nursing facility care need criteria. Of the 1,008 individuals who applied for the EDCD waiver, nearly half of the applicants also accessed DARS agency for assistance (n = 502; 49.8%). Table 1. Characteristics of Elderly and Disabled Consumer-Directed Waiver applicants (N = 1008) n (%) M (SD) Sex Female 757 (75.1) Male 351 (24.9) Age 80.08 (1.0) Race/Ethnicity White 400 (39.7) Black 471 (46.7) Asian 84 (8.3) Hispanic/Latino 22 (2.2) Other 31 (3.1) Rural Yes 296 (29.4) No 712 (70.6) Assessment site Hospital 190 (18.9) Community 818 (81.2) Waiver eligibility Eligible 643 (63.8) Ineligible 365 (36.2) Service recommendationa No services 164 (16.3) Limited services 201 (19.9) Full services 643 (63.8) Accessed DARSb Yes 502 (49.8) No 506 (50.2) Death Yes 271 (26.9) No 737 (73.1) n (%) M (SD) Sex Female 757 (75.1) Male 351 (24.9) Age 80.08 (1.0) Race/Ethnicity White 400 (39.7) Black 471 (46.7) Asian 84 (8.3) Hispanic/Latino 22 (2.2) Other 31 (3.1) Rural Yes 296 (29.4) No 712 (70.6) Assessment site Hospital 190 (18.9) Community 818 (81.2) Waiver eligibility Eligible 643 (63.8) Ineligible 365 (36.2) Service recommendationa No services 164 (16.3) Limited services 201 (19.9) Full services 643 (63.8) Accessed DARSb Yes 502 (49.8) No 506 (50.2) Death Yes 271 (26.9) No 737 (73.1) Note: aNo services = waiver-ineligible, received no services; Limited services = waiver-ineligible, received limited Medicaid services; Full services = waiver-eligible, received services. bDARS = Department of Aging and Rehabilitative Services. View Large Table 1. Characteristics of Elderly and Disabled Consumer-Directed Waiver applicants (N = 1008) n (%) M (SD) Sex Female 757 (75.1) Male 351 (24.9) Age 80.08 (1.0) Race/Ethnicity White 400 (39.7) Black 471 (46.7) Asian 84 (8.3) Hispanic/Latino 22 (2.2) Other 31 (3.1) Rural Yes 296 (29.4) No 712 (70.6) Assessment site Hospital 190 (18.9) Community 818 (81.2) Waiver eligibility Eligible 643 (63.8) Ineligible 365 (36.2) Service recommendationa No services 164 (16.3) Limited services 201 (19.9) Full services 643 (63.8) Accessed DARSb Yes 502 (49.8) No 506 (50.2) Death Yes 271 (26.9) No 737 (73.1) n (%) M (SD) Sex Female 757 (75.1) Male 351 (24.9) Age 80.08 (1.0) Race/Ethnicity White 400 (39.7) Black 471 (46.7) Asian 84 (8.3) Hispanic/Latino 22 (2.2) Other 31 (3.1) Rural Yes 296 (29.4) No 712 (70.6) Assessment site Hospital 190 (18.9) Community 818 (81.2) Waiver eligibility Eligible 643 (63.8) Ineligible 365 (36.2) Service recommendationa No services 164 (16.3) Limited services 201 (19.9) Full services 643 (63.8) Accessed DARSb Yes 502 (49.8) No 506 (50.2) Death Yes 271 (26.9) No 737 (73.1) Note: aNo services = waiver-ineligible, received no services; Limited services = waiver-ineligible, received limited Medicaid services; Full services = waiver-eligible, received services. bDARS = Department of Aging and Rehabilitative Services. View Large Waiver-eligibility and Service Use Waiver-eligibility was associated with several factors (Table 2). Older adults were 39% less likely to be waiver-eligible when rural-dwelling (OR = 0.61, p = .001). Individuals who were assessed in the community were twice as likely to be eligible, compared to individuals assessed in the hospital (OR = 2.13, p < .001). Likelihood of accessing services through DARS was associated with rurality (OR = 2.26, p < .001), as well as being assessed in the community (OR = 1.51, p = .015). Waiver-eligible individuals were 39% less likely to access DARS (OR = 0.61, p = .003), compared to waiver-ineligible individuals. Table 2. Predicting Service Use and Risk of Health Outcomes (controlling for age, sex, and race) (N = 1,008) EDCDa Waiver Eligibility Accessed DARSb Mortality Predictor (ref.) OR (SE) p value 95% CI OR (SE) p value 95% CI OR (SE) p value 95% CI Rural (nonrural) 0.61 (.09) .001* (0.45, 0.82) 2.26 (.34) <.001* (1.68, 3.05) 1.05 (.18) .794 (0.75, 1.46) Assessment site (hospital) 2.13 (.36) <.001* (1.53, 2.97) 1.52 (.26) .015* (1.08, 2.12) 0.84 (.16) .370 (0.58, 1.22) EDCD wavier eligibility (ineligible) – – – 0.61 (.09) <.001* (0.46, 0.80) – – – DARS (did not access) – – – – – – 0.77 (.12) .091 (0.57, 1.04) Service rec.c (No services) Limited services – – – – – – 0.39 (.09) <.001* (0.24, 0.63) Full services – – – – – – 0.48 (.10) <.001* (0.32, 0.70) Model fit (BIC)d 1,295.89 1,394.75 1,185.72 EDCDa Waiver Eligibility Accessed DARSb Mortality Predictor (ref.) OR (SE) p value 95% CI OR (SE) p value 95% CI OR (SE) p value 95% CI Rural (nonrural) 0.61 (.09) .001* (0.45, 0.82) 2.26 (.34) <.001* (1.68, 3.05) 1.05 (.18) .794 (0.75, 1.46) Assessment site (hospital) 2.13 (.36) <.001* (1.53, 2.97) 1.52 (.26) .015* (1.08, 2.12) 0.84 (.16) .370 (0.58, 1.22) EDCD wavier eligibility (ineligible) – – – 0.61 (.09) <.001* (0.46, 0.80) – – – DARS (did not access) – – – – – – 0.77 (.12) .091 (0.57, 1.04) Service rec.c (No services) Limited services – – – – – – 0.39 (.09) <.001* (0.24, 0.63) Full services – – – – – – 0.48 (.10) <.001* (0.32, 0.70) Model fit (BIC)d 1,295.89 1,394.75 1,185.72 Note: CI = Confidence interval; OR = Odds ratio; SE = Statndard error. aEDCD = Elderly and Disabled Consumer-Directed; bDARS = Department of Aging and Rehabilitative Services; cNo services = waiver-ineligible, received no services; Limited services = waiver-ineligible, received limited Medicaid services; Full services = waiver-eligible, received services; dBIC = Bayesian information criterion. View Large Table 2. Predicting Service Use and Risk of Health Outcomes (controlling for age, sex, and race) (N = 1,008) EDCDa Waiver Eligibility Accessed DARSb Mortality Predictor (ref.) OR (SE) p value 95% CI OR (SE) p value 95% CI OR (SE) p value 95% CI Rural (nonrural) 0.61 (.09) .001* (0.45, 0.82) 2.26 (.34) <.001* (1.68, 3.05) 1.05 (.18) .794 (0.75, 1.46) Assessment site (hospital) 2.13 (.36) <.001* (1.53, 2.97) 1.52 (.26) .015* (1.08, 2.12) 0.84 (.16) .370 (0.58, 1.22) EDCD wavier eligibility (ineligible) – – – 0.61 (.09) <.001* (0.46, 0.80) – – – DARS (did not access) – – – – – – 0.77 (.12) .091 (0.57, 1.04) Service rec.c (No services) Limited services – – – – – – 0.39 (.09) <.001* (0.24, 0.63) Full services – – – – – – 0.48 (.10) <.001* (0.32, 0.70) Model fit (BIC)d 1,295.89 1,394.75 1,185.72 EDCDa Waiver Eligibility Accessed DARSb Mortality Predictor (ref.) OR (SE) p value 95% CI OR (SE) p value 95% CI OR (SE) p value 95% CI Rural (nonrural) 0.61 (.09) .001* (0.45, 0.82) 2.26 (.34) <.001* (1.68, 3.05) 1.05 (.18) .794 (0.75, 1.46) Assessment site (hospital) 2.13 (.36) <.001* (1.53, 2.97) 1.52 (.26) .015* (1.08, 2.12) 0.84 (.16) .370 (0.58, 1.22) EDCD wavier eligibility (ineligible) – – – 0.61 (.09) <.001* (0.46, 0.80) – – – DARS (did not access) – – – – – – 0.77 (.12) .091 (0.57, 1.04) Service rec.c (No services) Limited services – – – – – – 0.39 (.09) <.001* (0.24, 0.63) Full services – – – – – – 0.48 (.10) <.001* (0.32, 0.70) Model fit (BIC)d 1,295.89 1,394.75 1,185.72 Note: CI = Confidence interval; OR = Odds ratio; SE = Statndard error. aEDCD = Elderly and Disabled Consumer-Directed; bDARS = Department of Aging and Rehabilitative Services; cNo services = waiver-ineligible, received no services; Limited services = waiver-ineligible, received limited Medicaid services; Full services = waiver-eligible, received services; dBIC = Bayesian information criterion. View Large Mortality Mortality was high among this sample of older adults (n = 271; 26.9%). Specifically, individuals deemed ineligible for waiver services were more likely to have died in the study period compared to individuals receiving full waiver services (OR = 0.48, p < .001) or limited Medicaid services (OR = 0.39, p < .001). Assessment site and rurality were not significantly associated with mortality. We ran analyses to test interactions between rurality, assessment site, waiver eligibility, and DARS access but they were not significantly associated with mortality. Preliminary Follow-up Interviews Six women and two men ranging in age from 64 to 89 years old (M = 71.5; SD = 8.26; Supplementary Material: Table 1) were interviewed for our preliminary inquiry of self-managing unmet care needs. When these older adults applied for waiver services, they were financially eligible but not yet functionally eligible (i.e., nursing facility level of care need) for waiver assistance. All of the older adults were currently widowed, divorced, or separated. Six of the participants were living alone; two older adults lived with their adult children. Half of the participants had accessed DARS agency to receive assistance. Individuals’ had self-reported IADL and ADL limitations at the time of the study interview (Supplementary Material: Table 2). Four themes emerged from data analysis, highlighting the unique and shared experiences of how older adults managed their functional care needs (Supplementary Material: Table 3). Getting Help The interviews revealed that older adults initially sought assistance for ongoing needs rather than a sudden health event that precipitated need for additional help. They were unsatisfied with their current situation and, thus, applied for the waiver to receive extra help with daily activities. After unsuccessfully seeking assistance through the Medicaid waiver program, these older adults did not give up. Rather, they persisted in various ways of getting help to manage anywhere from 6 to 11 self-reported functional limitations. All of the older adults were not currently married, and most lived alone. They managed their needs by continuing to rely on family and friends, formal services, or a mixture of both. For example, Mark lived with and relied on his son, but also received help from friendly neighbors who were more physically capable than he was. Alaina, on the other hand, lived alone and relied on her daughter for many care needs. Although she was reluctant to receive agency help because of concerns about trusting strangers from a service agency, Alaina was reconsidering her stance because she needed more help with personal care, housework, shopping, and meal preparation than her daughter could provide. Others like Mark, were fortunate to have a strong support system of formal and informal helpers to assist with his many limitations. “[My son] chauffeurs me around when we’re going different places … I have a friend, he’s a neighbor, and he’s been very helpful over the years. He is still able physically to do a lot of things that I can’t do.” In contrast, Diane, Henrietta, and Scott had limited family involvement and relied solely on formal agencies to provide some help with household chores, meals, and home modifications projects. Navigating Daily Tasks Participants employed a variety of internal and external strategies, independent or in combination to help them with navigating daily tasks. Internal strategies, like staying self-motivated, were reflected in the older adults’ positive outlook on how they managed their daily lives. “Think positive and don’t give up, and keep the good spirits up, and just try to do what you can and don’t overdo yourself” (Diane). Having inner strength helped nearly all the participants maintain a positive outlook in spite of being unable to secure additional help. When necessary, older adults adjusted their expectations to maintain control over declining health circumstances. Having inner strength or faith enabled many older adults to persevere in light of their difficult health-related circumstances. With the exception of Olivia, participants reported their quality of life as good or excellent. Olivia indicated that her family dynamics were exhausting; she reported low levels of well-being on all measures and scored the most severe score of depressive symptoms. External strategies reflected the implementation of behavioral or environmental modifications to adjust to disruptions in daily life. Most participants had mobility issues, and several older adults explained how having difficulty with mobility intensified their other existing self-care needs. They relied on assistive devices such as a cane, walker, or a motorized wheelchair to reduce their mobility difficulties. In conjunction, older individuals learned to listen to their body and limit themselves as they navigate their circumstances. By changing their environment to promote safety and independence, the older adults were better equipped to manage challenges associated with increasing levels of disability. Making modifications to the home environment helped several of them manage their functional care needs, like Bertha who had a ramp and “all these handles…to get in and out of the tub” installed. Ongoing Unmet Needs We assumed that at the time of application for waiver services, individuals believed they could benefit from additional assistance. Although we found that being deemed waiver-ineligible did not “break” them, older adults’ unmet needs persisted and were ongoing. In addition to ADL limitations, participants expressed having anywhere from four to eight IADL limitations. Although self-management strategies were helpful, our interviews with near-risk older adults revealed that they were not enough. Underlying mobility issues hindered individuals’ ability to carry out daily tasks. Not being able to get up and do everyday things was a source of frustration and distress. The most salient challenges were related to transportation, household chores, preparing food, grocery shopping, and doing laundry. Several older adults, like Oliva, described challenges with standing long enough to complete daily tasks, like preparing a meal or doing household chores. “I had to give up doing the vacuum cleaner because that really wore me out. Or standing and doing dishes. Pretty much standing any length or amount of time, it wears me out. It hurts. Causes me pain.” Adequate transportation was a challenge for seven participants, including scheduling issues and lack of available transportation services. They explained how reliable services would reduce the burden on family members to provide transportation and ensure transport for doctor visits, grocery shopping, and other engagements. Transportation was a longstanding issue, with one participant, Bertha, who remarked how it had not improved since she moved to the community nearly three decades ago. “We have called [the bus company] and they said they don’t come out in this area. They come up to the four-way where I live, where if you could get somebody to get you up there, and let them know, and make an appointment or a call, then they’ll meet you at the four-way stop.” The challenges older adults had with daily tasks were ongoing and indicative of a progression toward a higher level of disability. Yet, services were unavailable or insufficient to help participants with daily responsibilities and delay the progression. Because having even one unmet self-care need can be detrimental (Garfield et al., 2015), we asked participants about companionship, feeling left out, isolation, and symptoms of depression and used these variables as sensitizing concepts to explore the link between well-being and unmet needs. Although feeling left out and isolated were not concerns for participants, seven older adults reported they lacked companionship at least some of the time. Four of these individuals also reported symptoms indicative of probable depression (CESD-R-10 scale score of > 10). Concerns About the Future We asked participants to reflect on what would happen if they continued to receive insufficient help and their care needs were to spiral out of control. Their responses most often focused on either the refusal or acceptance of nursing home placement. Several participants expressed strong feelings against moving to a nursing facility, either because of negative experiences or, like Greta, the anticipation that family would take over their care. “I’d have somebody here to help me if I need anything.” Conversely, accepting nursing home placement as a care option was linked to family burden and not wanting to infringe on family’s time and responsibilities. “If I ever get down to where I cannot take care of myself, I’ll sign myself into a nursing home so fast [my daughters’] heads will spin. For this simple reason, …I know what it is to be tied up 24/7. . . . and I don’t want to put that responsibility on [daughters]” (Scott). For older adults with no family living nearby, they were most concerned about whether they could afford more help if care needs increased. Discussion In this longitudinal study, we focused on near-risk, low-income older adults who were deemed ineligible for Medicaid waiver services based on insufficient functional need. Among poor, community-residing older adults with multiple self-care limitations, receipt of generous services increased the likelihood of survival. Comparable to previous research that reported a link between inadequate help (He et al., 2015; Li et al., 2005) or high levels of functional dependence (Carey et al., 2008) and increased mortality, we found that near-risk individuals ineligible to receive desired assistance through Virginia’s EDCD waiver program had increased mortality. Specifically, 27% of older adults who applied for waiver assistance died within 2 years, with the greatest mortality risk among individuals who did not receive waiver assistance. Receiving services keep vulnerable people alive. Receiving full waiver services extended the lives of recipients; less generous services also extended life, but not to the same extent. We contend this high mortality is an unintended consequence of stricter functional eligibility criteria; that is, individuals who had functional care needs that remained unaddressed comprise a high-risk, vulnerable population who experienced increased mortality risk. Our findings suggest need-based (service recommendation, site of assessment) and enabling (rurality) characteristics play a critical role in older adults’ likelihood of receiving waiver assistance. Although waiver-ineligible older adults were more likely to access alternative services (i.e., services through DARS), they still experienced increased mortality risk. The alternative services and supports were not sufficient to address ongoing unmet needs of this near-risk population. Our findings show that individuals who received at least some level of assistance through Medicaid were more likely to survive. This suggests that older people’s lives could be extended if eligibility for publicly-funded community-based LTSS was liberalized. Expanding eligibility would likely improve quality of life for near-risk individuals and have a major impact on long-term cost-savings (Konetzka, Karon, & Potter, 2012; Lawson et al., 2013) by reducing risk of negative health outcomes, like hospitalization. This is the first study to examine the association between assessment site and LTSS eligibility. We anticipated individuals assessed at the hospital would have greater likelihood of waiver-eligibility than persons assessed in the community, but found the opposite relationship. The direction of this relationship is likely due to prehospital health and social characteristics. For this high-risk population, it may be difficult for hospital discharge staff to establish an appropriate community-based care system, particularly if individuals lack a strong and available support network. Assessors typically have an intense patient load and simply do as much as they can for high-risk patient within a limited time period. Thus, our findings likely reflect the structural challenges of discharging older adults with functional and medical needs from the hospital to community-based locations and suggest the value of considering site as a prognostic variable that predicts future likelihood of community-based LTSS. Alternatively, assessors may naively assume older adults’ needs were addressed during hospitalization or rehabilitation and dismiss the need for LTSS to deter functional decline postrecovery. Given the limited number of available covariates in the regression models, differences may be spurious, but findings underscore the importance of further inquiry using data typically obtained by agencies to explicitly examine the relationship between assessment site and eligibility outcome to better understand clients’ risk of adverse health outcomes. Rurality was not significantly associated with mortality. However, rural-dwelling older adults were less likely to be eligible for and thus receive waiver services. This is expected given that states are not required to provide waiver services in regions considered unfeasible for service delivery. Rural-dwelling individuals were, however, more likely to access alternative services through DARS compared to their nonrural counterparts. Our preliminary follow-up interviews revealed insightful information about self-management of ongoing unmet care needs among rural-dwelling older adults. Due to limited financial means and lack of assistance through waiver services, most participants depended on family members as their primary source of help. They exhibited resilience as evident by their use of physical and psychological self-management strategies to navigate daily challenges (Wagnild & Collins, 2009) and carry on as best as they could. By adopting a “new normal,” these older adults persevered in spite of functional difficulties and maintained a positive outlook on life. Our findings suggest the importance of addressing basic and instrumental ADL limitations. Through the interviews, we identified underlying mobility issues as the root of subsequent IADLs, complicating older adults’ efforts to maintain functional capacity. However, IADLs are not a component of nursing facility eligibility criteria used for waiver eligibility. Both types of need should be prioritized during assessment for service eligibility, especially among older adults living alone. Older adults may not receive sufficient help with every day activities, leaving them vulnerable to having ongoing unmet needs. Thus, among near-risk older adults with financial vulnerability, affordable (and available) services and supports need to complement and strengthen the ongoing self-management strategies. Although Medicaid-funded community-based services and supports are typically considered as a last resort, they often are the only viable option for low-income older adults struggling to meet their care needs. This study contributes new knowledge about the implications of restrictive state-level policies that limit eligibility for waiver assistance to individuals with greatest functional needs. Waiver services are designed to enhance the feasibility of older persons remaining in their homes. Ineligible individuals with financial need who have care needs that are considered less substantial (i.e., less need than required by nursing facility level of care criteria) cannot afford to pay for formal help, and thus, are at increased risk for adverse health outcomes. An unintended consequence of these policies is the increased mortality risk among near-risk older adults who were not yet functionally eligible for waiver services. Garfield and colleagues (2015)] found that having just one unmet self-care need can be detrimental. Thus, expanding access to affordable services for individuals with fewer limitations and/or IADL limitations (i.e., access to preventive services) is likely to decrease mortality among near-risk older adults. Preventive services not only support older adults’ health, functioning, and well-being, but may be cost-effective for publicly funded programs (Freedman & Spillman, 2014; Sands et al., 2008). Overlooking individuals with lesser functional need is harmful, forcing them to manage ongoing unmet needs without desired formal assistance and contributing to increased risk of adverse health outcomes. Based on our study findings, we recommend expanding services and supports to target individuals with lesser need which may reduce risk of costly hospitalizations and early mortality. Implications for Future Research and Practice This study is distinctive in its attention to individuals who were determined functionally ineligible for Medicaid-financed waiver services (i.e., a near-risk population of low-income older adults with perceived functional need). Using a longitudinal mixed-method study, we extend understanding of the social and health disadvantages of the high-risk, dual-eligible population reported by Allen and colleagues (2014). We linked administrative data from two agencies on application for LTSS with data on mortality over a period of 2 years. However, analyses were limited to pre-existing data collected for agency purposes, not research. With the emergence of “big data,” where archival and real-time health service use data from large populations is more readily available, there is tremendous potential triangulating agency-generated data to identify service use trends and respond to emerging care needs (Roberto & Blieszner, 2015). Researchers need to continue forging partnerships that enable access to health services data to identify when and how older adults use services. Developing strong partnerships with state-level agencies is a critical step that may expand opportunities to access additional agency-generated information or to collaborate with agencies to gather additional data that provides greater social context about clients’ situations. Assessment strategies that complement conventional methods used to assess unmet need are necessary; asking direct questions about felt needs was found to be a better predictor of nursing home admission or death than other types of functional assessment (Gaugler et al., 2005) Researchers have expressed the need for longitudinal studies of individuals experiencing unmet need (e.g., Li et al., 2012) and a better understanding how self-management strategies influence health and functioning over time. To contribute new knowledge about a very understudied population of older adults ineligible for Medicaid waiver assistance, we addressed the study question through the use of conventional quantitative procedures and complementary qualitative follow-up interviews with older adults living in rural communities. External constraints negatively affected our recruitment efforts and our small convenience sample was not representative of the population of waiver-ineligible older adults. As documented by Clark, Rogers, and Allen (2010), reaching Medicaid beneficiaries was challenging because valid contact information was often not available. We contend that theoretical sufficiency was met, even within our small sample, but interviews with a larger number of participants would strengthen understanding of how to promote cultural competency in service delivery (Sörensen, Hirsch, & Lyness, 2014) based on participants’ racial/ethnic background (Potter, Roberto, Brossoie, & Blieszner, 2017; Sayegh & Knight, 2011) or socioeconomic status (Clark et al., 2008). Researchers must consider social and cultural differences that may influence perceptions of service use and family caregiving, and how perceptions of control influence self-management strategies. More research also is needed that explicitly explores expectations for care. For example, our finding that rural older adults did not contemplate future care arrangements, beyond the role of family, if their health were to decline, supports previous research (Pinquart & Sörensen, 2002; Weaver, Roberto, & Blieszner, 2017). These types of inquiry will (a) illuminate challenges faced by individuals who are unable to pay for help but do not meet the criteria for services through a Medicaid waiver program, (b) point to skills and strategies older adults can hone to enhance their quality of life even if they experience unmet needs, and (c) contribute to the development of appropriate interventions that support community agencies’ efforts to provide LTSS that align with near-risk older adults’ care preferences. Supplementary Data Supplementary data are available at The Gerontologist online. Acknowledgments Appreciation is expressed to Dr. Jyoti Savla and Dr. Laura P. Sands who advised on statistical analyses and provided assistance throughout the writing process. 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The Gerontologist – Oxford University Press
Published: May 3, 2018
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