Prediction of Institutionalization for Patients With Dementia in Taiwan According to Condition at Entry to Dementia Collaborative Care

Abstract

This study aimed to examine the institutionalization rate in patients with dementia in Taiwan, identify the predictors of institutionalization, and conduct a mediation analysis of caregiver burden between neuropsychiatric symptoms and institutionalization. We analyzed data from a retrospective cohort registered in dementia collaborative care (N = 518). The analyses applied univariate and multivariate Cox proportional hazard regression with Firth’s penalized likelihood to assess the relationship between each predictor at entry and institutionalization for survival analysis. Thirty (5.8%) patients were censored due to institutionalization after a median follow-up of one-and-a-half years. Neuropsychiatric symptoms, loss of walking ability, and living alone predicted institutionalization. Caregiver burden may partially mediate the effects of neuropsychiatric symptoms and institutionalization. High caregiver burden due to presence of neuropsychiatric symptoms may partially contribute to institutionalization among people living with dementia in Taiwan. However, proper management of neuropsychiatric symptoms and caregiver empowerment may ameliorate institutionalization risk.

Keywords

caregiver burden dementia collaborative care institutionalization mediator neuropsychiatric symptoms

Introduction

Dementia significantly contributes to the institutionalization of older adults (Agüero-Torres et al., 2001). Cognitive and physical functions are impaired during the progression of brain diseases. However, the decision to move to a nursing home or institutionalize an older adult is complex and multi-factorial (Caron et al., 2006; Lu et al., 2021; Sansoni et al., 2013). Factors such as disease severity, capability of self-care, resource of informal care, care provider–recipient relationship, socio-cultural context, medical quality, and welfare system all need to be considered (Shepherd-Banigan et al., 2021). This may cause heterogeneous results on predictors of institutionalization in different space-time backgrounds. Although there are some existing studies regarding this issue (Brodaty et al., 2014; Luppa et al., 2012), data in Taiwan are scarce.

Institutionalization places extensive costs on individual family and national aspects (Kuo et al., 2010; Michel et al., 2001). The quality of life of nursing home residents with dementia is lower than that of home-dwelling persons (Olsen et al., 2016). Institutionalization sometimes involves a certain group of people mandating specialized care in different settings (Pinquart & Sörensen, 2006). Requiring caregivers to become equipped with the care skills and necessary resources might serve as a fundamental step in delaying such processes (Brodaty & Gresham, 1989). Foreseeing the obstacles may be helpful for dementia patients and their informal caregivers. In addition, identifying at-risk populations during the initial stage could make clinical practitioners develop individual care plans and, therefore, may delay the process of institutionalization.

It has been postulated that caregiver burden mediates the effect of certain risk factors on institutionalization, particularly on the issues of neuropsychiatric symptoms (de Vugt et al., 2005; Okura et al., 2011; Springate & Tremont, 2014; Terum et al., 2020). Neuropsychiatric symptoms are associated with greater caregiving time and cause a higher caregiver burden (Chen et al., 2018). Therefore, the aims of the study were to (1) probe the institutionalization rate in patients with dementia in Taiwan, (2) identify the predictors of institutionalization, and (3) conduct a mediation analysis of caregiver burden between neuropsychiatric symptoms and institutionalization.

Material and Methods

Participants

This study was conducted using data from a retrospective cohort registered in a dementia collaborative care model in a medical center in Taiwan. Inclusion criteria were (1) patients diagnosed with mild cognitive impairment or dementia by a neurologist, psychiatrist, or geriatrist at the memory clinic (an outpatient clinic setting); (2) entry between October 2015 and November 2020, and (3) consent from patients and their families to join the care model. Exclusion criterion was patients residing in a long-term care institution.

This care model was established in October of 2015. To better fit individual care needs and preferences in each patient and care partner group, detailed data profiles were collected (Jhang et al., 2019, 2020). Patient characteristics related to demographic profile, cognition level, function capability, neuropsychiatric symptoms, comorbidity, and socioeconomic condition were recorded. The stress, mood, and demographic profile of the caregiver were also recorded. An individualized care plan is formed after a team-approach assessment and care needs raised by patients and their families. The initial interview was conducted in person at entry. The collaborative care team remained in contact with the participants through monthly telephone survey and 6-month interval face-to-face interviews.

All data needed in the present study were extracted from electronic charts after deleting personalized information. This clinical study was approved by the institutional review board. Since the design of this study was a retrospective chart review, informed consent was waived by the institutional review board.

Outcome and Variables

The dependent variable was the time until institutionalization. The status of institutionalization was obtained when participants were contacted during follow-up visits or phone calls. Those who still resided in nursing homes in the following two contacts were censored as institutionalization (to exclude those with short-term respite stays in nursing institutions). Time until institutionalization was operationalized as days from the time of entry to dementia collaborative care to the reported institutionalization date. For non-institutionalized patients, time was censored at loss to follow-up, death, or in November 2020 (end of observation).

Dementia due to Alzheimer Disease (AD), Vascular Dementia, and Parkinson’s Disease Dementia were diagnosed according to National Institute on Aging-Alzheimer’s Association (Albert et al., 2011; McKhann et al., 2011), International Society for Vascular Behavioral and Cognitive Disorders (Sachdev et al., 2014), and Movement Disorder Society-Task force criteria (Emre et al., 2007), respectively. We categorized patients into AD and non-AD groups according to the type of dementia.

The Clinical Dementia Rating (CDR) scale was used to determine the severity of dementia and scored using the sum of boxes (CDR-SOB) method (O’Bryant et al., 2010). Walking capability was categorized as fully ambulatory, ambulatory with a cane or other assisting device, and wheelchair-bound or bed-bound. Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory (NPI) (Cummings et al., 1994). The presence of any neuropsychiatric symptoms at baseline (NPI > 0) was grouped with the contrary. Caregivers’ moods and burdens were assessed using the Center for Epidemiological Studies Depression (CES-D) Scale (Lewinsohn et al., 1997) and Zarit Burden Interview (ZBI) (Bédard et al., 2001).

Patient characteristics included disease, comorbidity, and socioeconomic factors. Disease factors included age, sex, CDR-SOB, NPI, etiologic classification (dementia type), and mobility status. Comorbidity included coronary vessel disease (CVD), diabetes mellitus (DM), and hypertension. Socioeconomic factors included education level (accomplishment of primary school education or not), marital status (married or unmarried including divorced, single, in couple, widowed, unspecified), living status (living alone or living with others), and allowance (none, receiving pension or retirement pay). Caregiver characteristics included CES-D, ZBI (0–88), kinship between patient and main caregiver (spouse or other), caregiver’s age, caregiver’s years of education, formal occupation, and marital status (married or unmarried). For characteristics that may vary with time, we chose those variables obtained at entry.

Statistical Analysis

Data were analyzed using R software (R Foundation for Statistical Computing). Nominal variables between patients admitted to institutions and those who were not were compared using Pearson’s chi-square test or Fisher’s exact test, while continuous variables were compared using Student’s t test or Kruskal–Wallis rank sum test. Cox proportional hazard regression was applied to assess the relationship between each predictor and incident institutionalization for survival analysis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. Due to a small sample size and an infrequent event occurrence, univariate Cox regression with Firth’s penalized likelihood (Lin et al., 2013; Van Calster et al., 2020) was performed for each patient’s and caregiver’s factor. Characteristics significant at the p < .1 level were included in the multivariate analysis. A p-value <.05 was considered statistically significant. A subsequent analysis between NPI and ZBI (both as categorical variables) to confirm non-independence was performed using the chi-square test.

Results

In this study, the total number of patients with complete data profiles was 518. Among these patients, 30 (5.8%) were censored due to institutionalization. The median number of censoring days of institutionalized individuals was 524.5. In the comparison of demographic characteristics (Table 1), those who were censored due to institutionalization had a higher CDR-SOB, larger presence of neuropsychiatric symptoms, and lower educational level; more of them lived alone and were unmarried than their counterparts.

Table 1.

Comparison of Covariates Between Institutionalized (1) and Non-Institutionalized (0) Groups.

	0	1	p
N	488	30
Censoring day (median [IQR])	620.00 [391.00, 1006.00]	524.50 [315.50, 854.00]	.183
Age (%)			.462
<70	79 (16.2)	3 (10.0)
70–80	185 (37.9)	10 (33.3)
>80	224 (45.9)	17 (56.7)
Male (%)	168 (34.4)	11 (36.7)	.958
CDR-SOB (median [IQR])	4.50 [2.00, 7.00]	6.00 [5.00, 8.75]	.006
Presence of any NPS (%)	338 (69.3)	27 (90.0)	.027
Non-AD (%)	217 (44.5)	12 (40.0)	.773
Mobility (%)			.184
Fully ambulatory	307 (62.9)	14 (46.7)
Walking with cane	122 (25.0)	10 (33.3)
Wheelchair- or bed-bound	59 (12.1)	6 (20.0)
With CVD (%)	39 (8.0)	4 (13.3)	.491
With DM (%)	144 (29.5)	7 (23.3)	.606
With HTN (%)	273 (55.9)	21 (70.0)	.187
Primary school graduate (%)	269 (55.1)	9 (30.0)	.013
Not married (%)	213 (43.6)	21 (70.0)	.009
Living alone (%)	30 (6.1)	6 (20.0)	.012
Allowance (%)			.811
None	164 (33.6)	10 (33.3)
Pension	294 (60.2)	19 (63.3)
Retirement pay	30 (6.1)	1 (3.3)
CESD ≥ 16 (%)	150 (30.7)	13 (43.3)	.215
ZBI (%)			.232
0_20	165 (33.8)	6 (20.0)
21_40	215 (44.1)	18 (60.0)
41_60	90 (18.4)	4 (13.3)
61_88	18 (3.7)	2 (6.7)
Non-spousal caregiver (%)	338 (69.3)	23 (76.7)	.515
Caregiver’s age (median [IQR])	55.00 [48.00, 65.00]	53.50 [48.00, 63.25]	.600
Caregiver’s education years (median [IQR])	12.00 [9.00, 14.00]	12.00 [6.75, 15.50]	.986
Caregiver with formal occupation (%)	268 (54.9)	17 (56.7)	1.000
Caregiver not married (%)	91 (18.6)	8 (26.7)	.398

CDR-SOB = clinical dementia rating scale scored using the sum of boxes; NPS = Neuropsychiatric symptom; AD = Alzheimer Dementia; CVD = Coronary vessel disease; DM = Diabetes; HTN = Hypertension; CES-D = Center for Epidemiological Studies Depression Scale; ZBI = Zarit burden interview.

In univariate Cox proportional hazards regression with Firth’s penalized likelihood for each patient’s and caregiver’s factor (Table 2), higher CDR-SOB, presence of neuropsychiatric symptoms, loss of walking ability, not accomplishing primary school education, unmarried, living alone, and higher ZBI had a higher HR with a p-value lower than .1. In the multivariate Cox regression with Firth’s penalized likelihood, the presence of any neuropsychiatric symptoms multiplied the risk of institutionalization by 2.90 (95% CI 1.04–11.06). Compared to those who were fully ambulatory, individuals who walked with a cane multiplied the risk of institutionalization by 2.63 (95% CI 1.05–6.40), and the wheelchair-bound and bed-bound groups scored 4.32 (95% CI 1.40–12.47). Those who lived alone carried a HR of 2.92 (95% CI 1.00–7.79).

Table 2.

Univariate and Multivariate Cox Regression with Firth’s Penalized Likelihood for Each Patient’s and Caregiver’s Factor.

Variable	Units	Univariate Analysis		Multivariate Analysis
		Hazard ratio (95% CI)	p-value	Hazard ratio (95% CI)	p-value
Age	<70	Ref
	70–80	1.11 [.36; 4.43]	.861
	>80	1.70 [.60; 6.47]	.339
Gender	Female	Ref
	Male	1.51 [.70; 3.09]	.283
CDR-SOB		1.07 [.99; 1.15]	.058	1.01 [.93; 1.09]	.822
NPI	0	Ref		Ref
	>0	4.06 [1.51; 15.10]	.003	2.90 [1.04; 11.06]	.042
Dementia type	AD	Ref
	Non-AD	1.09 [.52; 2.23]	.814
Mobility	Free	Ref		Ref
	With cane	2.72 [1.18; 6.10]	.020	2.63 [1.05; 6.40]	.039
	Wheelchair- or bed-bound	3.98 [1.46; 9.76]	.009	4.32 [1.40; 12.47]	.013
With CVD		1.74 [.55; 4.34]	.313
With DM		.91 [.37; 1.99]	.829
With HTN		1.70 [.82; 3.85]	.160
Primary school graduate		.39 [.17; .81]	.011	.50 [.22; 1.06]	.071
Unmarried		2.67 [1.28; 6.03]	.008	1.89 [.84; 4.47]	.125
Living alone		3.34 [1.28; 7.49]	.016	2.92 [1.00; 7.79]	.049
Allowance	None	Ref
	Pension	.80 [.38; 1.77]	.573
	Retirement pay	.63 [.07; 2.71]	.583
CES-D	≤16	Ref
	>16	1.78 [.86; 3.61]	.121
ZBI	0_20	Ref		Ref
	21_40	2.23 [.96; 5.93]	.063	1.80 [.75; 4.89]	.196
	41_60	1.42 [.39; 4.70]	.572	.92 [.25; 3.09]	.899
	61_88	4.09 [.75; 16.05]	.095	1.71 [.30; 7.07]	.505
Non-spousal caregiver		1.52 [.70; 3.71]	.306
Caregiver’s age		.98 [.96; 1.01]	.259
Caregiver’s education years		.99 [.92; 1.08]	.862
Caregiver with formal occupation		1.03 [.51; 2.15]	.925
Caregiver unmarried		1.77 [.76; 3.77]	.174

Factors significant at the p< .1 level in univariate analysis were included in the multivariate analysis. Values in bold indicate statistically significant results (p-value < .05) in multivariate analysis in Table 2. Values in bold indicate statistically significant results (p-value < .05) in Table 3.

CDR-SOB indicates clinical dementia rating scale scored using the sum of boxes; NPI, Neuropsychiatric Inventory; AD, Alzheimer dementia; CVD, coronary vessel disease; DM, diabetes; HTN, hypertension; CES-D, Center for Epidemiological Studies Depression Scale; ZBI, Zarit burden interview.

In the mediation analysis, non-independence was observed between NPI and ZBI using the chi-squared test (p = .001). Caregiver burden showed a trend toward institutionalization in the univariate analysis. NPS independently predicted institutionalization in the multivariate analysis. When ZBI was removed from the multivariate analysis, the HR of NPS increased from 2.90 (95% CI 1.04–11.06, p = .042) to 3.24 (95% CI 1.19–12.14, p = .019). The results are shown in Table 3. We succinctly depicted the mediating pathway shown in Figure 1.

Table 3.

Mediation Analysis of Caregiver Burden Between Neuropsychiatric Symptoms and Institutionalization.

	Step 1: ZBI has a Trend on Institutionalization		Step 2: Multivariate Analysis		Step 3: Multivariate Analysis Removing ZBI
	HR [95% CI]	p#	HR [95% CI]	p*	HR [95% CI]	p*
NPI> 0	-		2.90 [1.04; 11.06]	.042	3.24 [1.19; 12.14]	.019
ZBI Ref(0–20) 21–40	2.23 [.96; 5.93]	.063	1.80 [.75; 4.89]	.196	-
41–60	1.42 [.39; 4.70]	.572	.92 [.25; 3.09]	.899
61–88	4.09 [.24; 16.05]	.095	1.71 [.30; 7.07]	.505

In step 2 and 3, all other factors included to adjustment are the same as in Table 2. NPI indicates Neuropsychiatric Inventory; ZBI, Zarit burden interview.

^#p < .1; *p < .05.

Figure 1.

Mediating pathway of caregiver burden, neuropsychiatric symptoms (NPS) and institutionalization.

Discussion

In our study population, institutionalization percentage was much lower than in other countries. Studies from Germany, Australia, and the United States reported a percentage between 25% and 40% (Brodaty et al., 2014; Gaugler et al., 2011; Luppa et al., 2012). There were no data available for comparison with similar contexts in Taiwan. This lower rate may be due to the follow-up time since the care model has been in use for only 5 years with a median follow-up time of approximately one-and-a-half years. Additionally, family caregivers in Taiwan are unlikely to resort to institutionalization unless they can no longer care for their relatives with dementia. This cultural tendency may help to lower the percentage.

This study identified the risk factors associated with institutionalization in patients with dementia in Taiwan. We examined these in comparison to prior research results. CDR-SOB represents the severity of dementia in the present study. Although it was not a significant predictor of institutionalization in the multivariate analysis, a trend (HR = 1.07, 95% CI .99–1.15, p = .058) in nursing home placement was found through univariate analysis.

A previous case-control study in Taiwan found that level of mobility and living alone were associated with institutionalization (Huang et al., 2015). Another study using a similar assessment tool in Taiwan indicated that higher education levels are associated with lower degrees of disability (Huang et al., 2017). The association between marital status and institutionalization had previously been reported in a study in Germany (Luppa et al., 2012). The present study is the first to identify mobility levels and living status as independent predictors in a longitudinal cohort. Some contributing roles of education level and marital status were supported by univariate but not multivariate analysis.

In a systemic review examining the effect of functional status on institutionalization (Toot et al., 2017), the meta-analysis results mainly demonstrated that functional impairment is a significant risk factor. However, components of functional impairment are complicated in dementia, and details regarding the type of activity limitation are heterogeneous. A dementia patient’s ambulatory status is much more straightforward and easier to assess.

It is possible that caregiver burden mediates the effect of neuropsychiatric symptoms on institutionalization (Dufournet et al., 2019; Gaugler et al., 2011; Okura et al., 2011). Though the mediating effect in our mediation analysis was not as robust, the need for a dementia care team to explore and manage neuropsychiatric symptoms and observe their effect on caregiver burden is still worthy of consideration.

Strategies to assist people living with dementia and their caregivers are important. Since neuropsychiatric symptoms and walking ability independently predict institutionalization, a dementia collaborative team should provide individualized caregiver training. Such training would emphasize knowledge and care skills related to dementia, including the recognition of neuropsychiatric symptoms, translocation skills, and fall prevention strategies, among other topics.

Living alone was likely an unmodifiable institutionalization predictor in our study. Clinical practitioners might note this information, however, to identify at-risk groups during the initial approach and subsequently refer these individuals to corresponding social resources for support.

Our study’s strengths are its retrospective cohort design using a neutral data collection process from a collaborative team model and the keeping of reliable records of censoring. For factors that vary with time, we chose those variables obtained at entry. In addition to fitting the basic assumption of the Cox proportional hazard regression model, the initial encounter is certainly the most important part of establishing rapport and is a main determinant of willingness to stay in collaborative care. Previous studies have shown that when caregivers are appropriately supported (Koch et al., 2012; Mittelman et al., 2006; Parker et al., 2008), their perceived stress and willingness to institutionalize a patient may change. The more team members know about predictors of institutionalization and obstacles caregivers may face during care provision, the more and better care they can provide to both caregiver and patient.

The current study has some limitations. This is a single-centered study with a small sample size and an infrequent event occurrence. Caregiver burden showed a trend toward but did not attain significance as a predictor of institutionalization, which might be attributed to the fact that the caregiver burden was also obtained at entry. The mediating effect is not as robust as those measured immediately prior to institutionalization.

Conclusions

For people living with dementia in Taiwan, the presence of neuropsychiatric symptoms, loss of walking ability, and living alone all lead to institutionalization. Additionally, high caregiver burden due to the presence of neuropsychiatric symptoms may partially contribute to institutionalization. Proper management of neuropsychiatric symptoms and empowerment of caregivers may ameliorate the risk of institutionalization.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Approval

This study was approved by the Institutional Review Board of Changhua Christian Hospital (CCH IRB 201217).

Informed Consent

Since the design of the present study was a retrospective chart review. Informed consent was waived by the Institutional Review Board of Changhua Christian Hospital.

ORCID iDs

Yen-Jen Chen

Yi-Cheng Liao

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