Predictors of nursing-home entry for elders in Belgium

Background Due to the aging of the population the demand for long-term care services is expected to rise during the coming years. For a better planning of health care resources policy makers have to be aware of risk factors associated to nursing home entry (NHE). The present study aims to identify predictors of NHE in a representative sample of Belgian community dwelling older residents. Methods Date from the participants of the Belgian health interview survey (BHIS) 2013 aged 65 years and over were individually linked with longitudinal data from the Belgian compulsory health insurance data (BCHI) over a 5-year period (2012-2017). Institutionalized BHIS participants were excluded, resulting in a final database of 1,927 individuals. A multivariate Cox proportional hazards model was fit to estimate the hazard of NHE. The model examined the hazard of NHE over the follow-up period in function of predisposing, enabling and need variables observed at baseline. All analyses were done using SAS 9.3 taking into account the survey design settings. Results Over the follow-up period, 169 out of 1,927 individuals entered in NH (56% males, mean age =74.7±0.25). Significant predictors of NHE were older age (hazard ratio (HR) =2.40, CI = 1.23-4.67 and HR = 6.19, 95% CI = 2.75-13.92, respectively for 75-84 years and 85+ years compared to 65-74 years), living condition (HR = 4.28, 95% CI = 1.01-18.19 for living alone), severity of limitation in ADLs (HR = 2.61, 95% CI = 1.39-4.88 for moderate limitation and HR = 2.40, 95% CI = 1.10-5.26 for severe limitation, compared to those without limitation). Conclusions Apart from age and living condition, the ADLs limitations were the strongest predictors of NHE. Public health action to reduce NHE of older people should first of all focus on preventive action at middle age which will reduce activity limitations at later age. Key messages Risk profiles for NHE are highly dependent individuals. NH should be more specialized with qualified professionals.

Old, Frail, and Uninsured: Accounting for Features of the U.S. Long‐Term Care Insurance Market

Half of U.S. 50‐year‐olds will experience a nursing home stay before they die, and one in ten will incur out‐of‐pocket long‐term care expenses in excess of $200,000. Surprisingly, only about 10% of individuals over age 62 have private long‐term care insurance (LTCI) and LTCI takeup rates are low at all wealth levels. We analyze the contributions of Medicaid, administrative costs, and asymmetric information about nursing home entry risk to low LTCI takeup rates in a quantitative equilibrium contracting model. As in practice, the insurer in the model assigns individuals to risk groups based on noisy indicators of their nursing home entry risk. All individuals in frail and/or low‐income risk groups are denied coverage because the cost of insuring any individual in these groups exceeds that individual's willingness‐to‐pay. Individuals in insurable risk groups are offered a menu of contracts whose terms vary across risk groups. We find that Medicaid accounts for low LTCI takeup rates of poorer individuals. However, administrative costs and adverse selection are responsible for low takeup rates of the rich. The model reproduces other empirical features of the LTCI market including the fact that owners of LTCI have about the same nursing home entry rates as non‐owners.

Disparities in the Prevalence of Unmet Needs and Their Consequences Among Black and White Older Adults

Objective:We document differential prevalence of need for assistance with personal, instrumental, and mobility tasks and adverse consequences of unmet needs, nursing home relocation, and mortality among Black and White older adults. Method: Data are from the National Health and Aging Trends Study. Using logistic and multinomial logistic regression, we determine whether race is predictive of reporting need or adverse consequence and test the role of race as a moderator of the relationship between baseline need and three 1-year outcomes. Results: Black older adults are more likely to experience a consequence of unmet need (35.33% vs. 29.97%, p = .028) in unadjusted models. In adjusted models, we find no moderating effect of race on baseline need on nursing home placement (0.00, 95% confidence interval [CI] = [−2.43, 2.42], p = .991), mortality (0.73, 95% = [−1.58, 0.11], p = .089), or a Round 2 consequence of unmet (−0.51, 95% CI = [−1.15, 0.14], p = .121). Discussion: This work highlights the complex relationship between race, need, unmet need, mortality, and nursing home entry.

Predictors of nursing home admission among Alzheimer's disease patients with psychosis and/or agitation

ABSTRACTBackground: The purpose of this study is to identify factors that predict nursing home placement among community-dwelling Alzheimer's disease (AD) patients with psychosis and/or agitation in a randomized clinical trial (ClinicalTrials.gov number, NCT00015548).Methods: 418 participants with AD enrolled in the Clinical Antipsychotic Trial of Intervention Effectiveness – AD (CATIE-AD) trial of anti-psychotic medications and having no evidence of nursing home use at baseline were followed at 9 months post-random assignment using data provided by caregiver proxy. χ2 tests, t-tests and Cox proportional hazard modeling were used to examine the baseline correlates of nursing home use.Results: Of outpatients with no prior nursing home use, 15% were placed in a nursing home in the 9 months following baseline, with the average time to placement being 122 days. Bivariate analyses indicate that those with prior outpatient mental health use at study entry were more likely to be admitted; so too were those with worse physical functioning – i.e. lower scores on the AD Cooperative Study Activities of Daily Living Scale (ADCS-ADL), lower utility scores on the Health Utility Index (HUI)-III, and worse cognition on the Mini-mental State Examination. Controlling for other factors, non-Hispanic white race (hazard ratio [HR] = 2.16) and prior mental health use (HR = 1.87) increased the likelihood of admission. Those with higher ADCS-ADL scores were less likely to be placed (HR = 0.97).Conclusions: Factors leading to nursing home entry among psychotic/agitated AD patients are similar to the general population, though high incidence of nursing home entry highlights the importance of accounting for such utilization in health economic studies of AD outcomes. It also highlights the importance of using information on ADLs and other characteristics to develop profiles identifying those at greater or lesser risk of nursing home entry and, in so doing, inform population planning associated with AD and identification of those patients and caregivers who might benefit most from interventions to prevent eventual placement.