Factors Associated with Long-Stay Nursing Home Admissions Among the U.S. Elderly Population: Comparison of Logistic Regression and the Cox Proportional Hazards Model with Policy Implications for Social Work (original) (raw)
Related papers
Predictors of Nursing Home Admission: A Social Work Perspective
Australian Social Work, 2009
Institutionalisation of geriatric patients is a growing trend in ageing societies, such as Singapore. Earlier studies focused on the sociodemographic profile and attributes of nursing home residents and applications, but neglected to address the predictors of nursing home admission from a social work perspective. The present retrospective study identifies independent risk factors that predispose a patient to a nursing home discharge from a general rehabilitation ward in a community hospital in Singapore, with a multidisciplinary emphasis on clinical intervention. Factor analysis results reinforced findings that functional impairment and dementia are consistent predictors of nursing home admission. Multivariate logistic regression analysis showed that positive predictors of nursing home admission include older age, length of hospital stay, low socioeconomic status, dementia, and functional disability. Social work interventions include early referrals to the medical social worker, so that options for social and family support can be explored prior to deciding to place patients in a nursing home. Other interventions include suitable family therapy and counselling for patients and their families.
Predicting nursing home admission in the U.S: a meta-analysis
BMC Geriatrics, 2007
Background: While existing reviews have identified significant predictors of nursing home admission, this meta-analysis attempted to provide more integrated empirical findings to identify predictors. The present study aimed to generate pooled empirical associations for sociodemographic, functional, cognitive, service use, and informal support indicators that predict nursing home admission among older adults in the U.S.
Long-Term Nursing Home Entry: A Prognostic Model for Older Adults with a Family or Unpaid Caregiver
Journal of the American Geriatrics Society, 2018
To comprehensively examine factors associated with long-term nursing home (NH) entry from 6 domains of older adult and family caregiver risk from nationally representative surveys and develop a prognostic model and a simple scoring system for use in risk stratification. Retrospective observational study. National Long-Term Care Surveys 1999 and 2004 and National Health and Aging Trends Study 2011 and linked caregiver surveys. Community-living older adults receiving help with self-care disability and their primary family or unpaid caregiver (N=2,676). Prediction of long-term NH entry (>100 days or ending in death) by 24 months follow up, ascertained from Minimum Data Set assessments and dates of death from Medicare enrollment files. Risk factors were measured from survey responses. In total, 16.1% of older adults entered a NH. Our final model and risk scoring system includes 7 independent risk factors: older adult age (1 point/5 years), living alone (5 points), dementia (3 points)...
Determinants of long-term home nursing care among people over 65 years of age
Medical Studies, 2018
Introduction: With age comes increasing loss of efficiency, and thereby increasing dependence on others and increasing demand for nursing and care services Aim of the research: To determine the factors of demand for long-term home nursing care among people over 65 years old. Material and methods: The research was conducted on 504 subjects aged between 66 and 94 years. The qualified respondents for the long-term home-based nursing care scored no more than 40 points in Barthel's Index. The following research tools were used: Barhel's Index, IADL, GDS, AMTS, and an authorial interview questionnaire. Results: For long-term home-based nursing care 15.67% (n = 79) of subjects were qualified; there were more women (n = 61) than men (n = 18) (p < 0.05). The age of respondents qualified for long-term nursing care was higher than the age of other test subjects (p < 0.001). Among subjects qualified for long-term home-based nursing care there were more people with incomplete primary education (p < 0.01) and a higher number of multi-diseases than with the rest (p < 0.01). Moreover, people qualified for long-term nursing care had worsened agility to perform complex life activities and worsened cognitive and emotional performance (p < 0.001) than people who did not qualify for such services. Conclusions: The need for long-term nursing care was determined by progressing ageing, functional, emotional, and cognitive disorders, more frequent with women, people with low education, and multi-diseases. Streszczenie Wprowadzenie: Z wiekiem postępuje utrata sprawności, a także zwiększa się uzależnienie od innych osób i zapotrzebowanie na świadczenia pielęgnacyjne i opiekuńcze. Cel pracy: Określenie czynników determinujących zapotrzebowanie na długoterminową domową opiekę pielęgniarską u osób po 65. roku życia zamieszkujących na wsi. Materiał i metody: Badaniami objęto 504 osoby w wieku 66-94 lat. Do długoterminowej domowej opieki pielęgniarskiej zakwalifikowano respondentów, którzy w skali Barthel uzyskali nie więcej niż 40 pkt. W pracy zastosowano takie narzędzia badawcze, jak skala Barthel, IADL, GDS, AMTS oraz autorski kwestionariusz wywiadu. Wyniki: Do długoterminowej domowej opieki pielęgniarskiej zakwalifikowano 15,67% (n = 79) badanych, więcej kobiet (n = 61) niż mężczyzn (n = 18) (p < 0,05). Wiek respondentów zakwalifikowanych do długoterminowej opieki pielęgniarskiej był wyższy od wieku pozostałych badanych (p < 0,001). Wśród osób zakwalifikowanych do długoterminowej domowej opieki pielęgniarskiej było więcej osób z wykształceniem niepełnym podstawowym (p < 0,01
Aging clinical and experimental research, 2017
The need for long-term care services increases with age. However, little is known about the predictors of long-term care (LTC) entry among the oldest old. Aim of this study was to assess predictors of LTC entry in a sample of men and women aged 90 years and older. This study was based on the Vitality 90 + Study, a population-based study of nonagenarians in the city of Tampere, Finland. Baseline information about health, functioning and living conditions were collected by mailed questionnaires. Information about LTC was drawn from care registers during the follow-up period extending up to 11 years. Cox regression models were used for the analyses, taking into account the competing risk of mortality. During the mean follow-up period of 2.3 years, 844 (43%) subjects entered first time into LTC. Female gender (HR 1.39, 95% CI 1.14-1.69), having at least two chronic conditions (HR 1.24, 95% CI 1.07-1.44), living alone (HR 1.37, 95% CI 1.15-1.63) and help received sometimes (HR 1.23, 95% ...
BMC Geriatrics, 2022
Background: This study examines predictors of nursing home admission (NHA) in Belgium in order to contribute to a better planning of the future demand for nursing home (NH) services and health care resources. Methods: Data derived from the Belgian 2013 health interview survey were linked at individual level with health insurance data (2012 tot 2018). Only community dwelling participants, aged ≥65 years at the time of the survey were included in this study (n = 1930). Participants were followed until NHA, death or end of study period, i.e., December 31, 2018. The risk of NHA was calculated using a competing risk analysis. Results: Over the follow-up period (median 5.29 years), 226 individuals were admitted to a NH and 268 died without admission to a NH. The overall cumulative risk of NHA was 1.4, 5.7 and 13.1% at respectively 1 year, 3 years and end of follow-up period. After multivariable adjustment, higher age, low educational attainment, living alone and use of home care services were significantly associated with a higher risk of NHA. A number of need factors (e.g., history of falls, suffering from urinary incontinence, depression or Alzheimer's disease) were also significantly associated with a higher risk of NHA. On the contrary, being female, having multimorbidity and increased contacts with health care providers were significantly associated with a decreased risk of NHA. Perceived health and limitations were both significant determinants of NHA, but perceived health was an effect modifier on limitations and vice versa. Conclusions: Our findings pinpoint important predictors of NHA in older adults, and offer possibilities of prevention to avoid or delay NHA for this population. Practical implications include prevention of falls, management of urinary incontinence at home and appropriate and timely management of limitations, depression and Alzheimer's disease. Focus should also be on people living alone to provide more timely contacts with health care providers. Further investigation of predictors of NHA should include contextual factors such as the availability of nursing-home beds, hospital beds, physicians and waiting lists for NHA.
Predictors of entry to the nursing home: Does length of follow-up matter?
Archives of Gerontology and Geriatrics, 2011
This study examined the extent to which predictors of nursing home entry vary in their salience as a function of length of follow-up. Participants were 201 persons attending five senior day care centers. The impact of baseline assessment on nursing home entry was examined at one, two, and three-year follow-up periods. Analysis revealed that MMSE, IADL, physical non-aggressive agitated behavior, and 4 indicators of caregiver burden had significantly changing impacts on time to nursing home entry. Only depressed affect and age remained significant predictors at all three follow-up periods in the multivariate analysis. Physical and verbal aggressive agitation and declining caregiver health were significant predictors in the short term. Socializing and ethnicity became predictors at year three. We have demonstrated that while some predictors of nursing home placement are robust over varying follow-up times, the predictive value of others changes with length of the follow-up period. Length of follow-up needs to be taken into account in clarifying the processes that predict nursing home entry.