Predictors of Nursing Home Admission Among a Cohort of Homeless Older Adults Entering Emergency Shelter

Risk of dementia among veterans experiencing homelessness and housing instability

BACKGROUND

In the United States, nearly 85,000 Veterans experienced homelessness during 2020, and thousands more are experiencing housing instability, representing a significant proportion of the population.1 Many Veterans experiencing homelessness are aging and have complex co-occurring medical, psychiatric, and substance use disorders. Homelessness and older age put Veterans at greater risk for age-related disorders, including Alzheimer's disease and related dementias (ADRD).

METHODS

We examined the rate of ADRD diagnosis for Veterans experiencing homelessness and housing instability compared to a matched cohort of stably housed Veterans over a nine-year period using cox proportional hazard models.

RESULTS

In the matched cohort, 95% (n = 88,811) of Veterans were men, and 67% (n = 59,443) were White and were on average 63 years old (SD = 10.8). Veterans with housing instability had a higher hazard of 1.53 (95% confidence interval (CI) 1.50, 1.59) for ADRD compared to Veterans without housing instability.

CONCLUSIONS

Veterans experiencing housing instability have a substantially higher risk of receiving an ADRD diagnosis than a matched cohort of stably housed Veterans. Health systems and providers should consider cognitive screening among people experiencing housing insecurity. Existing permanent supportive housing programs should consider approaches to modify wraparound services to support Veterans experiencing ADRD.

Identifying Predictors of Nursing Home Admission by Using Electronic Health Records and Administrative Data: Scoping Review

Background

Among older adults, nursing home admissions (NHAs) are considered a significant adverse outcome and have been extensively studied. Although the volume and significance of electronic data sources are expanding, it is unclear what predictors of NHA have been systematically identified in the literature via electronic health records (EHRs) and administrative data.

Objective

This study synthesizes findings of recent literature on identifying predictors of NHA that are collected from administrative data or EHRs.

Methods

The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines were used for study selection. The PubMed and CINAHL databases were used to retrieve the studies. Articles published between January 1, 2012, and March 31, 2023, were included.

Results

A total of 34 papers were selected for final inclusion in this review. In addition to NHA, all-cause mortality, hospitalization, and rehospitalization were frequently used as outcome measures. The most frequently used models for predicting NHAs were Cox proportional hazards models (studies: n=12, 35%), logistic regression models (studies: n=9, 26%), and a combination of both (studies: n=6, 18%). Several predictors were used in the NHA prediction models, which were further categorized into sociodemographic, caregiver support, health status, health use, and social service use factors. Only 5 (15%) studies used a validated frailty measure in their NHA prediction models.

Conclusions

NHA prediction tools based on EHRs or administrative data may assist clinicians, patients, and policy makers in making informed decisions and allocating public health resources. More research is needed to assess the value of various predictors and data sources in predicting NHAs and validating NHA prediction models externally.

Predictors and consequences of homelessness in whole-population observational studies that used administrative data: a systematic review

BACKGROUND

Homelessness is a complex societal and public health challenge. Limited information exists about the population-level health and social care-related predictors and consequences of persons with lived experience of homelessness (PEH). Studies that focus on population subgroups or ad hoc questionnaires to gather data are of relatively limited generalisability to whole-population health surveillance and planning. The aim of this study was to find and synthesise information about the risk factors for, and consequences of, experiencing homelessness in whole-population studies that used routine administrative data.

METHOD

We performed a systematic search using EMBASE, MEDLINE, the Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and PsycINFO research databases for English-language studies published from inception until February 2023 that reported analyses of administrative data about homelessness and health and social care-related predictors and consequences. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

RESULTS

Of the 1224 articles reviewed, 30 publications met the inclusion criteria. The included studies examined a wide range of topic areas, and the homelessness definitions used in each varied considerably. Studies were categorised into several topic areas: Mortality, morbidity and COVID-19; health care usage and hospital re-admission; care home admission and shelter stay; and other (e.g. employment, crime victimisation). The studies reported that that the physical and mental health of people who experience homelessness was worse than that of the general population. Homeless individuals were more likely to have higher risk of hospitalisation, more likely to use emergency departments, have higher mortality rates and were at greater risk of needing intensive care or of dying from COVID-19 compared with general population. Additionally, homeless individuals were more likely to be incarcerated or unemployed. The effects were strongest for those who experienced being homeless as a child compared to those who experienced being homeless later on in life.

CONCLUSIONS

This is the first systematic review of whole-population observational studies that used administrative data to identify causes and consequences associated with individuals who are experiencing homelessness. While the scientific literature provides evidence on some of the possible risk factors associated with being homeless, research into this research topic has been limited and gaps still remain. There is a need for more standardised best practice approaches to understand better the causes and consequences associated with being homeless.