Associations with rates of falls among home care clients in Ontario, Canada: a population-based, cross-sectional study

Clinical and Sociodemographic Characteristics of New Residents of Assisted Living: A Nested Case-Control Study

OBJECTIVE

To examine transitions to an assisted living facility among community-dwelling older adults who received publicly funded home care services.

DESIGN

Nested case-control study.

SETTING AND PARTICIPANTS

Linked, population-level health system administrative data were obtained from adults aged 65 years and older who received home care services in Ontario, Canada, from April 1, 2018, to December 31, 2019. New residents of assisted living were matched on age, sex, and initiation date of home care (± 7 days) to community-dwelling home care recipients in a 1:4 ratio.

METHODS

Clinical and functional status, health service use, sociodemographic variables, and community-level characteristics were examined; conditional logistic regression was used to model associations with a transition to an assisted living facility.

RESULTS

There were 2427 new residents of assisted living who were matched to 9708 home care recipients [mean (SD) age 85.5 (6.02) years, 72% female]. Most of the new residents were concentrated in urban communities and communities with higher income quintiles. New residents had an increased rate of physician-diagnosed dementia [adjusted hazard ratio (aHR), 1.28; 95% CI, 1.14-1.43], mood disorders (aHR, 1.17; 95% CI, 1.05-1.29), and cardiac arrhythmias (aHR, 1.19; 95% CI, 1.07-1.32). They also had higher rates of mild cognitive impairment (aHR, 1.43; 95% CI, 1.24-1.66), 2 or more falls (aHR, 1.29; 95% CI, 1.11-1.51), participation in activities of long-standing interest in the past 7 days (aHR, 1.29; 95% CI, 1.11-1.50), and a lower rate of a spouse or partner unpaid caregiver vs a child (aHR, 0.66; 95% CI, 0.56-0.79).

CONCLUSIONS AND IMPLICATIONS

New residents of assisted living were mostly women, were cognitively impaired, had clinical comorbidities that could increase their risk of injuries, and had caregivers who were their children. These findings stress the importance of upscaling memory and dementia care in assisted living to address the needs of this population.

Profiling chronic diseases and hospitalizations in older home care recipients: a nationwide cohort study in Sweden

BACKGROUND

Older adults with home care (HC) often have complex disease patterns and use healthcare extensively. Increased understanding is necessary to tailor their care. To our knowledge, this is the first study to describe patterns of morbidity and hospitalizations among community-dwelling older HC recipients nationwide and in subgroups defined by age, sex, and amount of HC, and to compare patterns to community-dwelling older adults without HC.

METHODS

Nationwide register-based cohort study in community-dwelling adults aged 70 and older receiving publicly funded HC in Sweden on January 1st 2019 and an age-and-sex matched comparison group ("non-HC recipients"). Using register data from inpatient and specialized outpatient care, we assessed the prevalence of sixty chronic diseases, frailty, multimorbidity and hospitalizations, calculated incidence rates and explored reasons for hospitalizations during two years of follow-up.

RESULTS

We identified 138,113 HC recipients (mean age 85, 66% women, 57% ≥5 chronic diseases). The most prevalent diseases were hypertension (55%) and eye conditions (48%). Compared to non-HC recipients, HC recipients had a higher prevalence of almost all diseases, with an overrepresentation of neurological (26.1 vs. 9.5%) disease and dementia (9.3 vs. 1.5%). 61% of HC recipients were hospitalized at least once during two years, which was 1.6 times as often as non-HC recipients. One third of HC recipients´ hospitalizations (37.4%) were due to injuries, infections, and heart failure. Hospitalizations for chronic obstructive pulmonary disease, confusion, infections, and breathing difficulties were 3-5 times higher among HC recipients compared to non-HC recipients.

CONCLUSION

Compared to non-HC recipients, HC recipients more often live alone, have higher degrees of frailty, suffer from more chronic diseases, especially neurological disease, and are hospitalized almost twice as often. The results provide a thorough description of HC recipients, which might be useful for targeted healthcare interventions including closer collaboration between primary care, neurologists, and rehabilitation.

Comprehensive Geriatric Assessment in the era of telemedicine

The aging global population poses significant medical and social challenges, necessitating efforts to promote healthy aging. Comprehensive Geriatric Assessment (CGA) is a multidimensional diagnostic approach for older adults that aims to improve overall health. Remote CGA, facilitated by technological advancements, offers convenience and other potential advantages. It enables early disease detection, monitors chronic disease progression, delivers personalized care, and optimizes healthcare resources for better health outcomes in older individuals. However, remote CGA also has limitations, including technological requirements, data security, and the need for comprehensive evaluation and simplicity. Collaborative efforts are essential to developing a digital home-based CGA platform that addresses accessibility issues and tailors the assessment process to meet the needs of older adults. Continuous optimization of remote CGA can become a pivotal tool for advancing geriatric care and ensuring the well-being of the aging population. Geriatr Gerontol Int 2024; 24: 67-73.

Capturing Concerns about Patient Deterioration in Narrative Documentation in Home Healthcare

Home healthcare (HHC) agencies provide care to more than 3.4 million adults per year. There is value in studying HHC narrative notes to identify patients at risk for deterioration. This study aimed to build machine learning algorithms to identify "concerning" narrative notes of HHC patients and identify emerging themes. Six algorithms were applied to narrative notes (n = 4,000) from a HHC agency to classify notes as either "concerning" or "not concerning." Topic modeling using Latent Dirichlet Allocation bag of words was conducted to identify emerging themes from the concerning notes. Gradient Boosted Trees demonstrated the best performance with a F-score = 0.74 and AUC = 0.96. Emerging themes were related to patient-clinician communication, HHC services provided, gait challenges, mobility concerns, wounds, and caregivers. Most themes have been cited by previous literature as increasing risk for adverse events. In the future, such algorithms can support early identification of patients at risk for deterioration.

Identification of Contributing Factors of Falls and Non-Fall Accidents Among Home Care Clients: A Retrospective Study Using Incident Reports

To prevent falls and other accidents among home care clients, it is essential to gather high-quality information on the factors contributing to the accidents. Incident reporting systems are used in home care units to generate information for risk management. This study aimed to explore the contributing factors of falls and non-fall accidents among home care clients and to evaluate the accuracy of the information on contributing factors gained from the incident reporting system. An existing dataset was used—safety incident reports concerning accidents involving home care clients. The incident reports (n = 323) were stored in the social- and health care organization’s incident reporting database from 2018 to 2020. The free-text narratives describing factors contributing to the event’s occurrence were analyzed using inductive content analysis, and the frequencies of the main category codes were recorded. The results were then compared with the frontline managers’ analyses of the narratives, where the managers used the classification of contributing factors provided by the system. According to incident reports, intrinsic (person-specific), behavior-related and extrinsic (environment-related) factors contributed to accidents among home care clients. Intrinsic and behavior-related factors were reported more often than extrinsic factors. The classified information on contributing factors did not correspond in all respects to the descriptions in the incident reports. To ensure high-quality information for safety management, incident reporting tools must be appropriate for use in the home care context. Both the reporter of an adverse event and the individual responsible for analyzing the report play essential roles in identifying contributing factors of accidents.

Association between falls in elderly and the number of chronic diseases and health-related behaviors based on CHARLS 2018: health status as a mediating variable

OBJECTIVE

Falling is one of the main causes of death and morbidity in the elderly. This study aims to explore the association between elderly patients with chronic diseases and their health-related behaviors and falls in the elderly, and to provide clues for the prevention and intervention of injuries caused by falls in the elderly.

METHODS

Based on the basic demographic characteristics data, number of chronic diseases, health-related behaviors, and physical and mental health data of 5867 elderly people aged 60 and above in the 2018 CHARLS data, this paper used ordered logit regression to analyze the correlation between chronic diseases and their health-related behaviors and falls of Chinese elderly. On this basis, it also distinguishes whether there is care or not, explores whether the related factors of falls of elderly people will be different, and tests the intermediary effect of health status to further explore its mechanism.

RESULTS

The number of chronic diseases and health-related behaviors in the four dimensions of sleeptime, drinking, smoking, and activity are significantly correlated with falls in the elderly. Among them, health status plays a significant mediating role in the relationship of the number of chronic diseases and sleeptime and activity on the falls of the elderly. In addition, compared with the elderly without care, the risk of falls in the elderly in care is only related to the number of chronic diseases and sleeptime, while the elderly without care is related to the number of chronic diseases and multiple factors such as smoking, drinking and activity.

CONCLUSION

Falls are significantly associated with chronic disease and health-related behaviors, while risk or protective factors for falls vary according to whether older adults are cared for. Therefore, targeted interventions can be made for the factors that affect the fall of the elderly according to different situations.

Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature

BACKGROUND

The term "data science" encompasses several methods, many of which are considered cutting edge and are being used to influence care processes across the world. Nursing is an applied science and a key discipline in health care systems in both clinical and administrative areas, making the profession increasingly influenced by the latest advances in data science. The greater informatics community should be aware of current trends regarding the intersection of nursing and data science, as developments in nursing practice have cross-professional implications.

OBJECTIVES

This study aimed to summarize the latest (calendar year 2020) research and applications of nursing-relevant patient outcomes and clinical processes in the data science literature.

METHODS

We conducted a rapid review of the literature to identify relevant research published during the year 2020. We explored the following 16 topics: (1) artificial intelligence/machine learning credibility and acceptance, (2) burnout, (3) complex care (outpatient), (4) emergency department visits, (5) falls, (6) health care-acquired infections, (7) health care utilization and costs, (8) hospitalization, (9) in-hospital mortality, (10) length of stay, (11) pain, (12) patient safety, (13) pressure injuries, (14) readmissions, (15) staffing, and (16) unit culture.

RESULTS

Of 16,589 articles, 244 were included in the review. All topics were represented by literature published in 2020, ranging from 1 article to 59 articles. Numerous contemporary data science methods were represented in the literature including the use of machine learning, neural networks, and natural language processing.

CONCLUSION

This review provides an overview of the data science trends that were relevant to nursing practice in 2020. Examinations of such literature are important to monitor the status of data science's influence in nursing practice.

Comprehensive geriatric assessment

Geriatric assessment is a multidimensional and interdisciplinarily deployed diagnostic process to evaluate functional capacities and impairments in geriatric patients. The results of geriatric assessment are the basis for planning of therapeutic interventions in the multidisciplinary geriatrics team. Geriatric assessment adds essential information to the state-of-the-art diagnostic tests, such as physical examination, laboratory tests, or imaging techniques, to acquire a holistic picture about health and functional problems and needs of geriatric patients. Studies have demonstrated that geriatric assessment and the following geriatric treatment improves prognosis and increases the chance of older patients remaining in their own home after discharge from hospital after admission for an acute disease.