Résultats de recherche pour « Nursing homes »

Nursing homes and other long term-care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in U.S. nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, Washington to other skilled nursing facilities. The full extent of staff connections between nursing homes---and the crucial role these connections serve in spreading a highly contagious respiratory infection---is currently unknown given the lack of centralized data on cross-facility nursing home employment. In this paper, we perform the first large-scale analysis of nursing home connections via shared staff using device-level geolocation data from 30 million smartphones, and find that 7 percent of smartphones appearing in a nursing home also appeared in at least one other facility---even after visitor restrictions were imposed. We construct network measures of nursing home connectedness and estimate that nursing homes have, on average, connections with 15 other facilities. Controlling for demographic and other factors, a home's staff-network connections and its centrality within the greater network strongly predict COVID-19 cases. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Results suggest that eliminating staff linkages between nursing homes could reduce COVID-19 infections in nursing homes by 44 percent.

Infections occur frequently in nursing home residents. The most common infections are pneumonia, urinary tract infection, and skin and soft tissue infection. Aging-associated physiologic and pathologic changes, functional disability, institutionalization, and invasive devices all contribute to the high occurrence of infection. Antimicrobial agent use in nursing homes is intense and usually empiric. All of these factors contribute to the increasing frequency of antimicrobial agent-resistant organisms in nursing homes. Programs that will limit the emergence and impact of antimicrobial resistance and infections in nursing homes need to be developed.

Due to its high lethality amongst the elderly, the safety of nursing homes has been of central importance during the COVID-19 pandemic. With test procedures becoming available at scale, such as antigen or RT-LAMP tests, and increasing availability of vaccinations, nursing homes might be able to safely relax prohibitory measures while controlling the spread of infections (meaning an average of one or less secondary infections per index case). Here, we develop a detailed agent-based epidemiological model for the spread of SARS-CoV-2 in nursing homes to identify optimal prevention strategies. The model is microscopically calibrated to high-resolution data from nursing homes in Austria, including detailed social contact networks and information on past outbreaks. We find that the effectiveness of mitigation testing depends critically on the timespan between test and test result, the detection threshold of the viral load for the test to give a positive result, and the screening frequencies of residents and employees. Under realistic conditions and in absence of an effective vaccine, we find that preventive screening of employees only might be sufficient to control outbreaks in nursing homes, provided that turnover times and detection thresholds of the tests are low enough. If vaccines that are moderately effective against infection and transmission are available, control is achieved if 80% or more of the inhabitants are vaccinated, even if no preventive testing is in place and residents are allowed to have visitors. Since these results strongly depend on vaccine efficacy against infection, retention of testing infrastructures, regular voluntary screening and sequencing of virus genomes is advised to enable early identification of new variants of concern.

BACKGROUND: Despite numerous clinical and regulatory efforts, problems of poor quality of care in nursing homes continue, suggesting a need for effective management practices. OBJECTIVE: To test complexity hypotheses about the relationship between management practices (communication openness, decision making, relationship-oriented leadership, and formalization) and resident outcomes (aggressive behavior, restraint use, immobility of complications, and fractures), while controlling for case mix, size, ownership, and director's tenure and experience. METHOD: A cross-sectional correlational field study design was used. Primary data were obtained from directors of nursing and registered nurses employed in 164 Texas nursing homes. Investigators administered self-report surveys onsite. Secondary data were obtained from 1995 Medicaid Cost Reports and the Texas nursing home Minimum Data Set (MDS) and were linked to primary data using a unique identifier. RESULTS: Hypotheses were supported in that each management practice explained one or more of the resident outcomes. Larger size and longer director of nursing tenure and experience also explained better resident outcomes. Predictors explained 11% ñ 21% of the variance. DISCUSSION: Complexity science was used to explain the results. The findings open the door to rethinking nursing home management practice. Practices that increase communication and interaction among people are needed for better resident outcomes.

As the aging population increases and the shortage of healthcare workers increases, the need to examine other means for caring for the aging population increases. One such means is the use of humanoid robots to care for social, emotional, and physical wellbeing of the people above 65. Understanding skilled and long term care nursing home administrators' perspectives on humanoid robots in caregiving is crucial as their insights shape the implementation of robots and their potential impact on resident well-being and quality of life. This authors surveyed two hundred and sixty nine nursing homes executives to understand their perspectives on the use of humanoid robots in their nursing home facilities. The data was coded and results revealed that the executives were keen on exploring other avenues for care such as robotics that would enhance their nursing homes abilities to care for their residents. Qualitative analysis reveals diverse perspectives on integrating humanoid robots in nursing homes. While acknowledging benefits like improved engagement and staff support, concerns persist about costs, impacts on human interaction, and doubts about robot effectiveness. This highlights complex barriers financial, technical, and human and emphasizes the need for strategic implementation. It underscores the importance of thorough training, role clarity, and showcasing technology benefits to ensure efficiency and satisfaction among staff and residents.

AIM: The purpose of this study was to examine determinants of feeling at home and in particular the privacy in nursing homes in The Netherlands. The first question was to what extent nursing homes differed in the degree residents feel at home and experience privacy. The second question was whether feeling at home is related to privacy in the nursing homes. BACKGROUND: Feeling at home is of particular importance to residents of nursing homes because the average length of stay in The Netherlands is about 16 months. A growing number of people are of the opinion that the privacy of the residents has to be improved. Privacy in nursing homes, therefore, has been high on the political agenda over the last few years. Four aspects of privacy were distinguished: privacy related to the characteristics of the building, privacy as a consequence of the attitude of nurses towards residents, privacy in terms of choice and control over time schedules and activities, and privacy related to the amount of disturbance caused by other residents. DESIGN: The data were collected from individual interviews with 686 residents and family-members in 36 nursing homes in The Netherlands. RESULTS: Following quantitative data analysis, it was found that nursing homes differed in the proportion of residents feeling at home as well as in three aspects of privacy. Differences in feeling at home were found to be related to privacy, especially to the perceived attitudes of nurses and perceived disturbance caused by other residents. A weak relationship was found between residents and their perceived privacy of the building. CONCLUSIONS: A significant amount of variation in privacy was found at the nursing home level. This implies that feeling at home is not only individually determined but can be influenced by the nursing home's management policy.

Performance evaluation of nursing homes is usually accomplished by the repeated administration of questionnaires aimed at measuring the health status of the patients during their period of residence in the nursing home. We illustrate how a latent Markov model with covariates may effectively be used for the analysis of data collected in this way. This model relies on a not directly observable Markov process, whose states represent different levels of the health status. For the maximum likelihood estimation of the model we apply an EM algorithm implemented by means of certain recursions taken from the literature on hidden Markov chains. Of particular interest is the estimation of the effect of each nursing home on the probability of transition between the latent states. We show how the estimates of these effects may be used to construct a set of scores which allows us to rank these facilities in terms of their efficacy in taking care of the health conditions of their patients. The method is used within an application based on data concerning a set of nursing homes located in the Region of Umbria, Italy, which were followed for the period 2003--2005.

PURPOSE: This study examined organizational and market factors associated with nursing homes that are most likely to be early adopters of innovations. Early adopter institutions, defined as the first 20% of facilities to adopt an innovation, are important because they subsequently facilitate the diffusion of innovations to others in the industry. DESIGN AND METHODS: Two groups of innovations were examined, special care units and subacute care services. I used discrete-time logistic regression analysis and nationally representative data from 13,162 facilities at risk of being early adopters of innovations during twelve 6-month intervals from 1992 to 1997. RESULTS: Organizational factors that increase the likelihood of early innovation adoption are larger bed size, chain membership, and high levels of private-pay residents. Four market factors that increase the likelihood of early innovation adoption are: a retrospective Medicaid reimbursement methodology, a more competitive environment, higher average income in the county, and a higher number of hospital beds in the county. IMPLICATIONS: This analysis shows that organizational and market characteristics of nursing homes affect their propensity toward early adoption of innovations. Some of the results may be useful for nursing home administrators and policy makers attempting to promote innovation.

Nursing homes are critical facilities for caring frail older adults with round-the-clock formal care and personal assistance. To ensure quality care for nursing home residents, adequate staffing level is of great importance. Current nursing home staffing practice is mainly based on experience and regulation. The objective of this paper is to investigate the viability of experience-based and regulation-based strategies, as well as alternative staffing strategies to minimize labor costs subject to heterogeneous service demand of nursing home residents under various scenarios of census. We propose a data-driven analysis framework to model heterogeneous service demand of nursing home residents and further identify appropriate staffing strategies by combing survival model and computer simulation techniques as well as domain knowledge. Specifically, in the analysis, we develop an agent-based simulation tool consisting of four main modules, namely individual length of stay predictor, individual daily staff time generator, facility level staffing strategy evaluator, and graphical user interface. We use real nursing home data to validate the proposed model, and demonstrate that the identified staffing strategy significantly reduces the total labor cost of certified nursing assistants compared to the benchmark strategies. Additionally, the proposed length of stay predictive model that considers multiple discharge dispositions exhibits superior accuracy and offers better staffing decisions than those without the consideration. Further, we construct different census scenarios of nursing home residents to demonstrate the capability of the proposed framework in helping adjust staffing decisions of nursing home administrators in various realistic settings.

One of the tragic legacies of Hurricane Katrina in public consciousness was the disproportionate loss of life among older nursing home residents.1 Given the similar lack of preparation and reserves in the nursing home sector in the course of many other natural disasters, the coronavirus disease 2019 (COVID-19) pandemic poses urgent questions as to whether healthcare systems and professionals have learned from these experiences. Older age and the presence of comorbidities are associated with increased risk of mortality in the current pandemic. The high prevalence of functional and cognitive impairment and behavioural symptoms add to the risk posed to nursing home residents,2 as well as environments which present barriers to infection control.3 In addition, healthcare professionals globally of all hues have neglected research, recruitment incentivization and quality improvement in nursing home care relative to other areas of clinical practice.4 This is further reflected by evidence of variable and often inadequate preparation for pandemics in the sector,5,6 as well as the absence of infection control from descriptions of the competencies of nurses in care homes.7 The synergy of these factors is reflected in the first major study of COVID-19 in a nursing home. Nearly two-thirds of residents were infected over a 3-week period, with a death rate of 33%: 50 staff members and 16 visitors were also infected.8 In Spain, it has been reported that a significant proportion of COVID-19 associated deaths have been nursing home residents. There is also a concern that many jurisdictions are not including nursing home deaths in the COVID-19 death toll. Although general guidelines emphasize the importance of strict infection control protocols, little acknowledgement is given to the unique challenges faced by nursing homes with significant levels of close-contact physical care. Low staff to resident ratios are further impacted by COVID-19 related sick-leave, quarantine and absconding, threatening the provision of basic care to sick isolated residents. Implementation of isolation procedures and education of residents can be exceptionally complicated for those with significant cognitive impairment and walking with purpose,2 the person-centred term for wandering. Parallels may be drawn between challenges faced in nursing homes during the current pandemic and those seen in previous infectious outbreaks and epidemics. Following the severe acute respiratory syndrome epidemic in 2003, a study showed that the majority of residents in a Hong Kong nursing home reported poor knowledge of the condition and staff reported concerns about contracting the condition themselves9: the willingness and ability of staff to work, and remain at work, may be impacted upon by a disproportionate level of perceived threat during pandemics and disasters. Several governmental agencies and professional bodies have drafted guidelines and statements regarding the provision of residential care during the COVID-19 pandemic of varying quality, scope and emphasis. These sources include the World Health Organization, the Centers for Disease Control and the British Geriatrics Society: the latter laudably highlights that residents who ‘walk with purpose’ will require special consideration.10–12 The implementation of these recommendations requires a more clearly developed governance and leadership structure in nursing homes than is often the case currently, such as the medical director role required by law in the USA. A common strand highlighted is the importance of early, collaborative advanced care planning.10–12 Provision of decision-making support and adequately resourcing facilities to provide good palliative care should also be prioritized.12 Preventive measures and practical advice on social distancing within residential care facilities have been recommended.12 The necessity of these measures in order to protect residents, staff members and the public is widely acknowledged. However, in addition to the challenge of resident understanding and walking with purpose, restriction of visiting and group activities may have a very negative impact on residents’ mental and physical wellbeing and needs to be judiciously implemented. The important role of informal support networks and care staff in the provision of practical and emotional support are undermined during these restrictions. Of considerable importance also is the safeguarding of staff mental and physical wellbeing. On a more fundamental level, education of staff, many of whom will lack dedicated gerontological and healthcare training, is essential in order to dispel myths and impart accurate information concerning the pandemic and optimal support of residents. Older people resident in nursing homes are demonstrably the group most at risk of adverse outcomes and mortality during the current pandemic. Early, collaborative advanced care planning, more formalized leadership and governance, and provision of education and support for residents and staff is essential. At a more fundamental level, a radical rethink is needed on how to develop and integrate high-quality nursing home care into the canon of core healthcare services, with adequate input from a range of gerontological specialities.13 Conflict of interest: None declared.