Objective: in the past decades, many studies have examined predictors of nursing home placement (NHP) in the elderly. This study provides a systematic review of predictors of NHP in the general ...population of developed countries. Design: relevant articles were identified by searching the databases MEDLINE, Web of Science, Cochrane Library and PSYNDEXplus. Studies based on population-based samples with prospective study design and identification of predictors by multivariate analyses were included. Quality of studies and evidence of predictors were determined. Results: thirty-six studies were identified; one-third of the studies were of high quality. Predictors with strong evidence were increased age, low self-rated health status, functional and cognitive impairment, dementia, prior NHP and a high number of prescriptions. Predictors with inconsistent results were male gender, low education status, low income, stroke, hypertension, incontinence, depression and prior hospital use. Conclusions: findings suggested that predictors of NHP are mainly based on underlying cognitive and/or functional impairment, and associated lack of support and assistance in daily living. However, the methodical quality of studies needs improvement. More theoretical embedding of risk models of NHP would help to establish more clarity in complex relationships in using nursing homes.
Objective
To synthesize new findings from the THRIVE Research Collaborative (The Research Initiative Valuing Eldercare) related to the Green House (GH) model of nursing home care and broadly consider ...their implications.
Data Sources
Interviews and observations conducted in GH and comparison homes, Minimum Data Set (MDS) assessments, Medicare data, and Online Survey, Certification and Reporting data.
Study Design
Critical integration and interpretation of findings based on primary data collected 2011–2014 in 28 GH homes (from 16 organizations), and 15 comparison nursing home units (from 8 organizations); and secondary data derived from 2005 to 2010 for 72 GH homes (from 15 organizations) and 223 comparison homes.
Principal Findings
Implementation of the GH model is inconsistent, sometimes differing from design. Among residents of GH homes, adoption lowers hospital readmissions, three MDS measures of poor quality, and Part A/hospice Medicare expenditures. Some evidence suggests the model is associated with lower direct care staff turnover.
Conclusions
Recommendations relate to assessing fidelity, monitoring quality, capitalizing opportunities to improve care, incorporating evidence‐based practices, including primary care providers, supporting high‐performance workforce practices, aligning Medicare financial incentives, promoting equity, informing broad culture change, and conducting future research.
Green House Adoption and Nursing Home Quality Afendulis, Christopher C.; Caudry, Daryl J.; O'Malley, A. James ...
Health services research,
February 2016, Letnik:
51, Številka:
S1
Journal Article
Recenzirano
Odprti dostop
Objective
To evaluate the impact of the Green House (GH) model on nursing home resident‐level quality of care measures.
Data Sources/Study Setting
Resident‐level minimum data set (MDS) assessments ...merged with Medicare inpatient claims for the period 2005 through 2010.
Study Design
Using a difference‐in‐differences framework, we compared changes in care quality and outcomes in 15 nursing homes that adopted the GH model relative to changes over the same time period in 223 matched nursing homes that had not adopted the GH model.
Principal Findings
For individuals residing in GH homes, adoption of the model lowered readmissions and several MDS measures of poor quality, including bedfast residents, catheter use, and pressure ulcers, but these results were not present across the entire GH organization, suggesting possible offsetting effects for residents of non‐GH “legacy” units within the GH organization.
Conclusions
GH adoption led to improvement in rehospitalizations and certain nursing home quality measures for individuals residing in a GH home. The absence of evidence of a decline in other clinical quality measures in GH nursing homes should reassure anyone concerned that GH might have sacrificed clinical quality for improved quality of life.
Objective
To describe the Green House (GH) model of nursing home (NH) care, and examine how GH homes vary from the model, one another, and their founding (or legacy) NH.
Data Sources/Study Setting
...Data include primary quantitative and qualitative data and secondary quantitative data, derived from 12 GH/legacy NH organizations February 2012—September 2014.
Study Design
This mixed methods, cross‐sectional study used structured interviews to obtain information about presence of, and variation in, GH‐relevant structures and processes of care. Qualitative questions explored reasons for variation in model implementation.
Data Collection/Extraction Methods
Interview data were analyzed using related‐sample tests, and qualitative data were iteratively analyzed using a directed content approach.
Principal Findings
GH homes showed substantial variation in practices to support resident choice and decision making; neither GH nor legacy homes provided complete choice, and all GH homes excluded residents from some key decisions. GH homes were most consistent with the model and one another in elements to create a real home, such as private rooms and baths and open kitchens, and in staff‐related elements, such as self‐managed work teams and consistent, universal workers.
Conclusions
Although variation in model implementation complicates evaluation, if expansion is to continue, it is essential to examine GH elements and their outcomes.
Given the dynamic nursing home (NH) industry and evolving regulatory environment, depiction of contemporary NH culture-change (person/resident-centered) care practice is of interest. Thus, we aimed ...to portray the 2016/2017 prevalence of NH culture change-related processes and structures and to identify factors associated with greater practice prevalence.
We administered a nationwide survey to 2142 NH Administrators at NHs previously responding to a 2009/2010 survey. Seventy-four percent of administrators (1583) responded (with no detectable nonresponse bias) enabling us to generalize (weighted) findings to US NHs. From responses, we created index scores for practice domains of resident-centered care, staff empowerment, physical environment, leadership, and family and community engagement. Facility-level covariate data came from the survey and the Certification and Survey Provider Enhanced Reporting system. Ordered logistic regression identified the factors associated with higher index scores.
Eighty-eight percent of administrators reported some facility-level involvement in NH culture change, with higher reported involvement consistently associated with higher domain index scores. NHs performed the best (82.6/100 weighted points) on the standardized resident-centered care practices index, and had the lowest scores (54.8) on the family and community engagement index. Multivariable results indicate higher index scores in NHs with higher leadership scores and in states having Medicaid pay-for-performance with culture change-related quality measures.
The relatively higher resident-centered care scores (compared with other domain scores) suggest an emphasis on person-centered care in many US NHs. Findings also support pay-for-performance as a potential mechanism to incentivize preferred NH practice.
Many register studies make use of information about permanent nursing home residents. Statistics Denmark (StatD) identifies nursing home residents by two different indirect methods, one based on ...reports from the municipalities regarding home care in taken place in a nursing home, and the other based on an algorithm created by StatD. The aim of the present study was to validate StatD's nursing home register using dedicated administrative municipality records on individual nursing home residents as gold standard.
In total, ten Danish municipalities were selected. Within each Danish Region, we randomly selected one municipality reporting to Stat D (Method 1) and one not reporting where instead an algorithm created by StatD was used to discover nursing home residents (Method 2). Method 1 means that municipalities reported to Stat D whether home care has taken place in a nursing home or in a private home. Method 2 is based on an algorithm created by Stat D for the municipalities where Method 1 is not applicable. Our gold standard was the information from the local administrative system in all ten selected municipalities. Each municipality provided a list with all individuals > 65 years living in a nursing home on January 1st, 2013 as well as the central personal number. This was compared to the list of individuals >65 living in nursing home facilities in the same ten municipalities on January 1st, 2013 retrieved from StatD.
According to the data received directly from the municipalities, which was used as our gold Standard 3821 individuals were identified as nursing home residents. The StatD register identified 6,141 individuals as residents. Additionally, 556 of the individuals identified by the municipalities were not identified in the StatD register. Overall sensitivity for the ten municipalities in the StatD nursing home register was 0.85 (95% CI 0.84-0.87) and the PPV was 0.53 (95% CI 0.52-0.54). The municipalities for which nursing home status was based on the StatD algorithm (method 2) had a sensitivity of 0.84 (95% CI 0.82-0.86) and PPV of 0.48 (95% CI 0.46-0.50). Both slightly lower than the reporting municipalities (method 1) where the sensitivity was 0.87(95% CI 0.85-0.88) and the PPV was 0.57 (95% CI 0.56-0.59). Additionally, the sensitivity and PPV of the Stat D register varied heavily among the ten municipalities from 0.51 (95% CI 0.43-0.59) to 0.96 (95% CI 0.95-0.98) and PPV correspondingly, from 0.14 (95% CI: 0.11-0.17) to 0.73 (95% CI 0.69-0.77).
The overall PPV of StatD nursing home register was low and differences between municipalities existed. Even in countries with extensive nation-wide registers, validating studies should be conducted for outcomes based on these registers.
As in other Western countries, most Norwegian nursing home patients are suffering from multi-pathological conditions and a large majority of them will die in the nursing home. End-of-life care ...represents many challenges, and it is a widespread concern that several nursing homes lack both resources and competence to ensure good quality care. This article examines the types and prevalence of ethical challenges in end-of-life care as nursing home staff consider them, as well as what they believe can help them to better cope with the ethical challenges. It is based on a national survey probing Norwegian nursing homes’ end-of-life care at the ward level conducted in 2007. 664 respondents from 364 nursing homes answered the questionnaire, representing 68% of the patients and 76% of the nursing home sample.
Inadequate care due to lack of resources and breaches of the patient’s autonomy and integrity were the ethical challenges reported most often. Conflicts with the next of kin regarding nursing care and termination of life-prolonging treatment were reported more seldom. However, when asking the respondents to outline one of the most recent ethical dilemmas they had encountered, the majority of the respondents described ethical dilemmas concerning limitation of life-prolonging treatment, often mixed with disagreements between the wish of the family and that of the patient, or between the wish of the next of kin and what the staff consider to be right. Ethical dilemmas associated with breaches of the patient’s autonomy and integrity were also thoroughly described. According to the staff, better ethical knowledge along with more time to reflect on ethical dilemmas were the initiatives most desired to improve the staff’s way of handling ethical challenges. Furthermore, to have an opportunity to consult with a person holding ethical competence was emphasised by more than half of the respondents.
Objectives
To evaluate the trend in the use of direct care in a cohort of nursing home (NH) residents and explore its association with resident characteristics and organizational factors.
...Methods/design
A total of 696 NH residents from 47 Norwegian NHs were included at admissions at NH. In 537 residents, the use of direct care was assessed every 6 months over a course of 3 years. A multiple model was estimated to identify demographic, clinical, and organizational characteristics associated with the use of direct care time.
Results
Six months after admission, on average, 76.2 hours of direct care were rendered to each resident per month, while this number was reduced to 50.3 hours per month at the end of the study period. Most residents (92%) showed a stable use of direct care time, while a small group of residents displayed a much higher and varying use of direct care time. Increasing dementia, neuropsychiatric symptoms, and decreasing function in activities of daily living were associated with higher use of direct care time. Direct care time constituted about 50% of the staff's working time.
Conclusion
In Norwegian NHs, high use of direct care time was associated with younger age, more severe dementia, and severe neuropsychiatric symptoms. By identifying factors that impact on direct care time, preventive measures might be put in place to the benefit of the residents and possibly to improve resource use. Further research should explore the association between direct care time, quality of care, and the residents' quality of life.
Objective
To evaluate Minnesota's Return to Community Initiative's (RTCI) impact on community discharges from nursing homes.
Data Sources
Secondary data were from the Minimum Data Set and RTCI staff ...(April 2014 – December 2016). The sample consisted of 18 444 non‐Medicaid nursing home admissions in Minnesota remaining for at least 45 days, with high predicted probability of community discharge.
Study Design
The RTCI facilitates community discharge for non‐Medicaid nursing home residents by assisting with discharge planning, transitioning to the community, and postdischarge follow‐up. A key evaluation question is how many of those transitions were directly attributable to the program. Return to Community Initiative was implemented statewide without a control group. Program impact was measured using regression discontinuity, a quasi‐experimental design approach that leverages the programs targeting model.
Principal Findings
Return to Community Initiative increased community discharge rates by an estimated 11 percent (P < 0.05) for the targeted population. The program effect was robust to time and increased with level of facility participation in RTCI.
Conclusions
The RTCI had a modest yet significant impact on the community discharge rates for its targeted population. Findings have been applied in strengthening the RTCI's targeting approach and transitioning process.
A substantial proportion of hospitalizations of nursing home (NH) residents may be avoidable. Medicare payment reforms, such as bundled payments for episodes of care and value‐based purchasing, will ...change incentives that favor hospitalization but could result in care quality problems if NHs lack the resources and training to identify and manage acute conditions proactively. Interventions to Reduce Acute Care Transfers (INTERACT) II is a quality improvement intervention that includes a set of tools and strategies designed to assist NH staff in early identification, assessment, communication, and documentation about changes in resident status. INTERACT II was evaluated in 25 NHs in three states in a 6‐month quality improvement initiative that provided tools, on‐site education, and teleconferences every 2 weeks facilitated by an experienced nurse practitioner. There was a 17% reduction in self‐reported hospital admissions in these 25 NHs from the same 6‐month period in the previous year. The group of 17 NHs rated as engaged in the initiative had a 24% reduction, compared with 6% in the group of eight NHs rated as not engaged and 3% in a comparison group of 11 NHs. The average cost of the 6‐month implementation was $7,700 per NH. The projected savings to Medicare in a 100‐bed NH were approximately $125,000 per year. Despite challenges in implementation and caveats about the accuracy of self‐reported hospitalization rates and the characteristics of the participating NHs, the trends in these results suggest that INTERACT II should be further evaluated in randomized controlled trials to determine its effect on avoidable hospitalizations and their related morbidity and cost.
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