Predictors of mortality shortly after entering a long-term care facility.

OBJECTIVE: Moving into a long-term care facility (LTCF) requires substantial personal, societal and financial investment. Identifying those at high risk of short-term mortality after LTCF entry can help with care planning and risk factor management. This study aimed to: (i) examine individual-, facility-, medication-, system- and healthcare-related predictors for 90-day mortality at entry into an LTCF and (ii) create risk profiles for this outcome. DESIGN: Retrospective cohort study using data from the Registry of Senior Australians. SUBJECTS: Individuals aged ≥ 65 years old with first-time permanent entry into an LTCF in three Australian states between 01 January 2013 and 31 December 2016. METHODS: A prediction model for 90-day mortality was developed using Cox regression with the purposeful variable selection approach. Individual-, medication-, system- and healthcare-related factors known at entry into an LTCF were examined as predictors. Harrell's C-index assessed the predictive ability of our risk models. RESULTS: 116,192 individuals who entered 1,967 facilities, of which 9.4% (N = 10,910) died within 90 days, were studied. We identified 51 predictors of mortality, five of which were effect modifiers. The strongest predictors included activities of daily living category (hazard ratio [HR] = 5.41, 95% confidence interval [CI] = 4.99-5.88 for high vs low), high level of complex health conditions (HR = 1.67, 95% CI = 1.58-1.77 for high vs low), several medication classes and male sex (HR = 1.59, 95% CI = 1.53-1.65). The model out-of-sample Harrell's C-index was 0.773. CONCLUSIONS: Our mortality prediction model, which includes several strongly associated factors, can moderately well identify individuals at high risk of mortality upon LTCF entry.

Sequencing analysis of SARS-CoV-2 cases in Slovenian long-term care facilities to support outbreak control.

Introduction: Residents of long-term care facilities (LTCFs) are at high risk of morbidity and mortality due to COVID-19, especially when new variants of concern (VOC) emerge. To provide intradisciplinary data in order to tailor public health interventions during future epidemics, available epidemiologic and genomic data from Slovenian LTCFs during the initial phases of the COVID-19 pandemic was analyzed. Methods: The first part of the study included SARS-CoV-2 reverse-transcription Real-Time PCR (rtRT-PCR) positive LTCF residents, from 21 facilities with COVID-19 outbreaks occurring in October 2020. The second part of the study included SARS-CoV-2 rtRT-PCR positive LTCF residents and staff between January and April 2021, when VOC Alpha emerged in Slovenia. Next-generation sequencing (NGS) was used to acquire SARS-CoV-2 genomes, and lineage determination. In-depth phylogenetic and mutational profile analysis were performed and coupled with available field epidemiological data to assess the dynamics of SARS-CoV-2 introduction and transmission. Results: 370/498 SARS-CoV-2 positive residents as well as 558/699 SARS-CoV-2 positive residents and 301/358 staff were successfully sequenced in the first and second part of the study, respectively. In October 2020, COVID-19 outbreaks in the 21 LTCFs were caused by intra-facility transmission as well as multiple independent SARS-CoV-2 introductions. The Alpha variant was confirmed in the first LTCF resident approximately 1.5 months after the first Alpha case was identified in Slovenia. The data also showed a slower replacement of existing variants by Alpha in residents compared to staff and the general population. Discussion: Multiple SARS CoV-2 introductions as well as intra-facility spreading impacted disease transmission in Slovenian LTCFs. Timely implementation of control measures aimed at limiting new introductions while controlling in-facility transmission are of paramount importance, especially as new VOCs emerge. Sequencing, in conjunction with epidemiological data, can facilitate the determination of the need for future improvements in control measures to protect LTCF residents from COVID-19 or other respiratory infections.

Survival, Function, and Cognition After Hospitalization in Long-Term Acute Care Hospitals.

Importance: More than 70 000 Medicare beneficiaries receive care in long-term acute care hospitals (LTCHs) annually for prolonged acute illness. However, little is known about long-term functional and cognitive outcomes of middle-aged and older adults after hospitalization in an LTCH. Objective: To describe survival, functional, and cognitive status after LTCH hospitalization and to identify factors associated with an adverse outcome. Design, Setting, and Participants: This retrospective cohort study included middle-aged and older adults enrolled in the Health and Retirement Study (HRS) with linked fee-for-service Medicare claims. Included participants were aged 50 years or older with an LTCH admission between January 1, 2003, and December 31, 2016, with HRS interviews available before admission. Data were analyzed between November 1, 2021, and June 30, 2023. Main Outcomes and Measures: Function and cognition were ascertained from HRS interviews conducted every 2 years. The primary outcome was death or severe impairment in the 2.5 years after LTCH hospitalization, defined as dependencies in 2 or more activities of daily living (ADLs) or dementia. Multivariable logistic regression was performed to evaluate associations with a priori selected risk factors including pre-LTCH survival prognosis (Lee index score), pre-LTCH impairment status, and illness severity characterized by receipt of mechanical ventilation and prolonged intensive care unit stay of 3 days or longer. Results: This study included 396 participants, with a median age of 75 (IQR, 68-82) years. Of the participants, 201 (51%) were women, 125 (28%) had severe impairment, and 318 (80%) died or survived with severe impairment (functional, cognitive, or both) within 2.5 years of LTCH hospitalization. After accounting for acute illness characteristics, prehospitalization survival prognosis as determined by the Lee index score and severe baseline impairment (functional, cognitive, or both) were associated with an increased likelihood of death or severe impairment in the 2.5 years after LTCH hospitalization (adjusted odds ratio [AOR], 3.2 [95% CI, 1.7 to 6.0] for a 5-point increase in Lee index score; and AOR, 4.5 [95% CI, 1.3 to 15.4] for severe vs no impairment). Conclusions and Relevance: In this cohort study, 4 of 5 middle-aged and older adults died or survived with severe impairment within 2.5 years of LTCH hospitalization. Better preadmission survival prognosis and functional and cognitive status were associated with lower risk of an adverse outcome, and these findings should inform decision-making for older adults with prolonged acute illness.

Potentially inappropriate prescriptions for poly-treated patients in long-term care facilities: retrospective pharmacoutilization analysis.

BACKGROUND This study aimed to investigate, among elderly patients in long-term care (LTC) facilities, potentially inappropriate drug prescriptions, potentially interactions and verify whether they can be traced back to hospitalisations or accesses to the Emergency Department (ED). The study data were acquired by means of a case report form investigating the medication management process in LTCs. MATERIAL AND METHODS Analysis of pharmacutilisation in LTCFs patients aged ≥65 years on polypharmacy or excessive polypharmacy, January-July 2023. Data was extracted from a database (DB) containing the monthly prescriptions of medicines supplied by direct distribution (DD) to LTCs. The prevalence of PIMs was evaluated by applying the Beers and STOPP criteria to the medication profile of each patient. RESULTS The overall prevalence of polypharmacy and hyperpolypharmacy was 83% and 17%, respectively. PIMs were defined using Beers and STOPP criteria. The most frequent PIMs were proton pump inhibitors (19% e 15%), antiplatelets agent (17% e 13%) and non-associated sulfonamides (14% e 12%). Of the 1,921 PIMs, 121 were contraindicated or very serious (6%) and 1,800 were major (94%).The most common medicaments involved in drug-drug interaction are furosemide (21%), sertraline (19%), pantoprazole (16%) e trazodone (15%). LTCs participating in the study (56%) excluded polypharmacy as a cause of access to the ED and ADRs. Therefore no case was ever reported (100%). CONCLUSIONS Polypharmacy or excessive polypharmacy among elderly patients may increase PIMs and ADRs. A constant review of the therapeutic regimens and deprescribing decrease inappropriate use of medications and interactions, ADRs, and accesses to the ED with consequent reduction of pharmaceutical spending.

Older adults preferences for long-term caregivers in China: a discrete choice experiment.

OBJECTIVE: Understanding the preferences of old-age adults for their long-term caregivers can improve person-centred health care and the quality of long-term care (LTC). This study examines Chinese older adults' preferences for long-term caregivers. STUDY DESIGN: This is a cross-sectional study. METHODS: A national representative discrete choice experiment (DCE) surveyed 2031 adults aged 50-70 across 12 provinces in China. Each DCE scenario described five attributes: type of caregivers, place of LTC, contents of LTC, out-of-pocket payments, and quality of life (QoL). Preferences and the marginal willingness to pay (WTP) were derived using mixed-logit and latent class models. RESULTS: Older adults displayed higher preferences for long-term caregivers who improve their QoL, incur lower out-of-pocket payments, and provide medical LTC services at home, with the maximum WTP of $22.832 per month. QoL was rated as the most important LTC factor, followed by the place of LTC and the type of caregivers. When the level of QoL improved from poor to good, respondents would be willing to pay $18.375 per month more (95% confidence interval: 16.858 to 20.137), and the uptake rate increased by 76.47%. There was preference heterogeneity among older people with different sex, education, family size, and knowledge of LTC insurance. CONCLUSION: QoL was the most important factor in older Chinese adults' preference for caregivers. Home care and medical care from formal caregivers was preferred by older adults. We recommend training family caregivers, raising older people's awareness of LTC insurance, and guiding policymakers in developing people-oriented LTC and a multi-level LTC system.

Characteristics of first-time users of the nursing small-scale multifunctional home care service: a pooled cross-sectional study using Japanese long-term care insurance claims data from 2012 to 2019.

OBJECTIVES: In April 2012, the Japanese government launched a new nursing service called the nursing small-scale multifunctional home care (NSMHC) to meet the nursing care demands of individuals with moderate-to-severe activities of daily living (ADLs) dysfunction and who require medical care, thereby allowing them to continue living in the community. We aimed to preliminarily analyse the characteristics of first-time users of NSMHC service. DESIGN: This pooled cross-sectional study used the Japanese long-term care insurance (LTCI) claims data from the users' first use of NSMHC (from April 2012 to December 2019). SETTING: NSMHC includes nursing home visits, home care, daycare, overnight stays and medical treatment. PARTICIPANTS: The study population included LTCI beneficiaries who received their first long-term care requirement certification in Japan from April 2012 onwards, died between April 2012 and December 2019, and used any LTCI service at least once. RESULTS: Among the 836 563 individuals who used any LTCI service at least once, 3957 (0.47%) used NSMHC. We analysed 3634 individuals without any missing data regarding long-term care requirement certification. Most individuals were aged 80 years or older, with 64.3% requiring care level 3 or above, indicating complete assistance with ADLs. Regarding ADLs in individuals with dementia, 70.6% were at level 2 or below, indicating they can live almost independently even with dementia. A large proportion of NSMHC users availed the service approximately 6 months before death, with no prior use of any LTCI services; they continued using the service for around 4 months, although some people continued to use NSMHC until their month of death. CONCLUSIONS: Using individual data on nationwide LTCI, we described the characteristics of first-time users of NSMHC among those who died within 7.5 years from the first certification of care needs. Further studies are needed to investigate the effect of NSMHC use on user outcomes.

Trajectories of medical care expenditure in the last year of life associated with long-term care utilization in frail older adults: A retrospective cohort study.

BACKGROUND: Medical care and long-term care utilization in the last year of life of frail older adults could be a key indicator of their quality of life. This study aimed to identify the medical care expenditure (MCE) trajectories in the last year of life of frail older adults by investigating the association between MCE and long-term care utilization in each trajectory. METHODS: The retrospective cohort study of three municipalities in Japan included 405 decedents (median age at death, 85 years; 189 women [46.7%]) from a cohort of 1,658 frail older adults aged ≥65 years who were newly certified as support level in the long-term care insurance program from April 2012 to March 2013. This study used long-term care and medical insurance claim data from April 2012 to March 2017. The primary outcome was MCE over the 12 months preceding death. Group-based trajectory modeling was conducted to identify the MCE trajectories. A mixed-effect model was employed to examine the association between long-term care utilization and MCE in each trajectory. RESULTS: Participants were stratified into four groups based on MCE trajectories over the 12 months preceding death as follows: rising (n = 159, 39.3%), persistently high (n = 143, 35.3%), minimal (n = 56, 13.8%), and descending (n = 47, 11.6%) groups. Home-based long-term care utilization was associated with increased MCE in the descending trajectory (coefficient, 1.48; 95% confidence interval [CI], 1.35-1.62). Facility-based long-term care utilization was associated with reduced MCE in the rising trajectory (coefficient, 0.59; 95% CI, 0.50-0.69). Both home-based (coefficient, 0.92; 95% CI, 0.85-0.99) and facility-based (coefficient; 0.53; 95% CI, 0.41-0.63) long-term care utilization were associated with reduced MCE in the persistently high trajectory. CONCLUSIONS: These findings may facilitate the integration of medical and long-term care models at the end of life in frail older adults.

Ascertaining the Francophone population in Ontario: validating the language variable in health data.

BACKGROUND: Language barriers can impact health care and outcomes. Valid and reliable language data is central to studying health inequalities in linguistic minorities. In Canada, language variables are available in administrative health databases; however, the validity of these variables has not been studied. This study assessed concordance between language variables from administrative health databases and language variables from the Canadian Community Health Survey (CCHS) to identify Francophones in Ontario. METHODS: An Ontario combined sample of CCHS cycles from 2000 to 2012 (from participants who consented to link their data) was individually linked to three administrative databases (home care, long-term care [LTC], and mental health admissions). In total, 27,111 respondents had at least one encounter in one of the three databases. Language spoken at home (LOSH) and first official language spoken (FOLS) from CCHS were used as reference standards to assess their concordance with the language variables in administrative health databases, using the Cohen kappa, sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV). RESULTS: Language variables from home care and LTC databases had the highest agreement with LOSH (kappa = 0.76 [95%CI, 0.735-0.793] and 0.75 [95%CI, 0.70-0.80], respectively) and FOLS (kappa = 0.66 for both). Sensitivity was higher with LOSH as the reference standard (75.5% [95%CI, 71.6-79.0] and 74.2% [95%CI, 67.3-80.1] for home care and LTC, respectively). With FOLS as the reference standard, the language variables in both data sources had modest sensitivity (53.1% [95%CI, 49.8-56.4] and 54.1% [95%CI, 48.3-59.7] in home care and LTC, respectively) but very high specificity (99.8% [95%CI, 99.7-99.9] and 99.6% [95%CI, 99.4-99.8]) and predictive values. The language variable from mental health admissions had poor agreement with all language variables in the CCHS. CONCLUSIONS: Language variables in home care and LTC health databases were most consistent with the language often spoken at home. Studies using language variables from administrative data can use the sensitivity and specificity reported from this study to gauge the level of mis-ascertainment error and the resulting bias.

Long-term care needs and hospitalization costs with long-term care insurance: a mixed-sectional study.

Background: With the rapid aging of the population, the health needs of the older adult have increased significantly, resulting in the frequent occurrence of the "social hospitalization" problem, which has led to a rapid increase in hospitalization costs. This study investigates whether the "social hospitalization problem" arising from the long-term care needs can be solved through the implementation of long-term care insurance, thereby improving the overall health of the older adults and controlling the unreasonable increase in hospitalization costs. Methods: The entropy theory was used as a conceptual model, based on data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015 and 2018. The least-squares method was used to examine the relationship between long-term care needs and hospitalization costs, and the role that long-term care insurance implementation plays in its path of influence. Results: The results of this study indicated that long-term care needs would increase hospitalization cost, which remained stable after a series of tests, such as replacing the core explanatory variables and introducing fixed effects. Through the intermediary effect test and mediated adjustment effect test, we found the action path of long-term care needs on hospitalization costs. Long-term care needs increases hospitalization costs through more hospitalizations. Long-term care insurance reduces hospitalization costs. Its specific action path makes long-term care insurance reduce hospitalization costs through a negative adjustment of the number of hospitalizations. Conclusion: To achieve fair and sustainable development of long-term care insurance, the following points should be achieved: First, long-term care insurance should consider the prevention in advance and expand the scope of participation and coverage; Second, long-term care insurance should consider the control in the event and set moderate levels of treatment payments; Third, long-term care insurance should consider post-supervision and explore appropriate payment methods.

Costs of care trajectories of people with dementia compared with matched controls. Longitudinal analysis of linked health and administrative data.

OBJECTIVES: To provide insight into the health and social care costs during the disease trajectory in persons with dementia and the impact of institutionalization and death on healthcare costs compared with matched persons without dementia. METHODS: Electronic health record data from family physicians were linked with national administrative databases to estimate costs of primary care, medication, secondary care, mental care, home care and institutional care for people with dementia and matched persons from the year before the recorded dementia diagnosis until death or a maximum of 4 years after the diagnosis. RESULTS: Total mean health and social care costs among persons with dementia increased substantially during the disease trajectory, mainly due to institutional care costs. For people who remained living in the community, mean health and social care costs are higher for people with dementia than for those without dementia, while for those who are admitted to a long-term care facility, mean health and social care costs are higher for people without dementia than for those with dementia. CONCLUSIONS: The steep rise in health and social care costs across the dementia care trajectory is mainly due to increasing costs for institutional care. For those remaining in the community, home care costs and hospital care costs were the main cost drivers. Future research should adopt a societal perspective to investigate the influence of including social costs.

Long-term care use, hospitalizations and mortality during COVID-19 in Finland and Sweden: A nationwide register-based study in 2020.

AIM: To describe long-term care (LTC) use in Finland and Sweden in 2020, by reporting residential entry and exit patterns including hospital admissions and mortality, compared with the 2018-2019 period and community-living individuals. METHODS: From national registers in Finland and Sweden, all individuals 70+ were included. Using the Finnish and Swedish study populations in January 2018 as the standard population, we reported changes in sex- and age-standardized monthly rates of entry into and exit from LTC facilities, mortality and hospital admission among LTC residents and community-living individuals in 2020. RESULTS: Around 850,000 Finns and 1.4 million Swedes 70+ were included. LTC use decreased in both countries from 2018 to 2020. In the first wave (March/April 2020), Finland experienced a decrease in LTC entry rates and an increase in LTC exit rates, both more marked than Sweden. This was largely due to short-term movements. Mortality rates peaked in April and December 2020 for LTC residents in Finland, while mortality peaked for both community-living individuals and LTC residents in Sweden. A decrease in hospital admissions from LTC facilities occurred in April 2020 and was less marked in Finland versus Sweden. CONCLUSIONS: During the first wave of the pandemic mortality was consistently higher in Sweden. We also found a larger decrease in LTC use and, among LTC residents, a smaller decrease in hospital admissions in Finland than in Sweden. This study calls for assessing the health consequences of the differences observed between these two Scandinavian countries as part of the lessons from the COVID-19 pandemic.

Factors associated with dietitian referrals to support long-term care residents advancing towards the end of life.

BACKGROUND: Dietitians are central members of the multidisciplinary long-term care (LTC) healthcare team. The overall aim of this current investigation is to gain a better understanding of dietitian involvement in LTC resident's end-of-life care via referrals. METHODS: Retrospective chart reviews for 164 deceased residents (mean age = 88.3 ± 7.3; 61% female) in 18 LTC homes in Ontario, Canada, identified dietitian referrals and documented eating challenges recorded over 2-week periods at four time points (i.e., 6 months, 3 months, 1 month and 2 weeks) prior to death. Nutrition care plans at the beginning of these time points were also noted. Logistic mixed effects regression models identified time-varying predictors of dietitian referrals. Bivariate tests identified associations between nutrition orders and dietitian referrals that occurred in the last month of life. RESULTS: Nearly three-quarters (73%) of participants had at least one dietitian referral across the four observations. Referrals increased significantly with proximity to death; 45% of residents had a referral documented in the last 2 weeks of life. Dietitian referrals were associated with the number of eating challenges (odds ratio [OR] = 1.42, 95% confidence interval [CI] = 1.27, 1.58). Comfort-focused nutrition care orders were significantly more common when a dietitian was referred (25%) compared with when a dietitian was not referred (12%) in the final month of life (p = 0.04). CONCLUSIONS: Our findings suggest that dietitians are involved in end-of-life and comfort-focused nutrition care initiatives, yet they are not engaged consistently for this purpose. This presents a significant opportunity for dietitians to upskill and champion palliative approaches to nutrition care within the multidisciplinary LTC team.

Skin care types, frequencies and products: A cross-sectional study in German institutional long-term care.

AIM: The aim of the study was to describe types and frequencies of skin care interventions and products provided in institutional long-term care. MATERIALS AND METHODS: Baseline data from a cluster randomized controlled trial conducted in nursing homes in Berlin, Germany was collected before randomization. Numbers, proportions and frequencies of washing, showering and bathing, and the application of leave-on products were calculated. Product labels were iteratively and inductively categorized into overarching terms and concepts. RESULTS: A total of n = 314 residents participated in the study. In the majority, washing of the whole body was done once daily, and showering was performed once per week or more rarely. The majority received leave-on products daily on the face and once per week on the whole body. Most of the skin care interventions were delivered by nurses. There was marked heterogeneity in terms of product names, whereas the product names reveal little about the ingredients or composition. CONCLUSION: Personal hygiene and cleansing interventions are major parts of clinical practice in long-term care. Daily washing is a standard practice at the moment. In contrast, leave-on products are used infrequently. To what extent the provided care promotes skin integrity is unclear. Due to the heterogeneity and partly misleading labels of skin care products, informed decision making is difficult to implement at present. GOV IDENTIFIER: NCT03824886.

[Analysing the Need for Long-Term Care: Potential of Data from Long-Term Care Assessments of the Bavarian Medical Service for Public Health Research and Practice]. / Pflegebedürftigkeit analysieren ­ Potential der Daten aus Pflegebegutachtungen des Medizinischen Dienstes Bayern für Public Health-Forschung und -Praxis.

BACKGROUND: Despite demographic changes, there is still no systematic and comparable differentiation of nursing care reporting on a small-scale level in Germany, where outpatient long-term care is depicted. This article presents findings of care assessment data of the Medical Service of Bavaria and draws conclusions for future reporting on nursing. METHODS: For the analysis, anonymised initial long-term care assessments of the Bavarian Medical Service of 2019 were evaluated exemplarily using descriptive methods. The study describes the characteristics of persons with a care level recommendation, the distribution of care level categories, medical diagnoses and degree of independence in the areas of life. RESULTS: The persons assessed were on average 80 years old. At the time of the initial assessment, the largest proportion of persons with an assigned care level lived in an outpatient setting. Care level (PG) 1 (slight impairment of independence or abilities) was assigned to 35.1% of the insured, PG 2 (considerable impairment) to 43.1%, PG 3 (severe impairment) to 16.6%, PG 4 and 5 (most severe impairment) were each rarely assigned at the time of the initial assessment (3.9% and 1.4%, respectively). Medical diagnoses were dominated by gait and mobility disorders, unspecified dementia, heart failure and senility. In particular, there were impairments in the areas of 'mobility' and 'organisation of everyday life and social contacts'. CONCLUSIONS: The data available from the German Medical Service may be highly relevant to health research and policy and may provide a basis for planning interventions in long-term care.

The risk of fractures after entering long-term care facilities.

BACKGROUND: Stratifying residents at increased risk for fractures in long-term care facilities (LTCFs) can potentially improve awareness and facilitate the delivery of targeted interventions to reduce risk. Although several fracture risk assessment tools exist, most are not suitable for individuals entering LTCF. Moreover, existing tools do not examine risk profiles of individuals at key periods in their aged care journey, specifically at entry into LTCFs. PURPOSE: Our objectives were to identify fracture predictors, develop a fracture risk prognostic model for new LTCF residents and compare its performance to the Fracture Risk Assessment in Long term care (FRAiL) model using the Registry of Senior Australians (ROSA) Historical National Cohort, which contains integrated health and aged care information for individuals receiving long term care services. METHODS: Individuals aged ≥65 years old who entered 2079 facilities in three Australian states between 01/01/2009 and 31/12/2016 were examined. Fractures (any) within 365 days of LTCF entry were the outcome of interest. Individual, medication, health care, facility and system-related factors were examined as predictors. A fracture prognostic model was developed using elastic nets penalised regression and Fine-Gray models. Model discrimination was examined using area under the receiver operating characteristics curve (AUC) from the 20 % testing dataset. Model performance was compared to an existing risk model (i.e., FRAiL model). RESULTS: Of the 238,782 individuals studied, 62.3 % (N = 148,838) were women, 49.7 % (N = 118,598) had dementia and the median age was 84 (interquartile range 79-89). Within 365 days of LTCF entry, 7.2 % (N = 17,110) of individuals experienced a fracture. The strongest fracture predictors included: complex health care rating (no vs high care needs, sub-distribution hazard ratio (sHR) = 1.52, 95 % confidence interval (CI) 1.39-1.67), nutrition rating (moderate vs worst, sHR = 1.48, 95%CI 1.38-1.59), prior fractures (sHR ranging from 1.24 to 1.41 depending on fracture site/type), one year history of general practitioner attendances (≥16 attendances vs none, sHR = 1.35, 95%CI 1.18-1.54), use of dopa and dopa derivative antiparkinsonian medications (sHR = 1.28, 95%CI 1.19-1.38), history of osteoporosis (sHR = 1.22, 95%CI 1.16-1.27), dementia (sHR = 1.22, 95%CI 1.17-1.28) and falls (sHR = 1.21, 95%CI 1.17-1.25). The model AUC in the testing cohort was 0.62 (95%CI 0.61-0.63) and performed similar to the FRAiL model (AUC = 0.61, 95%CI 0.60-0.62). CONCLUSIONS: Critical information captured during transition into LTCF can be effectively leveraged to inform fracture risk profiling. New fracture predictors including complex health care needs, recent emergency department encounters, general practitioner and consultant physician attendances, were identified.

A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.

BACKGROUND: Numerous studies have identified risk factors for physical restraint (PR) use in older adults in long-term care facilities. Nevertheless, there is a lack of predictive tools to identify high-risk individuals. OBJECTIVE: We aimed to develop machine learning (ML)-based models to predict the risk of PR in older adults. METHODS: This study conducted a cross-sectional secondary data analysis based on 1026 older adults from 6 long-term care facilities in Chongqing, China, from July 2019 to November 2019. The primary outcome was the use of PR (yes or no), identified by 2 collectors' direct observation. A total of 15 candidate predictors (older adults' demographic and clinical factors) that could be commonly and easily collected from clinical practice were used to build 9 independent ML models: Gaussian Naïve Bayesian (GNB), k-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), support vector machine (SVM), random forest (RF), multilayer perceptron (MLP), extreme gradient boosting (XGBoost), and light gradient boosting machine (Lightgbm), as well as stacking ensemble ML. Performance was evaluated using accuracy, precision, recall, an F score, a comprehensive evaluation indicator (CEI) weighed by the above indicators, and the area under the receiver operating characteristic curve (AUC). A net benefit approach using the decision curve analysis (DCA) was performed to evaluate the clinical utility of the best model. Models were tested via 10-fold cross-validation. Feature importance was interpreted using Shapley Additive Explanations (SHAP). RESULTS: A total of 1026 older adults (mean 83.5, SD 7.6 years; n=586, 57.1% male older adults) and 265 restrained older adults were included in the study. All ML models performed well, with an AUC above 0.905 and an F score above 0.900. The 2 best independent models are RF (AUC 0.938, 95% CI 0.914-0.947) and SVM (AUC 0.949, 95% CI 0.911-0.953). The DCA demonstrated that the RF model displayed better clinical utility than other models. The stacking model combined with SVM, RF, and MLP performed best with AUC (0.950) and CEI (0.943) values, as well as the DCA curve indicated the best clinical utility. The SHAP plots demonstrated that the significant contributors to model performance were related to cognitive impairment, care dependency, mobility decline, physical agitation, and an indwelling tube. CONCLUSIONS: The RF and stacking models had high performance and clinical utility. ML prediction models for predicting the probability of PR in older adults could offer clinical screening and decision support, which could help medical staff in the early identification and PR management of older adults.

Cognitive Decline in Long-term Care Residents Before and During the COVID-19 Pandemic in Ontario, Canada.

This study examines the incidence of cognitive decline among long-term care residents in Ontario before and during the COVID-19 pandemic.

Association Between Changes in Postoperative Opioid Utilization and Long-Term Health Care Spending Among Surgical Patients With Chronic Opioid Utilization.

BACKGROUND: There is growing interest in identifying and developing interventions aimed at reducing the risk of increased, long-term opioid use among surgical patients. While understanding how these interventions impact health care spending has important policy implications and may facilitate the widespread adoption of these interventions, the extent to which they may impact health care spending among surgical patients who utilize opioids chronically is unknown. METHODS: This study was a retrospective analysis of administrative health care claims data for privately insured patients. We identified 53,847 patients undergoing 1 of 10 procedures between January 1, 2004, and September 30, 2018 (total knee arthroplasty, total hip arthroplasty, laparoscopic cholecystectomy, open cholecystectomy, laparoscopic appendectomy, open appendectomy, cesarean delivery, functional endoscopic sinus surgery, transurethral resection of the prostate, or simple mastectomy) who had chronic opioid utilization (≥10 prescriptions or ≥120-day supply in the year before surgery). Patients were classified into 3 groups based on differences in opioid utilization, measured in average daily oral morphine milligram equivalents (MMEs), between the first postoperative year and the year before surgery: "stable" (<20% change), "increasing" (≥20% increase), or "decreasing" (≥20% decrease). We then examined the association between these 3 groups and health care spending during the first postoperative year, using a multivariable regression to adjust for observable confounders, such as patient demographics, medical comorbidities, and preoperative health care utilization. RESULTS: The average age of the sample was 62.0 (standard deviation [SD] 13.1) years, and there were 35,715 (66.3%) women. Based on the change in average daily MME between the first postoperative year and the year before surgery, 16,961 (31.5%) patients were classified as "stable," 15,463 (28.7%) were classified as "increasing," and 21,423 (39.8%) patients were classified as "decreasing." After adjusting for potential confounders, "increasing" patients had higher health care spending ($37,437) than "stable" patients ($31,061), a difference that was statistically significant ($6377; 95% confidence interval [CI], $5669-$7084; P < .001), while "decreasing" patients had lower health care spending ($29,990), a difference (-$1070) that was also statistically significant (95% CI, -$1679 to -$462; P = .001). These results were generally consistent across an array of subgroup and sensitivity analyses. CONCLUSIONS: Among patients with chronic opioid utilization before surgery, subsequent increases in opioid utilization during the first postoperative year were associated with increased health care spending during that timeframe, while subsequent decreases in opioid utilization were associated with decreased health care spending.

Association of material deprivation with discharge location and length of stay after inpatient stroke rehabilitation in Ontario: a retrospective, population-based cohort study.

BACKGROUND: Low socioeconomic status is associated with increased risk of stroke and worse poststroke functional status. The aim of this study was to determine whether socioeconomic status, as measured by material deprivation, is associated with direct discharge to long-term care or length of stay after inpatient stroke rehabilitation. METHODS: We performed a retrospective, population-based cohort study of people admitted to inpatient rehabilitation in Ontario, Canada, after stroke. Community-dwelling adults (aged 19-100 yr) discharged from acute care with a most responsible diagnosis of stroke between Sept. 1, 2012, and Aug. 31, 2017, and subsequently admitted to an inpatient rehabilitation bed were included. We used a multivariable logistic regression model to examine the association between material deprivation quintile (from the Ontario Marginalization Index) and discharge to long-term care, and a multivariable negative binomial regression model to examine the association between material deprivation quintile and rehabilitation length of stay. RESULTS: A total of 18 736 people were included. There was no association between material deprivation and direct discharge to long-term care (most v. least deprived: odds ratio [OR] 1.07, 95% confidence interval [CI] 0.89-1.28); however, people living in the most deprived areas had a mean length of stay 1.7 days longer than that of people in the least deprived areas (p = 0.004). This difference was not significant after adjustment for other baseline differences (relative change in mean 1.02, 95% CI 0.99-1.04). INTERPRETATION: People admitted to inpatient stroke rehabilitation in Ontario had similar discharge destinations and lengths of stay regardless of their socioeconomic status. In future studies, investigators should consider further examining the associations of material deprivation with upstream factors as well as potential mitigation strategies.

Association of Proximity to a Long-Term Acute Care Hospital With Hospital Tracheostomy Practices.

OBJECTIVES: Availability of long-term acute care hospitals has been associated with hospital discharge practices. It is unclear if long-term acute care hospital availability can influence patient care decisions. We sought to determine the association of long-term acute care hospital availability at different hospitals with the likelihood of tracheostomy. DESIGN: Retrospective cohort study. SETTING: California Patient Discharge Database, 2016-2018. PATIENTS: Adult patients receiving mechanical ventilation for respiratory failure. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using the California Patient Discharge Database 2016-2018, we identified all mechanically ventilated patients and those who received tracheostomy. We determine the association between tracheostomy and the distance between each hospital and the nearest long-term acute care hospital and the number of long-term acute care hospital beds within 20 miles of each hospital. Among 281,502 hospitalizations where a patient received mechanical ventilation, 22,899 (8.1%) received a tracheostomy. Patients admitted to a hospital closer to a long-term acute care hospital compared with those furthest from a long-term acute care hospital had 38.9% (95% CI, 33.3-44.6%) higher odds of tracheostomy (closest hospitals 8.7% vs furthest hospitals 6.3%, adjusted odds ratio = 1.65; 95% CI, 1.40-1.95). Patients had a 32.4% (95% CI, 27.6-37.3%) higher risk of tracheostomy when admitted to a hospital with more long-term acute care hospital beds in the immediate vicinity (most long-term acute care hospital beds within 20 miles 8.9% vs fewest long-term acute care hospital beds 6.7%, adjusted odds ratio = 1.54; 95% CI, 1.31-1.80). Distance to the nearest long-term acute care hospital was inversely correlated with hospital risk-adjusted tracheostomy rates (ρ = -0.25; p < 0.0001). The number of long-term acute care hospital beds within 20 miles was positively correlated with hospital risk-adjusted tracheostomy rates (ρ = 0.22; p < 0.0001). CONCLUSIONS: Proximity and availability of long-term acute care hospital beds were associated with patient odds of tracheostomy and hospital tracheostomy practices. These findings suggest a hospital effect on tracheostomy decision-making over and above patient case-mix. Future studies focusing on shared decision-making for tracheostomy are needed to ensure goal-concordant care for prolonged mechanical ventilation.