Journal of the American Medical Directors Association最新文献

Objectives: This study examined the incidence of hospitalizations for urinary tract infections (UTIs) and associated factors among residents of long-term care facilities (LTCFs) during the first 12 months of their LTCF stay.

Design: Population-based retrospective cohort study.

Setting and participants: This study included people aged ≥65 years who first entered an LTCF between 2015 and 2018 using data from the Registry of Senior Australians National Historical Cohort.

Methods: The cumulative incidence of hospitalizations of UTI in the 12 months following LTCF entry was evaluated. Individual, facility, medicine, and service utilization-related factors associated with hospitalizations for UTIs were investigated. A Fine-Gray model was used to estimate subdistribution hazard ratios (sHRs) and 95% CIs.

Results: Of the 180,858 people included from 2464 LTCFs, 59.7% (n = 107,914) were female, with a median age of 85 years. The cumulative incidence of hospitalizations for UTIs in the 12 months after LTCF entry was 3.7% (95% CI 3.7-3.8). Factors associated with a higher rate of hospitalizations for UTIs included long-term urinary catheter use (sHR 3.39, 95% CI 3.16-3.65), history of hospitalizations with UTI (sHR 2.33, 95% CI 2.21-2.46), preferred language other than English (sHR 1.38, 95% CI 1.28-1.48), diabetes (sHR 1.29, 95% CI 1.22-1.37), high (sHR 1.30, 95% CI 1.19-1.41) or medium (sHR 1.21, 95% CI 1.11-1.32) need for assistance with activities of daily living, cerebrovascular disease (sHR 1.14, 95% CI 1.08-1.20), and urinary incontinence (sHR 1.08, 95% CI 1.01-1.15).

Conclusions and implications: A considerable burden of UTI-associated hospitalizations was observed in Australian LTCFs, which can be minimized through implementing effective UTI prevention, detection, and management strategies.

Objective: To develop and internally validate a malnutrition screening tool based on routinely collected data in the long-term care setting.

Design: Diagnostic prediction model development and internal validation study.

Setting and participants: Residents (n = 539) from 10 long-term care facilities in Australia.

Methods: Candidate variables identified through expert consultation were collected from routinely collected data in a convenience sample of long-term care facilities. Logistic regression using the Subjective Global Assessment as the reference standard was conducted on 500 samples derived using bootstrapping from the original sample. Candidate variables were selected if included in more than 95% of samples using backwards stepwise elimination. The final model was developed using logistic regression of selected variables. Internal validation was conducted using bootstrapping to calculate the optimism-adjusted performance. Overall discrimination was evaluated via receiver operator characteristic curve and calculation of the area under the curve. Youden's Index was used to identify the optimal threshold value for classifying malnutrition. Sensitivity and specificity were calculated.

Results: Body mass index and weight change % over 6 months were included in the automated malnutrition screening model (AutoMal), identified in 100% of bootstrapped samples. AutoMal demonstrated excellent discrimination of malnutrition, with area under the curve of 0.8378 (95% CI, 0.80-0.87). Youden's Index value was 0.37, resulting in sensitivity of 78% (95% CI, 71%-83%) and specificity of 77% (72%-81%). Optimism-corrected area under the curve was 0.8354.

Conclusions and implications: The AutoMal demonstrates excellent ability to differentiate malnutrition status. It makes automated identification of malnutrition possible by using 2 variables commonly found in electronic health records.

Objective: To examine whether having tele-mental health (tele-MH) visits with new providers is different by race, ethnicity, Medicare-Medicaid dual eligibility, and rurality.

Design: Retrospective study.

Setting and participants: This study linked 2019 and 2021 Medicare claims data. We included community-dwelling Medicare fee-for-service beneficiaries with Alzheimer's disease and related dementias who had at least 1 tele-MH visit in 2021.

Methods: The outcome variable was whether an individual had tele-MH visits with new providers in 2021, compared with providers they had in 2019, measured by comparing the list of providers they had visits with using Medicare outpatient claims data. The main variables of interest were race, ethnicity, Medicare-Medicaid dual eligibility, and rurality, measured using the Medicare Beneficiary Summary File. Logistic regression models, with zip code-level random effects, were estimated while accounting for individual- and community-level characteristics.

Results: The analytical sample included 99,329 individuals, of whom 53.6% had MH care with new providers via tele-MH services in 2021. After accounting for individual- and community-level characteristics, Black individuals (odds ratio [OR], 1.158; 95% CI, 1.096-1.222; P < .01), Medicare-Medicaid dual-eligibles (OR, 1.066; 95% CI, 1.027-1.105; P < .01), and rural residents (1.215; 95% CI, 1.125-1.312; P < .01) were more likely to have tele-MH visits with new providers compared with their White, nondual-eligible, and metropolitan counterparts, respectively.

Conclusions and implications: Telemedicine may improve MH care access for underserved populations by facilitating connections with new MH providers.

Objectives: Throughout the COVID-19 pandemic, public debate arose regarding the proportionality of infection prevention and control (IPC) measures in nursing homes (NHs), as these measures negatively impacted residents' well-being. To be better prepared for future outbreaks and pandemics, we need a deeper understanding of how NHs manage COVID-19 or influenza outbreaks, and which considerations are being made to balance IPC and well-being.

Design: Mixed-methods study.

Setting and participants: Fourteen Dutch NH organizations (176 NH locations) where COVID-19 or influenza outbreaks occurred during winter 2022-2023 were included.

Methods: We monitored the progression and management of 24 outbreaks by administering weekly questionnaires. Heterogeneous sampling was used to select 7 outbreaks for extensive monitoring, including epidemiologic data collection on the resident level and outbreak management evaluation through qualitative interviews (n = 7). Quantitative data were used for descriptive analysis (all outbreaks) and the generation of epidemiologic curves (extensively monitored outbreaks). Qualitative interview data were used to deepen our understanding of the considerations and adjustments made to IPC strategies by NH staff.

Results: We observed differences in IPC measures taken between NH organizations, but also within NH organizations, as IPC protocols were often customized to fit specific units, residents, or situations during outbreaks. Staff consistently considered the impact of IPC measures on residents against their beliefs about the effectiveness of measures, which occasionally led them to deviate from their IPC strategy in favor of residents' well-being.

Conclusion and implications: The current study provides an understanding of how COVID-19 and influenza outbreaks were managed, how NH staff considered the impact and effectiveness of measures, and consequently, how IPC strategies were gradually adjusted during outbreaks. Acknowledging that although the majority of NH staff consistently recognize the need to tailor IPC measures, they inconsistently apply such customization in practice, which may help NH organizations better prepare for future outbreaks.

Objectives: In preventing atherosclerotic cardiovascular diseases (ASCVDs) in frail older people, it is essential to balance estimated cardiovascular disease (CVD) risk with potential treatment benefits and harms. SCORE2-OP estimates CVD risk in older people but has not been validated in frail older patients. We evaluated the performance of SCORE2-OP for predicting CVD mortality in this group.

Design: External validation study.

Setting and participants: Amsterdam Ageing Cohort, including 1797 older outpatients.

Methods: Data on incident myocardial infarction and stroke were unavailable. Five-year all-cause and CVD mortality were calculated by Kaplan-Meier estimates. For calibration, we compared 5-year CVD mortality with 5-year CVD risk calculated by SCORE2-OP in observed-to-expected ratios. Discrimination was assessed with Harrell's C-index. Analyses were stratified by ASCVD history, and physical and cognitive functioning.

Results: We included 1797 patients (median age, 79 years; interquartile range, 75-84; 48% male; 39% ASCVD history). Over a median survival time of 2.0 years (interquartile range, 1.0-3.3), 623 people (35%) died, including 95 from CVD. The 5-year CVD mortality was 6.4% (95% CI, 5.1-7.7), the mean calculated CVD risk was 7.9%. The overall observed-to-expected ratio for cardiovascular mortality was 0.81 (95% CI, 0.80-0.82), and 0.52 (95% CI, 0.51-0.53) in people without ASCVD history. C-indices were 0.59 (95% CI, 0.47-0.70) overall and 0.67 (95% CI, 0.50-0.85) in those without ASCVD history. Stratification by physical and cognitive functioning did not impact C-indices.

Conclusions and implications: In a frail older outpatient population, SCORE2-OP showed notable discrimination for CVD mortality in those without ASCVD history. This suggests that SCORE2-OP can be used for CVD risk estimation in these frail outpatients.