Citations

The aim of this study was twofold—(1) to compare the current ED staffing workload alert system to clinicians’ perceptions of workload in the ED, and (2) to examine the potential impact of a multi-faceted, systems-level intervention on clinicians’ perceptions of workload. Constant flow of patients into the Emergency Departments (ED) regularly increases the workload of clinicians and can compromise the quality of care delivery and patient safety. An automatic staffing workload alert system was created and implemented in response to an observed shift in patient volume to the overnight hours at one academic quaternary care center. Surveys addressing workload and interruptions were administered to ED clinicians, pre-and post-intervention implementation. Output from the staffing workload alert system was recorded for each clinician shift. Clinicians’ perceptions of workload were able to predict swing shift activations, χ 2 (6) = 14.14, p = 0.028. Only the performance subscale significantly correlated with swing shift activations, p=0.006. A Kruskal-Wallis H test found perceived interruptions changed following systems-level changes, χ 2 (1) = 7.195, p = 0.007. Utilizing subjective measure of clinicians’ workload validated an objective, automated staffing workload alert system that determined if swing shift activations are necessary.

Objectives To examine the association between hospitalization, critical illness, and infection occurring during middle‐ and late‐life and structural brain abnormalities in older adults. Design Prospective cohort study. Setting Atherosclerosis Risk in Communities (ARIC) Study. Participants A community sample of adults who were 44 to 66 years of age at study baseline. Measurements Active surveillance of local hospitals and annual participant contact were used to gather hospitalization information (including International Classification of Diseases, Ninth Revision , codes) on all participants over a 24‐year surveillance period. Subsequently, a subset of participants underwent 3‐Tesla brain magnetic resonance imaging (MRI) to quantify total and regional brain volumes, white matter hyperintensity (WMH) volume, and white matter microstructural integrity (fractional anisotropy (FA) and mean diffusivity (MD) as measured using diffusion tensor imaging (DTI)). Results Of the 1,689 participants included (mean age at MRI 76±5), 72% were hospitalized, 14% had a major infection, and 4% had a critical illness during the surveillance period. Using covariate‐adjusted regression, hospitalization was associated with 0.12–standard deviation (SD) greater WMH volume (95% confidence interval (CI)=0.00–0.24) and poorer white matter microstructural integrity (0.17‐SD lower FA, 95% CI=–0.27 to –0.06; 0.16‐SD greater MD, 95% CI=0.07–0.25) than no hospitalization. There was a dose‐dependent relationship between number of hospitalizations, smaller brain volumes, and lower white matter integrity ( p ‐trends ≤.048). In hospitalized participants, critical illness was associated with smaller Alzheimer's disease (AD) signature region (–1.64 cm 3 , 95% CI=–3.16 to –0.12); major infection was associated with smaller AD signature region (–1.28 cm 3 , 95% CI=–2.21 to –0.35) and larger ventricular volume (3.79 cm 3 , 95% CI= 0.81–6.77). Conclusions Whereas all‐cause hospitalization was primarily associated with lower white matter integrity, critical illness and major infection were associated with smaller brain volume, particularly within regions implicated in AD.

AbstractObjectiveThe prognostic value of cerebrospinal fluid neurofilament light chain, total tau, phosphorylated tau181, and amyloid beta1‐42was examined in frontotemporal dementia subtypes.MethodsWe compared baseline biomarkers between 49 controls, 40 patients with behavioral variant frontotemporal dementia, 24 with semantic variant primary progressive aphasia, and 26 with nonfluent variant primary progressive aphasia. Linear mixed effect models were used to assess the value of baseline biomarkers in predicting clinical and radiographic change in patient cohorts over multiple yearly follow up visits.ResultsNeurofilament light chain concentrations were lowest in controls. Elevated baseline neurofilament light chain predicted faster worsening in clinical severity, frontotemporal volume and frontotemporal fractional anisotropy in patients with behavioral variant frontotemporal dementia and nonfluent variant primary progressive aphasia. High total tau similarly predicted faster progression in nonfluent variant primary progressive aphasia. In behavioral variant frontotemporal dementia, higher phosphorylated tau181predicted faster clinical progression whereas lower amyloid beta1‐42predicted faster volumetric and fractional anisotropy reduction. Neurofilament light chain and phosphorylated tau181were of greater predictive value in patients with tau pathology as compared toTDP‐43 pathology. Baseline neurofilament light chain correlated with baseline clinical severity and frontotemporal volume in behavioral variant frontotemporal dementia. Baseline total tau correlated with baseline clinical severity in semantic variant primary progressive aphasia.InterpretationHigh cerebrospinal fluid neurofilament light chain predicts more aggressive disease in behavioral variant frontotemporal dementia and nonfluent variant primary progressive aphasia. Total tau, phosphorylated tau181, and amyloid beta1‐42also predict some measures of disease aggressiveness in frontotemporal dementia.

AbstractRecent research has highlighted the importance of the human microbiome in many human disease and health conditions. Most current microbiome association analyses focus on unrelated samples; such methods are not appropriate for analysis of data collected from more advanced study designs such as longitudinal and pedigree studies, where outcomes can be correlated. Ignoring such correlations can sometimes lead to suboptimal results or even possibly biased conclusions. Thus, new methods to handle correlated outcome data in microbiome association studies are needed. In this paper, we propose the correlated sequence kernel association test (CSKAT) to address such correlations using the linear mixed model. Specifically, random effects are used to account for the outcome correlations and a variance component test is used to examine the microbiome effect. Compared to existing genetic association tests for longitudinal and family samples, we implement a correction procedure to better calibrate the null distribution of the score test statistic to accommodate the small sample size nature of data collected from a typical microbiome study. Comprehensive simulation studies are conducted to demonstrate the validity and efficiency of our method, and we show that CSKAT achieves a higher power than existing methods while correctly controlling the Type I error rate. We also apply our method to a microbiome data set collected from a UK twin study to illustrate its potential usefulness. A free implementation of our method in R software is available at https://github.com/jchen1981/SSKAT.

Objective Over the last decade, electronic health records (EHRs) have shaped clinical practice. In this article, we investigated the perceived effects of EHR use on clinical workflow and meaningful use (MU) performance metrics. Materials and Methods Semistructured interviews were conducted with 20 (n = 20) physicians at two urban emergency departments. Interview questions focused on time spent on EHR use, changes in clinical practices with EHR use, and the effect of MU performance metrics on clinical workflow. Qualitative coding using grounded theory and descriptive analyses were performed to provide descriptive insights. Results Physicians reported that EHRs improved their clinical workflow, especially on MU-related activities including door-to-doctor time and admit decision time. EHR use also affected physicians work efficiency, quality of care provided, and overall patient safety. Conclusion Physicians' perception of EHRs is likely to influence their practices. With negative perceptions of EHR usability problems, positive aspects of EHR use, including the influence on MU performance metrics, may be overridden.