The open EEGLAB portal Interface: High-Performance computing with EEGLAB.

EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety of neuroscience-related software on high-performance computing (HPC) resources in the U.S. XSEDE network. We have reported recently (Delorme et al., 2019) on the Open EEGLAB Portal expansion of the free NSG services to allow the neuroscience community to build and run MATLAB pipelines using the EEGLAB tool environment. We are now releasing an EEGLAB plug-in, nsgportal, that interfaces EEGLAB with NSG directly from within EEGLAB running on MATLAB on any personal lab computer. The plug-in features a flexible MATLAB graphical user interface (GUI) that allows users to easily submit, interact with, and manage NSG jobs, and to retrieve and examine their results. Command line nsgportal tools supporting these GUI functionalities allow EEGLAB users and plug-in tool developers to build largely automated functions and workflows that include optional NSG job submission and processing. Here we present details on nsgportal implementation and documentation, provide user tutorials on example applications, and show sample test results comparing computation times using HPC versus laptop processing.

What Can Local Transfer Entropy Tell Us about Phase-Amplitude Coupling in Electrophysiological Signals?

Modulation of the amplitude of high-frequency cortical field activity locked to changes in the phase of a slower brain rhythm is known as phase-amplitude coupling (PAC). The study of this phenomenon has been gaining traction in neuroscience because of several reports on its appearance in normal and pathological brain processes in humans as well as across different mammalian species. This has led to the suggestion that PAC may be an intrinsic brain process that facilitates brain inter-area communication across different spatiotemporal scales. Several methods have been proposed to measure the PAC process, but few of these enable detailed study of its time course. It appears that no studies have reported details of PAC dynamics including its possible directional delay characteristic. Here, we study and characterize the use of a novel information theoretic measure that may address this limitation: local transfer entropy. We use both simulated and actual intracranial electroencephalographic data. In both cases, we observe initial indications that local transfer entropy can be used to detect the onset and offset of modulation process periods revealed by mutual information estimated phase-amplitude coupling (MIPAC). We review our results in the context of current theories about PAC in brain electrical activity, and discuss technical issues that must be addressed to see local transfer entropy more widely applied to PAC analysis. The current work sets the foundations for further use of local transfer entropy for estimating PAC process dynamics, and extends and complements our previous work on using local mutual information to compute PAC (MIPAC).

Trial-by-trial source-resolved EEG responses to gait task challenges predict subsequent step adaptation.

A growing body of evidence indicates a pivotal role of cognition and in particular executive function in gait control and fall prevention. In a recent gait study using electroencephalographic (EEG) imaging, we provided direct proof for cortical top-down inhibitory control in step adaptation. A crucial part of motor inhibition is recognizing stimuli that signal the need to inhibit or adjust motor actions such as steps during walking. One of the EEG signatures of performance monitoring in response to events signaling the need to adjust motor responses, are error-related potential (error-ERP) features. To examine whether error-ERP features may index executive control during gait adaptation, we analyzed high-density (108-channel) EEG data from an auditory gait pacing study. Participants (N = 18) walking on a steadily moving treadmill were asked to step in time to an auditory cue tone sequence, and then to quickly adapt their step length and rate, to regain step-cue synchrony following occasional unexpected shifts in the pacing cue train to a faster or slower cue tempo. Decomposition of the continuous EEG data by independent component analysis revealed a negative deflection in the source-resolved event-related potential (ERP) time locked to 'late' cue tones marking a shift to a slower cue tempo. This vertex-negative ERP feature, localized primarily to posterior medial frontal cortex (pMFC) and peaking 250 ms after the onset of the tempo-shift cue, we here refer to as the step-cue delay negativity (SDN). SDN source, timing, and polarity resemble other error-related ERP features, e.g., the Error-Related Negativity (ERN) and Feedback-Related Negativity (FRN) in (seated) button press response tasks. In single trials, SDN amplitude varied with the magnitude of the cue latency deviation (the time interval between the expected and actual cue onsets). Regression analysis also identified linear coupling between SDN amplitude and the subsequent speed of gait tempo adaptation (as measured by the increase in length of the ensuing adaptation step). The SDN in this paradigm thus seems both to index the perceived need for and the subsequent magnitude of the immediate gait adjustment, consistent with performance-monitoring models. Future research might investigate relationships of these control processes to the impairment of gait adjustment in motor disorders and cognitive decline, for example to develop a biomarker for fall risk prediction in early-stage Parkinson's.

Measuring transient phase-amplitude coupling using local mutual information.

Here we demonstrate the suitability of a local mutual information measure for estimating the temporal dynamics of cross-frequency coupling (CFC) in brain electrophysiological signals. In CFC, concurrent activity streams in different frequency ranges interact and transiently couple. A particular form of CFC, phase-amplitude coupling (PAC), has raised interest given the growing amount of evidence of its possible role in healthy and pathological brain information processing. Although several methods have been proposed for PAC estimation, only a few have addressed the estimation of the temporal evolution of PAC, and these typically require a large number of experimental trials to return a reliable estimate. Here we explore the use of mutual information to estimate a PAC measure (MIPAC) in both continuous and event-related multi-trial data. To validate these two applications of the proposed method, we first apply it to a set of simulated phase-amplitude modulated signals and show that MIPAC can successfully recover the temporal dynamics of the simulated coupling in either continuous or multi-trial data. Finally, to explore the use of MIPAC to analyze data from human event-related paradigms, we apply it to an actual event-related human electrocorticographic (ECoG) data set that exhibits strong PAC, demonstrating that the MIPAC estimator can be used to successfully characterize amplitude-modulation dynamics in electrophysiological data.

Practice Transformation to Improve Cancer Screening Outcomes at an Academic Medical Center.

In 2011, Texas received federal approval of the 1115 Healthcare Transformation waiver, which went to support the Texas Delivery System Reform Incentive Payment Program (DSRIP) incentivizing the transformation of service delivery practices which included expanded coverage of preventive cancer screenings. There is limited evidence that quality improvement initiatives stemming from DSRIP improve cancer screening outcomes for the Medicaid, low-income, and uninsured (MLIU) patient population. The present the results of a quality initiative to improve breast, cervical, and colorectal cancer screening rates for MLIU patients receiving primary care at an academic medical center. The initiative included engaging multidisciplinary primary care teams, health information technology (IT), and quality departments to standardize workflows. We found significantly improved rates of cervical and colorectal cancer screening among patients eligible to receive one or more screenings. Aligning primary care, IT, and quality processes resulted in significant improvement in cancer screening.

Virtual Access to Subspecialty Care.

Telehealth programs existed in many subspecialities before the COVID-19 pandemic, and the public health event motivated many subspecialties to reflect on how current technologies could be leveraged to benefit patient outcomes and increase health-care access. This article reviews the history and current state of telehealth access in many areas of subspecialty care. Primary care physicians (PCPs) may be unaware of the telehealth services and options local subspecialists offer. To best serve patients, PCPs could partner with subspecialists to develop processes to link patients to the right subspecialist at the right time and in the right visit type.

Neural Oscillatory Abnormalities During Gaze Processing in Schizophrenia: Evidence of Reduced Theta Phase Consistency and Inter-areal Theta-Gamma Coupling.

BACKGROUND: Abnormal gaze discrimination in schizophrenia (SZ) is associated with impairment in social functioning, but the neural mechanisms remain unclear. Evidence suggests that local neural oscillations and inter-areal communication through neural synchronization are critical physiological mechanisms supporting basic and complex cognitive processes. The roles of these mechanisms in abnormal gaze processing in SZ have not been investigated. The present study examined local neural oscillations and connectivity between anterior and bilateral posterior brain areas during gaze processing. METHODS: During electroencephalography recording, 28 participants with SZ and 34 healthy control participants completed a gaze discrimination task. Time-frequency decomposition of electroencephalography data was used to examine neural oscillatory power and intertrial phase consistency at bilateral posterior and midline anterior scalp sites. In addition, connectivity between these anterior and posterior sites, in terms of cross-frequency coupling between theta phase and gamma amplitude, was examined using the Kullback-Leibler Modulation Index. RESULTS: Participants with SZ showed reduced total power of theta-band activity relative to healthy control participants at all sites examined. This group difference could be accounted for by reduced intertrial phase consistency of theta activity in SZ participants, which was related to reduced gaze discrimination accuracy in SZ. In addition, SZ participants exhibited reduced Kullback-Leibler indexing, both feedforward and feedback connectivity, between the posterior and anterior sites. CONCLUSIONS: These findings suggest that abnormal theta phase consistency and dysconnection between posterior face processing and anterior areas may underlie gaze processing deficits in SZ.

Dynamical mean field model of a neural-glial mass.

Our goal is to model the behavior of an ensemble of interacting neurons and astrocytes (the neural-glial mass). For this, a model describing N tripartite synapses is proposed. Each tripartite synapse consists of presynaptic and postsynaptic nerve terminals, as well as the synaptically associated astrocytic microdomain, and is described by a system of 13 stochastic differential equations. Then, by applying the dynamical mean field approximation (DMA) (Hasegawa, 2003a , 2003b ) the system of 13N equations is reduced to 13(13 + 2) = 195 deterministic differential equations for the means and the second-order moments of local and global variables. Simulations are carried out for studying the response of the neural-glial mass to external inputs applied to either the presynaptic terminals or the astrocytes. Three cases were considered: the astrocytes influence only the presynaptic terminal, only the postsynaptic terminal, or both the presynaptic and postsynaptic terminals. As a result, a wide range of responses varying from singles spikes to train of spikes was evoked on presynaptic and postsynaptic terminals. The experimentally observed phenomenon of spontaneous activity in astrocytes was replicated on the neural-glial mass. The model predicts that astrocytes can have a strong and activity-dependent influence on synaptic transmission. Finally, simulations show that the dynamics of astrocytes influences the synchronization ratio between neurons, predicting a peak in the synchronization for specific values of the astrocytes' parameters.

Anatomically-constrained effective connectivity among layers in a cortical column modeled and estimated from local field potentials.

We propose a neural mass model for anatomically-constrained effective connectivity among neuronal populations residing in four layers (L2/3, L4, L5 and L6) within a cortical column. Eight neuronal populations in a given column--an excitatory population and an inhibitory population per layer--are assumed to be coupled via effective connections of unknown strengths that need to be estimated. The effective connections are constrained to anatomical connections that have been shown to exist in previous anatomical studies. The neural input to a cortical column is directed into the two populations in L4. The anatomically-constrained effective connectivity is captured by a system of 16 stochastic differential equations. Solving these equations yields the average postsynaptic potentials and transmembrane currents generated in each population. The current source density (CSD) responses in each layer, which serve as the model observations, are equated in the model to the sum of all currents generated within that layer. The model is implemented in a continuous-discrete state-space framework, and the innovation method is used for estimating the model parameters from CSD data. To this end, local field potential (LFP) responses to forepaw stimulation were recorded in rat area S1 using multi-channel linear probes. LFPs were converted to CSD signals, which were averaged within each layer, yielding one CSD response per layer. To estimate the effective strengths of connections between all cortical layers, the model was fitted to these CSD signals. The results show that the pattern of effective interactions is strongly influenced by the pattern of strengths of the anatomical connections; however, these two patterns are not identical. The estimated anatomically-constrained effective connectivity matrix and the anatomical connectivity matrix shared five of their six strongest connections, although rankings according to connection strength differed. The strongest effective connections were from excitatory neurons in layer 4 to excitatory neurons in layer 2/3. Our study shows the feasibility of estimating anatomically-constrained effective connectivity within a cortical column, and indicates that there is a strong influence of anatomical connectivity on effective connectivity between cortical layers.

Longitudinal, multidisciplinary, resident-driven intervention to increase immunisation rates for Medicaid, low-income and uninsured patients.

INTRODUCTION: More payers are closely linking reimbursement to high-value care outcomes such as immunisation rates. Despite this, there remain high rates of pneumonia and influenza-related hospitalisations generating hospital expenditures as high as $11 000 per hospitalisation. Vaccinating the public is an integral part of preventing poor health and utilisation outcomes and is particularly relevant to high-risk patients. As part of a multidisciplinary effort between family and internal medicine residency programmes, our goal was to improve vaccination rates to an average of 76% of eligible Medicaid, low-income and uninsured (MLIU) patients at an academic primary care practice. METHODS: The quality improvement project was completed over 3 months by three primary care resident groups. The setting was a suburban academic primary care practice and eligible patients were 18 years of age or older. Our aim was to increase immunisation rates of pneumococcal, influenza, varicella, herpes zoster virus and tetanus and diphtheria vaccination. There were 1690 patients eligible for the vaccination composite metric. Data were derived from the electronic health record and administrative data. INTERVENTIONS: Cohort 1 developed an initial intervention that consisted of a vaccine questionnaire for patients to complete while in the waiting room. Cohort 2 modified questionnaire after reviewing results from initial intervention. Cohort 3 recommended elimination of questionnaire and implementation of a bundled intervention approach. RESULTS: There were minimal improvements in patient immunisation rates after using a patient-directed paper questionnaire. After implementation of multiple interventions via an improvement bundle, there were improvements in immunisation rates which were sustained and the result of special cause variation. CONCLUSION: A key to improving immunisation rates for MLIU patients in this clinic was developing relationships with faculty and staff stakeholders. We received feedback from all the medical staff and then applied it to the interventions and made an impact in the average of vaccinations.

The Impact of COVID-19 on Cancer Screening: Challenges and Opportunities.

Cancer is a leading cause of death in the United States and across the globe. Cancer screening is an effective preventive measure that can reduce cancer incidence and mortality. While cancer screening is integral to cancer control and prevention, due to the COVID-19 outbreak many screenings have either been canceled or postponed, leaving a vast number of patients without access to recommended health care services. This disruption to cancer screening services may have a significant impact on patients, health care practitioners, and health systems. In this paper, we aim to offer a comprehensive view of the impact of COVID-19 on cancer screening. We present the challenges COVID-19 has exerted on patients, health care practitioners, and health systems as well as potential opportunities that could help address these challenges.

From BIDS-Formatted EEG Data to Sensor-Space Group Results: A Fully Reproducible Workflow With EEGLAB and LIMO EEG.

Reproducibility is a cornerstone of scientific communication without which one cannot build upon each other's work. Because modern human brain imaging relies on many integrated steps with a variety of possible algorithms, it has, however, become impossible to report every detail of a data processing workflow. In response to this analytical complexity, community recommendations are to share data analysis pipelines (scripts that implement workflows). Here we show that this can easily be done using EEGLAB and tools built around it. BIDS tools allow importing all the necessary information and create a study from electroencephalography (EEG)-Brain Imaging Data Structure compliant data. From there preprocessing can be carried out in only a few steps using EEGLAB and statistical analyses performed using the LIMO EEG plug-in. Using Wakeman and Henson (2015) face dataset, we illustrate how to prepare data and build different statistical models, a standard factorial design (faces ∗ repetition), and a more modern trial-based regression approach for the stimulus repetition effect, all in a few reproducible command lines.

The impact of continuity of care on antibiotic prescribing in acute otitis media.

BACKGROUND: The rate of antibiotic prescribing for acute otitis media (AOM) remains high despite efforts to decrease inappropriate use. Studies have aimed to understand the prescribing patterns of providers to increase antibiotic stewardship. Watch and wait (WAW) prescriptions are effective at decreasing the number of antibiotic prescriptions being filled by patients. Additionally, poor continuity of care has been associated with higher cost and lower quality health care. OBJECTIVE: To understand the antibiotic prescribing habits for AOM in a largely Hispanic population. METHODS: A retrospective review was performed from 2016 to 2018 of all patients under 25 years old with a diagnosis of AOM seen at multiple outpatient primary care clinics of a single institution. Charts were reviewed for factors including race, ethnicity, gender, insurance status, presence of fever, primary care physician visit, and treatment choice. Data were collected and analyzed using STATA software with t-tests, ANOVA, and Pearson chi squared analysis. RESULTS: Antibiotics were prescribed 95.6% of the time with 3.8% being WAW prescriptions. There was no significant difference in antibiotic prescribing by race (p = 0.66), ethnicity (p = 0.38), gender (p = 0.34) or insurance status (p = 0.24). There was a difference between physicians, nurse practitioners, and physician's assistants and antibiotic prescribing rate (p < 0.01). Additionally, seen by their primary care provider were less likely to be prescribed antibiotics (85.8% vs 94.4%, p = 0.01). CONCLUSION: While a patient's race, ethnicity, gender, and insurance status did not influence the prescribing rate of physicians, continuity of care may play an important role in decreasing inappropriate antibiotic prescribing.

High-density EEG mobile brain/body imaging data recorded during a challenging auditory gait pacing task.

In this report we present a mobile brain/body imaging (MoBI) dataset that allows study of source-resolved cortical dynamics supporting coordinated gait movements in a rhythmic auditory cueing paradigm. Use of an auditory pacing stimulus stream has been recommended to identify deficits and treat gait impairments in neurologic populations. Here, the rhythmic cueing paradigm required healthy young participants to walk on a treadmill (constant speed) while attempting to maintain step synchrony with an auditory pacing stream and to adapt their step length and rate to unanticipated shifts in tempo of the pacing stimuli (e.g., sudden shifts to a faster or slower tempo). High-density electroencephalography (EEG, 108 channels), surface electromyography (EMG, bilateral tibialis anterior), pressure sensors on the heel (to register timing of heel strikes), and goniometers (knee, hip, and ankle joint angles) were concurrently recorded in 20 participants. The data is provided in the Brain Imaging Data Structure (BIDS) format to promote data sharing and reuse, and allow the inclusion of the data into fully automated data analysis workflows.

Primary Care Issues in Inner-City America and Internationally.

Inner-city patient populations are high-risk for poor outcomes, including increased risk of mortality. Barriers to delivering high-quality primary care to inner-city patients include lack of access, poor distribution of primary care providers (PCPs), competing demands, and financial restraints. Health care issues prevalent in this population include obesity, diabetes, cancer screening, asthma, infectious diseases, and obstetric and prenatal care. Population health management and quality improvement (QI) activities must target disparities in care. Partnering with patients and focusing on social determinants of health andmedical care are key areas inwhich to focus toimprove overall healthoutcomes inthispopulation.

Project RED Impacts Patient Experience.

BACKGROUND: Hospitalized patients are frequently unprepared to care for themselves after discharge often leading to unplanned hospital readmission. One strategy to reduce readmission rates is improving the quality of patient education and preparation before hospital discharge. The ReEngineered Discharge (RED) is a standardized hospital-based program designed to provide patients and caregivers the information they need to continue care at home. OBJECTIVES: We sought to study the impact of the RED intervention on posthospitalization adult patient experience scores in an urban academic safety-net hospital. METHODS: We conducted a descriptive study of a pilot program that compared posthospitalization survey responses to the Press Ganey survey item "Instructions were given about how to care for yourself at home." We compared the survey results for 3 groups of adult patients: those receiving the RED program, those receiving a standard discharge on the same hospital unit, and those receiving a standard discharge on other hospital units. RESULTS: A greater percentage of adult patients who received the RED discharge program rated the quality of their discharge as "very good" as compared to those receiving a standard discharge on the same hospital unit and those receiving a standard discharge on other hospital units (61%, 35%, and 41%, respectively, P = .0001). CONCLUSION: Delivery of a standardized hospital discharge program resulted in a larger proportion of top-box "very good" responses on a Press Ganey posthospitalization survey. Future research should examine whether hospital-based transition programs can sustain improvement in patient experience measures and whether these improvements can be observed in other patient populations.

Health Services Utilization Among Fee-for-Service Medicare and Medicaid Patients Under Age 65 with Behavioral Health Illness at an Urban Safety Net Hospital.

BACKGROUND: In 2011, fee-for-service patients with both Medicare and Medicaid (dual eligible) sustained $319.5 billion in health care costs. OBJECTIVE: To describe the emergency department (ED) use and hospital admissions of adult dual eligible patients aged under 65 years who used an urban safety net hospital. METHODS: This was a retrospective database analysis of patients aged between 18 and 65 years with Medicare and Medicaid, who used an urban safety net academic health center between January 1, 2011, and December 31, 2011. We compared patients with and without behavioral health illness. The main outcome measures were hospital admission and ED use. Chi-square and Wilcoxon rank-sum tests were used for descriptive statistics on categorical and continuous variables, respectively. Greedy propensity score matching was used to control for confounding factors. Rate ratios (RR) and 95% confidence intervals (CI) were determined after matching and after adjusting for those variables that remained significantly different after matching. RESULTS: In 2011, 10% of all fee-for-service dual eligible patients aged less than 65 years in Massachusetts were seen at Boston Medical Center. Data before propensity score matching showed significant differences in age, sex, race/ethnicity, marital status, education, employment, physical comorbidities, and Charlson Comorbidity Index score between patients with and without behavioral health illness. Analysis after propensity score matching found significant differences in sex, Hispanic race, and other education and employment status. Compared with patients without behavioral health illness, patients with behavioral health illness had a higher RR for hospital admissions (RR = 2.07; 95% CI = 1.81-2.38; P < 0.001) and ED use (RR = 1.61; 95% CI = 1.46-1.77; P < 0.001). Results were robust after adjusting for characteristics that remained statistically significantly different after propensity score matching. CONCLUSIONS: Adult dual eligible patients aged less than 65 years with behavioral health illness in the Medicaid fee-for-service plan had significantly higher rates of hospital admission and ED use compared with dual eligible patients without behavioral health illness at the largest urban safety net medical center in New England. Safety net hospitals care for a large proportion of dual eligible patients with behavioral health illness. Further research is needed to elucidate the systems-related and patient-centered factors contributing to the utilization behaviors of this patient population. DISCLOSURES: This research was funded in part by a National Research Service Award (T3HP10028-14-01). The authors have no conflicts of interests to disclose. Cancino had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design were contributed by Cancino, Jack, and Burgess, with assistance from Cremieux. Cancino and Cremieux took the lead in data collection, along with Jack and Burgess, and data interpretation was performed by Jarvis, Cummings, and Cooper, along with the other authors. The manuscript was written primarily by Cancino, along with Jack and Burgess, and revised primarily by Cancino, along with the other authors.

How Hospitals Reengineer Their Discharge Processes to Reduce Readmissions.

BACKGROUND: The Re-Engineered Discharge (RED) program is a hospital-based initiative shown to decrease hospital reutilization. We implemented the RED in 10 hospitals to study the implementation process. DESIGN: We recruited 10 hospitals from different regions of the United States to implement the RED and provided training for participating hospital leaders and implementation staff using the RED Toolkit as the basis of the curriculum followed by monthly telephone-based technical assistance for up to 1 year. METHODS: Two team members interviewed key informants from each hospital before RED implementation and then 1 year later. Interview data were analyzed according to common and comparative themes identified across institutions. Readmission outcomes were collected on participating hospitals and compared pre- versus post-RED implementation. RESULTS: Key findings included (1) wide variability in the fidelity of the RED intervention; (2) engaged leadership and multidisciplinary implementation teams were keys to success; (3) common challenges included obtaining timely follow-up appointments, transmitting discharge summaries to outpatient clinicians, and leveraging information technology. Eight out of 10 hospitals reported improvement in 30-day readmission rates after RED implementation. CONCLUSIONS: A supportive hospital culture is essential for successful RED implementation. A flexible implementation strategy can be used to implement RED and reduce readmissions.

Dose-response relationship between depressive symptoms and hospital readmission.

BACKGROUND: Evidence suggests depression increases hospital readmission risk. OBJECTIVE: Determine whether depressive symptoms are associated with unplanned readmission within 30 days of discharge of general medical patients. DESIGN: Secondary analysis of the Project Re-Engineered Discharge (RED) randomized controlled trials. SETTING: Urban academic safety-net hospital. PATIENTS: A total of 1418 hospitalized adult English-speaking patients. INTERVENTION: The 9-Item Patient Health Questionnaire (PHQ-9) was used to screen patients for depressive symptoms. MEASUREMENTS: Hospital readmission within 30 days of discharge. Poisson regression was used to control for confounding variables. RESULTS: There were 225 (16%) patients who screened positive for mild depressive symptoms (5 ≤PHQ-9 ≤ 9) and 336 (24%) for moderate or severe depressive symptoms (PHQ-9 ≥ 10). After controlling for confounders, a higher rate of readmission was observed in subjects with mild depressive symptoms compared to subjects with PHQ-9 <5, incidence rate ratio (IRR) 1.49 (95% confidence interval [CI]: 1.11-2.00). The adjusted IRR of readmission for those with moderate-to-severe symptoms was 1.96 (95% CI: 1.51-2.49) compared to those with no depression. CONCLUSIONS: Screening positive for mild and moderate-to-severe depressive symptoms during a hospitalization on a general medical service is associated with an increased dose-dependent readmission rate within 30 days of discharge in an urban, academic, safety-net hospital. Further research is needed to determine whether treatments targeting the reduction of depressive symptoms reduce the risk of readmission.

Comparing patient-level and site-level anticoagulation control as predictors of adverse events.

INTRODUCTION: Percent time in therapeutic range (TTR) is increasingly used to summarize anticoagulation control over time among patients receiving warfarin. Higher TTR improves outcomes of care, but studies have varied regarding whether TTR is best summarized as center-based percent time in therapeutic range (cTTR) or as individual percent time in therapeutic range (iTTR). Our aim was to compare cTTR to iTTR in predicting ischemic stroke, major hemorrhage, and all-cause mortality. MATERIALS AND METHODS: Veterans Health Administration data of 57,281 patients receiving warfarin therapy were included. iTTR was calculated using linear interpolation. Each site's mean TTR was calculated, and the cTTR was assigned to all patients at that site. We used Cox proportional hazards to examine cTTR and iTTR as predictors of major hemorrhage, ischemic stroke, and all-cause mortality. RESULTS: Comparing worst to best quartiles of INR control, cTTR was not a statistically significant predictor of major hemorrhage or ischemic stroke, hazard ratios (HR) were 1.02 (95% confidence interval [CI] 0.93-1.11) and 1.00 (95% CI: 0.88-1.13), respectively. cTTR was a weak predictor of all-cause mortality (HR: 1.14, 95% CI: 1.07-1.22). iTTR predicted major hemorrhage (HR: 1.79, 95% CI: 1.63-1.96), ischemic stroke (HR: 1.91, 95% CI: 1.67-2.19), and all-cause mortality (HR: 2.20, 95% CI: 2.05-2.35). CONCLUSION: iTTR significantly predicted risk of major hemorrhage, ischemic stroke, and all-cause mortality. cTTR was a weak predictor of all-cause mortality. Though cTTR may be a better target for site-level quality improvement efforts, iTTR may be a more suitable measure for use in comparative effectiveness research.