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BACKGROUND: Treatment with methadone and buprenorphine medications for opioid use disorder (MOUD) during incarceration may lead to better community re-entry, but evidence on these relationships have been mixed. We aimed to identify community re-entry patterns and examine the association between in-jail MOUD and a pattern of successful reentry defined by rare occurrence of reincarceration and preventable healthcare utilization. METHODS: Data came from a retrospective, observational cohort study of 6066 adults with opioid use disorder who were incarcerated in New York City jails and released to the community during 2011-14. An outcome was community re-entry patterns identified by sequence analysis of 3-year post-release reincarceration, emergency department visits, and hospitalizations. An exposure was receipt of in-jail MOUD versus out-of-treatment (42 % vs. 58 %) for the last 3 days before discharge. The study accounted for differences in baseline demographic, clinical, behavioral, housing, and criminal legal characteristics between in-jail MOUD and out-of-treatment groups via propensity score matching. RESULTS: This study identified five re-entry patterns: stability (64 %), hospitalization (23 %), delayed reincarceration (7 %), immediate reincarceration (4 %), and continuous incarceration (2 %). After addressing confounding, 64 % and 57 % followed the stability pattern among MOUD and out-of-treatment groups who were released from jail in 2011, respectively. In 2012-14, the prevalence of following the stability pattern increased year-by-year while a consistently higher prevalence was observed among those with in-jail MOUD. CONCLUSIONS: Sequence analysis helped define post-release stability based on health and criminal legal system involvement. Receipt of in-jail MOUD was associated with a marker of successful community re-entry.

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INTRODUCTION: This study aimed to assess emergency nurses' perceived barriers toward engaging patients in serious illness conversations. METHODS: Using a mixed-method (quant + QUAL) convergent design, we pooled data on the emergency nurses who underwent the End-of-Life Nursing Education Consortium training across 33 emergency departments. Data were extracted from the End-of-Life Nursing Education Consortium post-training questionnaire, comprising a 5-item survey and 1 open-ended question. Our quantitative analysis employed a cross-sectional design to assess the proportion of emergency nurses who report that they will encounter barriers in engaging seriously ill patients in serious illness conversations in the emergency department. Our qualitative analysis used conceptual content analysis to generate themes and meaning units of the perceived barriers and possible solutions toward having serious illness conversations in the emergency department. RESULTS: A total of 2176 emergency nurses responded to the survey. Results from the quantitative analysis showed that 1473 (67.7%) emergency nurses reported that they will encounter barriers while engaging in serious illness conversations. Three thematic barriers-human factors, time constraints, and challenges in the emergency department work environment-emerged from the content analysis. Some of the subthemes included the perceived difficulty of serious illness conversations, delay in daily throughput, and lack of privacy in the emergency department. The potential solutions extracted included the need for continued training, the provision of dedicated emergency nurses to handle serious illness conversations, and the creation of dedicated spaces for serious illness conversations. DISCUSSION: Emergency nurses may encounter barriers while engaging in serious illness conversations. Institutional-level policies may be required in creating a palliative care-friendly emergency department work environment.

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Background: The Functional Assessment of Cancer Therapy-General (FACT-G) is a widely used quality-of-life measure. However, no studies have examined the FACT-G among patients with life-limiting illnesses who present to emergency departments (EDs). Objective: The goal of this study was to examine the psychometric properties of the FACT-G among patients with life-limiting illnesses who present to EDs in the United States. Methods: This cross-sectional study pooled data from 12 EDs between April 2018 and January 2020 (n = 453). Patients enrolled in the study were adults with one or more of the four life-limiting illnesses: advanced cancer, Congestive Heart Failure, Chronic Obstructive Pulmonary Disease, or End-Stage Renal Disease. We conducted item, exploratory, and confirmatory analyses (exploratory factor analysis [EFA] and confirmatory factor analysis [CFA]) to determine the psychometric properties of the FACT-G. Results: The FACT-G had good internal consistency (Cronbach's alpha α = 0.88). The simplest EFA model was a six-factor structure. The CFA supported the six-factor structure, evidenced by the adequate fit indices (comparative fit index = 0.93, Tucker-Lewis index = 0.92, root-mean-square error of approximation = 0.05; 90% confidence interval: 0.04 - 0.06). The six-factor structure comprised the physical, emotional, work and daily activities-related functional well-being, and the family and friends-related social well-being domains. Conclusions: The FACT-G is a reliable measure of health-related quality of life among patients with life-limiting illnesses who present to the ED. Clinical Trial Registration: NCT03325985.

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Background: Precision medicine has led to the development of targeted treatment strategies tailored to individual patients based on their characteristics and disease manifestations. Although precision medicine often focuses on a single health outcome for individualized treatment decision rules (ITRs), relying only on a single outcome rather than all available outcomes information leads to suboptimal data usage when developing optimal ITRs. Methods: To address this limitation, we propose a Bayesian multivariate hierarchical model that leverages the wealth of correlated health outcomes collected in clinical trials. The approach jointly models mixed types of correlated outcomes, facilitating the "borrowing of information" across the multivariate outcomes, and results in a more accurate estimation of heterogeneous treatment effects compared to using single regression models for each outcome. We develop a treatment benefit index, which quantifies the relative treatment benefit of the experimental treatment over the control treatment, based on the proposed multivariate outcome model. Results: We demonstrate the strengths of the proposed approach through extensive simulations and an application to an international Coronavirus Disease 2019 (COVID-19) treatment trial. Simulation results indicate that the proposed method reduces the occurrence of erroneous treatment decisions compared to a single regression model for a single health outcome. Additionally, the sensitivity analysis demonstrates the robustness of the model across various study scenarios. Application of the method to the COVID-19 trial exhibits improvements in estimating the individual-level treatment efficacy (indicated by narrower credible intervals for odds ratios) and optimal ITRs. Conclusion: The study jointly models mixed types of outcomes in the context of developing ITRs. By considering multiple health outcomes, the proposed approach can advance the development of more effective and reliable personalized treatment.

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Rationale & Objective: Conservative kidney management (CKM) is a viable treatment option for many patients with chronic kidney disease. However, CKM practices and resources in the United States are not well described. We undertook this study to gain a better understanding of factors influencing uptake of CKM by describing: (1) characteristics of patients who choose CKM, (2) provider practice patterns relevant to CKM, and (3) CKM resources available to providers. Study Design: Cross-sectional study. Setting & Participants: This study is a cross-sectional analysis of data from US nephrology clinics enrolled in the chronic kidney disease Outcomes and Practice Patterns Study (CKDopps) collected between 2014 and 2020. Data for this study includes chart-abstracted characteristics of patients with an estimated glomerular filtration rate ≤30mL/min/1.73m2 (n=1018) and available information on whether a decision had been made to pursue CKM at the time of kidney failure, patient (n=407) reports of discussions about forgoing dialysis, and provider (n=26) responses about CKM delivery and available resources in their health systems. Analytical Approach: Descriptive statistics were used to report patient demographics, clinical information, provider demographics, and clinic characteristics. Results: Among data from 1018 patients, 68 (7%) were recorded as planning for CKM. These patients were older, had more comorbidities, and were more likely to require assistance with transfers. Of the 407 patient surveys, 18% reported a conversation about forgoing dialysis with their nephrologist. A majority of providers felt comfortable discussing CKM; however, no clinics had a dedicated clinic or protocol for CKM. Limitations: Inconsistent survey terminology and unlinked patient and provider responses. Conclusions: Few patients reported discussion of forgoing dialysis with their providers and even fewer anticipated a choice of CKM on reaching kidney failure. Most providers were comfortable discussing CKM, but practiced in clinics that lacked dedicated resources. Further research is needed to improve the implementation of a CKM pathway. Plain-Language Summary: For older comorbid adults with kidney failure, conservative kidney management (CKM) can be an appropriate treatment choice. CKM is a holistic approach with treatment goals of maximizing quality of life and preventing progression of chronic kidney disease (CKD) without initiation of dialysis. We investigated US CKM practices and found that among 1018 people with CKD, only 7% were planning for CKM. Of 407 surveyed patients, 18% reported a conversation with their provider about forgoing dialysis. In contrast, most providers felt comfortable discussing CKM; however, none reported working in an environment with a dedicated CKM clinic or protocol. Our data show the need for further CKM education in the United States as well as dedicated resources for its delivery.

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Cluster-randomized trials (CRTs) often allocate intact clusters of participants to treatment or control conditions and are increasingly used to evaluate healthcare delivery interventions. While previous studies have developed sample size methods for testing confirmatory hypotheses of treatment effect heterogeneity in CRTs (i.e., targeting the difference between subgroup-specific treatment effects), sample size methods for testing the subgroup-specific treatment effects themselves have not received adequate attention-despite a rising interest in health equity considerations in CRTs. In this article, we develop formal methods for sample size and power analyses for testing subgroup-specific treatment effects in parallel-arm CRTs with a continuous outcome and a binary subgroup variable. We point out that the variances of the subgroup-specific treatment effect estimators and their covariance are given by weighted averages of the variance of the overall average treatment effect estimator and the variance of the heterogeneous treatment effect estimator. This analytical insight facilitates an explicit characterization of the requirements for both the omnibus test and the intersection-union test to achieve the desired level of power. Generalizations to allow for subgroup-specific variance structures are also discussed. We report on a simulation study to validate the proposed sample size methods and demonstrate that the empirical power corresponds well with the predicted power for both tests. The design and setting of the Umea Dementia and Exercise (UMDEX) CRT in older adults are used to illustrate our sample size methods.

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BACKGROUND: Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for the first time, the function of the longitudinal regression tree algorithm as a non-parametric method after imputing missing data using SI and MI was investigated using simulated and real data. METHOD: Using different simulation scenarios derived from a real data set, we compared the performance of cross, trajectory mean, interpolation, copy-mean, and MI methods (27 approaches) to impute missing longitudinal data using parametric and non-parametric longitudinal models and the performance of the methods was assessed in real data. The real data included 3,645 participants older than 18 years within six waves obtained from the longitudinal Tehran cardiometabolic genetic study (TCGS). The data modeling was conducted using systolic and diastolic blood pressure (SBP/DBP) as the outcome variables and included predictor variables such as age, gender, and BMI. The efficiency of imputation approaches was compared using mean squared error (MSE), root-mean-squared error (RMSE), median absolute deviation (MAD), deviance, and Akaike information criteria (AIC). RESULTS: The longitudinal regression tree algorithm outperformed based on the criteria such as MSE, RMSE, and MAD than the linear mixed-effects model (LMM) for analyzing the TCGS and simulated data using the missing at random (MAR) mechanism. Overall, based on fitting the non-parametric model, the performance of the 27 imputation approaches was nearly similar. However, the SI traj-mean method improved performance compared with other imputation approaches. CONCLUSION: Both SI and MI approaches performed better using the longitudinal regression tree algorithm compared with the parametric longitudinal models. Based on the results from both the real and simulated data, we recommend that researchers use the traj-mean method for imputing missing values of longitudinal data. Choosing the imputation method with the best performance is widely dependent on the models of interest and the data structure.

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Background: Emergency providers' knowledge and attitudes may be a barrier to adopting hospice and palliative care practice. Objective: To assess provider characteristics associated with knowledge and attitudes toward hospice and palliative care (KAHP). Design: Cross-sectional analysis. Setting/Subjects: Emergency physicians, advanced practice providers (APPs), and nurses from 35 U.S. emergency departments (EDs) enrolled in a provider-focused intervention. Measurement: The outcome measures were the total and subscale scores of the KAHP scale. The predictor variables were age, sex, race/ethnicity, and years of practice. We reported the observed association using a linear mixed-effects regression model. Results: The mean KAHP score, rated from 10 to 50, was 36. Increased years of practice were associated with increased mean self-reported knowledge and attitudes scores among APPs and nurses. Conclusion: Understanding the provider characteristics associated with hospice and palliative care adoption in the ED may inform the development of interventions for specific providers. ClinicalTrials.gov (NCT03424109).

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Persons living with advanced cancer have intensive symptoms and psychosocial needs that often result in visits to the Emergency Department (ED). We report on program engagement, advance care planning (ACP), and hospice use for a 6-month longitudinal nurse-led, telephonic palliative care intervention for patients with advanced cancer as part of a larger randomized trial. Patients 50 years and older with metastatic solid tumors were recruited from 18 EDs and randomized to receive nursing calls focused on ACP, symptom management, and care coordination or specialty outpatient palliative care (ClinicialTrials.gov: NCT03325985). One hundred and five (50%) graduated from the 6-month program, 54 (26%) died or enrolled in hospice, 40 (19%) were lost to follow-up, and 19 (9%) withdrew prior to program completion. In a Cox proportional hazard regression, withdrawn subjects were more likely to be white and have a low symptom burden compared to those who did not withdraw. Two hundred eighteen persons living with advanced cancer were enrolled in the nursing arm, and 182 of those (83%) completed some ACP. Of the subjects who died, 43/54 (80%) enrolled in hospice. Our program demonstrated high rates of engagement, ACP, and hospice enrollment. Enrolling subjects with a high symptom burden may result in even greater program engagement.

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Background: EM Talk is a communication skills training program designed to improve emergency providers' serious illness conversational skills. Using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, this study aims to assess the reach of EM Talk and its effectiveness. Methods: EM Talk is one of the components of Primary Palliative Care for Emergency Medicine (EM) intervention. It consisted of one 4-hour training session during which professional actors used role-plays and active learning to train providers to deliver serious/bad news, express empathy, explore patients' goals, and formulate care plans. After the training, emergency providers filled out an optional post-intervention survey, which included course reflections. Using a multi-method analytical approach, we analyzed the reach of the intervention quantitatively and the effectiveness of the intervention qualitatively using conceptual content analysis of open-ended responses. Results: A total of 879 out of 1,029 (85%) EM providers across 33 emergency departments completed the EM Talk training, with the training rate ranging from 63-100%. From the 326 reflections, we identified meaning units across the thematic domains of improved knowledge, attitude, and practice. The main subthemes across the three domains were the acquisition of discussion tips and tricks, improved attitude toward engaging qualifying patients in serious illness (SI) conversations, and commitment to using these learned skills in clinical practice. Conclusion: Effectively engaging qualifying patients in serious illness conversations requires appropriate communication skills. EM Talk has the potential to improve emergency providers' knowledge, attitude, and practice of SI communication skills. Trial registration: NCT03424109.

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BACKGROUND: Blood pressure (BP) control is suboptimal in minority communities, including Asian populations. We evaluate the feasibility, adoption, and effectiveness of an integrated CHW-led health coaching and practice-level intervention to improve hypertension control among South Asian patients in New York City, Project IMPACT (Integrating Million Hearts for Provider and Community Transformation). The primary outcome was BP control, and secondary outcomes were systolic BP and diastolic BP at 6-month follow-up. METHODS: A randomized-controlled trial took place within community-based primary care practices that primarily serve South Asian patients in New York City between 2017 and 2019. A total of 303 South Asian patients aged 18-85 with diagnosed hypertension and uncontrolled BP (systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg) within the previous 6 months at 14 clinic sites consented to participate. After completing 1 education session, individuals were randomized into treatment (n=159) or control (n=144) groups. Treatment participants received 4 additional group education sessions and individualized health coaching over a 6-month period. A mixed effect generalized linear model with a logit link function was used to assess intervention effectiveness for controlled hypertension (Yes/No), adjusting for practice level random effect, age, sex, baseline systolic BP, and days between BP measurements. RESULTS: Among the total enrolled population, mean age was 56.8±11.2 years, and 54.1% were women. At 6 months among individuals with follow-up BP data (treatment, n=154; control, n=137), 68.2% of the treatment group and 41.6% of the control group had controlled BP (P<0.001). In final adjusted analysis, treatment group participants had 3.7 [95% CI, 2.1-6.5] times the odds of achieving BP control at follow-up compared with the control group. CONCLUSIONS: A CHW-led health coaching intervention was effective in achieving BP control among South Asian Americans in New York City primary care practices. Findings can guide translation and dissemination of this model across other communities experiencing hypertension disparities. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03159533.

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BACKGROUND: Numerous clinical trials have been initiated to find effective treatments for COVID-19. These trials have often been initiated in regions where the pandemic has already peaked. Consequently, achieving full enrollment in a single trial might require additional COVID-19 surges in the same location over several years. This has inspired us to pool individual patient data (IPD) from ongoing, paused, prematurely-terminated, or completed randomized controlled trials (RCTs) in real-time, to find an effective treatment as quickly as possible in light of the pandemic crisis. However, pooling across trials introduces enormous uncertainties in study design (e.g., the number of RCTs and sample sizes might be unknown in advance). We sought to develop a versatile treatment efficacy assessment model that accounts for these uncertainties while allowing for continuous monitoring throughout the study using Bayesian monitoring techniques. METHODS: We provide a detailed look at the challenges and solutions for model development, describing the process that used extensive simulations to enable us to finalize the analysis plan. This includes establishing prior distribution assumptions, assessing and improving model convergence under different study composition scenarios, and assessing whether we can extend the model to accommodate multi-site RCTs and evaluate heterogeneous treatment effects. In addition, we recognized that we would need to assess our model for goodness-of-fit, so we explored an approach that used posterior predictive checking. Lastly, given the urgency of the research in the context of evolving pandemic, we were committed to frequent monitoring of the data to assess efficacy, and we set Bayesian monitoring rules calibrated for type 1 error rate and power. RESULTS: The primary outcome is an 11-point ordinal scale. We present the operating characteristics of the proposed cumulative proportional odds model for estimating treatment effectiveness. The model can estimate the treatment's effect under enormous uncertainties in study design. We investigate to what degree the proportional odds assumption has to be violated to render the model inaccurate. We demonstrate the flexibility of a Bayesian monitoring approach by performing frequent interim analyses without increasing the probability of erroneous conclusions. CONCLUSION: This paper describes a translatable framework using simulation to support the design of prospective IPD meta-analyses.

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BACKGROUND AND AIMS: Opioid overdose is a leading cause of death during the immediate time after release from jail or prison. Most jails in the United States do not provide methadone and buprenorphine treatment for opioid use disorder (MOUD), and research in estimating its impact in jail settings is limited. We aimed to test the hypothesis that in-jail MOUD is associated with lower overdose mortality risk post-release. DESIGN, SETTING AND PARTICIPANTS: Retrospective, observational cohort study of 15 797 adults with opioid use disorder who were released from New York City jails to the community in 2011-2017. They experienced 31 382 incarcerations and were followed up to 1 year. MEASUREMENTS: The primary outcomes were death caused by accidental drug poisoning and all-cause death. The exposure was receipt of MOUD (17 119 events) versus out-of-treatment (14 263 events) during the last 3 days before community re-entry. Covariates included demographic, clinical, behavioral, housing, health-care utilization and legal characteristics variables. We performed a multivariable, mixed-effect Cox regression analysis to test association between in-jail MOUD and deaths. FINDINGS: The majority were male (82%) and their average age was 42 years. Receiving MOUD was associated with misdemeanor charges, being female, injection drug use and homelessness. During 1 year post-release, 111 overdose deaths occurred and crude death rates were 0.49 and 0.83 per 100 person-years for in-jail MOUD and out-of-treatment groups, respectively. Accounting for confounding and random effects, in-jail MOUD was associated with lower overdose mortality risk [adjusted hazard ratio (aHR) = 0.20, 95% confidence interval (CI) = 0.08-0.46] and all-cause mortality risk (aHR = 0.22, 95% CI = 0.11-0.42) for the first month post-release. CONCLUSIONS: Methadone and buprenorphine treatment for opioid use disorder during incarceration was associated with an 80% reduction in overdose mortality risk for the first month post-release.

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Background: Emergency providers can engage in goals of care discussions and hospice and palliative care referrals. Little is known about their knowledge and attitudes, which may influence these care practices. Objective: This study aims to re-validate the knowledge and attitude towards hospice and palliative care (KAHP) scale and assess the scale's latent constructs among emergency providers. Methods: The scale consists of ten items measured on a five-point Likert scale. Five of the ten items were reverse scored. Content validation was performed by ten experts in Hospice and Palliative Medicine and Emergency Medicine. Baseline surveys of emergency physicians, advance practice providers, and nurses conducted in the context of a pragmatic, randomized control trial were used for the item analysis and the exploratory and confirmatory factor analyses. Results: The KAHP scale is a ten-item scale scored from 10 to 50. Based on the synthesis of content validation results and the item analysis, all ten items were retained. The item and scale Content Validity Index were each .91. The reliability of the scale was .64 and the exploratory factor analysis identified three underlying constructs defined as self-rated knowledge, support for hospice and palliative care practice, and views on provider-patient communication. The presence of good model fit indices supported the structural integrity of the constructs. Conclusion: We present a validated instrument that is suitable for assessing knowledge and attitude variations toward interventions designed to improve hospice and palliative care practice among emergency providers.

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BACKGROUND: In 2021, Delta became the predominant SARS-CoV-2 variant worldwide. While vaccines have effectively prevented COVID-19 hospitalization and death, vaccine breakthrough infections increasingly occurred. The precise role of clinical and genomic determinants in Delta infections is not known, and whether they contributed to increased rates of breakthrough infections compared to unvaccinated controls. METHODS: We studied SARS-CoV-2 variant distribution, dynamics, and adaptive selection over time in relation to vaccine status, phylogenetic relatedness of viruses, full genome mutation profiles, and associated clinical and demographic parameters. FINDINGS: We show a steep and near-complete replacement of circulating variants with Delta between May and August 2021 in metropolitan New York. We observed an increase of the Delta sublineage AY.25 (14% in vaccinated, 7% in unvaccinated), its spike mutation S112L, and AY.44 (8% in vaccinated, 2% in unvaccinated) with its nsp12 mutation F192V in breakthroughs. Delta infections were associated with younger age and lower hospitalization rates than Alpha. Delta breakthrough infections increased significantly with time since vaccination, and, after adjusting for confounders, they rose at similar rates as in unvaccinated individuals. INTERPRETATION: We observed a modest adaptation of Delta genomes in breakthrough infections in New York, suggesting an improved genomic framework to support Delta's epidemic growth in times of waning vaccine protection despite limited impact on vaccine escape. FUNDING: The study was supported by NYU institutional funds. The NYULH Genome Technology Center is partially supported by the Cancer Center Support Grant P30CA016087 at the Laura and Isaac Perlmutter Cancer Center.

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BACKGROUND: The emergency department (ED) is a critical juncture in the care of persons living with dementia (PLwD), as they have a high rate of hospital admission, ED revisits, and subsequent inpatient stays. We examine ED disposition of PLwD compared with older adults with non-dementia chronic disease as well as healthcare utilization and survival. METHODS: Medicare claims data were used to identify community-dwelling older adults 66+ years old from 34 hospitals with either Alzheimer's disease/Alzheimer's disease related dementias (AD/ADRD) or a non-AD/ADRD chronic condition between January 1, 2014, and December 31, 2018. We compared ED disposition at the index visit, as well as healthcare utilization and mortality in the 12 months following an index ED visit, and adjusted for age, gender, and risk of mortality. RESULTS: There were 29,626 patients in the AD/ADRD sample, and 317,046 in the comparison sample. The AD/ADRD sample was older (82.4 years old [SD: 8.2] vs. 76.0 years old [SD: 7.7]) and had more female patients (59.9% vs. 54.7%). The AD/ADRD sample was more likely to experience ED disposition to acute care (OR 1.039, p < 0.001, 95% CI 1.029-1.050), to have an ED revisit (OR 1.077, p < 0.001, 95% CI 1.066-1.087), and an inpatient stay in the subsequent 12 months (OR 1.085, p < 0.001, 95% CI 1.075-1.095). ED disposition to hospice was low in both samples (0.2%). AD/ADRD patients had a higher risk of mortality (OR 1.099, p < 0.001, 95% CI 1.091-1.107) and high short-term mortality (31.9% within 12 months) than those without AD/ADRD (15.3% within 12 months). CONCLUSIONS: PLwD who visit the ED have high short-term mortality. Despite this, disposition to acute care, ED revisits, and inpatient stays, rather than hospice, remain the predominant mode of care delivery. Transition directly from the ED to hospice for PLwD is rare.

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To determine whether an opt-out approach is effective for referral to treatment for tobacco use, we designed a clinical reminder for nurses in a primary care setting that provides a referral for patients who smoke cigarettes. We will use a two-arm, cluster-randomized design to assign nurses at the VA New York Harbor Healthcare System to test which mode of referral (opt-in vs opt-out) is more effective. All patients will be referred to evidence-based treatment for tobacco cessation including counseling from the New York State Quitline, and VetsQuit, a text messaging-based system for tobacco cessation counseling. We will measure patient engagement with the referral both in the short and long term to determine if referral modality had an impact on tobacco cessation treatment. We will also measure nurse engagement with the referral before, during, and after the implementation of the reminder to determine whether an opt-out approach is cost effective at the health system level. At the conclusion of this project, we expect to have developed and tested an opt-out system for increasing tobacco cessation treatment for Veterans in VA primary care and to have a thorough understanding of factors associated with implementation. Trial Registration:Clinicaltrials.govIdentifierNCT03477435.

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INTRODUCTION: Effective communication is essential to good health care, and hearing loss disrupts patient-provider communication. For the more than 2 million veterans with severe hearing loss, communication is particularly challenging in noisy health care environments such as emergency departments. The purpose of this qualitative study was to describe patient and provider perspectives of feasibility and potential benefit of providing a hearing assistance device, a personal amplifier, during visits to an emergency department in an urban setting affiliated with the Department of Veterans Affairs. METHODS: This qualitative descriptive study was conducted in parallel with a randomized controlled study. We completed a semistructured interview with 11 veterans and 10 health care providers to elicit their previous experiences with patient-provider communication in the ED setting and their perspectives on hearing screening and using the personal amplifier in the emergency department. Interview data were analyzed using content analysis and Atlas.ti V8.4 software (Scientific Software Development GmbH, Berlin, Germany). RESULTS: The veteran sample (n = 11) had a mean age of 80.3 years (SD = 10.2). The provider sample included 7 nurses and 3 physicians. In the ED setting, hearing loss disrupts patient-provider communication. Screening for hearing loss in the emergency department was feasible except in urgent/emergent cases. The use of the personal amplifier made communication more effective and less effortful for both veterans and providers. DISCUSSION: Providing the personal amplifier improved the ED experience for veterans and offers a promising intervention that could improve health care quality and safety for ED patient populations.

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IMPORTANCE: Identifying successful strategies to increase COVID-19 vaccination among skilled nursing facility (SNF) residents and staff is integral to preventing future outbreaks in a continually overwhelmed system. OBJECTIVE: To determine whether a multicomponent vaccine campaign would increase vaccine rates among SNF residents and staff. DESIGN, SETTING, AND PARTICIPANTS: This was a cluster randomized trial with a rapid timeline (December 2020-March 2021) coinciding with the Pharmacy Partnership Program (PPP). It included 133 SNFs in 4 health care systems across 16 states: 63 and 70 facilities in the intervention and control arms, respectively, and participants included 7496 long-stay residents (>100 days) and 17 963 staff. INTERVENTIONS: Multicomponent interventions were introduced at the facility level that included: (1) educational material and electronic messaging for staff; (2) town hall meetings with frontline staff (nurses, nurse aides, dietary, housekeeping); (3) messaging from community leaders; (4) gifts (eg, T-shirts) with socially concerned messaging; (5) use of a specialist to facilitate consent with residents' proxies; and (6) funds for additional COVID-19 testing of staff/residents. MAIN OUTCOMES AND MEASURES: The primary outcomes of this study were the proportion of residents (from electronic medical records) and staff (from facility logs) who received a COVID-19 vaccine (any), examined as 2 separate outcomes. Mixed-effects generalized linear models with a binomial distribution were used to compare outcomes between arms, using intent-to-treat approach. Race was examined as an effect modifier in the resident outcome model. RESULTS: Most facilities were for-profit (95; 71.4%), and 1973 (26.3%) of residents were Black. Among residents, 82.5% (95% CI, 81.2%-83.7%) were vaccinated in the intervention arm, compared with 79.8% (95% CI, 78.5%-81.0%) in the usual care arm (marginal difference 0.8%; 95% CI, -1.9% to 3.7%). Among staff, 49.5% (95% CI, 48.4%-50.6%) were vaccinated in the intervention arm, compared with 47.9% (95% CI, 46.9%-48.9%) in usual care arm (marginal difference: -0.4%; 95% CI, -4.2% to 3.1%). There was no association of race with the outcome among residents. CONCLUSIONS AND RELEVANCE: A multicomponent vaccine campaign did not have a significant effect on vaccination rates among SNF residents or staff. Among residents, vaccination rates were high. However, half the staff remained unvaccinated despite these efforts. Vaccination campaigns to target SNF staff will likely need to use additional approaches. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04732819.

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Importance: COVID-19 convalescent plasma (CCP) is a potentially beneficial treatment for COVID-19 that requires rigorous testing. Objective: To compile individual patient data from randomized clinical trials of CCP and to monitor the data until completion or until accumulated evidence enables reliable conclusions regarding the clinical outcomes associated with CCP. Data Sources: From May to August 2020, a systematic search was performed for trials of CCP in the literature, clinical trial registry sites, and medRxiv. Domain experts at local, national, and international organizations were consulted regularly. Study Selection: Eligible trials enrolled hospitalized patients with confirmed COVID-19, not receiving mechanical ventilation, and randomized them to CCP or control. The administered CCP was required to have measurable antibodies assessed locally. Data Extraction and Synthesis: A minimal data set was submitted regularly via a secure portal, analyzed using a prespecified bayesian statistical plan, and reviewed frequently by a collective data and safety monitoring board. Main Outcomes and Measures: Prespecified coprimary end points-the World Health Organization (WHO) 11-point ordinal scale analyzed using a proportional odds model and a binary indicator of WHO score of 7 or higher capturing the most severe outcomes including mechanical ventilation through death and analyzed using a logistic model-were assessed clinically at 14 days after randomization. Results: Eight international trials collectively enrolled 2369 participants (1138 randomized to control and 1231 randomized to CCP). A total of 2341 participants (median [IQR] age, 60 [50-72] years; 845 women [35.7%]) had primary outcome data as of April 2021. The median (IQR) of the ordinal WHO scale was 3 (3-6); the cumulative OR was 0.94 (95% credible interval [CrI], 0.74-1.19; posterior probability of OR <1 of 71%). A total of 352 patients (15%) had WHO score greater than or equal to 7; the OR was 0.94 (95% CrI, 0.69-1.30; posterior probability of OR <1 of 65%). Adjusted for baseline covariates, the ORs for mortality were 0.88 at day 14 (95% CrI, 0.61-1.26; posterior probability of OR <1 of 77%) and 0.85 at day 28 (95% CrI, 0.62-1.18; posterior probability of OR <1 of 84%). Heterogeneity of treatment effect sizes was observed across an array of baseline characteristics. Conclusions and Relevance: This meta-analysis found no association of CCP with better clinical outcomes for the typical patient. These findings suggest that real-time individual patient data pooling and meta-analysis during a pandemic are feasible, offering a model for future research and providing a rich data resource.

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