Transitions of care between jail-based medications for opioid use disorder and ongoing treatment in the community: A retrospective cohort study.

BACKGROUND: Offering medications for opioid use disorder (MOUD) in carceral settings significantly reduces overdose. However, it is unknown to what extent individuals in jails continue MOUD once they leave incarceration. We aimed to assess the relationship between in-jail MOUD and MOUD continuity in the month following release. METHODS: We conducted a retrospective cohort study of linked NYC jail-based electronic health records and community Medicaid OUD treatment claims for individuals with OUD discharged from jail between 2011 and 2017. We compared receipt of MOUD within 30 days of release, among those with and without MOUD at release from jail. We tested for effect modification based on MOUD receipt prior to incarceration and assessed factors associated with treatment discontinuation. RESULTS: Of 28,298 eligible incarcerations, 52.8 % received MOUD at release. 30 % of incarcerations with MOUD at release received community-based MOUD within 30 days, compared to 7 % of incarcerations without MOUD (Risk Ratio: 2.62 (2.44-2.82)). Most (69 %) with MOUD claims prior to incarceration who received in-jail MOUD continued treatment in the community, compared to 9 % of those without prior MOUD. Those who received methadone (vs. buprenorphine), were younger, Non-Hispanic Black and with no history of MOUD were less likely to continue MOUD following release. CONCLUSIONS: MOUD maintenance in jail is strongly associated with MOUD continuity upon release. Still, findings highlight a gap in treatment continuity upon-reentry, especially among those who initiate MOUD in jail. In the wake of worsening overdose deaths and troubling disparities, improving MOUD continuity among this population remains an urgent priority.

Assessing the impact of jail-initiated medication for opioid use disorder: A multisite analysis of the SOMATICS collaborative.

The objective of this study was to estimate the associations of jail-initiated medication for opioid use disorder (MOUD) and patient navigation (PN) with opioid use disorder (OUD) at 6 months post-release. Three randomized trials (combined N = 330) were combined to assess whether MOUD (extended-release naltrexone or interim methadone) initiated prior to release from jail with or without PN would reduce the likelihood of a DSM-5 diagnosis of OUD 6 months post-release relative to enhanced treatment-as-usual (ETAU). Across the three studies, assignment to MOUD compared to ETAU was not associated with an OUD diagnosis at 6 months post-release (69% vs. 75%, respectively, OR = 0.67, 95% CI: 0.42 to 1.20). Similarly, PN compared to MOUD without PN was not associated with an OUD diagnosis (63% vs 77%, respectively, OR = 0.61, 95% CI: 0.27 to 1.53). Results underscore the need to further optimize the effectiveness of MOUD for patients initiating treatment in jail, beginning with an emphasis on post-release treatment adherence.

Sample size and power calculation for testing treatment effect heterogeneity in cluster randomized crossover designs.

The cluster randomized crossover design has been proposed to improve efficiency over the traditional parallel-arm cluster randomized design. While statistical methods have been developed for designing cluster randomized crossover trials, they have exclusively focused on testing the overall average treatment effect, with little attention to differential treatment effects across subpopulations. Recently, interest has grown in understanding whether treatment effects may vary across pre-specified patient subpopulations, such as those defined by demographic or clinical characteristics. In this article, we consider the two-treatment two-period cluster randomized crossover design under either a cross-sectional or closed-cohort sampling scheme, where it is of interest to detect the heterogeneity of treatment effect via an interaction test. Assuming a patterned correlation structure for both the covariate and the outcome, we derive new sample size formulas for testing the heterogeneity of treatment effect with continuous outcomes based on linear mixed models. Our formulas also address unequal cluster sizes and therefore allow us to analytically assess the impact of unequal cluster sizes on the power of the interaction test in cluster randomized crossover designs. We conduct simulations to confirm the accuracy of the proposed methods, and illustrate their application in two real cluster randomized crossover trials.

Impact of jail-based methadone or buprenorphine treatment on non-fatal opioid overdose after incarceration.

BACKGROUND: Non-fatal overdose is a leading predictor of subsequent fatal overdose. For individuals who are incarcerated, the risk of experiencing an overdose is highest when transitioning from a correctional setting to the community. We assessed if enrollment in jail-based medications for opioid use disorder (MOUD) is associated with lower risk of non-fatal opioid overdoses after jail release among individuals with opioid use disorder (OUD). METHODS: This was a retrospective, observational cohort study of adults with OUD who were incarcerated in New York City jails and received MOUD or did not receive any MOUD (out-of-treatment) within the last three days before release to the community in 2011-2017. The outcome was the first non-fatal opioid overdose emergency department (ED) visit within 1 year of jail release during 2011-2017. Covariates included demographic, clinical, incarceration-related, and other characteristics. We performed multivariable cause-specific Cox proportional hazards regression analysis to compare the risk of non-fatal opioid overdose ED visits within 1 year after jail release between groups. RESULTS: MOUD group included 8660 individuals with 17,119 incarcerations; out-of-treatment group included 10,163 individuals with 14,263 incarcerations. Controlling for covariates and accounting for competing risks, in-jail MOUD was associated with lower non-fatal opioid overdose risk within 14 days after jail release (adjusted HR=0.49, 95% confidence interval=0.33-0.74). We found no significant differences 15-28, 29-56, or 57-365 days post-release. CONCLUSION: MOUD group had lower risk of non-fatal opioid overdose immediately after jail release. Wider implementation of MOUD in US jails could potentially reduce post-release overdoses, ED utilization, and associated healthcare costs.

Serious illness communication skills training for emergency physicians and advanced practice providers: a multi-method assessment of the reach and effectiveness of the intervention.

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 consisted of one 4-h 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 to 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 Serious Illness (SI) communication skills, improved attitude toward engaging qualifying patients in SI conversations, and commitment to using these learned skills in clinical practice. CONCLUSION: Our study showed the extensive reach and the effectiveness of the EM Talk training in improving SI conversation. EM Talk, therefore, can potentially improve emergency providers' knowledge, attitude, and practice of SI communication skills. TRIAL REGISTRATION: Clinicaltrials.gov: NCT03424109; Registered on January 30, 2018.

What's in This For You? What's in This For Me?: A Win-Win Perspective of Involving Study Advisory Committee Members in Palliative Care Research.

Study advisory committees (SACs) provide critical value to clinical trials by providing unique perspectives that pull from personal and professional experiences related to the trial's healthcare topic. The Emergency Medicine Palliative Care Access (EMPallA) study had the privilege of convening a 16-person SAC from the project's inception to completion. The study team wanted to understand the impact this project had on the SAC members. In this narrative, we use reflective dialogue to share SAC members' lived experiences and the impact the EMPallA study has had on members both personally and professionally. We detail the (1) benefits SAC members, specifically patients, and caregivers, have had through working on this project. (2) The importance of recruiting diverse SAC members with different lived experiences and leveraging their feedback in clinical research. (3) Value of community capacity building to ensure the common vision of the clinical trial is promoted.

COVID-19 Convalescent Plasma Therapy: Long-term Implications.

Background: The long-term effect of coronavirus disease 2019 (COVID-19) acute treatments on postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) is unknown. The CONTAIN-Extend study explores the long-term impact of COVID-19 convalescent plasma (CCP) therapy on postacute sequelae of SARS-CoV-2 infection (PASC) symptoms and general health 18 months following hospitalization. Methods: The CONTAIN-Extend study examined 281 participants from the original CONTAIN COVID-19 trial (CONTAIN-RCT, NCT04364737) at 18 months post-hospitalization for acute COVID-19. Symptom surveys, global health assessments, and biospecimen collection were performed from November 2021 to October 2022. Multivariable logistic and linear regression estimated associations between the randomization arms and self-reported symptoms and Patient-Reported Outcomes Measurement Information System (PROMIS) scores and adjusted for covariables, including age, sex, race/ethnicity, disease severity, and CONTAIN enrollment quarter and sites. Results: There were no differences in symptoms or PROMIS scores between CCP and placebo (adjusted odds ratio [aOR] of general symptoms, 0.95; 95% CI, 0.54-1.67). However, females (aOR, 3.01; 95% CI, 1.73-5.34), those 45-64 years (aOR, 2.55; 95% CI, 1.14-6.23), and April-June 2020 enrollees (aOR, 2.39; 95% CI, 1.10-5.19) were more likely to report general symptoms and have poorer PROMIS physical health scores than their respective reference groups. Hispanic participants (difference, -3.05; 95% CI, -5.82 to -0.27) and Black participants (-4.48; 95% CI, -7.94 to -1.02) had poorer PROMIS physical health than White participants. Conclusions: CCP demonstrated no lasting effect on PASC symptoms or overall health in comparison to the placebo. This study underscores the significance of demographic factors, including sex, age, and timing of acute infection, in influencing symptom reporting 18 months after acute hypoxic COVID-19 hospitalization.

Psychometric Properties of the Functional Assessment of Cancer Therapy-General for Evaluating Quality of Life in Patients With Life-Limiting Illness in the Emergency Department.

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.

Emergency Nurses' Perceived Barriers and Solutions to Engaging Patients With Life-Limiting Illnesses in Serious Illness Conversations: A United States Multicenter Mixed-Method Analysis.

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.

Jail-based medication for opioid use disorder and patterns of reincarceration and acute care use after release: A sequence analysis.

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.

Improving Individualized Treatment Decisions: A Bayesian Multivariate Hierarchical Model for Developing a Treatment Benefit Index using Mixed Types of Outcomes.

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.

Conservative Kidney Management Practice Patterns and Resources in the United States: A Cross-Sectional Analysis of CKDopps (Chronic Kidney Disease Outcomes and Practice Patterns Study) Data.

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.

Sample Size Requirements to Test Subgroup-Specific Treatment Effects in Cluster-Randomized Trials.

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.

A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis.

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.

Emergency Providers' Knowledge and Attitudes Toward Hospice and Palliative Care: A Cross-Sectional Analysis Across 35 Emergency Departments in the United States.

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).

Engagement, Advance Care Planning, and Hospice Use in a Telephonic Nurse-Led Palliative Care Program for Persons Living with Advanced Cancer.

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.

Serious Illness Communication Skills Training for Emergency Physicians and Advanced Practice Providers: A Multi-Method Assessment of the Reach and Effectiveness of the Intervention.

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.

Integrating Community Health Workers into Community-Based Primary Care Practice Settings to Improve Blood Pressure Control Among South Asian Immigrants in New York City: Results from a Randomized Control Trial.

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.

Developing a Bayesian hierarchical model for a prospective individual patient data meta-analysis with continuous monitoring.

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.